NOMSA21 Open Up and Connect:
Education in a Digital Era Conference
Proceedings
Amit Dhakulkar & Jako Olivier, Eds.
NOMSA Open Up and Connect 2021
NOMSA21 Open Up and Connect: Education in a Digital Era Conference Proceedings
Online conference held 6-7 December 2021
2022, Network of OER and Multimodal Self-Directed Learning in Southern Africa
Amit Dhakulkar & Jako Olivier, Eds.
NOMSA21 Open Up and Connect: Education in a Digital Era Conference Proceedings
is made available under a Creative Commons Attribution-ShareAlike 4.0 Licence (international):
http://creativecommons.org/licences/by-sa/4.0.
Cite as:
Dhakulkar, A, & Olivier, J. (Eds.) (2022). NOMSA21 Open Up and Connect: Education in a Digital
Era Conference Proceedings. Online conference held 6-7 December 2021.
https://doi.org/10.5281/zenodo.7458973
NOMSA Open Up and Connect 2021
CONTENTS
Foreword ........................................................................................................................................................................1
Assessment of digitalized learning and teaching to senior high school in Pampanga, Philippines
............................................................................................................................................................................................2
Online group supervision as pedagogy under emergency conditions: optimising online
collaboration towards self-directed learning in a South African HEI .................................................. 14
Evaluation of digital educational initiative during the Covid-19 pandemic using concerns-based
adoption model ......................................................................................................................................................... 26
Face-to-Face Versus Remote Learning: Student Behaviour Analysis through Educational Data
......................................................................................................................................................................................... 34
Student plagiarism detection in distance higher education .................................................................... 44
An analysis of the impact of Covid-19 emergency remote learning on first-year LLB student
success rates............................................................................................................................................................... 55
An investigative study of opinion mining about e-learning and transformation that took place
during the Covid-19 pandemic ........................................................................................................................... 67
Reflective teaching and learners’ performance: the case of a selected region in Namibia .......... 77
Curbing exclusion: the experiences of students with visual impairments and their lecturers on
distance and online learning during the Covid-19 pandemic in Namibia .......................................... 84
Overcoming gender imbalance in ICT-related jobs ..................................................................................... 96
A study of MOOC learners’ learning expectations, learning engagement and satisfaction ...... 116
Flipped-classroom approach in the digital post-Covid-19 era: an EFL blended learning scenario
that promotes healthy eating habits .............................................................................................................. 128
The relationship between online professional learning communities and teaching presence
...................................................................................................................................................................................... 135
Technical support needs of distance students to participate in online courses at the centre of
open and lifelong learning ................................................................................................................................. 145
Exploring mobile technologies as mitigating tools for online learning crisis................................ 166
Lecturers’ recommendations on how learning management system training and support can
improve the implementation of blended learning in a higher education institution ................. 178
NOMSA Open Up and Connect 2021
FOREWORD
The Network of OER and Multimodal Self-Directed Learning in Southern Africa (NOMSA) and the
UNESCO Chair on Multimodal Learning and Open Educational Resources from the North-West
University, South Africa hosted the NOMSA21 Open Up and Connect: Education in a Digital Era
online conference on 6 and 7 December 2021. With the increase in the use of technology in
education and specifically in the context of the COVID-19 pandemic the realities of access to
enabling technologies and online learning were prominent and this informed the focus of the
conference. The conference welcomed papers based on empirical research as well as conceptual
papers with a specific focus on open education and/or the wider field of digital and online
education.
This conference was envisaged by the NOMSA advisory board as a means to promote a wider
South-South and North-South discourse on both open education and multimodal self-directed
learning. These two aspects are increasingly becoming important in an educational sphere where
costs of educational resources are rising and there is a need for relevant and localized content.
Moreover, the role of technology is also indisputable as delivery and learning is conducted through
different modalities. The conference included four keynote presentations, two workshops and 50
conference papers. Furthermore, the presenters come from 16 different countries: Canada, China,
Eswatini, Gabon, Greece, India, Indonesia, Mauritius, Namibia, Nepal, Nigeria, Pakistan,
Philippines, South Africa, Sri Lanka and Thailand. The keynote speakers of the conference were
Prof. Asha S. Kanwar, Commonwealth of Learning, Prof. Maha Bali, American University in Cairo,
Egypt, Prof. Moeketsi Letseka, UNISA, South Africa and Dr Kaviraj Sharma Sukon, Open
University of Mauritius, Mauritius.
These proceedings present 16 papers submitted to be part of the proceedings, and which were
accepted after a double-blind peer review. Only original research is included in the proceedings and
all papers have been subjected to a plagiarism check on all to ensure quality. The target audience of
the proceedings is specialists and academics.
The papers included in these proceedings provide an interesting glimpse on the nature of digital
education specifically within the context of COVID-19. Furthermore, these papers contribute not
only to providing useful recommendations for teaching and learning practices, but also in
broadening the scholarship of education in the digital era.
Amit Dhakulkar and Jako Olivier
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ASSESSMENT OF DIGITALIZED LEARNING AND TEACHING
TO SENIOR HIGH SCHOOL IN PAMPANGA, PHILIPPINES
Jennifer H. Operio
Holy Angel University, Philippines (nejoperio@gmail.com)
Abstract
This research assessed the value of digital technology to students’ learning in a private high school
in Pampanga, Philippines. It examined the redefinition of the approach to teaching by integrating
various forms of teaching methodologies to add value to classroom learning. This study is important
to the respondent private school owners, administrators, students, and teaching and non-teaching
staff in redefining teaching approach to a new breed of students. The research conducted descriptive
quantitative research. The conceptual framework illustrates the independent, dependent and
mediating variables. Teachers, with the courses they were teaching, and students, as the respondents,
were the independent variables, and digital technology integration was the mediating variable. The
dependent variables were the level of effectiveness of using technology for student engagement, and
learning satisfaction. The respondents in the study were the administrators, senior high school
students, and teaching and non-teaching staff in the school. The researcher used a self-developed
survey questionnaire that was piloted with a separate group of respondents who were not part of the
sample of participants identified for the study. As an ethical consideration, the proponent did not
have a direct hand in distributing the survey form. Also, the identity of respondents, specifically of
the students, was kept confidential. This study awakens the teaching community, particularly at high
school level, to the great value of digital technology. The contribution of this study to the body of
knowledge is an additional approach to teaching a millennial.
INTRODUCTION
Over the past 10 years, there has been an increasing use of the blended approach in teaching and
learning, which integrates digital technologies into traditional teaching methods. This approach
requires the physical presence of both the learner and tutor, but there is a component of authority over
location, schedule, and track or pace by the student (Smyth et al., 2012). This new instructional
approach is not just about increasing the units of computers inside classrooms; in other cases, it shows
a basic transformation to educators and learners’ expectation of the study experience. The innovators
of education by the name of Biggs and Tang (2011) agree that the mixed or blended teaching method
consists of three parts: (i) “actual classroom activities assisted by a qualified and well-trained
teacher”; (ii)”educational materials are uploaded online by that same teacher”; and (iii) “self-faced
study time guided by the online resources, while the expected skills developed in the classroom setup.”
The subject school is a private school located at MacArthur Highway in San Agustin, San Simon,
Pampanga, Philippines. It is one of the oldest institutions in the locality of San Simon under the
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management of the heirs of the late founders Erasmo G. Punsalan and his wife, Leonida (Student’s
handbook, 2018).
REVIEW OF RELATED LITERATURE AND STUDIES
A digitalized learning model uses an actual classroom schedule for various activities that benefit the
most from direct and actual interaction. Old system college education is more lenient to place an
emphasis on delivering material by way of a lecture, whereas a mixed-approach learning model
lecture can be pre-recorded so students can watch at their own pace. Time spent in classroom is more
likely to be for structural-designed activities that emphasize the application of the curriculum too sole
problems or to work through tasks (Poon et al., 2010).
In simple terms, hybrid learning can use classroom time at the start, then slowly increase the number
of tasks that learners do online independently at their own pace. However, a few argue that discussion
boards are a lot better if the students and teachers have seen each other first (Donnelly, 2010; Poon et
al, 2010). The shift to a digitalized approach in teaching and learning has inspired teachers to redefine
their traditional roles. Words such as “facilitator” became an alternate term to “teacher,” which
connotes a new lens of focus. The “facilitator” focuses on empowering learners with talents, skills
and knowledge basically needed to use most oof the materials online and independent study time,
leading learners to the most exciting and rewarding experience (Puentedura, 2014). They focus on
four key areas, namely: (1) creation of synchronous and asynchronous lesson content; (2) guiding
learners in communication with and among them, which includes the pedagogical aspect in content
online without using contextual clues; (3) assisting the learning experience of each learner and editing
material whenever possible to improve the learning experience; and (4) grading and assessing.
According to Biggs, emphasizing studying through guided and standard activities, the digitalized
approach to learning proved to be more inclined to what some institutions and organizations coin as
“hybrid training,” Through this approach, trainers can transfer their focus from knowledge delivery
to its actual manifestation, and organizations incur less costs in transporting their trainers around just
to look over the training activities and events (Biggs, 2011). The hybrid can become an effective
option if educational institutions are looking for other ways to provide their learners with a more
“personalized” experience in their studies, not worrying to stretch their budgets. It is a mixture of inperson instruction accompanied by online learning. Moreover, the hybrid approach to teaching and
learning yields positive outcomes. The US Department of Education in 2010 statistically discovered
that digitalized learning and teaching classes had a better outcome than their in-person meetings, nondigitalized equivalents. This rapidly increasing model not only grows the flexibility and
individualization of learners in their studying experiences but also allows instructors to expand the
time of their availability as guides of learning.
The digitalized approach is a form of learning in which learners work remotely, and resources are
basically delivered via an online platform. One-on-one meetings are optional; usually, learners can
chat with teachers via the Internet if they have questions. This type of approach is ideal for learners
who need more flexibility and independence in their daily schedules. It is becoming popular, and the
number of learners participating in digitalized learning and teaching has increased by about 15%
(Tang & Chaw, 2016). Evolving technology augments traditional learning, and the odd question is
how to apply digitalized learning in the traditional classroom set up. It is an instruction pattern that
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mixes various techniques in learning . Digitalized learning means the utilization of laboratory
equipment to support interactions in the classroom and improve the teaching process through
application of theories learned in class. The digitalized learning approach entails the complementary
use of electronic learning in the standard education model because of the benefits it offers on a wide
scale, for example, self-paced learning, testing and quizzing, monitoring, and feedback.
THEORETICAL FRAMEWORK
Puentedura’s “SAMR” model is a straightforward, simple structure that can be adopted in any type
of learning environment. There is a shift to adopting technology in education, which, Puentedura
believes, is followed by most educators upon initial introduction of technology to their students. In
this model, there is a significant increase in the form of complexity of substitution up to redefinition.
She believes that she is fortunate to have various technologies available for her to redefine and
augment classroom teaching and learning. The use of these classroom tools allowed her to completely
adopt a paperless and redefined classroom. Modifying traditional activities to facilitate a hands-on
experience to students materialized through these technologies. Downloading pre-made lessons from
various online teaching websites is even possible. Using mobile applications nowadays can help
around 50 students to control and be engaged in the digital content. When a tutor can utilize the
mobile application’s collaboration mode, teaching and learning can be transformed and redefined so
that individual students and groups of students can collaborate on a certain classroom task. To check
student performance, new systems innovation and design may be offered in several ways for both
formative and summative assessment. The new systems innovation and design of technologies can
provide endless possibilities for redefining distribution of knowledge content and letting students be
engaged. For example, an educator may start each lesson with some sort of assessment piece to gather
the data needed to evaluate student growth in the curriculum. A teacher may ask the students’
feedback in a public opinion poll, like a census, or insurance. Some students in groups may be given
a collaborative task for which they use the mobile application software to complete and then share to
other students. Closing the loop is to let students share their posts for peer review and with several
additional summative assessment questions. It is easier to redefine and transform classroom tasks
with classroom technologies.
The paradigm of the study depicts the mediating, independent and dependent variables: the
respondents, subjects and teachers, as the independent variables; the digitalized learning approach or
technique as the mediating variable; and the level of effectiveness of utilizing digitalized learning to
student engagement, and learning satisfaction as the dependent variables. Recommendations or
suggestion on the most and least effective aspect the blended approach is also summarized.
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Figure 1 illustrates the operational framework of the study, using the digital technology theory and
the SAMR model as bases for the approach.
Figure1: Operational framework
As shown in the framework, the digitalized approach was assessed on its effect on teaching students
in the subject private school.
METHODOLOGY
Research Problem
The research objective was to assess the value of digital technology to students’ learning in a private
high school in the province of Pampanga, Philippines. It examined a possible redefinition of the
approach in teaching by educators through integrating other forms of teaching methodologies to add
value to classroom learning. Particularly, it sought answers to the following questions:
•
•
•
•
•
Is digital technology being utilized in teaching subjects to senior high school students?
What are the barriers to using digital technology to teach these students?
How effective is the use of technology to students’ full engagement?
What is the overall satisfaction of senior high school teachers in integrating technology into
teaching?
What is the most and least effective aspect of applying technology in teaching?
Method
The research design for this study was a combination of both descriptive quantitative research
designs. Descriptive research is used to depict the features of a general population or peculiarity. In
this research, the survey method was adopted – questionnaires were circulated and distributed to
respondents, whereafter the questionnaires were dissected and analyzed by the researcher (Bryman
& Bell, 2011, p. 45). The descriptive research design was suitable for this study because it included
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gathering/collecting information to test questions concerning attitudes, feelings and opinions of the
respondents. Such design is used to test attitudes, feelings and opinions about occasions, people, or
procedures (Gay, 2003). Kothari (1995) notes that a descriptive survey design is concerned with
identifying, recording, investigating, analyzing and reporting good circumstances that exist(ed).
Engelhart (1972) contends that descriptive methods are used to acquire information helpful in
assessing present practices and giving the premise of decision-making. A quantitative research design,
as Bhandari (2022) defined it, “is a process of collecting and analyzing numerical data.” She also
claimed “it can be used to find patterns and averages, make predictions, test causal relationships, and
generalized results.”
Respondents
The group of respondents in this study comprised of 11 teachers, 7 administrators and non-teaching
personnel, and 29 senior high school students who were in the ABM strand of the respondent private
high school.
Research instrument
The researcher used a survey questionnaire to gather accurate information. The questionnaire was
designed in such a way that the participants could easily understand what was being asked. It
contained the respondents’ description (i.e., the classification, department, office and subject taught).
Section 1 focused on the respondents’ experience of using the digital learning approach. Section 2
referred to their satisfaction in using digital learning, and section 3 involved comments about digital
learning. In section 1, the first question was answered by either “yes” or “no”. When respondents
answered “yes,” additional information was requested, but they had to skip question 2. However,
respondents had to answer it when they answered “no” in question number 1. The third question used
a five-point Likert scale: 5=most effective, 4=more effective, 3=effective, 2=less effective, and
1=least effective. Section 2 was about the overall satisfaction with using the digital learning approach,
and a four-point Likert scale was used: 4=strongly agree, 3=agree, 2=disagree, and 1=strongly
disagree. Section 3 was about respondents’ comments on the use of digital teaching and learning.
Questions in this section were about three topmost advantages of using digital learning, the most and
least effective aspect of digital learning and teaching.
Data-gathering procedures
The researcher asked the permission of the owners and administrators through the school principal,
Madam Amelia D. Tan, to distribute the survey questionnaire. Prior to the actual survey, the researcher
opted to have an in-person meeting with the principal to verbally ask approval. Once the request was
granted, the researcher determined the total number of survey forms that had to be distributed to all
teachers, non-teaching staff, administrators, and senior students in the high school. As an ethical
consideration, the author had no direct involvement in the distribution and collection of the filled-out
survey forms.
DATA ANALYSIS
The researcher classified, tallied and organized the information into tables, using qualitative and
quantitative descriptions. The statistical tools that were utilized were frequency, percentage, and
means with standard deviation to describe the questions. Frequency and percent were used for
nominal data. Means together with standard deviation were computed for questionnaire items on fivepoint and four-point rating scales. The following tables were used to evaluate the ordinal data:
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Table 1: The most and least effective aspect of digital learning and teaching
Likert Scale
Likert Description
Value Allocation
(1)
(2)
(3)
1
Least effective
1.00-1.49
2
Less effective
1.50-2.49
3
Effective
2.50-3.49
4
More effective
3.50-4.49
5
Most effective
4.50-5.00
Table 2: Overall satisfaction of digital learning and teaching
Likert Scale
Likert Description
Value Allocation
(1)
(2)
(3)
1
Strongly disagree
1.00-1.49
2
Disagree
1.50-2.49
3
Agree
2.50-3.49
4
Strongly agree
3.50-4.00
RESULTS AND DISCUSSION
The study was an assessment of the effect of digitalized learning and teaching on student engagement
and learning satisfaction. A survey was conducted to investigate the utilization of digitalized teaching
and learning and its effectiveness. The results obtained were put through statistical analysis and are
presented in the succeeding statements. The first table (please see List of Tables) shows the
classification of the respondents, with a total of 47 participants. The majority of the participants were
Grade 12 students. The succeeding table (table 2) presents the subjects taught by the respondents
alphabetically. Eleven courses or subjects were listed in the table. Table 3 describes the utilization of
digital media, also known in the school as “Genyo” learning, for teaching. The findings showed that
five out of 11 teachers used the digital approach to teaching; one administrator and one non-teaching
staff were amenable to the application of digitalized teaching and learning. Interestingly, the greatest
number of students either used technology and internet to support their learning or appreciated the
integration of the aforementioned in learning their subjects very much. The top three barriers in
digitalization (see table 4) were as follows: (1)”unstable internet connection”; (2)”weak signal”; and
(3)”availability of internet connection at home.” The level of effectiveness of the digitalized approach
in teaching and learning using the Likert scale is shown in table 5 – the table shows that it was more
effective compared to the traditional approach in teaching and learning. It shows a final mean figure
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of 3.74. The participants in general, as depicted in table 6, indicated that they would like to have
another school year of digitalized learning and teaching approach. The mean was 3.02, and the
interpretation was “agree.” The overall satisfaction rating of the 47 participants was 2.92, which was
interpreted as “agree.” This means that they were all satisfied with the digitalized approach. As per
comments of the respondents about the approach, table 8 showed the top two answers as regards the
advantages and disadvantages of using digital technology. “Flexibility” in completing assignments
was number one, with 28 respondents who voted, or around 59.57% of the total participants. This
was followed by “it is a requirement of the course.” Table 9 presents the top five choices of the
participants in respect of the most effective aspect of this approach. The number one answer was
“easily gets information and ideas.” Finally, in table 10, the least effective aspect of this approach
was “it has replaced old way of interacting inside the four-walled classroom.” This lesser interaction
between students and teachers paves way to more complicated issues in the younger generation.
Students nowadays are more dependent on technological access, leading to less dependence on books
in the library. The results also show that most teachers are still amenable to an in-person discussion
of the topics rather than taking advantage of social media or online communication platforms.
CONCLUSION
This research shows that technology with development in inevitable. The integration and utilization
of technology is affecting the present way of delivering information and teaching and a new breed of
students – the millennials. The results also gave some fascinating insights into the continuous use of
traditional teaching and learning in our present education system. Based on the results, depending on
the subject being taught, technology may or may not be applicable. Interestingly, the results showed
that the PE teacher used videos and audio to augment his teaching style and help students remember
certain topics. For theoretical subjects or courses, like philosophy and entrepreneurship, the use of
digitalized approach is not practical. On the other hand, others may view video material as a resource
to augment teaching and learning in the classroom. It is also interesting to note that some of the
respondents agreed that the digitalized approach could capture the interest of learners and help them
to be more engaged in classroom activities.
RECOMMENDATIONS AND DIRECTION FOR FUTURRE RESEARCH
The following recommendations are based on the study findings:
•
•
•
Unavailability of internet at home and in school is a significant barrier to integrating technology in the teaching and learning approach at the senior high school level of the subject
private high school. More research is needed to identify effective ways as to how to make
internet more available in schools and classrooms. Research should address structural an attitudinal barrier and how these might be overcome.
Weak signal and unstable internet connection proved to be another significant barrier to applying the blended-learning approach. Future research could explore possible ways in which
international telecommunication companies can be allowed to break the long period of oligarchy in the telecommunications industry. Research would also need to address monopolistic control of the industry, giving way to equal chances to all students, regardless of area and
economic status.
Non-teaching staff disagreed the application of the digitalized approach to teaching methods. Research may look into deeper issues such as lack of training in technology and adapting an e-learning educational system for the school. Research should assess training needs
and readiness of both teaching and non-teaching personnel to utilize technology.
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•
•
Technology and advancements have their own pros and cons. Research could be conducted
to get an equal footing for all types of students on the use and application of technology to
the current curriculum (K-12) without allowing the more emphatic way of addressing their
needs.
Further research could be conducted across public and private schools in the province(s) of
Pampanga and/or Bulacan
Acknowledgements
I want to express gratitude to the following persons for their cooperation and support : Pampanga
Central College Secondary Principal, Madam Alma Tan; Office Administrator, Madam Gadelyn
Aguilar; the School Director; faculty members of the Senior High School; non-teaching personnel;
and Grade 12 students.
REFERENCES
Bhandari, P.(rev.July,2022). What is quantitative research? Definitions, uses and methods.
https://www.scribbr.com/methodology /quantitative-research/
Biggs, J., & Tang, C. (2011) Teaching for quality learning at university (4th ed.). Open University
Press.
Bryman, A., & Bell, E. (2011). Business research methods. Oxford University Press. P. 15-50.
Donnelly, R. (2010). Harmonizing technology with interaction in blended problem-based learning.
Computer & Education, 54(2), 3503359. https://doi.org/10.1016/j.compedu.2009.08012
Engelhart, M. D. (1972). Methods of educational research. Rand McNally.
Gay, L. R. (2003). Educational research: competencies for analysis and applications (7th ed.).
Merrill/Prentice Hall.
Kothari, C. R. (1995). Research methodology. Wishawa Prakashan.
NMC Red Archive. (2012). Ruben Puentedura, Board Member. http://redarchive.nmc.org/rubenPuentedura-board-member.
Operio, Jennifer H. (May, 2019). Impact assessment of technology to a private college in Bulacan,
Philippines: mediating effect of hybrid approach. Paper presented at the 2019 IRES
International Conference, Manila, Philippines. IJMAS-IRRAJ-DOI-15507.
Poon, J., Royston, P., & Fuchs, W. (September, 2010). An examination of the critical factors for
developing a successful blended learning teaching method for RICS and CIOB accredited
courses. Paper presented at the RICS Foundation Construction and Building Research
Conference (COBRA 2010), Paris, France.
Puentedura, R. (2003, July 15). An introduction. http://www.hippasus.com/rrpweblog/archives
/000001.html.
Puentedura, R. (2014, September 24). SAMR and Bloom’s taxonomy: assembling the puzzle.
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https://www.graphite.org/blog/samr-and-blooms-taxonomy-assembling-the-puzzle
Puentedura, R. (2014, November 12). SAMR: first steps. http://www.hippasus.com/rrrrpweblog/
archives/2014/11/13/SAMR_FirstSteps.pdf
Smyth, S., Houghton, C., Cooney, A., & Casey, D. (2012). Students’ experiences of blended
learning across a range of postgraduate programmes. Nurse Education Today, 32(4),
464-468, https://doi.org/10.1016/j.nedt.2011.05.014
Students’ Handbook (2018-2019). Pampanga Central High School, San Agustin, San Simon,
Pampanga.
Tang, C. M., & Chaw, L. Y. (2016). Digital literacy: A prerequisite for effective learning in a
blended learning environment? The Electronic Journal of e-Learning, 14(1), 54-65. ISSN
1479-4403.
LIST OF TABLES
Table 1: Classification of respondents
Description
Frequency
Percentage
Administrators and NTP
7
14.90%
Faculty Members
11
23.40%
Grade 12 Students
29
61.70%
Total
47
100%
Table 2: Subjects taught
Subjects
Frequency
Percentage
Applied Economics
1
9.09%
Contemporary Philippine Art
1
9.09%
Earth and Life Science
1
9.09%
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Empowerment Technologies
1
9.09%
English
1
9.09%
General Mathematics
1
9.09%
P.E.
1
9.09%
Personal Development
1
9.09%
Philosophy
1
9.09%
Practical research 2
1
9.09%
TVL-Cookery 12
1
9.09%
11
100%
Total
Table 3: Utilization of hybrid learning in teaching
Answers
Administrators
& NTP
Faculty
Grade 12
students
Frequency
Percentage
Yes
2
5
25
32
68.09%
No
5
6
4
15
31.91%
Total
7
11
29
47
100%
Table 4: Barriers to utilizing hybrid learning
Barriers
Frequency
Percentage
1. Unstable internet connection
2. Weak Signal
15
31.91%
12
25.53%
3. Availability of internet at home
4. Availability of internet at school
5. Others: not applicable
to the subject
Total
8
17.02%
6
12.77%
6
12.77%
47
100%
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Table 5: Level of effectiveness of hybrid learning
Likert Scale
Likert
Description
Value Allocation
Frequency
(1)
(2)
(3)
(4)
1
Least effective
1.00-1.49
3
3
2
Less Effective
1.50-2.49
3
6
3
Effective
2.50-3.49
12
36
4
More effective
3.50-4.49
14
56
5
Most effective
4.50-5.00
15
75
47
176/47=3.74
More effective
Sum [(1)*(4)]/n
Table 6: Have another hybrid learning approach in teaching
Likert Scale
Likert
Description
Value Allocation
Frequency
Sum
(1)
(2)
(3)
(4)
[(1)*(4)]/n
1
Strongly disagree
1.00-1.49
4
4
2
Disagree
1.50-2.49
4
8
3
Agree
2.50-3.49
26
78
4
Strongly agree
3.50-4.00
13
52
47
142/47=3.02
Agree
Table 7: Overall satisfied with hybrid learning
Likert Scale
Likert
Description
Value
Allocation
Frequency
Sum
(1)
(2)
(3)
(4)
[(1)*(4)]/n
1
Strongly disagree
1.00-1.49
2
2
2
Disagree
1.50-2.49
10
20
3
Agree
2.50-3.49
25
75
4
Strongly agree
3.50-4.00
10
40
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Agree
47
137/47=2.92
Table 8: Advantages of using hybrid learning
Advantages
Frequency
Percentage
1. Flexibility to complete assignments
28
59.57%
2. Convenience
4
8.51%
3. It is a requirement for course
11
23.40%
4. The only available option
2
4.26%
5. Job responsibilities
2
4.26%
47
100%
Total
Table 9: Most effective aspect of hybrid learning
Most effective
Frequency
Percentage
1. Easily get information
and idea
2. Helps to understand lessons
3. Learners could work independently
4. More effective on students
5. Students can watch lessons repeatedly
6. More efficient learning
20
42.55%
7
14.89%
9
19.14%
3
6.38%
2
4.26%
2
4.26%
7. It helps students recall
topics
8. Students can easily be
motivated
Total
2
4.26%
2
4.26%
47
100%
Table 10: Least effective aspects of hybrid learning
Least effective
Frequency
Percentage
1. Less student-teacher interaction
2. A lot of fake news and
information
3. Abuse of technology
18
38.29%
25
53.19%
2
4.26%
4. More of a distraction
2
4.26%
Total
47
100%
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ONLINE GROUP SUPERVISION AS PEDAGOGY UNDER
EMERGENCY CONDITIONS: OPTIMISING ONLINE
COLLABORATION TOWARDS SELF-DIRECTED LEARNING IN
A SOUTH AFRICAN HEI
Brenda van Wyk
University of Pretoria (Brenda.vanwyk@up.ac.za)
Quraisha Dawood
Varsity College (qdawood@varsitycollege.co.za)
Abstract
The higher education institution (HEI) under study adopted a group supervision model for their
honours students doing research projects. Implemented correctly, group supervision pedagogy offers
opportunities for collaborative learning, addressing the challenges posed by one-on-one supervision
in respect of improved peer learning and ensuring equity in delivery. It demands a specific skill set
from supervisors in traditional face-to-face settings. In an emergency online environment, and
compounded by an inherited unequal ecosystem, these skills and desired outcomes require an indepth understanding of the nature of the learning continuum. Ideally, online supervision should guide
students in a group setting to progress and build competencies needed for self-directed learning where
the student actively takes responsibility for their learning. The goal is to instil self-determined
learning competencies for future readiness and success in a connected world. The pandemic posed
restrictions on movement and demanded an immediate shift from the existing approach to a fully
online mode. The model reported on in this study was implemented via the learning management
system two years prior to lockdown. Subsequent lockdowns accelerated the roll out, inter alia, to all
supervisors and students, as a compulsory mode of delivery. This mode change of delivery exposed
shortcomings in existing supervisory skills, connectivity and technological accessibility, research and
digital literacy competencies, and inclusivity challenges faced by all students, but more particularly
by students from disadvantaged backgrounds. Through a conceptual framework, drawing on the neoWeberian and Universal Design for Learning (UDL) approaches, this paper shows that the pandemic
posed significant inequality challenges. Based on qualitative data from interviews with supervisors,
substantiated by documentary data, the paper explores the nature and transition of supervision
pedagogy in an emergency remote ecosystem to achieving self-directed competencies using online
collaborative learning. Key requirements are recommended for the future success of group
supervision on the learning continuum.
Keywords: Supervision pedagogy, critical pedagogy, peer learning, group supervision, online
supervision, self-directed learning
INTRODUCTION
Postgraduate and research supervision is generally described in literature (e.g., Petrucka, 2019;
Maistry, 2017; Kanwal & Ahmed. 2021) as the process of guiding postgraduates throughout their
research by engaging in guiding communication so that they succeed in their research journey and
develop and transform into independent researchers. Ideally, the supervisor must mentor the student
to become both a self-reliant and self-determined researcher (Wingrove, 2020). Literature abounds
on the challenges faced during this liminal process where both supervisor competencies and student
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responsiveness are critical variables for success. Maistry (2017) laments the paucity of research on
postgraduate supervision in South Africa and stresses that much more must be done to build
competencies and skills of supervisors.
Although distance programmes made use of online supervision before lockdown, it was during the
outbreak of COVID-19 that many supervisors in HEIs were compelled to continue supervision online.
The pandemic exposed the inequalities in the South African education system; HEIs had to address
inherent problems such as digital exclusion, online pedagogy and digital fluency while resorting to
measures to continue online education and, in this case, online supervision. In an emergency online
environment, and compounded by an inherited unequal ecosystem, these skills and desired outcomes
require an in-depth understanding of the nature of the learning continuum at postgraduate level.
Ideally, online group supervision should provide guidance to students in a group setting to progress
and build competencies required for self-directed learning, where students actively take responsibility
for their own progress, learning and success. Tsotetsi and Omodan (2021) warn about the power
dynamic present in the supervision–student relationship where the student could be viewed as the
neophyte and the supervisor as authoritative expert. This could be a challenge, as the goal of
postgraduate supervision is to prepare students for self-determined learning to complete their research
project or report. Knowledge about the research process and research competencies for future
readiness and success of researchers must be achieved. Group supervision has been offered as an
avenue to bolster peer learning and to build research capacity. It is a concept that has increasingly
been introduced to build on the affordances of collaborative learning. The objective to get young
researchers ready for future and lifelong learning predisposes the need to guide them to become
independent and self-determent in their research learning.
The pandemic posed restrictions on movement and demanded an immediate shift from the existing
approach to a fully online mode. The change in relationship often occurred without having the
requisite preparation for it, compounding the challenges in an existing unequal landscape (as reported
by Van Wyk et al., 2020). This mode change of delivery exposed shortcomings in existing supervisory
skills, connectivity and technological accessibility, gaps in research and digital literacy competencies
and inclusivity challenges faced by all students, but more particularly by students from disadvantaged
backgrounds.
Through a conceptual framework, drawing on a neo-Weberian and Universal Design for Learning
(UDL) lens, the study illustrates that the pandemic posed significant inequality challenges. Based on
qualitative data from a focus interview with a group of supervisors and substantiated by documentary
data, the paper explores the liminality of supervision pedagogy and praxis in an emergency remote
ecosystem. It explores the potential for achieving self-directed competencies by online collaborative
learning. The paper further recommends key requirements for the future success of group supervision
on the learning continuum.
The aim of this study was to explore an existing group of online supervisors’ perceptions and
experiences of striving to supervise research projects against the backdrop of a pandemic in a lived
experience. The study also set out to ascertain whether a collaborative learning online supervision
experience could counteract the negative aspects of the supervision power dynamics.
BACKGROUND AND LITERATURE REVIEW
The study was conducted at a private HEI in South Africa among a group of supervisors doing online
group supervision of students conducting research projects during lockdown. The case under study
reported to have implemented their learning management system (LMS) two years prior to the
COVID-19 pandemic and lockdown of universities in March 2020 (Van Wyk et al., 2020). Subsequent
lockdowns accelerated the roll out, inter alia, to all supervisors and students, as a compulsory mode
of delivery. The HEI started group supervision for their Psychology Honours research projects.
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Supervisors are under increasing pressure to guide an ever-growing number of students who lack
literacy skills and experience in writing logically and academically. Implemented correctly, group
supervision pedagogy could pave the way towards collaborative learning, addressing the challenges
posed by one-on-one supervision in respect of improved peer learning and ensuring equity in delivery.
It demands a specific skill set from supervisors in traditional face-to-face settings.
Foundational constructs of supervision
Critical pedagogy and supervision
According to Qureshi and Vazir (2016), the primary focus of research supervision is on discipline
content knowledge and, presumably, the research expertise of a supervisor, but they lament that
pedagogical content knowledge of research and supervision praxis is often negated to the detriment
of the student:
It does not take into account that supervision is more than overseeing students produce written
research reports; it is a complicated and intensive form of one‐on‐one teaching of research
which takes on a unique form of sustained interaction over at least one and a half years…
(Qureshi & Vazir, 2016, p. 95)
Supervision pedagogy through the lens of critical pedagogy has a place in the South African learning
ecosystem. Overcoming inequalities and oppression is at the heart of critical theory and critical
pedagogy. The Brazilian philosopher and educator Paolo Freire is the founder of critical pedagogy
theory. Looking at power dynamics in education, the educational philosophy critical pedagogy applies
concepts of critical theory (Freire & Ramos, 1970). In turn, critical pedagogy sets out to emancipate
through critical consciousness. When achieved, critical consciousness encourages individuals to
effect change in their world through social critique and political action towards self-actualisation.
Supervisor attributes and competencies
Reported research (including the studies of Maistry, 2017; Terentev & Dzhafarova, 2020; Tsotetsi &
Omodan, 2021) stresses the importance of effective research supervision of research output – not just
is it of major importance to increase completion rates but also to produce credible research and build
capacity among young academics.
Attributes and qualities expected of supervisors include a deep knowledge of the discipline, the ability
to give constructive feedback, and being approachable. Doing online group supervision is a
challenging and complex task (Maistry, 2017; Lawrence, 2019). Maor and Currie (2017) add that
group supervision success depends on the following:
• communicating and agreeing on roles and realistic expectations;
• creating a structure to inform the process;
• generating research output and scholarship;
• having set goals and focusing on the end result;
• creating the space where groups could interact meaningfully.
Over and above knowledge of the research process and research literacy acumen, online supervisors
are burdened with the need for digital fluency in navigating and managing the online setting.
Supervisors seldom receive additional training and development, and supervision is learnt through
practice. This poses challenges to new supervisors, who often lack in-depth research experience and
research literacies. Maistry (2017, p. 19) calls this phenomenon “parallel learning” and warns that
there is a real threat that may impact student attributes and leave young academics without the
requisite deep conceptual level of research. Maor and Currie (2017) reported on studies conducted in
Australia and Finland and concluded that the praxes that stood out throughout were:
•
•
the importance of communication and dialogue between students and supervisors;
deploying collaborative-based technology, such as online meeting platforms;
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• navigating and emphasising being part of a collaborative community.
Human agency in an online setting is critical, and Tsotetsi and Omodan (2021) warn against the
inability of supervisors to sustain connectedness and understanding, especially when students’
circumstances change, as many supervisors can testify is what occurred during COVID-19.
Group supervision
Research on group supervision of postgraduate research has been reported since 2000. McFarlane
(2009) posits that the time constraints of supervisors against the growing number of students is a
reason to move to group supervision. Maistry (2017) points out that there is a period of liminality and
dissonance where supervised students are particularly anxious and fear failure. This period of
transition must be carefully managed, with due cognisance that students may display a range of
behaviours of what they feel they are expected to do without achieving long-term development.
Maistry (2017) alludes to core threshold milestones that supervisors must consciously instil and
mentor. The incorporation of communities of practice, as theorised by Wenger (1999), is offered as
an avenue to navigate the transition to becoming researchers in their own right (Maistry, 2017).
Supervision on the learning continuum
Supervisors are often not sensitised to actively mentor students to become future-ready and selfdetermined in honing their skills as future researchers. They require intrinsic motivation, and the will
to collaborate and engage for the inherent rewards of the behaviour itself plays a key role in selfdetermination theory (Peters & Romero, 2019). Self-determined learning (SDL) hinges on autonomy
and competence. It requires a level of maturity in taking responsibility for one’s success. Blaschke
(2012) describes it as a process in which learners take ownership and responsibility, recognising their
research literacies and learning needs, identifying learning resources, implementing problem-solving
strategies, and reflecting on the learning processes to challenge existing assumptions and increase
learning capabilities.
Challenges of online learning and online group supervision
Online group supervision is a more recent practice, and Maor and Curry (2017) explain that it is
dependent on connectiveness, including online meetings through Skype, e-mails, and short message
systems. They report that supervision became more participatory when research communities of
practice were formed and resulted in more teamwork and collaborative learning (Maor & Currie,
2017, p. 14).
McFarlane (2009) alludes to the resistance of supervisors to engage in group supervision and ascribes
this to ineffective time management and the inability to manage social and group diversity often
prevalent in the South African context. In a more recent South African study, Mhlahlo (2020) reported
that inadequate academic literacy among South African postgraduate students remain a stumbling
block in South African HEIs. He warns that where this gap remains unaddressed, students may feel
marginalised and excluded (Mhlahlo, 2020).
The online environment calls for an additional set of skills. The complex and multifaceted aspects of
digital exclusion, or “digital inequality”, as Zheng and Walsham (2021:2) suggest, compound longstanding social inequalities that are reproduced in a recurring cycle between social and digital
inequalities (Park & Humphrey, 2019:938). This subjugates certain members of society based on
exclusion and erects parameters around those who reap the benefits of inclusion. Park and Humphrey
(2020) further deliberate that social exclusion exists where students cannot collaborate and participate
fully due their level of education, location, economic status, language, gender, or employment. Owing
to the recurring cycle of inequality, social exclusion also implies a lack of control over one’s status in
society, and little potential for social mobility prevails. Compounding this is digital exclusion, which
is the inability to take part in society due to a lack of access to contemporary digital technology,
including access to social media. Essentially, the exclusionary nature of society and digital
technology, despite success in automation and information systems, creates gulfs of inequality
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between members of society. Debates about digital inequalities are no longer restricted to who has a
personal computer and who does not; rather, it is a fact that people can “no longer play a meaningful
role in contemporary society without using digital technology” (Van Dijk, 2020).
In line with the arguments of neo-Weberian proponents, social and digital inequality and exclusions
result in the social position of individuals in society based on power, social structures and access
(Saks, 2016).
CONCEPTUAL FRAMEWORK
The complexities of a fully inclusive design for guiding young researchers in an unequal learning
ecosystem are immense. Not only is South African HE still battling continued eradication of past
inequalities, the ubiquitous and disruptive technological changes and the unprecedented pandemic
were exasperating barriers and challenges. It stands to reason that a single approach and frame would
not support these complexities.
Mehta and Aguilera (2020) remind us about Freire’s motivation and conviction in aspiring critical
pedagogies to address the dehumanising effect of exclusion. Research in critical theory and critical
pedagogy has offered solutions in the past, and strength can be drawn from this seminal work to
address the identified problem of the case at hand. Value was derived from components in the neoWeberian framework and Universal Design for Learning (UDL).
Considering the affordances of neo-Weberian principles as foundation and point of departure
Social stratification has long been a concern for neo-Weberian theorists, who traditionally view
divisions in society along racial, economic and gendered lines. Further, the pandemic has exposed
inequalities in society, necessitating a relook at the neo-Weberian framework to contemporary South
African society, paying particular attention to inequalities that have arisen in the digital sphere in the
context of COVID-19. The neo-Weberian approach looks at three components of equality in society:
class, status and power (Ragnedda, 2016). The framework is particularly suitable for research affected
by fast-changing modern technologies and inequality and fluctuations in society.
In support of the deconstruction of prevailing power dimensions, Zheng and Walsham (2021:2)
elaborate that digital inequality operates at the “intersection of multiple fracture lines of difference
that mediates the various spaces of inclusion and exclusion”. Thus, it is pertinent to note that
inequalities are interconnected, such that there is a spectrum along which exclusion and shelters of
inclusion exist rather than a clear digital divide as previously theorised.
This application of the neo-Weberian approach is particularly relevant to the South African context,
which bears the brunt of a legacy engrained in racial and geographic segregation, and contemporary
inequalities in access to technology and digital education.
The value of UDL as lens for supervision
Sanger (2020) describes UDL as an inclusive pedagogy where the aim is to make learning as
accessible and welcoming to all students as possible. The value of UDL to frame online learning has
been heralded of late. The three networked principles underpinning UDL that can also be applied to
supervision are as follows:
•
•
•
Affective network – The “why” of supervision and entails motivation, engagement, purpose,
reflection and self-regulation to create learners who are purposeful and motivated;
Recognition network – The “what” of supervision and involves background knowledge, vocabulary, visuals, information processing and contextual understanding to create learners who
are resourceful and knowledgeable;
Strategic network – The “how” of supervision and includes goal setting, planning, strategies
and monitoring to create learners who are strategic and goal directed.
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These qualities are sought by online group supervision. Authors (Sanger, 2020; Wichmann-Hansen,
Thomsen, & Nordentoft, 2014) highlight the value of peer-to-peer learning in an inclusive learning
environment, such as that offered in group supervision. It is during these sessions that students are
afforded meaningful exposure to the theoretical and methodological approaches of their peers under
the guidance of their supervisor. The desired outcome of online group supervision is to motivate and
support novice researchers to become confident, self-reliant, and self-determined students and
researchers. Building on the foundational insights of the neo-Weberian model, a scaffold conceptual
framework was derived to frame this study.
Figure 1: A conceptual framework for studying online research supervision
The combined conceptual framework provides a lens to guide the study and focus on inclusivity
towards self-determination of young academics being supervised as well as on social and cultural
levels of inequality experienced by many South African students. It allows for critical theory to inform
critical pedagogy. The framework is explained in figure 1 above.
RESEARCH DESIGN
Sampling, data collection and analysis
Qualitative data were collected through a focus group interview session with a group of postgraduate
supervisors who had to conduct group supervision online and guide their students to conduct their
research projects online. Vaismoradi et al. (2016) state that qualitative research – as a group of
approaches for the collection and analysis of data – aims to provide an in-depth, socio-contextual and
detailed description and interpretation of the research topic. Further, focus groups allow for
clarification of questions, the emergence of topics that the researcher may not have anticipated, and
rich discussions that provide in-depth data “unmatched” by quantitative methodologies (SIS
International Research, 2020).
Eight supervisors, responsible for postgraduate honours research students at the private HEI’s
campuses across South Africa, were purposively selected and invited to participate in the one-hour
focus group. All accepted, signed the informed consent and participated. An observation schedule
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was used with a focus group interview schedule. Observation in qualitative research can be described
as the systematic description of participant behaviour and, in this case, the online setting chosen for
this study (Bezuidenhout, Davis, & Du Plooy-Cilliers, 2014). One of the researchers facilitated the
focus group, while the other noted observations and clarified where necessary.
Observations enabled the researcher to describe the existing research environment using their senses
to create a resemblance of the group. Participant observation allowed the researcher to be part of the
focus group activities and to get a better understanding of the phenomenon under study. The
observations allowed for triangulation of data collected during the interviews. The qualitative data
collected during the focus group interviews were analysed using thematic reflective analysis.
PRESENTATION AND DISCUSSION OF FINDINGS
The study set out to gauge and report on a group of supervisors doing online group supervision. The
focus group interview was recorded and transcribed. The transcript was audited as a truthful copy of
the recordings. Findings were analysed thematically.
Thematic analysis is related to phenomenology, as it focuses subjectively on the human experience
(Noon, 2018). This approach focused on the participants’ reported experiences, perceptions, opinions,
and feelings as the object of study. The data that emerged from the transcribed recording, field notes
and observation schedule were triangulated.
According to participants, students mentioned that there was a burden to ensure that the online
research reached the right participants and recipients. Also, they could not ensure that research
subjects were in a space where they felt comfortable to share confidential information.
On resistance to group supervision in an online setting:
Findings indicated that although supervisors had been trained in online pedagogy and supervision,
there was still a margin of resistance and a preference for face-to-face supervision:
I think a lot of things happened across a number of honours supervision, hmm, it is easier to
interact face to face. (Participant 1)
And
I agree with what XX [identified as participant 1] has to say. It is a problem with lack to seeing
and interacting with students. That was first problem, hmmm… And then technical problems.
They were new to using technology as we were. It was definitely more difficult online.
(Participant 2)
On inclusivity in an online supervisory setting:
Participants in the focus group interview reported that many of their students were from marginalised
communities, where the blurring of home and studies was experienced negatively. Participants said
the following with regard to the challenges of digital exclusion and access to the required technology:
With poor connection experienced by some students you would find that they often miss chunks
of information. Where there were electricity cuts, I found that the flow of though was disrupted,
and you see someone go offline, trying to come back on and loose that strand of logic.
(Participant 3)
We have a WhatsApp group to support students. Or… Finding that intrinsic motivation… for
some student’s home is in a rural area…So, you had to wait for them to get into town to where
they could listen to a recording … and …You really had to find that balance…Some had great
connectivity and some not. (Participant 3)
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On digital fluency:
Findings suggest that not just students faced challenges of digital literacy; supervisors also reported
concerns about their own competencies:
I think the often happens easier face to face, but in a virtual space it is much trickier… we may
have cameras on or cameras off … There are distractions that may be an extra burden on
students. We do not know the circumstances of the student online, and how open and honest
they can be…we don’t even know.
… I think [of] the challenges of being a supervisor… we go the extra mile. There are a lot of
compounding variables…Our honours classes have grown very quickly – it is difficult to say
which had the impact – maybe because I am not that comfortable with technology…I did feel
that I was less engaged online. (Participant 5)
On building trust relations online:
While the face-to-face environment allowed supervisors to build trust relationships with students and
facilitated relationships between students, the online environment impeded the usual. Participants 4,
5 and 6 lamented this as follows:
I think building on what my colleagues have said…, from my own experience as being
supervised for my masters…you learn to adapt to your teaching styles… You build a
relationship with your supervisor, even if this is not as daunting on honours level…the online
detract from that ability. The way we convey the information … it became blanket vanilla way
offering of teaching… you have an introspective look… are we doing what we should…
(Participant 4)
And
It takes some time to relax and then trust was not built because of strangeness of online we
never really got to build that, never got to the point where people could trust each other. They
might go to the canteen, have coffee together, And the never socialised as class… so I think
(Participant 5)
…I think made face to face classes where they see each other outside of class and where they
can socialise…THAT leads to collaboration… and... and... creates that trust… (Participant 6)
On group facilitation skills:
Participants all reported that online supervision required a measure of role extension and asked much
more from them than the face-to-face sessions. They reported that some students would be hesitant
to voice opinions and participate, while others could dominate conversations.
On collaborative learning:
Participants reported that a level of socialisation among students facilitated collaborative learning,
and they lamented that the online environment did not accommodate this:
…And the never socialised as class… so I think THAT… and that I think made face to face
classes where they see each other outside of class and where they can socialise…THAT leads
to collaboration… and…creates that trust…They never really had that online and never had
these in between chats. Dare I call it social distancing.
… it took me a while to get used to it… some of that comfort was problematic as habits had to
be undone…. Some students avoided to participated and has excuses such as constantly
complaining their mikes are not working…whereas, in class it is easier to get students
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involved… online they could effectively disappear.
On human agency in online supervision:
This is going to sound heartless…I did not give emotional support. I did not want to open
myself… I did not want to… I have never really reflected on this. I think it was a mechanism
to protect myself, I did not want to go down that rabbit hole… I did not see a need for emotional
support… (Participant 1)
The participants, being academics and supervisors reporting on their experiences, displayed a good
understanding of the HEI’s codes, policies and research ethics. They could identify, elaborate and
report on research ethics risks posed by doing online research. Participants reported similar
disengagement during online and group supervision sessions conducted via the LMS. The identified
themes coded after the thematic analysis correspond with the constructs of the neo-Weberian
stratification of three class systems, namely wealth, class and power.
It is clear that supervisors in this study needed more preparation, support and training to successfully
mentor and supervise students online. Sadeck (2016) posits that a focus must be more on e-teaching
and facilitation than on e-learning in an online setting. He distinguishes this as follows: whereas elearning can be seen as technology enhanced teaching and learning for students, e-teaching focuses
on what the lecturer does and how they apply technology to pedagogy (Sadeck, 2016).
The LMS is effective for continued e-learning, but research and supervision were not geared for
online engagement. The HEI has embedded digital sources and services to assist students, but these
sources must be advocated to improve usage. It is clear that continuous lecturer and supervisor
training and support are needed to manage difficult online situations, such as disengagement, dropouts
and especially plagiarism and reported research ethics problems.
The finding and observations of this study are in line with the study that Tsotetsi and Omodan
conducted in 2021: the researchers observed that supervisors were at times overwhelmed by the
supervision load. In this case, they were hampered by the number of hours allocated to do supervision.
The findings of the study are in line with similar and previously reported research (e.g., Devkota,
2021). Moreover, the findings correlate with the desk research reported by Ragnedda and Muschert
(2015) in which they justify the usefulness of the neo-Weberian framework to explore the
complexities of the digital divide as a social phenomenon. Online group supervision posed challenges
to the participants in this study. Both elements of group supervision as well as the online setting were
said to be improved. The findings of this study are in line with similar studies that found that where
research supervision is approached as a pedagogy, success for students is higher (Engebretson et al.,
2008). In online supervision, challenges are faced with establishing human agency, continuation of
meaningful collaboration and the management of diversity. Participants echoed the sentiments
expressed by Qureshi and Vazir (2016) that alluded to the negations of the various technical roles a
supervisor must take on to facilitate students’ progress (e.g., instructor, mentor, coach, advisor and
councillor, among others, which are all teachers’ roles).
Wittman and Olivier (2021) concur with Guglielmino (2013) (as cited in Wittman & Olivier, 2021)
that information and technology grow exponentially, and they remain important to cultivate selfdirectedness in educators to transfer these skills to students in the attainment of lifelong learners. For
this to happen, students and young researchers must take responsibility and be motivated.
Responsibility and collaborative control of the cognitive (self-monitoring) and contextual (selfmanagement) processes in constructing and confirming meaningful and worthwhile learning
outcomes. (Wittman & Olivier, 2021, p. 74)
Al-Shahrani and Mohamad (2018) posit that these qualities and competencies must first be present in
the supervisors. Mehta and Aguilera (2020) warn about the essence of creating a supportive learning
environment and allude that critically framed approaches are essential to humanising critical digital
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pedagogies and supervision towards improved inclusive learning environments across online
contexts.
RECOMMENDATIONS AND CONCLUSION
The key recommendation stemming from this study is that online supervision needs to form part of
the continuum of learning towards lifelong and self-determined learning. Supervisor training should
focus on humanising research capacity building in an online environment. Supervisors should be
sensitised to the complexities and challenges of inequalities faced by postgraduate students doing
research via online group supervision. The exposure of both students and supervisors to an
institutional research culture would greatly enhance chances for successful supervision praxis.
Although the focus group scenario does not allow for generalisations per se, it is clear from this study
that supervisors felt that they were not fully supported nor equipped to do online group supervision.
Subsequently, the deconstruction of oppressive components present in supervision may not succeed.
Taking into account that in their seminal work, Freire and Ramos (1970) stressed the importance that
education must prepare students for meaningful civic participation, it stands to reason that the
outcome of postgraduate research should move in the direction of self-directed learning. However,
this may not immediately be achievable in research projects on NQF 8; it serves as a liminal pathway
in the transition to and process of becoming self-determent and self-reliant academic contributors.
This document is released under a Creative Commons by SA, as indicated in figure 2.
Figure 2: The Creative Commons by SA icon
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EVALUATION OF DIGITAL EDUCATIONAL INITIATIVE
DURING THE COVID-19 PANDEMIC USING CONCERNS-BASED
ADOPTION MODEL
Divya C. Senan
Assistant Professor, Department of Education, University of Kerala, India (mail2divyacsenan@gmail.com)
Seenathmol, N.
Research Scholar, Department of Education, University of Kerala, India
Jayapraveen, J.
ICSSR Doctoral Scholar, Department of Education, University of Kerala, India
Abstract
The World Health Organization (WHO) regards the COVID-19 pandemic as the most challenging
health crisis the world has ever faced (UN Policy Brief, 2020). It has affected all sectors of society
badly. The pandemic has forced education sectors to shift dramatically to virtual and blended modes
of teaching and learning with the help of various ICT tools. The crisis has stimulated innovation in
the field of education. India has also seen various innovative approaches and solutions of ICT-led
educational initiatives to reach out to everyone, including the most marginalised populations who
may lack access to education, digital devices and connectivity. Kerala, the most literate state in India,
has paved the path to effectively using technology to ensure continuous learning by enabling universal
access to ICT infrastructure for remote learning. The Government of Kerala launched a digital
educational initiative named “First Bell” that was broadcast on VICTERS Educational Channel, an
educational television channel launched in 2005 with the vision of taking the benefits. The team effort
of the Director of General Education, State Council of Education Research and Training (SCERT),
Samagra Shiksha Kerala (SSK), State Institute of Educational Technology (SIET), and Kerala
Infrastructure and Technology for Education (KITE) ensured the successful implementation of the
new culture of learning. Apart from television, the sessions were made available on the web page of
KITE, on Facebook, and on YouTube. The concerns-based adoption model (CBAM) was used to
collect survey and qualitative interview data to inform the implementation of the “First Bell”
programme. This paper presents data collected through CBAM and the analysis that identified and
interpreted both the concerns and extent of the digital programme.
Keywords: First Bell programme, digital learning, concerns-based adoption model
INTRODUCTION
The traditional way of learning offers students little scope of engagement, as the dynamics of a
traditional classroom comprise students, textbooks and educators for learning. On the other hand, the
digital education system provides a wide variety of options for students to learn. Digital learning can
be defined as the use of computer and internet technologies to deliver a broad array of solution[s] to
enable learning and improve performance (Ghirardini, 2011). The limitless availability of images and
video content, virtual reality, interactive sessions and many more make the digital learning method
more engrossing and smoother for students to grasp. Digital education systems and technology
permeate the gaps, while in traditional classrooms, teaching drops back. The former offers several
advantages for students, including the opportunity to study flexibly and from a place that suits them.
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The blend of technology and education has made education available to all by addressing the
constraints of traditional models of learning.
As the impact of COVID-19 spread across the globe, schools started to quickly adapt to the online
way of doing things. Though the importance of virtual classrooms was not clear before, it has now
captured considerable attention. With this sudden shift away from the classroom in many parts of the
globe, the adoption of digital learning will continue to persist in the post-pandemic education
scenario. The governments of most countries ordered to lock down and asked people to stay at their
homes due to the danger of this virus to human life. In this period, teachers in different countries
started using e-learning to teach students. While the whole world is fighting the invisible enemy
(COVID-19), which has kill thousands of people around the globe, the teaching and learning process
moved on by using digital learning technologies.
DIGITAL EDUCATION: THE INDIAN SCENARIO
With the technological advancement in the past decade, “digital classrooms” have become more
prevalent and relevant in India. The Government of India launched the Digital India initiative in 2015
to ensure that the services of the Government are made available electronically to all citizens. This
objective is achieved by strengthening online infrastructure and improving internet connectivity
across the country. The major objectives of the Digital India initiative were the development of a
stable and secure digital infrastructure, delivering government services digitally, Universal Digital
Literacy, et cetera. The programme envisioned inclusive growth in all sectors. The e-education
initiative started as part of Digital India programmes provided through online education in remote
and urban areas, using smartphones, apps and internet services. It also included plans to connect rural
areas with high-speed internet networks and improve digital literacy. The comprehensive initiative
called “PM e-Vidya” was launched in May 2020. This initiative aims to unify all efforts related to
online education to enable equitable multimode access to education. Another significant initiative is
DIKSHA (Digital Infrastructure for Knowledge Sharing) which focuses on “one nation, one digital
platform” for school education in India. Apart from this, the Government also started TV channels
for mass reach of eLearning. Swayam Prabha – a series of 32 channels – was launched. E-textbooks
were launched under ePathshala, where the government provides a plethora of educational content
(especially NCERT). The Government has taken multiple initiatives in 2020 for the improvisation
and accessibility of digital education, including radio broadcasting, for the differently abled.
KERALA MODEL DIGITAL LEARNING INITIATIVE
The State of Kerala, in the southwestern part of India, is the most literate state in India and holds a
distinctive position on the development map of the world. The State can be compared with many
developed nations in respect of its unique socio-economic and demographic characteristics
(Ramachandran, 1996; Oommen, 1992, 1999, Vol. 1 & 2). The State has also paved the way in
effectively using technology to ensure continuous learning by enabling universal access to ICT
infrastructure for remote learning and has become the first state in the country to have high-tech
classrooms in all of its public schools. The schools in Kerala are categorised by three funding models:
government schools are funded by the government; aided schools receive government funding for
teachers’ salary but not for school infrastructure; and unaided schools are funded solely by the private
sector. All receive institutional support from the State Council of Educational Research and Training
(SCERT).
The following are the various initiatives of the government towards digitalization of education in the
state:
•
•
•
all government and aided schools in the state are equipped with ICT hardware, broadband
connectivity and infrastructure;
information technology has become a compulsory subject in the school curriculum;
all teachers are trained in ICT and are regularly updated;
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•
•
•
•
active participation of teachers and students in computer literacy programmes;
teachers create most of the ICT content;
students are exposed to the latest trends in ICT;
several academic and scholastic e-Governance applications are put in place by IT@School
Project.
Hi-Tech School Initiative of Kerala
The Public Education Rejuvenation Mission of the Government of Kerala aims to bring all classrooms
up to worldwide standards, and the “Hi-Tech School” programme is a significant component of this
initiative. As the pioneer of ICT-enabled education in the state for more than a decade, Kerala
Infrastructure and Technology for Education (KITE) was selected as the implementing agency for the
scheme. KITE created a programme that has modernized 450 000 classrooms in 4 752 schools. The
4 752 schools comprise government and aided higher institutions, advanced placement and vocational
advanced placement schools. Each high-tech classroom has a laptop, a ceiling-mounted multimedia
projector, HDMI cables and faceplates, a whiteboard/projection screen, USB speakers, high-speed
broadband internet, and access to the Samagra Resource Portal. The advanced IT labs are equipped
with laptops, a sound system, and multifunction printers. In addition, each of the 4 752 schools
received a 42-inch LED television, a webcam with Full HD resolution, and a DSLR camera. The IT
labs and classrooms are network-connected via a central server in the lab, allowing for the sharing of
information. KITE has been an advocate for free and open-source software for decades, as it allows
for the unrestricted creation, editing and sharing of educational information. KITE has built its own
operating system, IT@School Ubuntu, which has several educational apps.
ICT: Access and availability
The report on the implementation of the Kerala Government’s Hi-Tech School programme showed
that 83% of teachers had computer (laptop/desktop) at home, 70% had internet connectivity at home,
and 99% had access to a smart phone. Of the instructors, 40.30% had computers in their classrooms,
while 39.17% had computer labs that they could arrange for their pupils to use. Additionally, 12.55%
of educators had a portable laptop. The availability of instructional technology in Kerala schools is
seen in the graph below.
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Figure 1: Technologies available for teaching
FIRST BELL PROGRAMME
The COVID-19 pandemic has virtually made social life come to a standstill and has consequentially
affected mobility. The spread of the pandemic has forced the education department to proactively
plan new initiatives to cope with the unprecedented situation. Against this background, the
Government of Kerala introduced an online platform for the teaching–learning process. Kerala
Government started a virtual class initiative called “First Bell”. The virtual classes for state school
students were organized so that education was imparted amid the COVID-19 crisis. The “First Bell”
programme was aired on VICTERS educational channel. This format is not intended to compensate
for the minimum instructional days that a school year should hold as per the provisions of the RTE
Act (2009) and the Kerala Education Rules, but rather to keep abreast of the process of education,
which the students would have otherwise undergone under normal conditions. To avoid any kind of
discrimination, especially against marginalized groups, government-formulated programmes, with
the help of the community, were telecast to ensure access to all children to attend the digital classes,
and it was decided that each child must come under the ambit of the programme. In addition to
television, the sessions were made available on www.victers.kite.kerala.gov.in, on Facebook, and on
YouTube. For students who could not view the class due to power failure or otherwise, the classes
could be downloaded and used later or be repeatedly viewed, thereby ensuring that no student was
denied availability of the classes, thus, envisaging a continuing process of education.
Specific ICT online training was provided to 81 000 primary school teachers. This training was
completed within five days by effectively making use of hi-tech facilities in schools. The teachers
used Samagra Resource Portal (www.samagra.kite. kerala.gov.in) for self-learning, with the help of
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numerous digital contents available in the portal. Moreover, necessary support systems were set up,
such as video conferencing, with a mentor for a fixed number of schools, social media, and help desks
for clearing and monitoring doubts. Massive state-level training for teachers was introduced through
KITE VICTERS educational channel that was simultaneously streamed on the Web and mobile
phones.
THE CONCERNS-BASED ADOPTION MODEL
CBAM is a conceptual framework that provides tools and techniques for facilitating and assessing
the implementation of new innovations or reform initiatives. This model applies to those experiencing
change; this may include policy-makers, teachers, parents, and students (Hall & Hord, 1987; Hord,
Rutherford, Huling-Austin, & Hall, 1987; Loucks-Horsley & Stiegelbauer, 1991). CBAM has a
diagnostic component and a prescriptive component. The diagnostic component comprises three
dimensions:
•
•
•
stages of concern (SoC) deal with the feelings of individuals involved in change;
levels of use (LoU) describe how individuals interact with a new programme;
innovation configurations are the adaptations made to the programme.
Concerns-based models do not focus on the why of the innovation but on the assumption that an
understanding of the concerns and adoption process can facilitate success with the adoption of new
technology. The theoretical framework of this study was based on the three diagnostic dimensions of
CBAM: stages of concern (SoC); level of use (LoU); and innovation configuration (Hall & Hord,
1987, 2011).
Seven distinct levels of concern have been identified. The first stage is called “unconcerned”.
Respondents show little concern about innovation at this time (George et al., 2006, p. 8). The first
stage of the innovation process is known as “Informational” and it involves an individual’s curiosity
about gathering facts and studying the basics of the topic. In stage 2 (Personal), the individual begins
to worry about how the invention may affect them personally. During stage 3 (Management), the
focus shifts to how the individual performs tasks. Fourth stage (Consequence) examines how
students’ specific worries would be affected by innovation. In the fifth stage (Collaboration), the
innovator begins to consider working with others to implement the new idea. Stage 6 (Refocusing)
involves individuals modifying the invention to increase its usefulness.
The SoC questionnaire (SoCQ) was used in the quantitative phase of the study to identify teachers’
concerns about the First Bell programme. The Innovation Configuration and LoU interview protocol
were used in the qualitative phase of the study to explore teachers’ involvement in the First Bell
programme.
RESEARCH QUESTIONS
The main purpose of this study was to assess the concerns of high school teachers in Kerala, India,
about the First Bell programme. The goals of the present study were:
i.
ii.
to identify peak concerns of teachers when implementing the First Bell programme;
to determine teachers’ perspectives of the use of ICT-enabled instruction during the First Bell
programme.
To achieve the above goals, the following research questions guided this study:
i.
ii.
Which areas of peak stage concern (as described in the SoCQ) are most prevalent among
teachers in the use of ICT-enabled instruction during the First Bell programme?
How do teachers of Kerala describe their experiences during the First Bell programme?
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RESEARCH METHODOLOGY
A mixed-methods approach was used, blending quantitative and qualitative methods, to discover the
level of teachers’ concerns about implementing the First Bell programme. The study sample consisted
of 200 secondary school teachers from Trivandrum district. Researchers used the random sampling
technique (McMillan & Schumacher, 2010). A Google Form was developed and sent via a link to all
of the participants to complete the SoCQ survey.
The 35-item SoC questionnaire (SoCQ) (eight-point Likert scale) was used to evaluate the concerns
of teachers during the implementation of the First Bell programme. By picking a number between 0
and 7, teachers expressed their level of concern about the First Bell programme. The raw results of
each questionnaire item were transformed to percentile ratings, which indicate the seven levels of
concern among teachers. According to the SoCQ handbook, the percentile score represents the
relative level of concern at each stage. The greater the score, the more pressing the issues. “The lower
the score, the fewer severe the concerns at that time” (George et al., 2006, p. 32). The approach to
assessing the SOCQ score was based on the suggestion made by George et al. (2006) in their
handbook.
DATA ANALYSIS PROCEDURE
Table 1 shows the general characteristics of teachers who participated in the online survey.
Table 1: General characteristics of the online survey respondents
Education Status
Post-graduate degree
67%
Bachelor’s degree
26%
Doctoral degree
1%
Other
6%
Discipline
Science
52%
Arts
39%
Commerce/Management
7%
Other
2%
ICT Access and Usage
Computer (laptop/desktop) at home
83%
Internet Access at Home
70%
Smart Phone Access
99%
Research question 1: Which areas of peak stage concern (as described in the SoCQ) are most prevalent
among teachers during the First Bell programme?
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Using descriptive data, the highest level of concern was identified. The peak level of concern has the
highest score of the seven phases. To determine the highest and second highest stage scores in the
category of peak stage scores, the researcher followed the SoCQ manual’s instructions. The
researchers averaged the raw score for each stage based on group data and referred to these averages
as the percentiles score. The percentile score is a predefined score assigned to each raw score
produced by the SoCQ. Individual and group peaks were compared to demographic information and
free-form questions. This phase allowed the researchers to investigate why different stages were
characterized by less or more significant concerns.
The analysis of the top two issues offered further information about the kind of concern among high
school teachers. As seen in table 2, the majority of respondents (26.5% or 53 respondents) scored
highest on stage 0 (unconcerned). The overall number of responders for stage 5 (collaboration) and
stage 1 (informational) was relatively comparable (48 and 49). There were no responses from
instructors to the stage 4 (consequence) or stage 6 questions (refocusing).
Table 2: Frequency of peak (highest) stage of concern among teachers
Highest Stage of
Concern
Number of
Respondents
Percent of
Respondents
0
1
2
3
4
5
6
Total
57
43
36
12
0
52
0
200
28.5%
21.5%
18%
6%
0%
26%
0%
100%
Table 3 shows teachers’ second highest stage of concern. Teachers indicated their second highest
concern in two stages: stage 1 (informational) and stage 5 (collaboration). These findings suggest that
teachers wanted more information and were interested in learning more about digital learning
practised through the First Bell programme; however, teachers were not concerned about the First
Bell programme’s consequences for students (as per stage 4). The high score in stage 5 indicates that
teachers were very interested in learning from others (participating in collaboration) rather than
leading collaboration themselves.
Table 3: Frequency of second peak (highest) stage of concern among teachers
Second Highest Stage of
Concern
0
1
2
3
4
5
6
Total
Number of Respondents
25
57
30
26
0
57
5
200
12.5%
28.5%
15%
18%
0
28.5%
2.5%
100%
Percent of Individuals
Research question 2: How do teachers of Kerala describe their experiences during the First Bell
programme?
The qualitative section discuses teachers’ experiences during the First Bell programme. A semistructured interview question was used to elicit the teachers’ reactions to the current position of the
First Bell programme and their pedagogical practices with digital learning. Twenty teachers were
interviewed. The duration of the interview was about 15 to 20 minutes. Regarding the course content
structure of the First Bell programme, including video, study materials, et cetera, teachers gave very
good responses. The majority of the teachers (95%) had little concern with the course content, and
95% of them showed a positive attitude towards the course design of the innovation introduced.
Course design is the process and methodology of creating quality learning environments and
experiences for students. Through deliberate and structured exposure to instructional materials,
learning activities and interaction, students are able to access information, obtain skills, and practise
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higher-level thinking. The teachers believed that learning through a digital medium is innovative,
supports setting the pace, builds a physical space intended for learning, and continues to encourage
in the absence of daily face-to-face interaction. Also, the First Bell programme creates quality
learning environments and a good learning experience for students. They argued that the First Bell
programme provides good learning activities, interaction with new technology, and is a top-priority
for engaging teaching and implementing active learning. With respect to student participation in
digital learning, teachers and parents had some concerns, like student distractions, lack of in-person
interaction, and isolated learners, et cetera. The analysis revealed that only a few teachers responded
positively to questions on student participation. The study shows that the participation of students in
the online programme was a big challenge because of lack of interest on the part of the students.
CONCLUSION
The main purpose of this study was to understand the concerns of high school teachers in Kerala,
India, when the First Bell programme was implemented during the COVID-19 pandemic. The study
used multiple data points (the SoCQ instrument, open-ended concern statements, and interview
questions) to collect evidence on teacher concerns. The quantitative phase, using the SoCQ instrument
data, indicated that the informational aspect and collaboration were the major concerns. The
qualitative phase, using open-ended statement and interviews, supported the evidence from the SoCQ
instrument. This research has raised many questions in need of further investigation. A follow-up
study could focus on the effect of intervention strategies to address teachers’ peak stage concerns.
Also, further studies can use the innovation configuration dimension of the CBAM model, which
looks into the operational aspects of innovation.
REFERENCES
George, A. A., Hall, G. E., & Stiegelbauer, S. M. (2006). Measuring implementation in schools: the
stages of concern questionnaire. Austin, TX: Southwest Educational Development Laboratory.
Ghirardini, B. (2011). E-learning methodologies: A guide for designing and developing e-learning
courses. Food and Agriculture Organization of the United Nations.
Hall, G. E., & Hord, S. M. (1987). Change in schools: Facilitating the process. New York: State
University of New York Press.
Hall, G., & Hord, S. (2011). Implementing change: Patterns, principles, and potholes (3rd ed.).
Needham Heights, MA: Allyn and Bacon.
Hall, G. E., Hord, S., Rutherford, W. L., Loucks, F., Huling, L. L., & Heck, S. A. (1982). Workshop
on Innovation configurations: The Teachers’ Manual. University of Texas.
Loucks, Horsley, S., & Stiegelbauer, S. (1991). Using knowledge of change to guide staff
development. In A. Lieberman & L. Miller (Eds.), Staff development for education in the 90’s:
New demands, new realities, new perspectives (2nd ed.) (pp. 15–36). Teacher College Press.
McMillan, J. H., & Schumacher, S. (2010). Research in Education: A conceptual introduction (5th
ed.). Longman.
Oommen, M. A. (1992). The Kerala Economy. New Delhi: Oxford and IBH.
Oommen, M. A. (1999). Kerala's Development Experience, Vol. 1 & 11. ed. Concept Publishing.
Ramachandran, V. K. (1996). On Kerala's Development Achievements. In J. D. A Sen (Ed.), Indian
Development: Selected Regional Perspectives (pp. 205–356). Oxford University Press.
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FACE-TO-FACE VERSUS REMOTE LEARNING: STUDENT
BEHAVIOUR ANALYSIS THROUGH EDUCATIONAL DATA
Martha Mosha
Department of Social Sciences, School of Humanities, Society and Development, University of Namibia
(marthamosha@gmail.com)
Abstract
At the University of Namibia (UNAM), courses were taught face to face using the blended learning
approach through a learning management system (LMS), Moodle. Due to COVID-19, the courses
had to be offered via remote teaching, which meant adopting and adjusting to the online learning
approach. Since the introduction of LMSs, there have been new opportunities to use Big Data mining
for education, also known as educational data mining (EDM). EDM was used in this study to unearth
and compare student behavioural patterns during the face-to-face and remote learning of two courses
offered in two different years. The one was during the time of COVID-19, and the other was the year
prior to that. Analytics from log-in details, learning resources, discussion forums, chats, assessments,
and use of plug-ins, such as the plagiarism software, were used to map out student behaviour. Key
preliminary findings show that students increased their participation in forums and chats; there was
not much of a difference in cases of plagiarism; and more students accessed Moodle through their
mobile phones after moving from face-to-face to remote teaching.
INTRODUCTION
Educational data mining (EDM) is defined as an “interdisciplinary research area that deals with the
development of methods to explore data originating in an educational context” (Romero & Ventura,
2010, p. 601). Owing to the enormous amount of data generated by learning management systems
(LMSs), there is a need to use “Big Data technologies and tools into education, to process the large
amount of data involved” (Sin & Muthu, 2015, p. 1035). EDM allows for one to analyse the mass
amount of data gathered by an LMS, extract some useful results that can be used to improve students’
learning experience, advance the courses offered by an institution, and enhance educational processes.
“Educational big data is at a point of its evolution where researchers and practitioners are transitioning
from a point of mere awareness to action” (Quadir et al., 2020, p. 1552). Thus, this research aimed to
analyse previous course records of two courses in two different years and map out the behaviour of
students. The results then mapped out the learning style of the students, which may inform future
course planning and designing.
EDUCATIONAL DATA MINING
“Students’ activities through learning management systems create large amount of data that can be
utilized in developing the learning environment, helping the students in learning and improving the
overall learning experience” (Sin & Muthu, 2015, p. 1035). This data, however, need to be
transformed “into information and knowledge and provide services for educational decision making,
teaching optimization and academic improvement” (Zhang & Qin, 2018, p. 83). EDM can be used in
a number of ways, among others, for data visualisation and behaviour detection (Roy & Singh, 2017;
Sin & Muthu, 2015). “Prediction and analysis of student academic performance are essential for
student academic growth” (Zaffar et al., 2017, p. 7). “One of the biggest challenges that educational
institutions face is the exponential growth of educational data and the transformation of this data to
new insights that can benefit students, teachers, and administrators” (Romero & Ventura, 2010, p.
602).
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“There are numerous approaches to analyze educational data, numerous tasks that are tackled and
interesting findings that are discovered” (Merceron, 2015, p. 106). Some popular categories of data
mining technologies include regression and prediction, classification, clustering and diagnosis
(Aldowah et al., 2019; Asif et al., 2017; Berland et al., 2014; Dutt et al., 2015; Liñán & Pérez, 2015;
Papamitsiou & Economides, 2014; Prakash et al., 2014; Roy & Singh, 2017; Sin & Muthu, 2015;
Zhang & Qin, 2018). The cluster technique was used in this research.
According to Vellido et al. (as cited in Asif et al., 2017, p. 180), “clustering students is a proper
technique to find similar learning behaviours”. This is further explained by Berland et al. (2014, p.
210), who state that “cluster analysis finds the structure that emerges naturally from data, allowing
researchers to search for patterns in student behavior that commonly occur in data, but which did not
initially occur to the researcher”. In addition, “clustering in higher education might still be considered
as an effective technique to group students based on their learning characteristics, individual learning
style preferences, academic performance, and behavioural interaction” (Aldowah et al., 2019, p. 24).
This research worked with forming clusters, as outlined in the framework, to find behavioural patterns
that students share.
THE CASE OF FACE-TO-FACE VERSUS REMOTE LEARNING
The Department of Social Sciences of the University of Namibia (UNAM) offers the following
courses during semester two of the university calendar: Digital Media (hereafter referred to as Course
1) and Mobile Journalism (hereafter referred to as Course 2). Digital Media is an examinable course,
whereas Mobile Journalism is not, as it is a practical course. In 2019, the two courses were offered
face to face with some elements being taken up online (i.e., blended mode). Elements such as
assessments, learning resources, grades, and some forums were conducted online. However, this
changed in 2020; due to COVID-19, the courses were offered fully online. It is the change in mode –
from face to face to online – that led to this study so as to analyse if the change influenced student
behaviour.
UNAM uses Moodle as an LMS, which features Moodle Learning Analytics – a plug-in installed by
the system administrator. “Most LMSs incorporate their own tools to automatically generate
customizable statistics reports of course development, these are often quite basic” (Liñán & Pérez,
2015, p. 102). The data for the study were, therefore, collected from Moodle, and some data were
analysed using Moodle Learning Analytics.
FRAMEWORK
The educational data mining framework was used. “[D]ata mining and big data integration on elearning process can derive the advance features such as pattern generation, pattern analysis,
predictive analysis and knowledge discovery, which is needed to identify learning needs along with
learners needs in future e-learning revolutions” (Udupi et al., 2016, p. 258).
Figure 1 illustrates the framework, showing that data were collected from the LMS. The data
underwent detection, processing and classification to prepare the data for analysis. The data were then
analysed and grouped into clusters, which, in this case, were visualised to come up with findings.
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Figure 1: The educational data mining framework. From Educational data mining and big
data framework for e-learning environment by P. K. Udupi, N. Sharma and S. K. Jha, 2016,
International Conference on Reliability, Infocom Technologies and Optimization (Trends and
Future Directions) (ICRITO), p. 258–261. Copyright 2016 by IEEE.
LIMITATIONS
It must be noted that the move to the online mode of teaching was initiated by the move to remote
teaching because of COVID-19. The students, and the whole world, at the time were undergoing a lot
of change and unpredictability. This might influence the findings even though the students were
supported in every way possible with pocket Wi-Fi and laptops to transition to remote teaching via
online mode.
ETHICAL CONSIDERATIONS
Ethical clearance to conduct this study was issued by UNAM. The datasets used in this study
contained student names, thus care was taken not to have them revealed in the findings. The datasets
were handled by only one person (the researcher), and all datasets are stored safely on a hard drive to
be destroyed in future.
METHODOLOGY
The research design was quantitative with an exploratory approach. Datasets were gathered from
Moodle course analytics; these included competency breakdown, logs, activity reports, course
participation, activity completion content accesses and statistics.
The datasets pulled all of the above from four courses: two from the year 2019, and the other two
from the year 2021. The total population was as follows:
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Table 1: Dataset population and instances
2019
2020
Course 1
50 students
Data Instances: 7 794 rows
38 students
Data Instances: 21 095 rows
Course 2
45 students
Data Instances: 7 416 rows
40 students
Data Instances: 19 855 rows
Some data were analyzed through Moodle Learning Analytics. Other datasets were downloaded as
comma-separated values (CSV) files, and some were cleaned up using Microsoft Excel. This is due
to the fact that “[t]he collected data often contain some important information missing, incorrect or
containing noise, inconsistency and other issues, data preprocessing technology can improve data
quality to meet the requirements of educational data mining, common preprocessing operations can
use data cleansing” (Zhang & Qin, 2018, p. 84).
The result of these were analyzed using Orange, an open-source data visualization software program.
Orange can produce graphs using visualization widgets, which “include scatter plot, box plot and
histogram, and model-specific visualizations like dendrogram, silhouette plot, and tree visualizations,
just to mention a few” (University of Ljubljana, 2021). Moreover, Orange “has a cleaner and easier
to understand interface, with color-coded widgets differentiating between data input and cleaning,
visualization, regression and clustering” (Slater et al., 2017, p. 92).
Figure 2. Cycle of applying educational data mining in research. From “Predicting student
performance in higher educational institutions using video learning analytics and data mining
techniques,” by R. Hasan, S. Palaniappan, S. Mahmood, A. Abbas, K. U. Sarker and M. U.
Sattar, 2020, Applied Sciences, 10(11), 3894
FINDINGS
The research revealed a few interesting findings. It must be noted that the number of students enrolled
for the two courses reduced in number from 2019 to 2020; however, Courses 1 and 2 had an increase
in activity of 171% and 168%, respectively, in 2020. The way in which the students accessed the
LMS was investigated, as access to LMSs through mobile devices is an increasing trend in online
learning. Downloading of the Moodle mobile app is also promoted at UNAM due to easy access to
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the chat feature, which minimises the need to set up a WhatsApp class group, as is the trend at the
University.
Figure 3 shows the way in which students accessed the course on Moodle, with the options being
through the web browser or through the Moodle mobile app. In 2019, 98.96% of the students accessed
Course 1 via the web compared to 1.04% who accessed it via the mobile app. In 2020, the same
course had 94.76% of the students accessing from the web compared to 5.24% on the mobile app.
Students in Course 2 had a similar pattern in both years, with 2019 seeing 98.98% accessed via the
web compared to 1.02% via the mobile app. In 2020, Course 2 had 92.18% of the students accessing
the course via the web compared to 7.82% via the mobile app.
Figure 3: Way in which the students accessed the course from for Course 1-2019 (top left),
Course 1-2020 (top right), Course 2-2019 (lower left) and Course 2-2020 (lower right) [Yaxis=Frequency, X-axis=Origin]
Figure 4 shows the frequency of dates accessed in the semester, with the red line indicating the dates
on which there was an assessment that had a specific submission deadline (note that this does not
include assessments such as discussions, as these were ongoing assessments for a period of time).
The figures for 2019 show that access to the courses was much later, with peaks around dates that an
assessment was due. Some students, however, continued to access the course even after the semester
was due. The figures for 2020 show that students almost evenly accessed the course all the way till
the end of the semester, with peaks around dates that assessments were due. In this case, once the
semester was over, the students stopped accessing the course.
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Figure 4. Dates students accessed Course 1-2019 (top left), Course 1-2020 (top right), Course
2-2019 (lower left) and Course 2-2020 (lower right) [Y-axis=Frequency, X-axis=Dates in a
semester]
One of the interesting findings was the times that the students accessed the courses. Figure 5 shows
the times that students accessed the courses, and it shows that in both courses, in 2019, the students
accessed the course more during working hours. However, this pattern changed in 2020 where the
students accessed the course throughout the day, with some reductions between the hours of 1am and
9am. The least accessed hour was 4am in both courses. Course 1 shows a peak within the hour of
1pm and 3pm, with the latter having the highest peak for 2019. Course 2 shows a peak within the
hour of 9am, 10am, and 1pm, with the highest peak being at 10am for 2019.
Figure 5. Times students accessed Course 1-2019 (top left), Course 1-2020 (top right), Course
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2-2019 (lower left) and Course 2-2020 (lower right) [Y-axis=Frequency, X-axis=Time in 24
hours]
Several components were accessed with the course, with general access to Moodle being the highest
in all four cases as shown in figure 6. The next highest for 2019 were the quizzes, followed by
assignments. This was not the case in 2020, as the next highest were the assignments followed by
forums, then lessons, and then quizzes. The biggest change is the forums which moved from 0.17%
in 2019 to 12.28 in 2020 for Course 1, and from 0.11% in 2019 to 15.85% in 2020 for Course 2.
Figure 6: Components of the course accessed by students for Course 1-2019 (top left), Course
1-2020 (top right), Course 2-2019 (lower left) and Course 2-2020 (lower right) [Yaxis=Frequency, X-axis=Moodle Component]
Figure 7 is scatter plots of all the activities mapped by the time of day they happened. This paints an
overall picture of the activities that took place and is used to illustrate an overview of the activities.
The plots show that for both courses, 2020 was a year with a number of activities throughout the day
and the semester.
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Figure 7: Scatter plot of events for Course 1-2019 (top left), Course 1-2020 (top right), Course
2-2019 (lower left), and Course 2-2020 (lower right) [Y-axis=Time in 20 hours, X-axis=Dates
in a semester]
DISCUSSION
It was thought that with the move to remote teaching, most students would resort to using their mobile
phones to access the course. This might have been the case, but students still accessed the course
using the web browser instead of the mobile app. Efforts were made to communicate to the students
the benefits of and instruction on switching to the mobile App; however, it seems not many students
went for the option.
It is lovely to discover that in 2019, the students accessed the course way past the finish date of
classes. For Course 1, this could have been the case because they had an exam to write, hence they
were seeking understanding. This phenomenon cannot be explained for Course 2, as there were no
exams to be written. However, maybe the students accessed the course to check for their final
continuous assessment marks. As for 2020, the students ended the activities in the course as the
semester ended. This can be attributed to the fact that the semester ended late (into November), and
fatigue kicked in as the semester and year seemed to had taken a toll on everyone.
The peak in times that the students accessed Course 1 and 2 in 2019 follow the time schedule for
face-to-face classes. This means then the students would log in to the course during class attendance.
These findings could be explained by the fact that the students needed to access content for the class
on Moodle. In addition, these times were the ones set for quizzes. The access to the course on Moodle
shows interesting times for 2020 for both Course 1 and 2, as there were activities throughout the day,
with a dip at 4am. This dip at this specific hour cannot be explained. One would have thought that the
students would have chosen the telephone company’s “happy hour” of 12am to 6am to use the
Internet, as surfing is free, but the numbers indicate something else.
The difference in access to components is ascribed to the fact that there were more quizzes in 2019
compared to 2020, which saw a shift to more assignments. However, discussion forums came in at
number three for both courses in 2020. This is because there were no face-to-face sessions; hence,
discussions were at an appointed virtual meeting and these carried on to Moodle as others looked for
understanding and/or wished to share their points of view. In the previous year, students were
encouraged to assume uncompleted discussions online the case when class time is up and the
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discussion is still strong. However, not many materialised. Most would wait until the next class to
pick up the discussion or followed the lecturer to the office to finish the discussion.
The research had hoped, but failed, to look at the issue of plagiarism, which is a growing issue in the
online learning environment (Romero & Ventura, 2017). It is noted that “[r]esearchers have not
addressed how data mining can be applied to plagiarism detection” (Huebner, 2013). In addition, due
to the practical nature of the courses, there were not enough similar theoretical assessments that could
be compared.
CONCLUSION
The results reveal a number of interesting facts that would aid in the course development update. The
fact that students accessed the course online at all times of the day during lockdown allows for content
to be developed in a more asynchronous manner to allow for access at a time that is convenient to the
students. Strangely, the optimisation of free surfing hours during late night and early mornings was
not taken up by most students. Other findings showed that the use of discussion forums increased in
the 2020 course components in each course. This means the use of this component should be
encouraged, especially for general discussions. Very few students used the Moodle mobile app. This
app needs more promotion in the future, as this would ease access to the course and may even increase
the number of chats that take place in a course. Future studies would hopefully look into the issue of
plagiarism and how students fared in this regard.
ACKNOWLEDGEMENTS
Thanks to the University of Namibia for granting research permission.
REFERENCES
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analytics for 21st century higher education: A review and synthesis. Telematics and
Informatics, 37, 13–49.
Asif, R., Merceron, A., Ali, S. A., & Haider, N. G. (2017). Analyzing undergraduate students'
performance using educational data mining. Computers & Education, 113, 177–194.
Berland, M., Baker, R. S., & Blikstein, P. (2014). Educational data mining and learning analytics:
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Dutt, A., Aghabozrgi, S., Ismail, M. A. B., & Mahroeian, H. (2015). Clustering algorithms applied
in educational data mining. International Journal of Information and Electronics
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Hasan, R., Palaniappan, S., Mahmood, S., Abbas, A., Sarker, K. U., & Sattar, M. U. (2020).
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analytics and data mining techniques. Applied Sciences, 10(11), 3894.
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Quadir, B., Chen, N. S., & Isaias, P. (2020). Analyzing the educational goals, problems and
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STUDENT PLAGIARISM DETECTION IN DISTANCE HIGHER
EDUCATION
Booysen Sabeho Tubulingane
NUST, University of Giessen/UNICAF (ngane432@gmail.com)
Abstract
Students are usually cautioned by their universities to refrain from practising plagiarism when
completing their academic work. However, plagiarism is still a serious problem experienced by
private and public universities in both developed and developing countries. Consequently, many
universities around the world have implemented measures to combat plagiarism in students’
academic work. Yet, some of those efforts might have led to contributing to the general student
confusion about what plagiarism is, as similarity detection software such as Turnitin is regarded as
plagiarism-detection software. Thus, there was a need for this study that proposes an innovative way
of estimating plagiarism from analysing students’ continuous assessment and final subject marks. A
longitudinal, descriptive and predictive quantitative research design was applied in this study. All
complete numeric records (29 343) of students’ continuous assessment and final subject marks for the
academic years 2018 and 2019 at a Namibian university were applied in the study. Descriptive
statistics in the form of averages were computed, and linear regression was used to model and predict
the contribution of the continuous assessment marks to the final student subject marks. During the
2019 academic year, plagiarism was estimated at 7% and 3% for distance and contact education,
respectively. Analyses of distance data conveyed a moderate correlation of 0.56 between continuous
assessment and final subject marks. Thus, only 31% of the alterations in the student final subject
marks is explained by continuous assessment marks of distance students. To reduce plagiarism among
distance students, it is recommended that a switch be implemented from assignment-based (written
without invigilation at own time) continuous assessments to face-to-face written tests (in the presence
of invigilators). This new proposed continuous assessment model is likely to increase the influence of
continuous assessments on the final subject marks of distance students.
INTRODUCTION
Students are usually cautioned by their universities to refrain from practising plagiarism when
completing their academic work. This is accomplished when students are educated about how to avoid
plagiarism in the set university anti-plagiarism policies and measures (Sibomana et al., 2018).
However, plagiarism is still a serious problem experienced by private and public universities in both
developed and developing countries (Anney & Mosha, 2015; Ison, 2018; Lilian & Chukwuere, 2020).
Plagiarism is the act of using someone else’s ideas (words/sentences) in the exact or modified way as
your own without acknowledging the source of such idea/words. In other words, according to Selwyn
(as cited in Heckler & Forde, 2015, p. 61), plagiarism is the “reproduction of text from other academic
sources, such as journal articles, books, or lecture notes without adequate acknowledgement of the
source, copying some or all of other students’ assignments”.
Many universities around the world have implemented measures to combat plagiarism in students’
academic work. However, some of those efforts might have led to contributing to the general student
confusion about what plagiarism is, as similarity detection software such as Turnitin is regarded as
plagiarism-detection software (Louw, 2017). This is because a “similarity is not necessarily an act of
plagiarism if referenced correctly; in the same vein, a stolen idea, worded differently, is not picked
up by software like Turnitin. Moreover, Turnitin would not have seen similarities between the two
songs or the two movies, for example” (Louw, 2017, p. 122).
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The current study provides statistical analyses aimed at detecting plagiarism per respective education
offering types (contact and distance) based on students’ continuous assessment and final subject
marks. The study also determines to what extent the application of information communication
technologies (ICTs), such as computers and the Internet, influences plagiarism among distance
students.
LITERATURE REVIEW
Why students plagiarise
A student’s lack of understanding is positively associated with plagiarism (Finchilescu & Cooper,
2018). A lack of understanding is likely to lead to students experiencing difficulties to complete their
university schoolwork, particularly when they are faced with family responsibilities. According to
Musingafi et al. (2015), the most reported challenges that accelerate plagiarism among distance
students are lack of sufficient time for study (time management), difficulties in accessing and using
ICTs (including the Internet), ineffective feedback, and lack of study materials. Similarly, Bibi and
Hafeez (2018) state that the common situations that lead to students plagiarising are poor time
management and less or no skill to integrate others’ intellectual work and ideas. Furthermore, students
who are afraid of failure to cope with their academic work are more likely to take risks, which include
plagiarising. For instance, Sibomana et al. (2018) contend that students plagiarise due to laziness,
lack of confidence and an inability to correctly reference or cite source materials. Some students
plagiarise unconsciously and unwillingly, while others do it consciously and willingly.
Plagiarism by study offering mode
Evidence is accumulating on how to make online or distance learning effective, as concerns are
growing about problems that distance education pose for students’ academic integrity (Bell &
Federman, 2013). There is a high rate of academic dishonesty in the online/distance learning
environment to the point that it is now a standing issue that is challenging higher education institutions
(Lilian & Chukwuere, 2020). For instance, plagiarism is more than 12 times more likely to be
committed by distance students than by face-to-face students (Lucky, Branham, & Atchison, 2019).
According to Bell and Federman (2013, p. 177), academic dishonesty in a distance/e-learning
environment is typically characterised by the following offenses: “acts of plagiarism, using concealed
notes to cheat on tests, exchanging work with other students, buying essays or, in some extreme and
notorious cases, asking others to sit examinations for you”. This suggests that “distance learning
assessments can be artificially inflated by cheating, suggesting that evaluations of distance learning
should be considered in light of academic dishonesty” (Lucky et al., 2019, p. 414).
Information communication technologies as a catalyst for plagiarism
The emergence of modern information technologies, such as the Internet, has made the control,
managing and elimination of plagiarism very difficult (Lilian & Chukwuere, 2020). Lilian and
Chukwuere (2020) discovered that plagiarism occurs more over the Internet because a load of
material is readily available for students to copy and paste when completing their academic work. In
the same way, Heckler and Forde (2015) and Ison (2018) argue that the Internet has accelerated the
rate at which students practise plagiarism in institutions of higher learning. This is detailed and
highlighted below by Ison (2018) and Levine and Pazdernik (2018), respectively:
Even with improved technologies to detect plagiarism, such effort requires time and energy on
the part of faculty and the institution not to mention the cost of its adoption. Complicating the
upholding of academic integrity is the ease of access to information made available by the
Internet. Students are presented with almost endless amounts of text from which to cut and
paste through a simple online search (p. 293).
The expansion of the Internet has led to increased access to databases and other information
that students can easily use when completing assignments. For instance, the ready availability
of information through the Internet makes it easier for students to copy and paste information
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into academic work. The growth of the Internet has also led to an increased number of online
educational programmes offered by higher education institutions, which adds another
dimension to the possibility of academic dishonesty (p. 1094).
Based on the above statements, the Internet has become the centre of attention in the fight against
plagiarism in the higher education sector. Internet plagiarism is common when students copy and
paste information from the Internet without acknowledging sources. Plagiarism is also more evident
with online course offerings in cases where a university lacks an effective and efficient verification
system to ensure that people who are writing online tests are registered students for that specific
academic course.
Solution to plagiarism
An effective anti-plagiarism programme can reduce the number of incidents of plagiarism among
university students (Levine & Pazdernik, 2018). In addition to Levine and Pazdernik’s (2018)
suggestion, such a programme can focus on the use of policies and procedures and can educate
students on plagiarism by providing good student support through the institution’s writing centre and
incorporation of Turnitin plagiarism-detection software. Moreover, plagiarism education programmes
can target students who plagiarise because of laziness, poor time management and planning skills.
Such students need to know that people are credited because of what they have done and that the
purpose of the course is to learn and develop skills and not just to graduate (Harris as cited in
Sibomana et al., 2018, p. 20). Likewise, Heckler and Forde (2015) acknowledge that when a
university has a culture of academic accomplishment by emphasising learning over grades,
connecting assignments to course objectives and deterring cheating, plagiarism is more likely to be
reduced. This infers that there is a relationship between students’ cultural background and plagiarism.
However, Ison (2018) contends that there is no relationship between students’ cultural background
(in Europe, Africa, Middle East, USA, China, India) and the incidence of plagiarism.
According to Bibi and Hafeez (2018), solutions to plagiarism can include, but are not limited to:
•
•
making students undergo a mandatory pre-programme course focusing on how to properly
reference academic materials and how to avoid plagiarism. In addition, lecturers can develop
a guide that encourages or educates students about scholarly thinking and how to maintain
proper documentation during their academic assignment development;
there is a need for the establishment of online student support services that aim to communicate the university’s convention on plagiarism, urging students to implement anti-plagiarism
behaviours to stop the violation of intellectual property rights in face-to-face or open distance
learning.
Lilian and Chukwuere (2020, p. 14685) derived the following recommendations to combat student
plagiarism in the higher education sector:
•
•
•
students and any content generator (writers and lecturers) should be educated and informed
about the consequences of plagiarism;
students should be taught how to reference properly in any form of assessment;
higher education institutions should provide a mandatory module covering plagiarism for students to be informed.
The literature above shows that plagiarism is a serious challenge for higher education institutions,
particularly for open, online and distance programmes offered around the world. Numerous authors
also highlight ICTs as a catalyst for plagiarism; ICTs make it easy for students to plagiarise. The
literature also shows that when students do not understand their academic materials, they revert to
academic dishonesty to do their academic work. Moreover, solutions to plagiarism involve educating
students about how to properly acknowledge others’ work and promoting an anti-plagiarism mindset
among students.
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Continuous assessment and final subject marks
There is a high correlation between the marks obtained by students in their coursework and their
examination marks, as students rely a lot on the marks obtained in their continuous assessments to
expand their examination marks (Pudaruth et al., 2013). However, if students are not marked properly
for continuous assessments and if they are given high marks, they can become overconfident and may
not prepare themselves adequately for examinations.
Reboredo (2017) discovered that continuous assessment grades were a poor indicator of final
examination grades in a micro-economics course. This was due to students with higher continuous
grades focusing more on subjects with which they were struggling. Likewise, Al-Maskari (2017)
revealed that there is no strong correlation between continuous assessment marks and final
examination marks. This weak correlation between continuous assessment and final marks indicates
that assessment criteria are perhaps not set well. The high success rate in the continuous assessments
likely indicates inflation in marks, and this gives the students an inaccurate indication of their
performance (Al-Maskari, 2017). Poor student academic performance monitoring through continuous
assessments can result in students articulating poor final subject marks after examinations.
RESEARCH METHODOLOGY
Research design
A longitudinal, descriptive and predictive quantitative research design was applied in this study. No
sampling was done, as all complete records of Namibian university students’ continuous assessment
and final subject marks for the academic years 2018 and 2019 were applied in the study. Descriptive
statistics in the form of mean or averages were computed for continuous assessment and final subject
marks variables. Linear regression was used to model and predict the contribution of continuous
assessment marks to final student subject marks.
Study variables
The plagiarism variable was established based on the differences between students’ continuous
assessment marks and final subject marks. Therefore, final subject marks represent the dependent
variable, while continuous assessment marks represent the independent variable.
RESULTS AND DISCUSSION
Student academic attainment per study mode and plagiarism
The students’ academic achievement based on continuous assessment and final subject marks after
examinations was used to estimate plagiarism per respective education offering type. Plagiarism in
the form of the difference between the average continuous assessment marks (ACAMs) and the
average final subject marks (AFSMs) for distance students was established at 7% for the year 2019.
Moreover, a 3% difference (between ACAMs and AFSMs) was calculated for students who were
enrolled in contact classes for the same 2019 period, as is shown in table 1 below. The results in table
1 are in line with those of Bell and Federman (2013) and Lilian and Chukwuere (2020), who
established that plagiarism in distance education is much higher than in contact or face-to-face
education offering. The high plagiarism among distance students is mainly catalysed by the lack of
time to study or to complete academic work by the majority of employed distance students
(Finchilescu & Cooper, 2018; Musingafi et al., 2015). Family responsibilities also negatively impact
distance students, as less time is allocated to studying, which leads to less understanding of academic
materials, thus they resort to hiring other persons to complete their assignments.
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Table 1: Average continuous assessment marks and final subject marks per offering mode
Offering type
Contact (Full
time and Part
time)
Distance
Grand Total
2018 Academic Year
Average of
Average of
ACAMs Continuous
Final Subject
AFSMs (%)
Assessment
Marks
Marks
(AFSMs) (%)
(ACAMs) (%)
61
59
2
62
61
54
58
8
3
2019 Academic Year
Average of
Average of Fi- Plagiarism =
Continuous
nal Subject
ACAMs Assessment
Marks
AFSMs (%)
Marks
(AFSMs) (%)
(ACAMs) (%)
62
59
3
61
62
54
58
7
4
Figure 1 presents a scatter plot with a positive correlation of 0.86 between final subject marks and
continuous assessment marks for contact students. An increase in continuous assessment marks would
increase final student subject marks.
Figure 1: Average continuous assessment marks and final subject marks for contact offering
Table 2 introduces a linear regression analysis between final subject marks and continuous assessment
marks for contact students. A unit increase in the continuous assessment mark would increase the
final subject mark by 0.92 units. Moreover, the p-value is < 0.05, stipulating that the relationship
between the final subject mark and continuous assessment mark is significant when testing at a 0.05
significance level. Furthermore, the adjusted R-squared is 0.74, which indicates that 74% of changes
or variations in the student final subject marks are explained by continuous assessment marks.
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Table 2: Linear regression model summary: final subject marks and continuous assessment
marks for contact students
Coefficients:
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
2.346597
0.146184
16.05
<2e-16 ***
Continuous Assessment Marks
0.921395
0.002335
394.63
<2e-16 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 5.819 on 53684 degrees of freedom, Multiple R-squared: 0.7437, Adjusted R-squared: 0.7436, F-statistic: 1.557e+05 on 1 and 53684 DF, p-value: < 2.2e-16
Figure 2 shows a scatter plot of the final subject marks and continuous assessment marks for distance
students. There is a positive correlation of 0.56 between the final subject marks and continuous
assessment marks variables. This means that when the continuous assessment mark increased, the
final student subject mark of the distance student also increased.
Figure 2: Average continuous assessment marks and final subject marks for distance offering
The linear regression results in table 3 show that a unit increase in the continuous assessment mark
would result in an increase of 0.57 units of the final subject mark in a distance study mode. The
relationship between the final subject mark and continuous assessment mark is significant at a 0.05
significance level, as the p-value is < 0.05 in table 3. The adjusted R-squared is 0.31, which reveals
that only 31% of changes or alterations in the students’ final subject marks are explained by
continuous assessment marks. The other variations (69%) of the final subject marks are explained by
factors that are not included in the linear regression model presented in table 3. This indicates that
continuous assessments completed by distance students only contributed 31% towards their academic
success.
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Table 3: Linear regression model summary: final subject marks and continuous assessment
marks for distance students
Coefficients:
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
19.252848
0.449981
42.79
<2e-16 ***
Continuous Assessment Marks
0.567763
0.007269
78.10
<2e-16 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9.619 on 13375 degrees of freedom, Multiple R-squared: 0.3132, Adjusted
R-squared: 0.3132, F-statistic: 6100 on 1 and 13375 DF, p-value: < 2.2e-16
Distance education discipline and plagiarism
Students who were enrolled for subjects in the computing and informatics discipline articulated a
high level of plagiarism, as the difference between the continuous assessment and final subject marks
was 18%, as per table 4 below. The continuous assessment marks were higher than the final subject
marks; this may mean that the continuous assessments were correctly set and did not underestimate
the students’ capabilities and, therefore, distance students were given accurate feedback (Pudaruth et
al., 2013). Nevertheless, distance student continuous assessments are done without the presence of
tutors – so, some of the students are highly engaged in plagiarism. Many distance students at the
Namibian university have a habit of hiring other persons to complete their assignments that constitute
their continuous assessment marks, thus failing their examination, as is evidenced by the lower final
subject marks. Computing and informatics distance subjects such as Management Information
Systems (MIS) require students to use ICTs, including the Internet, which accelerates plagiarism in
the discipline (Heckler & Forde, 2015; Ison, 2018; Lilian & Chukwuere, 2020).
Table 4: Final subject and continuous assessment marks and plagiarism among distance
students
Discipline
Computing and Informatics
Health and Applied Sciences
Human Sciences
Management Sciences
Nat Resource & Spatial Science
Grand Total
Average of
Continuous
Assessment Marks
(ACAMs) (%)
69
60
59
64
69
61
Average of Final
Subject Marks
(AFSMs) (%)
52
50
56
54
64
54
Plagiarism
(%)
18
10
3
11
5
7
There was a moderate (neither strong nor weak) positive correlation of 0.65 between the final subject
marks and continuous assessment marks of distance computing and informatics students, as shown
in Figure 3.
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Figure 3: Average continuous assessment marks and final subject marks for distance
computing and informatics students
The linear regression results in table 5 specify that a unit increase in the continuous assessment marks
increased the final subject marks of the distance computing and informatics students by 0.81 units.
The relationship between the final subject marks and continuous assessment marks is significant at
0.05 significance level, as the p-value is < 0.05 in table 5. The adjusted R-squared is 0.41, which
exposes that only 41% of changes in the student’s final subject marks are explained by continuous
assessment marks. This shows that continuous assessments completed by distance computing and
informatics students only contributed 41% towards their final grades. The availability of ICTs for
educational purposes nowadays has led to a rapid shift from a traditional distance (where assignments
were physically mailed) to online education (where assignments/examinations are completed online),
and there is a need to improve the quality and variety of students’ assessment methods and strategies
to reduce plagiarism in addition to just depending on plagiarism detection software (McCord, 2008).
This can include randomly assigning assignment topics to online students so that each student
produces unique assignment solutions. Also, the online or distance student assessments model need
to require students to provide solutions to assignments in component parts, which provides an
opportunity for the lecturer to evaluate student work at multiple points during the semester, thereby
increasing the chance for the lecturer to note structural and stylistic changes in students’ work as the
semester unfolds.
Table 5: Linear regression model summary: final subject marks and continuous assessment
marks for computing and informatics distance students
Coefficients:
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
-8.7440
12.4792
-0.701
0.488
Continuous Assessment Marks
0.8064
0.1640
4.916
2.37e-05 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9.78 on 33 degrees of freedom, Multiple R-squared: 0.4227, Adjusted Rsquared: 0.4052, F-statistic: 24.16 on 1 and 33 DF, p-value: 2.366e-05
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Figure 4 presents a scatter plot stipulating a positive correlation of 0.73 between final subject marks
and continuous assessment marks for distance Human Sciences students.
Figure 4: Average continuous assessment marks and final subject marks for distance Human
Sciences students
Table 6 shows that a unit increase in the continuous assessment marks resulted in an increase of the
final subject marks of distance Human Sciences students by 0.80 units. The p-value is < 0.05, which
indicates that the relationship between the final subject marks and continuous assessment marks was
significant at a 0.05 significance level. The adjusted R-squared is 0.53, which uncovers that 53% of
variations in the students’ final subject marks were explained by continuous assessment marks. This
shows that continuous assessments completed by distance Human Sciences students contributed 53%
towards their final subject marks.
Table 6: Linear regression model summary: final subject marks and continuous assessment
marks for human sciences distance students
Coefficients:
Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
8.69747
0.59469
14.62
<2e-16 ***
Continuous Assessment Marks
0.80168
0.01004
79.87
<2e-16 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 7.175 on 5735 degrees of freedom, Multiple R-squared: 0.5266, Adjusted
R-squared: 0.5265, F-statistic: 6380 on 1 and 5735 DF, p-value: < 2.2e-16
CONCLUSION AND RECOMMENDATION
The study shows how statistical analyses of students’ continuous assessment and final subject marks
can be employed as a plagiarism detection mechanism. Plagiarism was estimated at 7% and 3% for
distance and contact education offerings, respectively, for the 2019 academic year. A strong
correlation of 0.86 between continuous assessment and final subject marks for the contact education
offering mode was established. Analyses of distance data conveyed a moderate correlation of 0.56
between continuous assessment and final subject marks. A unit increase in the continuous assessment
marks would increase contact students’ final subject marks by 0.92 units. The continuous assessment
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marks for students enrolled in contact mode explain 74% of variations of their final subject marks.
When it came to distance students, only 31% of the alterations in the students’ final subject marks
was explained by continuous assessment marks. Moreover, a unit increase in the continuous
assessment marks only adds 0.57 units to the final subject marks. Distance subjects under the
computing and informatics discipline articulated a high level of plagiarism of 18% due to the high
usage of ICTs and the Internet during the completion of continuous assessments.
To reduce plagiarism among distance students, it is recommended that a switch be implemented from
assignment-based (written without invigilation at own time) continuous assessments to face-to-face
written tests (in the presence of invigilators). This new proposed continuous assessment model is
likely to increase the influence of continuous assessments on the final subject marks of distance
students, as plagiarism would be reduced.
Acknowledgements
Appreciation goes to the conference organisers for awarding the author a grant to attend the
NOMSA21 Open Up and Connect: Education in a Digital Era conference.
REFERENCES
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scores. OQNHE Conference 2015, Muscat, 24–25 February. Quality Management &
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Anney, V. N., & Mosha, M. A. (2015). Student’s plagiarisms in higher learning institutions in
the era of improved internet access: case study of developing countries. Journal of
Education and Practice, 6(13), 203–216. https://eric.ed.gov/?id=EJ1080502
Bell, B., & Federman, J. (2013). E-learning in postsecondary education. Futur Child, 23(1),
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Bibi, T., & Hafeez, A. (2018). Exploration of plagiarism practices in open and distance learning
(ODL). Pakistan Journal of Distance & Online Learning, May, 49–62.
Finchilescu, G., & Cooper, A. (2018). Perceptions of academic dishonesty in a South African
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Heckler, N. C., & Forde, D. R. (2015). The role of cultural values in plagiarism in higher education.
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Ison, D.C. (2018). An empirical analysis of differences in plagiarism among world cultures. Journal of
Higher Education Policy and Management, 40(4), 291–304.
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Levine, J. & Pazdernik, V. (2018). Evaluation of a four-prong antiplagiarism program and the
incidence of plagiarism: a five-year retrospective study. Assessment & Evaluation in Higher
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Lilian, N., & Chukwuere, J. (2020). The attitude of students towards plagiarism in online learning:
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Louw, H. (2017). Defining plagiarism: Student and staff perceptions of a grey concept. South
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Lucky, A., Branham, M., & Atchison, R. (2019). Collection-based education by distance and face
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Musingafi, M. C. C., Mapuranga, B., Chiwanza, K., & Zebron, S. (2015). Challenges for open and
distance learning (ODL) students: experiences from students of the Zimbabwe Open
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Namibia University of Science and Technology (NUST). (2021). Turnitin Student Quickstart.
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AN ANALYSIS OF THE IMPACT OF COVID-19 EMERGENCY
REMOTE LEARNING ON FIRST-YEAR LLB STUDENT SUCCESS
RATES
Sharna-Lee Clarke
IIE Varsity College Deputy Head of School of Law (fkaplan@varsitycollege.co.za)
Fiona Kaplan
IIE Varsity College Head of School of Law (sclarke@varsitycollege.co.za)
Abstract
In March 2020, the COVID-19 pandemic was declared a national disaster globally and in South
Africa, with the country placed under a strict lockdown. This led to emergency remote teaching and
learning (ERTL) in the higher education sector. At the time, the 2020 first-year LLB cohort at a higher
education institution (HEI) had just begun their first semester in higher education with traditional
face-to-face learning. With the announcement of the national lockdown, these students were suddenly
faced with vastly different teaching and learning strategies. Many of these students had no experience
in online learning and were still transitioning to higher education. Traditionally, first-year students
are most vulnerable to poor performance, as they move from secondary to higher education.
Moreover, the LLB degree is historically one with high drop-out and low throughput rates. Emergency
remote learning (ERL) has exacerbated this position and has adversely impacted the success rates of
first-year LLB students at an HEI. Therefore, the purpose and significance of this paper are to
determine what the impact of ERL was on the success rates of first-year LLB students at an HEI. This
is necessary to determine how best to support these students and personalise their learning in
subsequent years of their LLB degree and for further research in legal education. This was done by
a literature review of secondary sources of law and legal education, an empirical analysis of primary
data related to the 2020 module success rates (MSRs) of LLB first-year modules at an HEI and finally,
a comparative assessment of the MSRs of the 2020 first-year cohort and previous cohorts who had
experienced traditional face-to-face teaching and learning in their first year of study.
INTRODUCTION
The declaration of a national state of disaster in South Africa in March 2020 due to the COVID-19
pandemic saw the move from traditional face-to-face teaching and learning in the classroom, with a
lecturer and peers present, to emergency remote learning (ERL) in a private and isolated environment
for many higher education institutions (HEIs). ERL is defined as “a temporary shift of instructional
delivery to an alternate delivery model due to crisis circumstances” (Hodges et al., 2020).
At the time, the first-year Bachelor of Laws (LLB) students at an HEI had commenced lectures on 12
February 2020 – a mere four weeks prior to the declaration of the national state of disaster on 15
March 2020. The declaration of the national state of disaster disrupted the academic calendar, as the
HEI prepared a shift of its teaching and learning strategy to remote learning platforms. This resulted
in a month’s break in contact with students and the resumption of lectures on 15 April 2020. From
this date, while under a hard lockdown, the HEI conducted all lectures remotely via the learning
management system (LMS) – a distance learning system that provided students with the opportunity
to attend virtual classrooms from their homes.
There are various factors to consider when determining the impact of ERL on first-year LLB students
at an HEI. While the physical and psychological impact of the COVID-19 pandemic was considerable
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(Aristovnik et al., 2020), the national state of disaster and lockdown exacerbated its impact on
particularly first-year students, who had just begun their tertiary studies and transition from secondary
to higher education.
This paper focuses on the main factors that affect the success rates of first-year LLB students under
normal circumstances, such as the transition from secondary to higher education and the historical
challenges of the four-year LLB degree (Whitear-Nel & Freedman, 2015). This is necessary to
determine the position and context of first-year LLB students when the abrupt transition to ERL took
place and to ultimately determine its impact on LLB success rates. The purpose of this paper is thus
to determine the impact of ERL on the success rates of first-year LLB students at an HEI. The authors
predict that ERL had a negative impact on student success rates. Thus, to ascertain the actual impact
of ERL on the 2020 first-year LLB student success rates, the researchers conducted a literature review
of secondary sources of law and legal education, an empirical analysis of primary data related to the
2020 module success rates (MSR) of first-year LLB modules at an HEI and finally, a comparative
assessment of the MSRs of the 2020 first-year cohort and previous cohorts who had experienced
traditional face-to-face teaching and learning in their first year of study.
This paper starts with a discussion of the background and context of this analysis. Key terms, as they
relate to this study, are also defined. Thereafter, factors that affected first-year LLB students are
considered, namely the impact of the COVID-19 pandemic and the national state of disaster and
lockdown on higher education and student readiness generally, as the students transitioned from
secondary to higher education. Understanding the context and background of the LLB degree, the
impact of COVID-19 on higher education and the transition from secondary to higher education in
South Africa is crucial to determine the impact of ERL on first-year LLB students. Thereafter, the
paper delves into the MSRs of first-year LLB students and provides an analysis of their results when
compared to the 2019 cohort to determine the impact ERL had on first-year LLB student success
rates.
BACKGROUND TO AND CONTEXT OF THIS STUDY
Brief background to legal education in South Africa
The current legal education system in South Africa is reflective of the exceedingly narrow legal
profession that offers primarily only two options to LLB graduates, which is to become either an
attorney or an advocate (Leach, 2019). At present, legal education therefore consists of two distinct
phases (the two-phase approach) that prepare students for admission to the legal profession. The first
phase is the acquisition of the LLB degree by a student at a public university or an HEI in South
Africa, and the second phase is a practical component and is provided by legal practitioners as
vocational training. Completing both phases are prerequisites for admission to the legal profession.
A long history of inequality in education and the socio-economic divide of the Apartheid society are
what first led to the introduction of the four-year undergraduate LLB degree to South Africa in 1997
by way of the Qualification of Legal Practitioners Amendment Act. The LLB programme provided a
more streamlined and cost-effective degree for persons to gain access to the legal profession by
implementing a four-year professional qualification that permitted graduates access to phase two of
the current South African legal education system. Previously, persons wanting access to the legal
profession were required to acquire a Baccalaureus Procurationis degree (BProc) or any three-year
undergraduate degree and a post-graduate LLB degree before commencing phase two. This was a
lengthy and costly process that excluded most South African persons, particularly persons who were
previously disadvantaged under the Apartheid regime.
Thus, the purpose of the four-year LLB degree was to address the historical legacy of Apartheid and
its effect on legal practice, which was mainly a lack of sufficient representation and inclusion in the
legal profession (Greenbaum, 2010.) However, 24 years after the introduction of the first LLB, the
two-phase approach to legal education still reflects the divided legacy of Apartheid. The present
narrow pathway to becoming a legal practitioner continues to permeate society with the ever56
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widening socio-economic gaps between South African persons in that LLB graduates who choose the
attorney route do so with very low starting salaries, while those who choose the advocate route do so
without any pay initially. Many LLB graduates from previously disadvantaged backgrounds are
responsible for providing for their extended families or require a place to live and transport to their
place of employment and cannot afford this on minimal remuneration. Therefore, the narrow legal
profession remains elitist in its exclusion, as many LLB graduates are unable to obtain practical
vocational training. While most people would assume that students attending an HEI are from affluent
backgrounds, this is not true, as South Africa’s middle class has grown and diversified in racial terms
(Soudien et al., 2021). Thus, the HEI student body consists of students from various backgrounds and
financial positions.
Defining key terms of this study
The internal academic management platforms of the HEI were consulted to measure student success.
A comparative assessment of the MSRs of the respective 2019 and 2020 first-year LLB cohorts was
undertaken using two of the internal systems. The first internal system produced an academic result
report, displaying each student’s individual assessment results at a modular level. The second results
analysis dashboard provided access to key performance measures drawn from other internal
management and student information systems. MSRs are utilised to measure student success in each
first-year LLB module. MSRs is the percentage of students who passed the module relative to the
number of students who registered for the first-year LLB module. The terms module success rate and
student success rates are used interchangeably and have the same meaning. This study also refers to
module throughput rates and pass rates. A module throughput rate refers to the percentage of students
who were able to complete the module successfully within the time stipulated for that specific
module, whereas the module pass rate refers to the percentage of students who have passed and
completed the module.
THE CHALLENGES IN LEGAL EDUCATION
The challenges of the transition from secondary to higher education
In addition to the South African socio-economic context, it is necessary to consider the nature of
education in South Africa to fully understand the impact of the COVID-19 national state of disaster
on higher education. The South African education system is still attempting to divest itself of the
Apartheid regime (Soudien et al., 2021). The legacy of Apartheid has resulted in a vastly unequal
South African schooling system which amplifies the already difficult transition from secondary
education to higher education (Dlamini, 1992). Research on the schooling system has shown that it
is largely characterised by levels of inequality (Hunter, 2019). Seventy-five per cent of all schoolgoing children in the system attend no-fee schools, which serve previously disadvantaged
communities (Spaull, 2019). These schools are characterised by shortages of educators, poor
discipline, overcrowded classrooms, inadequate infrastructure and a lack of resources (Parker et al.,
2020). This unequal schooling system was recently confirmed in the media – it was found that
COVID-19 highlighted the inequality in the schooling system (Isaacs, 2021).
These socio-economic factors are relevant to this paper, as South African achievement in higher
education is still linked to race and socio-economic inefficiencies (Soudien et al., 2021) and thus has
a knock-on effect on students’ success in higher education. A study of drop-out rates at public
universities in South Africa indicated that 30% of students drop out in the first year of study, with a
further 20% dropping out during the second and third years of study (Scott et al., 2007).
Like the inequalities of the past that still permeate the legal profession and the LLB degree today,
these inconsistencies have resulted in an unequal South African basic and secondary schooling
system. This leads to discrepancies in the education backgrounds of students, which play a pivotal
role in student success rates (Greenbaum, 2010). Coupled with the unequal educational background
with which students enter higher education, English is not a first language of many students despite
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English being the language of instruction at the HEI. These factors reinforce the cycle of disadvantage
that then infuse the legal profession (Greenbaum, 2010).
The general impact of the COVID-19 national state of disaster and lockdown on higher
education
With the scramble to ERL when the national state of disaster was declared in South Africa in March
2020, all HEIs had to develop creative ways to present theoretical and practical modules and
alternative ways of assessing students. As a result, academics had to quickly upskill themselves in
this regard. While the 2015 #FeesMustFall movement may have prepared some of the public
universities for this transition to some extent (Hedding et al., 2020), the HEI under analysis was not
affected by the #FeesMustFall movement and thus had not previously been exposed to ERL. While
the move to ERL forced academics to re-assess their teaching and learning pedagogy and re-evaluate
their assessment methods, in a country such as South Africa, other factors affected the successful
move to ERL. To understand the impact of the COVID-19 national state of disaster and lockdown on
higher education, it is important to consider the South African socio-economic context. While South
Africa has attempted to alleviate impoverishment, poverty rates remain exceptionally high (Soudien
et al., 2021) and factors such as high data costs and access to technological devices pose a stumbling
block to successful ERL. There are some data-free academic resources available online; however,
unfortunately, the online learning management system (LMS) used by the HEI is not hosted in South
Africa and therefore could not be accessed free of charge. Thus, the HEI negotiated with cellular
network providers to provide data and technological devices to students who required these at a
preferable rate.
Although most attention was focused on the move to ERL in higher education, little consideration
was given to the broader impact of the COVID-19 national state of disaster and the lockdown on
academics and students (Hedding et al., 2020). At the time, many academics and students were
working and studying under heightened anxiety. Some had young children to care for at home and
had to juggle child care, home schooling older children, working remotely, and studying. In addition,
the psychological effect of forced solitude cannot be ignored. The lockdown affected all persons
differently, with some being entirely isolated by themselves without family or friends. Therefore, this
study cannot generalise or highlight any groups of students as being more vulnerable than others
under the COVID-19 national state of disaster and lockdown. Instead, it is important to see all students
as a collective in this situation (Hedding et al., 2020).
MODULE SUCCESS RATES FOR THE 2020 COHORT OF FIRST-YEAR LLB STUDENTS
AT A HIGHER EDUCATION INSTITUTION
New LLB student registrations in 2020
The HEI under analysis offered the LLB degree in three provinces of South Africa, namely the
Western Cape, Gauteng and KwaZulu-Natal (KZN). The table below indicates that in 2020, the HEI
acquired a total number of 635 registrations for the first-year programme of the LLB.
Table 1: Quantitative summary of 2020 first-year registrations
New students
Returning students
Full load
228
Repeat students
298
89
58
Total students
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Table 2: Demographics of the 2020 new first-year LLB students
African
Coloured
Indian/Asian
White
Other/Unknown
81
31
53
59
4
The 2020 LLB cohort consisted of 228 new students who had not been registered at the HEI
previously and registered for the first time in 2020; 298 returning students who registered for a full
load of first-year modules in 2020 and had previously been registered at the HEI; and 89 returning
students who repeated a few of the first-year modules while also being registered for second-year
modules and had also previously been registered at the HEI. Therefore, 407 first-year LLB students
in 2020 had been registered at the HEI previously and had been exposed to the traditional face-toface teaching and learning pedagogy in previous years. In 2020, 228 first-year LLB students
registered at the HEI for the first time and, as mentioned above, had experienced traditional face-toface teaching and learning for one month before the declaration of a national state of disaster and
lockdown and the subsequent abrupt move to ERL. Therefore, only 36% of registered first-year LLB
students in 2020 were students who had gone into ERL without any experience of traditional face-toface teaching and learning and assessment styles. The focus of this research was on these identified
students so as not to skew the findings reported in this paper by including returning students who had
experience of traditional face-to-face pedagogies before the COVID-19 national state of disaster.
In addition, the data indicate that 165 of the 2020 new first-year LLB students were from previously
disadvantaged backgrounds. This equates to 72% of the 2020 new first-year LLB students being from
previously disadvantaged backgrounds. The demographics of the new LLB first-year students in 2020
are relevant to this paper, as this data relate to the challenges faced in legal education (discussed in
section 2.1 above) and the transition to higher education (discussed in section 3.1 above) and shows
that the 2020 new first-year LLB students registered at the HEI under analysis were predominantly
from previously disadvantaged backgrounds.
LLB module success rates in 2020
The following table provides a summary overview of first-year LLB students’ module throughput,
distinction, pass and dropout rates:
Table 3: Percentage of module throughput, distinction, pass and dropout rates 1
Module Throughput
Rate %
Module Distinction
Rate %
Module Pass Rate %
Module Dropout
Rate %
2019
2020
Variation
2019
2020
Variation
2019
2020
Variation
2019
2020
Variation
Cape Town
68
64
-4
28
38
10
85
83
-2
20
23
3
Gauteng
68
63
-5
30
36
6
87
81
-6
22
22
0
KZN
74
71
-3
29
41
12
88
87
-1
17
18
1
Overall
average %
70
66
-4
29
38
9
87
84
-3
20
21
1
The data used in table 3 were obtained electronically from the institutional data analytics platform. The information
provided by this system was used to make evidence-based decisions in respect of the HEI’s teaching and learning strategy
and student support.
1
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The table above shows an overall decrease in module throughput rates and pass rates in relation to
the 2020 first-year LLB cohort. This means that in all regions where the LLB is offered by the HEI,
there was a decrease in the number of students who were able to complete their first-year modules
within the required time of one year when compared to the 2019 first-year LLB cohort. This decrease
in throughput and pass rates is aligned with the initial prediction of the authors that ERL could have
a negative impact on student success rates. As a result of the decrease in throughput and pass rates,
the 2020 LLB first-year cohort may have had to repeat first-year modules in 2021 and was, therefore,
possibly unable to progress to all their second-year modules. In addition, these students are likely to
be unable to complete their LLB degree within the minimum time of four years. This decrease in
throughput and pass rates has a further impact on the retention rates of the HEI, as experience has
shown that unsuccessful students often do not return to complete their studies in subsequent years.
This is confirmed by the increase in dropout rates, which indicates an overall average of a 1% increase
in the dropout rates in 2020.
The variation in the dropout rate is difficult to attribute solely to the impact of ERL without comparing
the variation to the dropout rate in previous years. The overall average dropout rate in the LLB degree
at the HEI in 2018 was 40%. High dropout rates are generally attributed to the fact that students often
embark on studies in a field because they believe they are competent in that area and university study
is the next logical step in their lives. They quickly discover that they are not competent in that area or
that their expectations and assumptions of the area of study or chosen profession were incorrect. This
often results in dropouts and changing of qualifications, which has become commonplace in
universities today (Willmot & Perkin, 2011). However, notably, for the LLB degree, previous studies
have shown that only 22% of LLB students graduate within the minimum time. This is the lowest
percentage of graduation rates when compared to other disciplines at HEIs (Greenbaum 2010). Data
acquired directly from LLB students at the HEI who had dropped out in 2018 indicate various reasons
for doing so, such as gaining admission to the LLB at another institution; financial reasons; a lack of
interest in the law; and changing to a different qualification offered by the HEI.2
The HEI that is the focus of this study introduced its first LLB cohort in 2018 and, therefore, the
2018, 2019 and 2020 dropout rates could not be compared to previous years. However, it is interesting
to note that the data show a significant decrease in the dropout rate from 2018 to 2019 and then a
slight increase in 2020 with the introduction of ERL. It can be deduced that although it is a slight
increase, the impact of COVID-19 and ERL on higher education are contributory factors to the
increase of 1% in the dropout rate in 2020. The authors recommend further study on this issue to
determine what the other related factors are to the student dropout rate. By comparison, the increased
college student dropout rate in the United States was even more evident. Of the 2.6 million students
who had started college in the autumn of 2019, 26.1% did not return in 2020. This figure was an
increase of two percentage points over the previous year and the highest share of students not
returning for their second year of tertiary studies since 2012 (Krupnick, 2022).
It is interesting to note an increase in the number of students who obtained distinctions for their
modules. Most noteworthy is the high rate of distinction passes (41%) in the KZN region. Distinction
passes in the LLB degree are usually rare and rates are low due to the nature of this professional
degree. The authors deduct that the increase in distinction rates is likely due to the assessment strategy
that was implemented in 2020, which resulted in all formative and summative assessments being
written as take-home assessments where students were provided with five days to complete and
submit their assessment as well as the opportunity to resubmit their assessment at a later stage after
having made improvements to their initial submission according to their lecturer’s feedback.
2
The data were acquired directly from students who had dropped out via brief telephone conversation and e-mail.
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Therefore, it would be interesting for further research to be conducted to determine why these rates
increased substantially in 2020.
The new first-year LLB students were registered for 12 modules in 2020 that were evenly spread
across two semesters. Four of these modules were non-law modules, which provided the students
with two compulsory modules to prepare them for higher education and an opportunity to choose two
elective modules offered in a discipline other than law. The remaining nine modules were compulsory
law modules. The table below illustrates the MSRs at a modular level, which is necessary to determine
priority or at-risk modules and those that require intervention and support. For this paper, the focus
is on the law modules only.
Modules
Law of
Persons and
the Family 1A
Fundamentals
of the South
African Legal
System
Law of
Persons and
the Family 1B
English for
Law
General
Principles of
Criminal Law
Foundations
of the South
African Law
Work
Integrated
Learning 1
Table 4: Comparison of Module Success Rates in 2018/2019/2020
2018
72
65
63
68
47
62
67
2019
79
74
57
70
52
58
74
2020
73
64
47
64
64
52
67
As predicted, table 4 indicates a decrease in the MSRs of all first-year law modules in 2020 when
compared to the 2019 results. All first-year law modules saw a decrease in the MSRs of 6% or more
when compared to the 2019 results. Notably, the MSRs in 2018 showed an increased variation in
2019 in the majority of modules. While the MSRs in 2020 were mostly above the pass rate of 50%,
it is still concerning that the variation in results dropped. This relates to the module pass rates provided
in table 3, which indicate a variance in module pass rates in 2020 when compared to 2019. There is
one module, the Law of Persons and the Family 1B, which had a module success rate of 47% in 2020.
This MSRs was below the pass rate of 50%. However, this module is historically one with low pass
rates at the HEI and, therefore, interventions and support in this regard are discussed in the next
section. Nevertheless, the 2020 first-year LLB cohort had mostly passed their modules despite the
decrease in overall MSRs when compared to their 2019 peers. Despite having mostly passed their
modules, due to the complex background of the LLB degree and legal profession, a student’s module
result is exceptionally important for the student to gain access to the second phase of legal education
– namely, vocational training mentioned in the section above. Acquiring a position for vocational
training at a law firm is extremely competitive in South Africa, and law firms shortlist students for
vocational training based on their LLB module results. Therefore, the variation in the 2020 MSRs
could potentially impact this cohort’s access to phase two (vocational training) of legal education and
ultimately the student’s access to the legal profession.
INTERVENTIONS AND SUPPORT OFFERED DURING EMERGENCY REMOTE
LEARNING
At the onset of the national state of disaster and lockdown, the need to support students academically,
physically and psychologically was quickly identified at the HEI. As the LLB students came from
diverse social and economic backgrounds, the need to orientate and address the varying levels of
student preparedness and accessibility to resources was critical to enable students to continue their
studies remotely, to set them up for success, and to enable them to feel emotionally secure in their
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learning. Owing to the limited scope of literature on ERL that was available at the time and the
essential need to provide adequate interventions to support the students, there was insufficient time
to conduct a formal research-based needs assessment of student preparedness.
Thus, the HEI undertook an informal needs analysis telephonically to determine a foundation for
training students on the use of remote learning tools. The outcome of this assessment illustrated that
many students would require support and access to the requisite technologies to support their
continued learning in an online environment. To address this, the HEI provided data to students to
ensure that there were no constraints to accessing the LMS and other academic material or resources.
In addition, academic staff were sensitised to facilitate online lectures in a “data light” environment.
For example, lecturers ensured that real-time engagement with students was kept short and that only
the most pertinent sections of an online lecture were made available on the institutional LMS for
students to download at a later stage.
To develop a greater understanding of online teaching and learning, the LLB academic staff received
structured training on the pedagogical approach to online teaching and marking, which was
implemented as a quick response to the declaration of the national state of disaster and lockdown.
Moreover, students and academic staff received scaffolded training on the LMS from the teaching
and learning specialist staff at the HEI during the period March to April 2020. This assisted students
and academic staff to become familiar with and to engage more confidently in a virtual classroom
environment. Every effort was made to ensure that “no student was left behind”. Furthermore, a short
learning programme outlining useful tips on how to study effectively in an online environment was
released on the institutional LMS and made available to all students.
To support students academically in the transition to ERL and a new and different assessment model,
continuous assessment marks (CASS) were waivered. Under normal circumstances, students need a
weighted average CASS mark of 40% to gain entry into the summative assessment of a particular
module. CASS was waivered, in line with the HEI’s commitment to “no student left behind”, to
provide every student with access to the summative assessments. In addition, students were given
five days within which to complete and submit their formative and summative take-home assessments
via the LMS. The HEI took this decision to counter the data and connectivity challenges faced by
many students. In addition to the initial academic support to enable a smooth transition to ERL, the
Student Support Services department of the HEI made non-academic support available for extended
periods to support students with any physical, psychological and emotional difficulties, as well as
other methods of support to assist students in staying motivated and productive during this
challenging period.
The level of student engagement during online lectures was tracked by the academic support team.
Personal contact was made telephonically and electronically with students identified as being
academically “at risk”. Students who had not participated in any online lectures owing to technology
issues encountered at home or due to struggling with connectivity issues were categorised as “at risk”.
Consequently, during the period 17 June to 31 July 2020, additional online support for certain firstsemester LLB modules was provided for the at-risk first-year LLB students to assist them in preparing
for their summative assessments and successfully completing their academic year. This additional
support, called “boot camp(us)”, entailed workshop-like sessions provided on campus in a face-toface environment prior to the summative assessment period for those students who had not been able
to participate in the online process.
With the transition to ERL, the HEI identified the need to develop alternative ways of delivering the
practical aspects of the LLB curriculum. This entailed the moving of practical tasks to the online
environment rather than being held as in-person interactions. For example, traditionally first-year
LLB students participated in a face-to-face Moot Court competition as one of the components of their
work-integrated learning module intending to expose students to trial advocacy skills from their first
year of studies. However, in 2020, participation in the Moot Court competition was held online via
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the LMS. Moreover, the criteria for the assessment thereof were adapted to suit an online
environment.
The need to create opportunities for students to communicate beyond the classroom was identified
by Garcia as one of the most challenging communication problems to ERL during the COVID-19
pandemic (Garcia-Verdrenne et al., 2020). Therefore, to support students further, lecturers were
encouraged to engage with students using the discussion forum facility on the LMS to clarify any
task instructions and facilitate collaboration for any group tasks assigned to students. The discussion
forum and “breakout room” tools were also utilised extensively. A “breakout room” is a private online
space where smaller groups of students and lecturers can meet separately from the larger classroom
(Garcia-Vedrenne et al., 2020). A specific number and/or group of students per room can be set in
advance, or students can be assigned to groups randomly by the LMS. This enabled students to
communicate with their lecturer and with their peers through group work and class discussions, thus
providing an alternative opportunity to engage without the ability to have face-to-face meetings in a
physical lecture room. Further support for the 2020 first-year LLB students was provided in the
development of detailed lesson plans outlining the content, pre- and post-reading and activities to be
completed for each specific topic in a module. In addition, short instructional videos on key concepts,
with a maximum duration of 15 to 20 minutes, were created by subject matter experts to introduce
the students to new study material that would also be covered during online lectures, using platforms
such as the LMS, PowerPoint and/or YouTube. The provision of the short instructional videos and
additional study materials allowed students to access these resources asynchronously and on multiple
occasions whenever they felt the need to do so.
LESSONS LEARNT AND THE WAY FORWARD
This section aims to present both the lessons learnt and challenges experienced in relation to student
success rates during the national state of disaster for the 2020 first-year LLB students at the HEI. In
response to the seismic disruption of student learning during the national state of disaster, which
continued throughout the 2020 academic year, regular communication with the LLB students to assess
their specific learning needs was a critical factor in the transition from face-to-face tuition to ERL.
Academic staff had to respond to the challenges presented by the need to transition to ERL with
creativity, agility and compassion for students. A longitudinal study into the student interventions
provided for this cohort during COVID-19 could be conducted in future years to assess their level of
preparedness for legal practice.
The scarcity of interpersonal relations during ERL resulted in students feeling somewhat detached
and demotivated. This was a challenge faced by many of the 2020 first-year LLB students and was
addressed by the HEI through their Student Support Services department. However, a lesson learnt is
to be more aware of the holistic needs of students – particularly new first-year students who are still
transitioning to higher education in times of crisis, such as the national lockdown – and to be more
cognisant of their psychological and emotional needs and not focus solely on their academic needs.
A positive takeaway from the experience of ERL is that the academic staff at the HEI were given the
opportunity to re-evaluate their online teaching practices. This included the development of both
synchronous and asynchronous activities for the first-year LLB students to engage with the study
material through the provision of lesson plans, introductory videos and learning activities prior to
each online lecture. This resulted in the creation of a more flexible and inclusive approach for students
to acquire conceptual knowledge of foundational legal concepts. Furthermore, it gave lecturers the
opportunity for self-reflection and to upskill themselves in an evolving world where skills in online
teaching and learning are becoming a prerequisite.
One of the initial challenges of the transition to ERL was that the HEI did not foresee the COVID-19
pandemic continuing for the prolonged period that it did. Initially, the transition to ERL was believed
to be temporary and, therefore, as South Africa moved down the levels of lockdown, the HEI made
an intentional effort to bring students back to campus, in classrooms, for face-to-face lectures.
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In the second semester of 2020, a revised teaching and learning model was introduced by the HEI
that consisted of the contact time for each module being divided as follows: 50% of online lectures;
25% of face-to-face lectures; and 25% of self-directed learning (SDL). In the latter category, students
were expected to engage with the extra academic material and resources provided for their modules,
including the videos that were created by tenured lecturers, and lecturers were tasked with providing
meaningful feedback on activities completed and to engage with students individually. Importantly,
for LLB students, SDL equips students with skills that go beyond the lecture room and often emulate
professional practice (Gibbons, 2002; Pedley & Arber, 1997). Although this revised model was a
necessary effort to recoup the remainder of the academic year, more cognisance should have been
taken of the physical and psychological impact of the national state of disaster and lockdown on
academic staff and students. For example, many academic staff members and students were daunted
by the prospect of returning to campus for face-to-face lectures.
To provide support in this regard, the HEI decided to live stream face-to-face lectures for students
who were unable to physically be on campus for the face-to-face lecture. This, in turn, placed a burden
on lecturers to upskill in the use of technological devices necessary for the live streaming and other
considerations when teaching to a physical class and others streaming into the lecture. This model
also meant that the HEI had to renovate lecture venues to ensure that social distancing was observed.
As a result, classes had to be split to ensure that the lecture venue capacity was not exceeded, which
resulted in lecturer workloads increasing, live-streaming equipment had to be acquired, and data
needed to continue being supplied to students with data-related challenges and who needed to live
stream their lectures. Not only was this a time-consuming and expensive exercise, but the student
attendance of face-to-face lectures was poor despite all the necessary precautions having been taken
to ensure the safety of students and staff.
CONCLUSION
The rich history of the offering of the professional LLB degree in South Africa has illustrated that
this is a challenging qualification for new students to grapple with. This contextual reality coupled
with the historical legacy of Apartheid and its effect on legal practice make the completion of the
LLB degree even more challenging in its exclusivity; there is a lack of consideration of socioeconomic factors that impact students and persons in the legal profession. In addition to the socioeconomic considerations, it is imperative to consider the South African legacy and its relation to
secondary education. This impact, which has led to an unequal South African schooling system, has
a knock-on effect on the ability of new students to transition from secondary education to an HEI, as
many new students do not have the necessary skills to cope with higher education.
When analysing student success rates, it is important to remain cognisant of the challenges outlined
above, as most of the students at the HEI are from previously disadvantaged backgrounds. In addition,
the unprecedented challenges posed by the COVID-19 pandemic exacerbated the already difficult
position that students found themselves in and impacted student success rates. With the national state
of disaster, the HEI was challenged with the rapid move to ERL and alternative ways of assessing
students. Both the academic staff and students were required to upskill their technology skills rapidly,
and both groups were also challenged by the physical and psychological impact of being confined to
their homes due to public health concerns – some with a lack of technological access and/or some
having to contend with increased domestic responsibilities and having to make the move to ERL.
The findings of this study revealed that only 36% of first-year LLB students in 2020 were new
students and, therefore, these students were the focus of this paper. This is because these students did
not have much exposure to and experience of traditional face-to-face teaching and learning before
being forced to grapple with ERL, whereas returning students had experienced a normal academic
year, with traditional face-to-face teaching and learning in 2019 prior to the national state of disaster.
In addition, the demographics of this group of new students indicated that 72% of students registered
at the HEI for the 2020 first year of the LLB degree were from previously disadvantaged backgrounds
and, therefore, the demographic challenges are valid and relevant to this cohort of students. These
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socio-economic challenges coupled with the traditional challenges of the LLB degree, the physical
and psychological impact of the COVID-19 state of disaster and lockdown and ERL were bound to
have an impact on student success rates of this new cohort of LLB students.
This research found that despite the MSRs of most of the law modules undertaken by this cohort in
2020 being above the pass rate of 50%, there was an overall decline in the module throughput and
pass rates, an increase in module dropout rates and, interestingly, an increase in module distinction
rates compared to 2019. Moreover, when considering specific LLB MSRs at the first-year level, it
was found that all MSRs declined by 6–10% year on year. While most students passed their first-year
LLB modules, the lower-than-usual pass rates may potentially impact this cohort’s access to the
extremely competitive legal profession, where results are often consulted before offering students
placements at law firms for their vocational training. On the other hand, the increase in the distinction
rate may positively impact those students’ ability to acquire placement for vocational training and,
ultimately, entry into the legal profession.
The reflection on the HEI’s response to the transition to ERL has been most valuable in identifying
ways in which student support services can be enhanced. It is clear that the HEI put many
interventions put in place to support students and academic staff in the transition to ERL and the
successful completion of their first-year modules. The physical need for data and technological
devices was provided for by the HEI as well as psychological support through the Student Support
Services department. However, the authors are of the view that there is potential for the improvement
in the HEI’s support of students with their transition to higher education generally. Further research
into whether this will have the desired knock-on effect on academic success rates can be conducted
at a future date.
One of the primary lessons learnt during the ERL period was the need for agility and adaptability.
Both students and academic staff showed great ability in these characteristics and took the transition
to ERL mostly in their stride. The opportunity for academic staff to upskill in an evolving world was
beneficial to all stakeholders, as the way we live, work and study has been forever changed by the
COVID-19 pandemic.
Like all new experiences, some aspects of ERL worked well, while others did not. The use of the
LMS for live online lecture sessions, breakout rooms and discussion forums was a great success in
creating opportunities and a sense of community for engagement between lecturers and students, and
amongst students and their peers. Similarly, the HEI’s decision to include SDL in a module’s contact
time was beneficial to the first-year LLB students, as it mirrored professional legal practice and
allowed students some autonomy and responsibility for their learning. On the other hand, the HEI
quickly learnt that the multiple submission assessment strategies were burdensome on lecturers and
not always ideal for students.
The way forward is positive and has room for further research on this topic. The authors are keen to
continue their research and determine the perceptions of LLB students and academic lecturing staff
concerning the transition to ERL and the HEI’s response to ERL, as well as to determine the impact
of the 2020 MSRs on the subsequent years of study for this LLB cohort. In addition, after the 2020
first-year LLB cohort has graduated and entered the world of work, it would be interesting to evaluate
whether, if at all, ERL has had an impact on their abilities in the workplace.
Considering the above, this paper has met its stated purpose and confirmed the authors’ prediction in
that the 2020 national state of disaster negatively impacted the MSRs of first-year LLB students in
the 2020 academic year. It is recommended that further studies be conducted to determine what other
factors contributed to the increased dropout rates of first-year LLB students in 2020.
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AN INVESTIGATIVE STUDY OF OPINION MINING ABOUT ELEARNING AND TRANSFORMATION THAT TOOK PLACE
DURING THE COVID-19 PANDEMIC
Shubham Dubey
University of Debrecen, Hungary (shubhamdubey1312@gmail.com)
Prasun Sharma
Etvos Lorand University, Hungary
Abstract
Several innovations and strategies were executed during the period of COVID-19, resulting in a huge
e-learning acceptance rate among learners. Numerous educational tools, platforms, and products as
a service came in contrast during COVID-19. Both teachers and students have accepted the electronic
means of learning optimally. This study investigated the level of acceptance and changes that took
place during the pandemic. This includes opinion mining about ICT in education and expected
transformation in pedagogy. The data from a survey were used for an opinion and association
analysis of several factors that affect learners’ expectations in order to adopt a virtual mode of
learning. The data were collected from 8 392 respondents during the pandemic when schools and
colleges were shut in India. Around 25% of the total respondents admitted that ICT had transformed
their learning habits and countered the shortcomings of the traditional learning setup. Out of 8 392
respondents, 7 392 (88%) realized and stated that ICT-supported learning could raise educational
standards. The majority (85%) believed that ICT-enabled learning could supplement classroom
learning. Moreover, the mutual relation between the opinion of respondents and the factors associated
with e-learning and the transformation that took place during the pandemic were investigated. After
analyzing the data, one can say learners have accepted the electronic mode of learning because of
several handy tools, portals, resources, and quality content. Of course people complained about less
interaction with respect to the face-to-face mode, stress and eye strain, addiction to technology,
etcetera. In this study, the Apriori algorithm was used to find relations among several factors that
needed to be analyzed for e-learning. This research is useful for the future researcher and policymakers when it comes to implementing and planning ICT-supported education at a further level and
for a longer duration.
Keywords: e-learning, opinion mining, association analysis, Apriori algorithm, ICT in education
INTRODUCTION
The world of academics is changing rapidly. The COVID-19 pandemic has brought some coincidental
positive impacts too (Mishra et al., 2020). The world has embraced the ICT-supported educational
setup (Ali, 2020). However, there is no doubt that several hitches hinder the success of the e-learning
setup. Educational data mining has become a well-known field after the growth of ICT-supported
education (Baker & Yacef, 2009). In the contemporary era, there are several social sites, social
platforms and forums that are optimally exploited by learners of all fields. Several studies are
conducted on finding an association among several factors that affect the education system. In ICTsupported education, there are several factors that affect readers’ motivation. An experimental study
was conducted about this phenomenon (Dubey & Marton, 2021).
Classification techniques like the KNN algorithm, the decision tree algorithm, the SVM algorithm,
the Naïve Bayes and Random Forest algorithms are very famous algorithms (Witten & Frank, 2002;
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Zaki et al., 2014). These are frequently used algorithms in academics to achieve classification tasks
for different purposes. Classification can be concluded as an association rule too (Liu et al., 2001).
An association rule is an antecedent and consequent notation of a frequent itemset. “A⇒B” is an
association rule that denotes that A and B are highly associated for certain support and confidence
values (Han et al., 2011; Zheng et al., 2001). The first step to find the association rule is to get the
frequent itemset. Later in the second step, the rules are made based on step 1. If the values are
quantitative, one can easily find a relation between attributes using correlation (Pearson coefficient),
regression, or some other schemes (Sheugh & Alizadeh, 2015). However, when the attributes are
qualitative, it becomes very difficult to find an association among them. This research is a classic
example of such issues – applying a quantitative algorithm to a qualitative dataset that is transformed
into quantitative dataset and again re-transformed to the qualitative dataset.
LITERATURE REVIEW
Online learning was merely considered an experiment before the COVID-19 pandemic. The
pandemic made us realize the urge of online learning. This unprecedented situation of COVID
brought about radical transformation in the existing education system. This led to the unexpected and
forceful implementation of online learning processes (Ionescu et al., 2020). Online education
platforms and their execution were put to the test to prove their worth. During the COVID-19
pandemic, online learning came as an unknown and unpracticed tool, but with the time, many
technical and pedagogical amendments were made. Quality improvement of several online libraries
was demanded to meet learners’ satisfaction (Dubey et al., 2020).
When lockdowns were implemented everywhere, it was recommended that online education be
implemented to continue education and school activities. Initially, students and teachers were
struggling, and there were some flaws in online learning platforms (Baber, 2021). Gradually, teachers
and students learned to deal with technical problems and to choose the right platform for their
convenience. Studies (Baber, 2021; Bączek et al., 2021) have shown that not only students have
accepted online learning, but teachers have also left the zone of discomfort with online education.
There is a gradual positive progression in the level of acceptance among teachers (Mseleku, 2020).
Some studies also investigate the level of satisfaction from e-learning among students and teachers;
mixed reviews have been provided in this regard (Al-Okaily et al., 2020; Baber, 2020). This highlights
the need for further enhancements and improvements (Dubey et al., 2020; Giray, 2021).
In many studies, comparative evaluation was done of the acceptance of online learning among
students and teachers from pre-COVID-19 and during COVID-19. They found that prior to the
pandemic, teachers and other educators had numerous doubts about the implementation of online
learning and they showed less interest in trying out online learning in their classroom (Amir et al.,
2020; Olum et al., 2020). However, during the pandemic, the same teachers had completely changed
their attitude towards online learning. Teachers are coming up with suggestions for the betterment of
online learning, and it is changing rapidly (Ibrahim et al., 2021; Puljak et al., 2020).
If we look at technical enhancement and improvements made by the online learning platform to make
things more systematic, easy and effective, countable changes have been made in this dimension and
have also been well analyzed and reported by Radha et al. (2020). According to Zalat et al. (2021), a
techno-savvy pedagogical dimension has been introduced during the pandemic, where teachers
moved out of their comfort zone and regularly worked hard to match the rhythm. To the maximum
extent, this dimension had a significant effect on the quality of online learning in the years 2019 to
2021 (Khan et al., 2021).
The discussion above indicates that several studies have been conducted in the field of ICT-supported
education, and they have shown success as well. However, when it comes to the feedback analysis or
opinion analysis of learners during COVID-19, there is a big research gap. This research gap was
filled in the present study.
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METHODOLOGY
Dataset
The dataset used for the research was open-source data. This was available in an open-source data
library known as Kaggle. The data were gathered when the first lockdown was implemented in India.
During the lockdown, data administrators implemented online learning using WhatsApp. Later,
facilitators asked for learners’ feedback and opinions regarding their experience of the established
ICT-supported learning setup in WhatsApp. A total of 8 392 responses were captured for the purpose.
The link to the data is https://www.kaggle.com/hemantapalivela/student-learning-using-whatsapp-incovid19. There were 43 columns in the feedback data. These were reduced to certain numbers when
features were selected for the analysis of association. The list of selected attributes is shown below:
A1: Integration of ICT in academics is important
A2: ICT can deal with the shortcoming in traditional and classical academic patterns
A3: ICT has increased the communication between instructors and students
A4: ICT-supported education is a supplement to face-to-face communication pattern
A5: Instructors use WhatsApp to teach and motivate you to use ICT for academics
A6: Instructors share the study materials and e-content as complement using WhatsApp
A7: Instructors permit uploading assignments using WhatsApp
A8: WhatsApp groups in the class support announcements and meeting scheduling
A9: WhatsApp has allowed communication with peers studying at other universities
A10: WhatsApp supports 24x7 contact facility with teachers and students
A11: There is more frequent interaction between instructors and students due to WhatsApp
A12: WhatsApp motivates you to overcome reservedness to talk with instructor and students
A13: WhatsApp helps out to share study material
A14: Is “lack of time” a main barrier to integration of ICT in learning?
A15: Is “syllabus pressure” a main obstacle to assimilation of ICT in learning?
A16: Is “infrastructure inability” a main barrier to integration of ICT in learning?
A17: Is “addiction to the technology” a main obstacle to amalgamation of ICT in learning?
A18: Is “not interacting face-to-face with people” the major obstacle to integration of ICT in
academics?
A19: Is “non-reliability of online content” the chief obstacle to assimilation of ICT in learning?
A20: Is “need internet connection all the time” the major difficulty for addition of ICT in academics?
A21: “Stress” is the main problem in ICT-supported learning
A22: “‘Information overload’ stress” is the main problem in ICT-supported learning
A23: Reliability and distractions are the main problems in e-learning
Apriori algorithm
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The data were analyzed for rule mining; the rules were used for further inference mining. To find
considerable and valid association rules, there was a need to find the frequent itemset. Apriori
algorithm uses the concepts of frequent items (Han et al., 2011). Two terms drive the frequent set
mining process until the rule mining, namely support and confidence.
Support: Support can be understood as interestingness. In a generic way, one can understand it as the
frequency of an item or a set of items with respect to the total number of transactions (Bhandari et
al., 2015). Support count is the number of times an item or an intended itemset appears. Item “P”
appeared four times, so the support count for {P} was 4, which is 100% (table 1).
Confidence: Confidence of an association rule is basically the ratio of the counts of transactions
having all the items of a consequent and an antecedent, and the count of transitions having all items
in an antecedent (Han et al., 2011).
Table 1: Transaction and items
Transaction
Items
R1
P,S,T,U
R2
P,Q
R3
S,Q,P
R4
S,T,P,Q,U
The table of the frequency is shown below. Table 2 is derived from table 1.
Table 2: 1-Frequent itemsets
Itemset
{P}
{Q}
{S}
{T}
{U}
Frequency
4
3
3
3
2
The minimum support count for the rule establishment was 3, which is 60% of the total number of
transactions (i.e., 4). So, itemset {U} did not qualify for the next iteration. Table 3 represents the two
frequency tables.
Table 3: 2-Frequent itemsets
Itemset
Frequency
{P,Q}
3
{P,S}
{P,T}
{Q,S}
{Q,T}
{S,T}
3
2
2
1
2
Again, itemsets {P,T}, {Q,S},{Q,T} and {S,T} had support less than or equal to 2. This is less than
60% (i.e., < 3). So, itemset {P, Q} and {P,S} participated in the next iteration (Moens et al., 2013).
Table 4 shows the 3-frequent itemsets.
Table 2: 3-Frequent itemsets
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Itemset
{P,Q,S}
Frequency
2
Support of {P,Q,S} is less than minimum support value (3). Hence, {P,Q,S} was not part of further
analysis. So, the itemsets that qualified for the association rule were {P,Q} and {P,S}. The rules were
then checked for confidence (table 5).
Table 3: Rules with support and confidence value
Association rule
Support
Confidence
Selection
P⇒Q
¾=0.75
¾=0.75 (75%)
X
Q⇒P
¾=0.75
3/3= 1 (100%)
✔
P⇒S
¾=0.75
¾= 0.75 (75%)
X
S⇒P
¾=0.75
3/3 =1 (75%)
X
Minimum confidence was 90%. So, rule Q⇒P was the final rule that was selected for the given
support and confidence value. Similarly, the data taken from the survey were used to reduce the
dimensions. There were 43 columns in the main dataset; these were optimized enough up to 23. The
sample of 8 392 respondents was analyzed for association rule mining. The analysis is briefly
described in the next section.
ANALYSIS
Association rule mining
The prepared data were sent to the association rule miner tool, which is designed in C language. The
updated and latest version 6.29 (2020.06.15) was used to analyze the data. The sample of the input
table can be seen in table 6.
The questions asked in the survey were transformed into itemsets (attribute, namely A1, A2, A3, A4
... A23). Most of the questions were from a five point-based Likert scale. If the respondents were
found positive, then the qualitative values were replaced with a “1”, and if the respondents’ response
were negative qualitatively, it was replaced with a blank. All the 1’s in a column were replaced with
the column’s name (attribute).
The input table looked like table 6(b) which was transformed from table 6(a).
Table 6: Transformation of input table
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1
1
1
1
1
…..
1
A1 A2 A3
A5 ….. A23
1
1
…..
1
A1
A5 ….. A23
1
1
…..
1
1
…..
1
1
…..
1
1
1
1
1
A3
A3 A4 A5 …..
A1
1
6(a) Table before transformation
A4 A5 …..
A1 A2 A3 A4 A5 ….. A23
6(b) Transformed table
The transformed table was named my_file and was converted into a CSV file that was fed into the
Apriori tool. The syntax of the input file was as follows (figure 1):
Figure 1. Syntax of Apriori tool execution in command prompt
The standard syntax is:
>apriori –tr –confidence -support name_of_intpufile.txt name_of_outfilename.txt
For example, if we want to input the file for support value 95 and confidence value 90 for an output
file “op.txt”, then the syntax would be:
>apriori –tr –c90 –s95 my_file.txt op.txt
After the execution of the tool, table 7 was prepared, and this led the discussion towards association
rule decoding. The Apriori tool was executed in the given dataset, and the results were captured in
several output text files containing the rules for different support and confidence values. Table 7
contains the number of association rules for several support and confidence values. S: Support; C:
Confidence; N: Number of rules for corresponding “S” and “C” values.
Table 4: Number of rules for different support and confidence values
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S
80 80 80 80
85 85 85 85
C
85 90 95 100 85 90 95 100 85 90 95 100 85 90 95 100 85
90
95
N
143 48 20 0
2
None None
43 17 6
0
90 90 90 90
15 6
1
0
95 95 95 95
4
2
0
0
100 100 100
4
100
100
RESULT AND DISCUSSION
There are many rules when the support value is lesser. This causes the association rule explosion. The
value of support and confidence were kept higher when the significant rules were mined from all
association rules. Associations between several attributes are presented in table 8. The rules having
their support ≥ 85 qualified to be the part of this table.
Table 5: Rules qualified the threshold support and confidence values
Rules
A20 ⇒ A8 A13 (85.2772, 90.1345)
A20 ⇒ A8 A1 (86.6157, 90.287)
A8 ⇒ A20 (88.1453, 91.1063)
A20 ⇒ A13 A1 (88.9101, 90.3226)
A13 ⇒ A20 (88.1453, 93.9262)
A1 ⇒ A20 (88.1453, 96.0954)
A1 ⇒ A8 A13 (85.2772, 97.0852)
A13 ⇒ A8 A1 (86.6157, 95.585)
A8 ⇒ A13 A1 (88.9101, 93.1183)
A13 ⇒ A8 (89.4837, 95.2991)
A8 ⇒ A13 (92.543, 92.1488)
A1 ⇒ A8 (89.4837, 96.7949)
A8 ⇒ A1 (94.8375, 91.3306)
A1 ⇒ A13 (92.543, 96.0744)
A13 ⇒ A1 (94.8375, 93.75)
The threshold value for the rule picking was support=85 and confidence=85. The above-listed rules
totaled less than 43, as some self-associations were eliminated. To derive the inference, the minimum
support was kept 85 and minimum confidence 90. The next step was decoding the association rules.
A20⇒A8 A13 (85.2772, 90.1345) – This rule shows that there was a considerable association
between attributes {A20: The main hindrance of ICT-supported education is it needs internet
connection all the time} and {A13: WhatsApp helped learners to share documents and resources, A8:
ICT-supported education has changed the mean of communication as meeting and classes can be
scheduled as per easiness}.
Opinions about “WhatsApp helped learners to share documents” and “Resources and ICT integration
in education is important” had the strongest associations, with 94.8375 support value and 93.75
confidence value (namely A13⇒A1). “ICT-supported education is important” and “ICT-supported
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education has changed the way students interact with teachers” were tightly coupled – evidence is
A1⇒A8 (89.4837, 96.7949) and A8⇒A1 (94.8375, 91.3306).
A deeper insight into the rules shows that certain attributes appeared frequently in the association
rules; A1, A8, A13, A20, A3 (ICT has enhanced communication among teachers and students) and
A6 (Changes in communication behavior due to ICT using WhatsApp). These frequent itemsets were
the main attributes that made a significant impact on learners’ opinion about ICT-supported education
systems. The inferences derived from this section are summarized next.
CONCLUSION
COVID-19 has transformed the pattern of both teaching and learning. Policy-makers, educationists
and academics are working continuously to improve the quality of ICT-supported education in favor
of learners’ motivation (Dubey & Piroska, 2019). Learners and teachers’ feedback become very
important to discover the scope of improvement. In this study, the opinions of learners who followed
ICT-supported learning were analyzed. The findings add facts and quantitative association between
several opinions (attributes). The impact Rule A20 ⇒ A8 A13 shows that learners spent time in ICTsupported learning, so they needed to share the documents and also get connected whenever a meeting
was scheduled. They considered these two as positive aspects of ICT-supported learning. On the other
hand, however, they complained that there was a need for the Internet all the time, which is a
hindrance to ICT-supported education. This relation (A13⇒A1) concludes that learners felt
comfortable in ICT-supported education, but they wanted further improvement in the quality and
services of ICT-supported education.
The discussion above indicates that learners followed the online mode of learning using WhatsApp.
There were several issues while implementing it, but also some goods. The problem of consistent
internet connection is the biggest challenge. Other than that, the difficulties in communication or
reduced communications are big issues. Regarding content delivery and resources availability, the
respondents favored that the sharing of content using WhatsApp brought easiness in their academics
(Baishya & Maheshwari, 2020).
The advantage of finding association between such factors is that the handling of the hitches in ICTsupported learning will become easier. The association shows that the attributes were tightly coupled,
so solving one problem would definitely help indirectly solve the related attributes as well. This paper
gives a future direction and guidance for upcoming research on analyzing learners’ feedback and
opinions.
Acknowledgements
Authors would like to acknowledge and thank the University of Debrecen for the smooth conduct of
research and analysis phase of this work. This study was supported by the Stipendium Hungaricum
fund.
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REFLECTIVE TEACHING AND LEARNERS’ PERFORMANCE:
THE CASE OF A SELECTED REGION IN NAMIBIA
Dr Simasiku Limbo Enock
University of Namibia (lesimasiku@unam.na)
Abstract
This study was conducted in a selected region of Namibia. The purpose of study was to determine
teachers’ understanding and application of reflective teaching and how it influenced learner
performance in the national examinations. Reflective teaching is a treasured teaching approach in
which teachers gather information about their own classes and pay close attention to their behaviour
and teaching strategies. Hence, teachers can evaluate themselves to discover their strengths and
weaknesses. Technology plays a critical role in teachers’ ability to gather data on self-reflective
teaching. Lately, the positive effects of reflective teaching on its potential to improve learner
performance are obvious to most teachers (Spalding, 2020). In this study, the possible application of
reflective teaching in different aspects of teaching was investigated. A mixed-methods case study
design was used in this study. The target population was the teachers in all senior secondary schools
in a selected region (Namibia). A purposively selected sample of five senior secondary schools out of
10 was considered for this study. Stratified purposive sampling was applied in selecting 15 teachers
to participate in this study. The school principals automatically constituted the sample of the study,
which implied that the inclusive sample consisted of 20 participants (teachers and principals
included). The following instruments were used to identify teachers’ reflective teaching skills:
Reflective Teaching Closed- and Open-Ended Questionnaire; Reflective Teaching Lesson
Observation Checklist; and the Reflective Teaching Interview Schedule for teachers and principals.
In this study, common trends in the data were analysed by adapting the steps developed by Creswell
and Clark (2018) for data analysis. The findings of the study revealed that teachers were not wellequipped with skills and knowledge, and digital resources were necessary to effectively engage in
reflective teaching. As argued by Ferwana (2006), a good reflective disposition of a teacher can
improve learners’ performance.
Keywords: reflective teaching, reflective practice, reflection in action, reflection-on-action,
reflection-for-action, social constructivism, cognitive constructivism; metacognition.
BACKGROUND
In most Namibian schools, reflective teaching is left to the discretion of the teacher to decide whether
to apply it. This is mainly because there seems to be no clear rule, policy, guidelines or education Act
on the implementation of reflective teaching in schools. Reflective teaching is an important approach
to teachers, since it helps them develop in many ways, like problem-solving and decision-making
processes, and it fosters critical-thinking abilities. Reflective teaching is an innovative approach in
teaching. It is a valuable approach in which teachers use their intuitions and experiences to observe
their performance, evaluate themselves, criticise their practices, and accept other criticism openmindedly. It helps them to progress and develop their teaching performance. Therefore, reflective
teaching is a useful process that leads to teachers’ professional growth.
Moreover, the reflective approach to teaching involves changes in the way we usually perceive
teaching and our role in the process of teaching. Teachers, who explore their own teaching through
critical reflection, develop changes in attitudes and awareness that they believe can benefit their
professional growth as teachers and improve the kind of support they provide to their students.
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However, like other forms of self-inquiry, reflective teaching is not without its disadvantages, since
journal writing, self-reporting, or making recordings of lessons are definitely time-consuming.
Though there are other approaches that are known to influence the quality of teaching in the
classroom, this study focused on teachers’ application of reflective teaching as an approach to enhance
the quality of teaching. National and international literature suggests that the ability of teachers to
efficiently apply reflective teaching is the mother of factors influencing the quality of teaching that
happens in the classroom. Swarts (1998) suggests that without applying reflective teaching, teachers
may not be able to identify certain areas of concern in the teaching profession.
The data collected from the questionnaires, classroom observation, interviews and end-of-year results
were used as a measure of teachers’ reflectivity. Zwozdiak-Myers (2009) argues that reflective
teaching enables teachers to do introspection in teaching and ultimately affects improved academic
performance of learners. It can therefore be suggested that a continuous decline or consistently poor
academic performance of learners is an indicator of the absence or lack of teaching reflectivity in the
classroom.
PROBLEM STATEMENT
Reflective teaching is known to improve the quality of teaching and learning that precede quality
performance by learners in the national examinations (Ferdowsi & Afghari, 2015). In the region
where this study was conducted, there seemed to be a consistent lower achievement of quality
symbols by learners in the national examinations. Therefore, this study was undertaken to determine
how teachers engaged in reflective teaching and how their engagement influenced learners’
performance in the selected region.
The objectives of the study were as follows:
i.
ii.
iii.
to elicit teachers’ responses on their understanding of reflective teaching in the selected
region;
to establish the value attached by teachers of applying reflective teaching in the selected
region;
to determine how principals assessed the application of reflective teaching and its influence
on learners’ performance in the selected region.
LITERATURE REVIEW AND THEORETICAL FRAMEWORK
The concept of reflective teaching stems from reflective practice – a concept that originated from the
work of John Dewey (1859–1952), an American who took the notion of reflection from philosophy
and introduced it to the fields of psychology and pedagogy. According to Zwozdiak-Myers (2009),
Dewey’s ideas provided a basis for the concept of reflective practice which gained influence with the
arrival of Schon’s idea in 1983. One of Schön’s (1983) most important and enduring contributions
was to identify two types of reflection: reflection-on-action and reflection-in-action. In both types of
reflection, professionals aim to connect with their feelings and attend to relevant theory. Reflective
teaching means looking back at what you do in the classroom and giving it a meaning by attaching the
why question to what you go through (Bailey, 2012; Loughran, 2006; Spalding, 2020). Bailey (2012)
further asserts that in the classroom setting, reflective teaching would then mean gathering data on
learning and teaching, organising, analysing and presenting the data, and making informed decisions
that lead to better learning and teaching. They seek to build new understandings to shape their action
in the unfolding situation.
Reflective teaching is closely associated with three theories that rope the link between reflective
teaching and learner performance: social constructivism, cognitive constructivism, and metacognitive
theory. This study adopted metacognition as a theoretical framework. The theory of metacognition
relates to the principles of reflective teaching in that it is cognition about cognition, thinking about
thinking, knowing about knowing, becoming aware of awareness, and higher-order thinking (Philip
& Dwayne, 2010). John Flavell originally coined the term metacognition in the late 1970s to mean
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“cognition about cognitive phenomena”, or more simply “thinking about thinking” (Flavell, 1979, p.
906). Subsequent development and use of the term have remained relatively faithful to this original
meaning.
As Kuhn and Dean (2004) explain, metacognition is what enables a learner who has been taught a
particular strategy in a particular problem context to retrieve and deploy that strategy in a similar but
new context. In cognitive psychology, metacognition is often defined as a form of executive control
involving monitoring and self-regulation – a point also echoed by other researchers (McLeod, 1997;
Schneider & Lockl, 2002).
In her research report on metacognition, Lai (2011) postulates that educational psychologists have
long promoted the importance of metacognition for regulating and supporting learner learning. Lai
(2011) states that the partnership for 21st-century skills has identified self-directed learning as one of
the life and career skills necessary to prepare learners for post-secondary education and the workforce.
However, educators may not be familiar with methods for teaching and assessing metacognition,
particularly among elementary aged learners.
Definition of reflective teaching
Bolton (2010) states that reflective teaching is a process of learning and developing through
examining one’s own practice and opening this to wider scrutiny by others and studying texts from
other spheres. Bolton believes that knowledge is stored in stories and moments; in those fragments it
can be retrieved from our memory, and by reviewing the fragments, elements that were not seen in the
course of the action can be discovered.
Reflection-in-action is a cognitive habit of observing how we think in the process of the action and
adapting our thoughts to the requirements of the change we are trying to achieve (Schön, 1983). It is
the management at real time of the approach we are using for analysing the situation, the assumptions
we are taking for granted, the main characteristics of our mental model in respect of the problem we
are addressing. Donald Schön referred to reflective teachers as professionals who have developed
their capacity for reflection-in-action, reflection-on-action and reflection-for-action, for being aware
of the conversation they are having with the situations when they are trying to make a change, the
capacity of seeing the external (physical and social) reality, and their internal cognitive reality.
In the wake of the COVID-19 pandemic, reflective teaching needed to embrace technology as an
enabler for teachers to gather data on their application of reflective teaching. Moreover, multimodal
avenues for sourcing data on reflective teaching had become a necessity as schools became more
characterised by random closures on the basis of the recorded cases of the global pandemic (COVID19).
Methods of reflective teaching
The rationale for including the methods of reflective teaching in this study was primarily to compare
the methods of reflective teaching that are applied in the Zambezi Region compared to the
internationally renowned methods of reflective teaching. These methods further informed some
questions included in the data collection tools used in this study. Zwozdiak-Myers (2009)
recommended the following as methods of engaging in reflective teaching: reflective journaling; peer
mentoring; video/audio recording of lessons; teacher’s portfolio. Additionally, action research and
reflective supervision are central methods of reflective teaching, as suggested by Coghlan (2015) and
Parlakian (2001), respectively. It is important to note that most of these methods can still be used in
the remote teaching situation that the COVID-19 pandemic imposed upon the world.
Models of reflective teaching
A model is something used as an example to follow or imitate (Henderson, 2001). Reflective teaching
is an inquiry approach that emphasises an ethic of care, a constructivist approach to teaching, and
creative problem-solving (Henderson, 2001). A reflective teaching model can, therefore, be defined
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as an example of an inquiry approach that emphasises ethics of care, constructivist teaching and
creative problem-solving that teachers may follow or imitate in teaching.
In this study, the following models of reflective teaching were expounded: Lawrence Stenhouse’s
(1975) model of reflective practice, Kolb’s (1984) learning cycle model, Gibbs’ (1988) reflective
cycle model, Syrjala’s (1996) collaborative model of reflective practice, and Mathos et al.’s (2010)
model of reflective teaching. These models were relevant to this study because they informed the
questions included in the data collection tools.
Levels of reflective teaching
Once teachers have chosen a particular model of reflection, the next step or question to ask is: To
what extent do or should I reflect? Farrell (2016) asserts that educators split reflective practice into
three hierarchical levels as follows:
•
•
•
Level 1: Action in the classroom. When teachers plan at this level, they are concerned only
with what they do in their classrooms.
Level 2: Involves analysing the reasons for the actions taken. It is also called reflection at
contextual level; what teachers focus on the theory behind their classroom practices. They can
then look into alternative practices they might prefer to use, depending on their learners’
needs.
Level 3: Encourages teachers to justify the work they do and reflect within the broader context
of society.
Theoretical framework
This study was primarily grounded in three theories that rope the link between reflective teaching and
learner performance: social constructivism, cognitive constructivism, and metacognitive theory.
These theories view learning and teaching as a constructed phenomena (Akdeniz et al., 2016). These
theories share focus in viewing teaching as a process of facilitating learning (Akdeniz et al., 2016).
By combining elements of the three theories, this study aimed to provide a holistic and transparent
description of dynamics in the classroom.
METHODOLOGY
This study followed a mixed-methods case study design. Such a study design involves qualitative and
quantitative data collection, results and interpretations to provide in-depth evidence for a case(s) or
to develop cases for comparative analysis (Creswell & Clark, 2017). Creswell and Clark (2017)
further state that a mixed-methods case study is especially suited for learning more about a littleknown or poorly understood situation. This design was most suited to this study, as little was known
about the Grade 12 teacher’s understanding of reflective teaching and learners’ performance in the
selected region.
The study population consisted of 10 senior secondary schools from the selected region. A sample of
five schools was purposely selected for this study. Three research instruments were used to gather
findings. Data-generation procedures included handing out the RTCOEQ to teachers two days in
advance; thereafter, the completed RTCOEQ were collected. At the time of collecting the RTCOEQ,
an agreement with the participating teachers on the time for the lesson observation was reached. Data
were presented by means of verbatim responses, tables, charts and graphs. The collected data were
predominantly qualitative, with fewer cases of quantitative data collected to support the qualitative
data. Common trends in the data were analysed by adapting the steps developed by Creswell and
Clark (2018) for mixed-methods designs.
FINDINGS
The data led to the conclusion that teachers in the selected region had a high regard for reflective
teaching as a means to improve teacher and learner performance. However, it is important to note that
data from the three tools equally revealed that teachers were not well-equipped with skills, knowledge
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and digital resources necessary to effectively engage in reflective teaching, especially during the
COVID-19 pandemic. As argued earlier by Ferwana (2006), a good reflective disposition of a teacher
can improve learner performance. It can therefore be taken to inversely imply that teachers’ lack of
understanding in reflective teaching may be a contributing factor to the persistent lower achievement
of quality symbols in the selected region – a situation that resembles the observed situation of learners’
performance in the national examinations in the selected region.
Below are the selected verbatim responses of teachers on how they understood reflective teaching:
Teacher 1: A systematic approach in teaching where a practitioner (teacher) looks back at his
work or practice with the aim of improving his/her own practice.
Teacher 2: Reflective teaching refers to a review which is carried out after presenting a lesson
to evaluate or identify the weakness and strength of a lesson.
Teacher 6: To check back on how well teaching went on. Did learners understand or not.
Teacher 7: Visualising your ended lesson to establish the strength and weakness of the lesson
taught.
Further, Teacher 9, 12, 13, & 15 indicated that they were not familiar with reflective teaching, while
teacher 14, omitted the question.
In summary, 67% of the teachers claimed to know the meaning of reflective teaching. However, when
these teachers were asked to further explain the application of reflective teaching, it emerged that
they lacked understanding and application of reflective practice.
Taking it from the perspective that reflective teaching is a teacher’s assessment tool for shaping
effective teaching and the learning environment, it can be concluded that teachers from the selected
region who participated in this study lacked training on reflective teaching. Teaching that lacks
reflection is tantamount to poor learner performance on tasks taught. As Ferwana (2006) points out,
learners who attend classes where teachers engage in structured reflection on learning and teaching
are more likely to achieve a high understanding of the content taught than those who are taught in a
class where no or less structured reflections take place.
The study revealed that teachers lacked skills and knowledge required to successfully execute
reflective teaching. Teachers also highlighted lack of equipment and stringent schedules as some of
the reasons why they did not really engage in reflective teaching. Failure to engage in effective
reflections further imply stagnation in professional growth and development. Lack of professional
growth and development are the detrimental ingredients of constant poor performance in the
workplace (including the classroom where learning and teaching ought to take place). During lesson
observations by using the RTLOC, it was found that teachers were not so familiar with the application
of reflective teaching, though they claimed to be familiar with reflective teaching. This may explain
the observed stagnation of the selected region in the national regional rankings of the national
examinations. This is in line with Fullan (1991), who holds the view that educational change depends
on what teachers do and think. Clift et al. (1990) and Evans (2002) further state that self-reflection on
teaching is one of the best ways in which teachers can consistently monitor and improve their ability
to teach effectively.
It can be concluded that the poor performance of learners in the national examination that was
observed in the selected region was greatly influenced by teachers’ lack of understanding and
application of reflective teaching. This is in line with literature by Bolton (2010), Bababei and
Abednia (2016), Fatemipour (2012), Lai (2011), Spalding (2020), Swarts (1998) and ZwozdiakMyers (2009), who collectively argue that reflective teaching is a professional tool for teachers to
improve the teaching–learning environment.
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CONCLUSION AND RECOMMENDATIONS
This study revealed information about the state of reflective teaching in the selected region, its
characteristics and impact. It was concluded from the findings that teachers’ lack of reflective
attributes impacted learner performance in the national examinations. The findings further revealed
that teachers in the selected region valued reflective teaching as tool to improve teaching and learning.
All teachers are expected to engage in reflective teaching. Engaging in reflective teaching takes time
and effort, but the rewards can be great (Zeichner & Liston, 1996). Reflective teaching should be
inseparable from teaching at all levels in the selected region and Namibia at large to foster better
performance of teachers and learners. In line with the global endeavour to assimilate industrial
revolution, the integration of digital media in the process of reflective teaching is recommended.
Thus, teachers are advised to embrace the multimodal approach in the implementation of reflective
teaching.
Recommendations for improving teaching and learning through reflective teaching in the selected
region were categorised as follows: Recommendations for teachers; Recommendations for school
principals; Recommendations for the Directorate of Education in that region; and Recommendations
for teacher training institutions.
It was recommended that teachers and school principals take deliberate steps in seeking opportunities
to better their understanding and application of reflective teaching. The Directorate of Education was
advised to facilitate the creation of platforms where teachers can learn skills and knowledge in the
application of reflective teaching. Teacher training institutions were recommended to consider
including adequate content on reflective teaching to ensure production of teachers who are competent
to teach reflectively.
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relationships in the context of teaching EFL in Iran. Australian Journal of Teacher Education,
41(9), 1–26.
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an analysis of issues and programs. Teachers College Press.
Coghlan, D. (2015). Organization development: action research for organizational change. In H.
Bradbury (Ed.), The SAGE handbook of action research (pp. 417–423). SAGE Publications
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Creswell, J. W., & Clark, V. I. (2017). Designing and conducting mixed methods research (3rd ed.).
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Evans, L. (2002). What is teacher development? Oxford Review of Education, 28(1), 123–137.
Farrel, T. S. (2016). Reflection practice in action: 80 reflection breaks for busy teachers. Corwin
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Fatemipour, H. (2012). The efficiency of the tools for reflective teaching in ESL context. Paper
presented at the 3rd world conference on learning, teaching and educational leadership. Iran.
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Ferdowsi, M., & Afghari, A. (2015). The effects of reflective teaching on teachers’ performance.
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Ferwana, K. M. (2006). Levels of reflective teaching among the student teachers of English in Gaza
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Universities. (Masters’ thesis). Gaza Strip: University of Gaza.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive
developmental inquiry. American Psychologist, 34(10), 906–911.
Fullan, M. (1991). The new meaning of educational change. Falmer.
Gibbs, G. (1988). Learning by Doing: A guide to learning and teaching methods.
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Henderson, J. G. (2001). Reflective teaching: Professional artistry through inquiry. Upper Saddle
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Kolb, D.A. (1984). Experiential learning experience as a source of learning and development.
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Kuhn, D., & Dean, D. (2004). A bridge between cognitive psychology and educational practice.
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Lai, R. E. (2011). Metacognition: A literature review. Research report. U.K. Pearson Publishers.
Loughran, J. J. (2006). A response to ‘‘Reflecting on the self’’. Reflective Practice, 7, 43–53.
Mathos, E., Tullier, S., and Nevalga, A. D. (2010). Presentation from Michigan Campus Compact
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Parlakian, R. (2001). Look, listen, and learn: Reflective supervision and relationship-based work.
Washington, DC: ZERO TO THREE.
Philip, A. T., & Dwayne, D. G. (2010). Guiding reflective practice: an auditing framework to assess
teaching philosophy and style. Journal of Marketing Education, 32(2), 182–196.
Schneider, W., & Lockl, K. (2002). The development of metacognitive knowledge in learner and
adolescents. In T. Perfect & B. Schwartz (Eds.), Applied metacognition. Cambridge
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Schön, D. A. (1983). The reflective practitioner. Basic Books.
Sharifi, Sh., & Abdolmanafi Rokini, J. (2014). The effect of reflective teaching on pre-service
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Spalding, A. (2020). How to encourage reflective teaching in your school.
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Stenhouse, L. (1975). An introduction to curriculum research and development. Heinemann.
Swarts, P.S. (1998). The transformation of teacher education in Namibia: The development of
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Syrjala, L. (1996). The teacher as a researcher. In E. Hujala (Ed.), Childhood education
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Associates, Inc., Publishers.
Zwozdiak-Myers, P. (2009). An analysis of the concept reflective practice and an investigation into
the development of learner teachers’ reflective practice within the context of action research
(Doctoral dissertation). http://vscheiner.brunel.ac.uk/bitstream/2438/4316/1/FulltextThesis.pdf.
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CURBING EXCLUSION: THE EXPERIENCES OF STUDENTS
WITH VISUAL IMPAIRMENTS AND THEIR LECTURERS ON
DISTANCE AND ONLINE LEARNING DURING THE COVID-19
PANDEMIC IN NAMIBIA
Mirjam Sheyapo
University of Namibia (msheyapo@unam.na)
Isobel Green
Namibia University of Science and Technology (igreen@unam.na)
Abstract
Owing to the coronavirus outbreak (COVID-19) towards the end of 2019 in Wuhan, China, higher
education institutions (HEIs) had to shift from traditional teaching to remote teaching and learning.
This shift affected lecturers and tested the readiness of open and distance learning (ODL) centres of
various HEIs, particularly for students with visual impairments (SVI) who mainly depend on face-toface lectures. Students had to source technological devices, acquaint themselves with e-learning
applications, relocate to gain access to the Internet, and adapt to the new learning modes. The abrupt
transition from the traditional face-to-face teaching method to online had several shortcomings
despite many success stories. Noting an increase in access to higher education, particularly to SVI,
it is also sad to note that this group of students remains excluded and thus less visible in the Open
and Distance Learning (ODL) programme. A phenomenological design was used in this study. Six (6)
lecturers who included SVI during distance learning participated in a focus group discussion. In
addition, two SVI narrated their accounts in semi-structured interviews. The participants revealed
various challenges and opportunities. Among others, the students and lecturers pointed out that lack
of technological devices, instructional materials, preparedness, knowledge and skills were barriers
to inclusion. The paper concludes that most institutions remain reluctant to prepare for and be
proactive in including SVI in ODL programmes. Consequently, this results in the exclusion of SVI
during unforeseen situations, such as the COVID-19 pandemic. The paper calls for policy
transformation at the national, ministerial and institutional level to facilitate the move towards
inclusive education through all learning modes, including the ODL programme.
Keywords: visual impairments; open and distance learning; exclusion; inclusion; inclusive education
INTRODUCTION
Access to higher education maximises employment opportunities for individuals with or without
disabilities (Reed & Curtis, 2012). According to the National Development Plan (NDP 5), access to
higher education is a crucial enabler of economic freedom in Namibia. It also plays a vital role in
poverty eradication, improving quality of life, and strengthening economic situations for the country,
families and individuals (Government of the Republic of Namibia, 2017/2018 to 2021/2022).
Responding to the call for Education for All (EFA), higher education institutions (HEIs) in Namibia
have maximised access to higher education. Students with different disabilities are in various
programmes offered by different universities in the country. Some students with disabilities have
obtained qualifications in various fields and compete in the job market.
Namibia and the world have guiding policies that compel academic institutions to provide education
for all (Mole, 2012). The Universal Declaration of Human Rights (UDHR) of 1948 assured the rights
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to education, and it asserts “higher education shall be equally accessible to all based on merit” (Article
26, section (a)). In addition, the Salamanca Declaration of 1994 supports the inclusion of students
with special needs in regular schools. The declaration urges educational systems to implement
programmes that consider individual unique characteristics, interests, abilities and learning needs
(United Nations Educational, Scientific and Cultural Organisation [UNESCO], 1994). It further
alludes that inclusive education is imperative to combating discriminatory attitudes and creating
welcoming communities. The Salamanca Declaration recommends sound student-centred pedagogy
with extensive support from which all students can benefit (UNESCO, 1994). Furthermore, the World
Declaration on Higher Education for the Twenty-First Century: Vision and Action of 1998 affirms the
rights to education and access to higher education. It calls for unique materials and educational
solutions that can reduce the barriers faced by students with disabilities to accessing and continuing
higher education (UNESCO, 1998).
An increase in the diversity of students entering HEIs has prompted student support services to ensure
inclusion and equitable quality education (Dhillon, McGowan, & Wang, 2008). In addition, Namibia
remains committed to implementing the Sustainable Development Goals stipulated by the United
Nations Development Programme (UNDP). Goal 4 calls for inclusive and equitable quality education
at all levels of education and promotes lifelong opportunities for all. Education is a constitutional
right of all citizens and enables poverty eradication (Government of the Republic of Namibia,
2017/2018 to 2021/2022). In 2013, Namibia developed a National Sector Policy on Inclusive
Education to facilitate inclusive education at all levels in all education sectors (Ministry of Education,
2013).
The roles of university education are to facilitate skills development and increase long-term economic
growth (Conlon, 2014). In 2018, about 59 208 students were registered at different HEIs in Namibia,
studying through various modes, of which 32.5% were through Open and Distance Learning (ODL)
modes (National Council of Higher Education, 2018, p. 6). A total of 98 413 (4.7%) of the Namibian
population are people living with visual impairments (NSA, Government of the Republic of Namibia,
2012). In this study, students with visual impairments (SVI) refer to any student who may need
additional support due to limited vision. However, this is not limited to blind and partially sighted
students in HEIs. Although the prevalence of SVI in higher education in Namibia is not consistent,
there are limited reports on statistics on the enrolment of students with disabilities in higher education
in Namibia, particularly in ODL modes. Some years, more SVI enrol, while very few students enrol
in other years.
The outbreak of COVID-19 in Namibia brought about disruption to all levels of education. In March
2020, all educational institutions were closed to prevent the spread of COVID-19. The situation did
not allow lecturers and students to plan but shifted to online and distance learning. Unfortunately,
when we turned to online and distance learning due to COVID-19, most staff had to work from home,
and most of the facilities, for example, technological devices, were in offices.
Students living in hostels had to relocate back home, and most students lived in rural areas. Students
and lecturers had to rely on technology to ensure that the semester continued uninterrupted
(UNESCO, 2020). Most students and lecturers were used to the face-to-face mode, and the practice
of using technology in learning was new to most. They had no choice but to acquaint themselves with
the new norm of e-learning platforms.
During the online and distance learning due to COVID-19, most HEIs depended on the existing
facilities and learning materials used by ODL centres. The regional centres had to step in to facilitate
the unplanned online and distance learning for all students during the pandemic. They had to ensure
the support of students and lecturers for effective teaching and learning.
There is limited SVI in ODL programmes, making most centres more reactive and not proactively
prepared for all students. In some courses, there were various SVI who mainly depended on the faceto-face mode. Many researchers reveal challenges SVI face in HEIs while in face-to-face mode
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(Haihambo, 2010; Josua, 2013; Sheyapo, 2017). Given the abrupt shift to online and distance mode,
this paper sought to answer the following questions: What were the challenges and opportunities for
SVI? How did SVI access the instructional materials? How did lecturers ensure the inclusion of SVI
during online and distance learning (support to meet individual needs)?
Therefore, this paper presents the experiences of students and lecturers regarding online and distance
teaching and learning during the COVID-19 pandemic. It narrates their challenges, opportunities and
coping mechanisms.
LITERATURE REVIEW
Hewett et al. (2017) underscore that moving towards inclusive education requires institutions to invest
more in resources that ensure equal opportunities and equity for all levels and modes of learning.
They state that HEIs should strengthen their support services to meet the unique needs of students
through the various available modes of learning. Ciobanu (2013) investigated the roles of student
services in improving students’ experience in higher education and found that students who lack
academic, emotional and social connection with the institution are at risk of giving up their studies if
adequate support is not provided. Reed and Curtis’ (2012) findings show that some students shy away
from seeking admission to institutions and hold a perception that there are less academic and social
support.
To ensure the inclusion of all students, Liakou and Manousou (2015) conclude that HEIs must provide
training to educators as to how to support students during teaching and learning to provide equal
education opportunities to all students, particularly SVI. They further advise that HEIs must capitalise
on the options to record class materials, supportive equipment and assistive technology such as visual
and tactile aids (Liakou & Manousou, 2015).
Ciobanu (2013) acknowledges that student support services contribute to the quality of learning
experience among students and their academic success and decrease the university dropout rate. Reed
and Curtis (2012) assert that understanding the unique needs of SVI could lead to more success in
various study programmes for these students. Moreover, Butler et al. (2017) emphasise that while
students should be allowed to learn independently, it still is the responsibility of universities to ensure
equitable access to the learning materials for all students.
Liakou and Manousou (2015) and Tichauya et al. (2014) mention various challenges to providing
distance learning for visually impaired students. Such challenges include lack of graphic learning
materials, unreliable supportive equipment, lack of academic experts to support SVI, lack of
intermediary staff to facilitate the studies of SVI, and limitations on library services to cater for the
needs of SVI. These challenges are common in most HEIs.
Reed and Curtis (2012) highlight some barriers that impede the successful completion of university
programmes by SVI. They point out the poor quality and timeliness of alternate print formats and
poor access to computer-based materials. Similarly, a different study (Luque, 2018) was conducted
to identify the practices and perceptions of educators and visually impaired learners regarding their
inclusion in computing education programmes. The study reported that graphical information was
one of the challenges SVI faced.
Luque (2018) concluded that the inclusion of SVI depends on educators’ creativity to find approaches
and methods that can meet the needs of SVI. Moreover, Luque (2018) stated that most educators do
not change their lecturing methods, thus making SVI depend on volunteer sighted learners for
support. Ciobanu (2013) highlights that the beliefs and values of staff, institutional policies,
curriculum, services and the learning environment influence the help availed to students with
disabilities, particularly SVI.
Mahyoob (2020) highlighted some of the technical issues students had during e-learning during
COVID-19 remote learning. Amongst others, he indicated that internet connectivity posed challenges
to accessing classes for most students and downloading course materials. Barrot et al. (2021) echoed
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similar sentiments, namely that online and distance learning affected the quality of the learning
experience. However, they acknowledged that students employed resource management and
utilisation strategies, help-seeking, technical aptitude enhancement, time management, and learning
environment control.
The study drew on the social model of disabilities that emerged between 1960 and 1970 as individuals
with disabilities started to radically question the institutionalisation and segregation of people with
disabilities (Levitt, 2017). They criticised and interrogated the medical model that supported
segregation and institutionalisation of people with disabilities.
The social model interrogates the roles of institutions in addressing organisational, pedagogical and
attitudinal barriers (Bishop & Rhind, 2011). It advocates for equitable access to quality education for
all through curriculum and policy transformation – an approach that should also reach ODL centres
to anticipate the needs of students with disabilities, particularly SVI. Furthermore, the social model
believes that society imposes these barriers. Subsequently, a lack of inclusive learning management
systems (LMS) and inclusive instructional materials and methods are some forms of exclusion for
SVI in higher education (Inclusion London, 2015).
McKenzie and Dalton (2020) highlight the need to incorporate Universal Design for Learning (UDL)
into policy, research and teaching practice, because it is a concept that can enhance inclusive
education.
To date, most students with disabilities face different forms of exclusion due to various barriers
created by the existing education systems. As a result, SVI turn to self-advocacy to ensure success in
their academic endeavours (Bishop & Rhind, 2011). Consequently, in the context of this paper, the
social model of disabilities encourages institutional preparedness for all students. It also advocates
for proactiveness to anticipate the needs of all students in all modes of learning. Finally, it calls for
an adjustment to the virtual and distance learning environment that includes improved online
instructional materials and assessment methods and support staff with the necessary training and
attitudinal change (Williams et al., 2017).
RESEARCH METHODS
The researchers used the qualitative phenomenological research design to gather data through virtual
semi-structured interviews with two SVI. The latter were in their final year in different programmes
at the selected HEI. Furthermore, six lecturers who included SVI in their courses during online and
distance learning participated in a virtual focus group discussion. Students and lecturers were
purposefully selected to narrate their experiences of inclusion in online and distance learning that
resulted from the COVID-19 pandemic.
Interpretive phenomenological analysis (IPA) was used to analyse the data. The researcher first read
and re-read the narratives to generate themes. The researcher also looked for connections and patterns
from the narratives and finally made interpretations to deduce meanings from the data. Moreover, the
discussion of findings in this paper considers the three key features of IPA: firstly, the experience of
SVI of the shift to online and distance learning during the initial lockdown due to COVID-19;
secondly, ideography takes into account the participants’ uniqueness and perspectives while inferring
meanings and understanding with due respect to individual integrity; and finally, the researcher
interpreted the narratives without interfering with the participants’ contexts. The original accounts of
participants are used to present their voices.
FINDINGS AND DISCUSSION
Four main themes emerged from the structured interviews and focus group discussion. This section
presents the original narratives as echoed by the participants, followed by a discussion of the findings
in relation to the reviewed literature.
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SVI and lecturers’ readiness to shift to online and distance mode
SVI preparedness
On the questions regarding students’ encounters with online and distance teaching and learning, the
interviews exposed issues of unpreparedness and SVI anticipated exclusion even before the
commencement of the online and distance mode. This is what one SVI had to say:
The day the university announced that we had to shift to online and distance learning due to
COVID-19, I was very angry with the university management, thinking they decided to
introduce online learning without considering the students with special needs. I was angry and
depressed, feeling that I would be left out. (SVI Participant 1)
In his narrative, the participant anticipated exclusion soon after receiving the news about shifting to
online and distance learning due to COVID-19. The participant doubted and was worried about
support. Likewise, Reed and Curtis (2012) indicated that students anticipate a lack of support and
thus shy away from seeking admission to institutions. Student support is an assurance and, as alluded
to by Ciobanu (2013), it is crucial that it contributes to the quality of learning experience and academic
success. The other participant had this to say:
I was in the North as it was an institutional break, and my laptop was in Windhoek. (SVI
Participant 2)
The participant narrated that he was not ready to shift to the online and distance mode. He recounted
that he was not prepared for the new learning mode and that he was caught off guard because the
announcement came during a semester break when most students travelled home for the holiday. The
participant expressed worry and panic and felt that he was not in his usual learning setting and
separated from his learning enabler (his laptop). Since there was pressure on both the student and the
lecturers, students anticipated little support from their lecturers and peers.
I gave up and submitted to spend one more year at the university because I thought I would not
manage. (SVI Participant 1)
In the beginning, I felt like I was excluded. Most lecturers were trying to speed up to cover the
contents. Everyone was confused and panicking. (SVI Participant 2)
These utterances depict the pressure and loss of hope the students sensed. According to Luque (2018),
most educators do not change their lecturing methods, which could cause doubt among SVI.
Similarly, Ciobanu (2013) highlights that the beliefs and values of staff, institutional policies,
curriculum, services and the learning environment influence the support availed to students with
disabilities, particularly SVI.
Lecturers’ preparedness
Inclusion relied on the preparedness of lecturers and the institution. Impressively, one participant
indicated readiness to include all students. She narrated that she was aware of the SVI prevalence in
her class and was thus ready. Lecturers who had encountered SVI before were very positive and
prepared to have them:
I was ready because I was aware that I have an SVI in my class. It was not my first time to
include an SVI. (Lec Participant 1)
Furthermore, the participants echoed insufficient readily available instructional materials for SVI;
consequently, they had to use what was available. This is what they had to say:
[S]ince there were no materials ready for SVI, we had to fit them in with what we had. (Lec
Participant 2)
It came as a surprise, and we were unprepared for the distance mode. Some of us were not even
conversant with technology. It was a struggle. When I started, I did not even think of how to
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cater for SVI. (Lec Participant 4)
On the other hand, other participants indicated that they were not ready to meet the needs of SVI.
They alluded to limited ability to use technology. Ironically, this implies that it was a struggle to use
technology and that they had not even thought of SVI. The findings support those of Butler et al.
(2017) and Hewett et al. (2017), who emphasised that inclusive education requires institutions to
invest more in resources that ensure equal opportunities.
Challenges experienced by SVI during online and distance learning
The study explored the experiences of SVI and their lecturers during online and distance learning in
HEI in Namibia. Various challenges were identified that impacted on the inclusion of SVI during
online and distance learning. Most challenges emanated from societal/social barriers in and outside
the university. Similar barriers that impede inclusion were also echoed by Mahyoob (2020) – for
example, that there were many technical issues students had to deal with during online and distance
learning that included internet connectivity. Similarly, Bishop and Rhind (2011) stated that SVI face
attitudinal, institutional, environmental and physical barriers while in HEIs. Online and distance
education due to COVID-19 introduced many challenges. The participants in this study revealed
technological and infrastructural and environmental challenges. These challenges are discussed
below.
Technological and infrastructural challenges
One participant narrated the dilemma of shifting from face-to-face to online and distance learning.
This response revealed infrastructural limitations and challenges to using technology for learning in
a rural setting. Limited access to electricity was worsened by the lockdowns of all shebeens and
village cuca shops that were the means and points of accessing electricity to charge their devices. As
his voice trembled, he recounted the severity of the situation while showing the urge and desire to
continue with his academic work. This is what one participant had to say:
I had no choice but to use my phone for all school activities. We had difficulties accessing
electricity to charge our phones. We depended on the shebeens and nearby shops, which were
also closed because of the regulations. It was a challenge, and we used the Chinese small solar
panels to charge, which caused damage to the phone batteries. (SVI Participant 1)
Findings showed that online learning revolved around technological interdependency. Participants
underscored limited access to technical services, such as stable networks and internet connectivity, in
different environments where they lived. Some participants who had smartphones and laptops needed
power to charge the devices, better internet connectivity (data) and a stable network. Finally, students
mentioned challenges with the LMS (Moodle platform) used for online learning.
The participants expressed limitations to and disappointment in using the LMS (Moodle) during
online learning:
Moodle platform was congested; everyone was using the internet, and it was overloaded. The
live classrooms were impossible; mainly, I depended on friends to read for me on the platform;
without my laptop, where I have a reliable screen reader, it was a struggle, and the network was
very slow. I could not attend the virtual class. (SVI Participant 1)
I only used the platform to submit assignments and not have lessons on the platform before the
pandemic. It was a challenge because I was not introduced to the system. (SVI Participant 2)
With frustration, the participants described the shortfalls and cumbersomeness of using the e-learning
platform due to limited internet and network connections and system overload, which made it difficult
to attend virtual live class sessions. In addition, the participants revealed challenges of using their
phone, instead of their laptop, which was compatible with the screen reader software.
Findings revealed technological barriers resulting from technology malfunctioning, lack of skills and
system overload. Similarly, Mahyoob (2020) indicated that internet connectivity challenges accessing
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classes and downloading course materials online and distance learning. Findings revealed that online
and distance learning was costly. Students needed devices, the skills to use them, internet and network
connectivity, power to charge the devices, and essential applications and software, such as screen
readers. Although participants acknowledged efforts and support from the university, these were not
sufficient to sustain continuous learning.
Home environment challenges
Other challenges revealed by the participants during online and distance learning were the remoteness
of their home environments, household chores, inconsideration of parents, and timetabling.
Consequently, students had to balance household chores and academic demands. One participant had
this to say:
Another thing was the timing of the classrooms (timetable). We had to partake in the household
chores. In the afternoon, we were exhausted. It was also the time we searched for power to
charge our devices. The time was challenging with school and household chores. (SVI
Participant 2)
The participant narrated a story of a typical life in a village household. With pressure, he felt caught
between academic work and household chores. Worth noting from the participant’s utterance were
timetabling challenges. The university adopted the usual face-to-face timetables, and it was nearly
impossible for SVI to attend the virtual sessions during the day due to household chores. Findings
concur with Barrot et al. (2021), who state that the home environment was a barrier to learning during
the COVID-pandemic.
When I returned to Windhoek, I received support, and things were much better. I used the phone
and laptop to follow the lessons; I joined WhatsApp groups; and I had access to power and a
better internet connection in the hostel. (SVI Participant 2)
The participant expressed relief upon returning to the city. The findings revealed that online and
distance learning was more favourable in urban than in rural settings. The participant affirmed that
learning improved when he gained access to his laptop. Thus, it was clear that the significant enablers
of online and distance learning were a computer/laptop instead of a mobile phone, access to
power/electricity, better and accessible internet connections, and multiple platforms, including
WhatsApp.
Regarding home environment challenges, most students lived in rural areas where modern
infrastructure remain inaccessible to most families. Moreover, most village households had no
electricity to charge their devices; thus, synchronous (live virtual sessions) was unsustainable.
Students also had to balance household chores and academic workloads.
Pedagogical challenges
Participants highlighted delayed access to notes, visual information (graphics) without interpretation,
lack of lecturer and student interaction, and difficulties downloading the recorded audios. The
participants had this to say:
I concentrated more when we interacted, debated or discussed. We had no group discussion,
which generally helps me understand the content. One lecturer told me that I should take notes
during the virtual lessons. You know, lecturers do not know us and our conditions. They treat
us the same. Also, at the beginning of online learning, some lecturers were using pictures and
diagrams. I had no one to explain or interpret the charts to understand. (SVI Participant 1)
Lecturers took time to upload the notes, and we needed to read the notes before the assessments.
It was also challenging to download the Panopto recordings. When I wrote the tests, it was
challenging to achieve the planned target for the year because I did not have notes. (SVI
Participant 2)
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Butler et al. (2017) advised that universities should ensure access to instructional materials for all
students in fair and equitable access while enabling students to learn independently in their comfort
spaces. Though lecturers tried to promote independence, they neglected the unique needs of
individual students, particularly SVI. The participants felt that some lecturers unintentionally
excluded them, while some were intentional in this regard. As Firat (2021) echoed, SVI face many
barriers to learning, such as a lack of learning materials, accessing lecture notes and poor academic
support. They also highlighted other forms of pedagogical exclusion – such as lack of interpretation
of diagrams, charts and maps, contents in preferred formats, and limited interaction – that affect the
academic performance of SVI. This not only impact on content comprehension; it also affects
academic achievement.
Coping strategies during online and distance learning
Coping strategies of SVI
Despite the challenges, the participants showed commitment, willingness and effort. They explained
various coping strategies they used to ensure they were part of the teaching and learning process.
Lesson recording was the primary method used that made learning possible. One participant had this
to say:
I asked lecturers to record the lessons and listen to them late in the evening. I also researched
how the platform operates. During the day, we took the phones for charging most of the time.
During the evenings, the network was better, and one could download or play the audios better.
(SVI Participant 2)
Bravely, the participant expressed satisfaction and pride in his success. Moreover, self-directed
learning, self-empowerment and self-advocacy played significant roles. The students sought support,
directed their learning and discovered suitable times to use the Internet. The efforts invested show a
will to learn, self-reliance and autonomy despite the challenges. Although there were efforts of the
virtual live sessions, online became asynchronous because of the technological challenges, and SVI
took charge of their learning.
Lecturers coping strategies
Lecturers revealed lesson recording and live virtual class sessions as the strategies they used to ensure
effective online and distance teaching and learning. They also recognised efforts of the university,
such as training on online facilitation, and recording of sessions via various platforms, such as
BigBlueButton, MS Teams, Panopto, PowerPoints with audio, and Zoom. However, the participants
acknowledged that there were no considerations on including SVI. One participant said:
The university gave us several pieces of training on how to use Moodle and Panopto, MS teams,
PowerPoint with audios and BigBlueButton to avail the contents to the students, but nothing
much about SVI. (Lec Participant 2)
The university exposed us sufficiently to various methods, but SVI preferred recorded audio. I
mainly recorded the sessions and virtual classes, and I had to keep track of my student to ensure
that he received the contents on time. (Lec Participants 4)
The above participant confidently and positively stated how she kept track of her SVI. Her statement
suggests that SVI were included, depending on lecturers’ knowledge, efforts, attitude and willingness.
Although the university tried its best to empower lecturers with regard to technology for teaching,
there was little consideration of SVI.
Opportunities
Opportunities for SVI
Speaking with a smile, the participants felt successful in overcoming the challenges. They related that
challenges became steppingstones. It was impressive that the participants did not feel lonely in their
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predicaments; they kept referring to “we”, showing a sense of unity. They highlighted an
improvement in typing skills, advanced technological expertise, time and resource management, and
organising and research skills. This is what one participant had to say:
We improved on typing, advanced our technological expertise, time and resource management
and, organising ourselves and learnt a lot about research. We had to find the articles online to
complete our projects. It was great exposure, and I learned to save my little. (SVI Participant
2)
One participant recounted:
…the pandemic has taught us that life cannot be the same. (SVI Participant 1)
Although the participants reported many challenges during online and distance learning due to
COVID-19, they underscored various opportunities.
Opportunities for lecturers
The online and distance learning opportunities highlighted by lecturers included creativity,
technological advancement, and collegial and institutional support. Participants shared their
experiences and demonstrated excitement:
It was challenging yet a great opportunity to some of us especially, using technology for
teaching. (Lec Participant 2)
I became more creative; you cannot imagine the type of activities, assessments and the many
methods I was exposed to during the remote teaching. (Lec Participant 4)
Further, they recounted that they had significant exposure to multiple teaching and assessment
methods. However, they did not indicate the inclusive practices they used. One participant (Lec
Participant 6) relayed that collegial support and training offered helped her cope with the online
teaching and learning platforms:
[W]e used colleagues to assist with the use of Moodle platforms, and more training helped us
cope.
Thus, the participants expressed satisfaction with the support and the new knowledge and skills
gained during online and distance learning. These narratives support the findings of Luque (2018)
that the inclusion of SVI depends on educators’ creativity to find approaches and methods that can
meet the needs of SVI.
CONCLUSION
The findings showed that SVI anticipated exclusion due to a lack of institutional preparedness during
online and distance learning. Despite the prevalence of ODL units and their immense advancement
in new teaching and learning technology, most of the technology had limits on addressing the needs
of SVI. Subsequently, most HEIs did not anticipate the needs of students with special needs,
particularly SVI, but instead, reacted to their needs. There is still a reluctance to proactively prepare
for all students. The extent to which SVI were included depended on the lecturers’ willingness,
knowledge and exposure.
Furthermore, it was concluded that online and distance learning depends on the interdependency of
technology; those who had smartphones and laptops needed power to charge their devices, a stable
network, internet connectivity, and knowledge and skills to use online learning platforms. However,
lack of access to such technologies was the main barrier to learning.
Notwithstanding a lack of appropriate instructional materials and teaching methods as barriers to
learning, the study further concludes that pedagogical exclusion of SVI was worsened by these
students’ home environment, ranging from remoteness and timing to balancing household chores with
the timetable.
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In addition, although learning was asynchronous, the lack of student–lecturer and student–student
interaction, a lack of text and audio readers, and inappropriate font sizes affected the academic
performance of SVI who depended on fellow students for further explanations of contents.
Despite the many challenges, SVI and lecturers demonstrated perseverance, positive attitudes and
willingness to learn. Moreover, SVI discovered strategies to control and manage their learning; they
reverted to self-directed learning, self-empowerment and self-advocacy, finding a suitable time to use
the Internet and managing their home environment. Also, participants developed self-reliance,
autonomy and independence, technological advancement, creativity, research skills, good
communication and a relationship with colleagues. These were benefits of online and distance
learning. Finally, it is worth noting that SVI were more instrumental to their academic success during
online and distance learning due to COVID-19.
RECOMMENDATIONS
Firstly, institutional policy transformation is recommended to facilitate the move towards inclusive
education in all learning modes, including the ODL programme.
Secondly, it is recommended that HEIs adopt the Universal Design for Learning (UDL) and
differentiated instructional strategies (DIS) to curb pedagogical exclusion by proactively planning for
all students. Also, institutions should empower lecturers with essential inclusive pedagogies.
Thirdly, HEIs should be mindful of the needs of SVI when investing in teaching and learning
technologies. Moreover, ODL units should design inclusive online instructional materials, for
example, online learning platforms, to be accessible and compatible with SVI devices. There is also
a need to consider adjustable font size on quizzes for partially sighted assistive technology devices
such as screen readers and to develop varied materials aligned with the diverse needs of students. In
addition, HEIs should consider diverse students’ home environment when preparing ODL
instructional materials, timetables and assignment due dates – for example, remoteness, lack of
infrastructure, household chores, et cetera.
Lastly, the researchers took cognisance of the study’s limitations. First, the researchers are emerging
and novice scholars with limited expertise on IPA. Furthermore, the sample size was limited to the
number of SVI registered during the time of data collection. Thus, it is recommended that further
research be conducted on a similar phenomenon with a larger sample and includes the perspectives
of student support officers in different ODL centres at HEIs.
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OVERCOMING GENDER IMBALANCE IN ICT-RELATED JOBS
T. Luckho, P. Appavoo, R. Doomun, P. Dookhun, Y. Boodhun, and T. Jutton
Open University of Mauritius, Réduit (t.luckho@open.ac.mu)
Abstract
According to a report by the United Nations, women worldwide are at high risk of losing out
compared to their male counterparts when talking about tomorrow’s Science, Technology,
Engineering and Mathematics (STEM) jobs. For every 20 jobs lost in competing industries, only one
woman is expected to be hired in the STEM field, whereas out of every four jobs lost in competing
industries, one man is expected to be employed in the STEM field. This gender bias is also observed
in the Mauritian information, communication and technology (ICT) sector. Therefore, there is an
urgent need to understand the origin of this bias and how education can be the bridge to this
employment gap. This study was conducted across the ICT industry in Mauritius. The main objectives
were to compare the number of girls and boys who had opted for Computer Science at School
Certificate level over the last four years and to assess the perception of women of the working
conditions prevailing in the sector, identifying the challenges they face. A quantitative research design
was adopted. First, secondary data were extracted from the Mauritius Examination Syndicate (MES)
reports from 2015–2019. The second phase of data collection was done via a questionnaire survey
administered to women already working in the ICT sector. The main observations from the survey
were that working in the Mauritian ICT sector was tedious, sometimes to the detriment of their work–
life balance. However, most respondents believed that working in that sector offered promotional
prospects and was associated with high socio-economic status. Nevertheless, they insisted on the need
for more incentives to encourage women to opt for an ICT career, as they felt that the sector was
mostly male dominated.
Keywords: gender bias, STEM jobs, ICT career
INTRODUCTION
It is a fact that women and girls make up half of the world’s population. While there are growing
efforts geared towards promoting gender equality as per the Sustainable Development Goal 5, there
are still existing loopholes preventing its proper materialisation. According to a UN report published
in July 2017, ICT is key towards helping drive gender equality. The report Emerging TrendsICT4SDG/SDG5 (2018) shows that there is presently a 200-million-person shortage of ICT-skilled
workers around the world, and despite the increasing number of women completing tertiary
education, this is not filling the gap. In the same vein, Manpower (2015) states that the global “talent
shortage” is at 38%, with the top 10 hardest jobs to fill in the science, technology, engineering and
mathematics (or STEM) professions.
Given the increasing labour and skills mismatch and gender disparity, it is imperative to explore the
situation in the Mauritian context and come up with ways to reduce the gender gap in the ICT sector
while also ensuring a proper career choice by skilled girls graduating in this field. Mauritius has
around 700 ICT-BPO-based enterprises, and the ICT industry currently employs over 21 500
professionals. In line with the Government strategy to move Mauritius towards a full-fledged digital
economy, the information and communications (ICT) sector is expected to grow by 6%, according to
Statistics Mauritius (2017). The goal of the Economic Vision 2030 of the Government of Mauritius
is to transform the ICT industry into a key sector by fostering innovation and creativity and
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value opportunities for citizens. This clearly shows that the ICT sector is one of the major pillars of
the economy in Mauritius.
However, according to the ESI (2018) report, when we look at the number of students enrolled in
tertiary institutions by field of study, it is seen that women were under-represented in science-related
fields such as engineering (2.0% versus 10.3%) and information technology (5.4% versus 15.0%). In
this context, a study was carried out across the ICT industry in Mauritius to explore the ratio of women
working in the ICT sector and assess the working conditions and challenges they face to eventually
map out the reasons why they opted for ICT subjects and a career in this field. A two-phased
quantitative approach was employed; this approach initially involved the use of secondary data to
understand the trends (per gender) in the pass rate of students opting for Computer Science at School
Certificate level and second, a survey analysis to understand the working conditions and challenges
faced by women currently working in the ICT sector. The findings of this research provided empirical
evidence on the working conditions of women in the Mauritian ICT sector and may assist authorities
in devising new strategies to attract more girls to follow ICT courses.
LITERATURE REVIEW
Despite the significant progress achieved by Mauritius in the last decades, the female unemployment
rate is very high; more than half of working-age females do not form part of the labour force (IMF,
2016). The female labour-force participation in Mauritius has remained far below the benchmark in
upper middle-income countries. Although Mauritian women perform well in respect of educational
achievement, this has not been reflected in more employment, wage equality, income levels, or
political representatives and higher-level positions in public and private organisations. Nevertheless,
the Government of Mauritius has decided to increase the female labour participation from 43.3%
currently to 50% by 2030, as recommended in its Strategic Plan 2017–2020 (Strategic Plan 2017–
2020 – MOFED, 2017).
Several studies have been conducted in various parts of the world, aiming to identify factors that led
to the under-representation of women in the ICT sector. Dunn and Samuels (2016) conducted a study
to examine factors causing women’s unequal access to the Caribbean ICT industry and determine the
consequences and possible solutions. They observed that Caribbean women with superior
qualifications did not seem to have as many opportunities to advance in the ICT sector compared to
their male colleagues. Most senior positions in the ICT field were occupied by men. The results
showed that unequal access to ICT for women led to gender gaps in the ICT sector employment.
Another study by Khayyat (2014) focused on female employees’ access to training and development
in the ICT sector. The study revealed that training activities increased the gender gap, since male
employees were given preference over their female colleagues when it came to technical and
expensive training. The results showed that a gender pay gap and social challenges hindered female
employees’ potential for career growth.
Moreover, the European Institute for Gender Equality (EIGE, 2018) showed how much the
employment gap was widening between women and men in the ICT sector. Even if employment
growth in ICT is more than eight times higher than the average employment growth in the EU, only
17% of the almost eight million specialists are women. Mauritius is no less in this aspect. According
to the World Economic Forum (Global Gender Gap Report, 2018), the global rank of Mauritius is
109 out of 149 countries, with a global gender gap score of 0.663. Micheni et al. (2015) conducted a
study to examine ICT-career gender exclusion, the status and trend of job opportunities in the Kenyan
ICT sector and the contribution of the narrow definition of ICT. They found that there was a distinct
gap between perception and use of ICTs and their applications between the different genders. The
study established that the narrow definition negatively influenced ICT as a career of choice among
girls. Broadening the ICT definition to include ICT-related careers that have more social rather than
technical aspects accordingly is likely to influence more women to join the field.
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On another note, Valenduc (2011) reviewed research that focused on education and training, examined
the gendered representation of computer science and technology and the ways in which this impacted
on school guidance of students in secondary and higher education. He also conducted research
focusing on women’s work and the labour market, examining gender inequalities or discrimination
in working conditions, quality of employment, careers, and work–life balance. He stated that women
working in ICT professions did not report any specific problem with technology itself. They described
the ICT universe as creative, stimulating, fascinating and a source of satisfaction. Their professional
orientation was not strongly influenced by their family environment. Furthermore, although previous
studies provided evidence of demanding working conditions, particularly concerning working hours,
the author indicated that women did not consider working conditions as the main factor that explained
the limited presence of women in the profession. He described the current situation of women in the
ICT sector as characterised by three paradoxes. The first being the fact that despite various efforts,
the situation of women in ICT professions had not improved. Secondly, he observed that many female
ICT professionals did not have ICT educational backgrounds. Finally, he stated that there was no
correlation between the gender gap in general and that in ICT professions.
According to Dasgupta and Stout (2014), the UK STEM (Science, Technology, Engineering or
Mathematics) industries reported that women and girls tended to give up on STEM careers because
they believed that such careers were not for people like them. Furthermore, the report indicated that
female and other minority groups were under-represented in the STEM industry. It was found that
teachers often had lower (stereotypical) expectations of under-represented groups, including women
in STEM, thereby reinforcing their non-STEM self-identity. The most important factor would be for
girls to self-identify with STEM. However, the report showed that more female undergraduates were
studying languages than those studying engineering, computing, physical sciences and mathematics
combined. Furthermore, the Engineering UK statistics showed in 2011 that only half of women with
an engineering and technology degree work in the sector compared to 2/3 males. The WISE analysis
of the Labour Force Survey showed that from 2012–2014, ICT was taken up at a much greater rate
by men, with a 7% increase in the number of male ICT professionals to 723 000 (3.5% for women to
125 000). Women made up only 15% of this category. Moreover, there had been a 15% decline in the
number of female ICT technicians to 40 000 (4% increase for men to 146 000). Women only made
up 21.5% of this category in 2014 compared with 25% in 2012. It was noted that the UK had the
lowest participation of women in the STEM workforce in Europe, particularly in engineering and
ICT.
METHODOLOGY
Given the nature of the research that was undertaken – whereby data on the factors affecting the
choice of women to embark on a career in the information and technology (IT) sector had to be
collected at several stages of the decision-making pyramid, each having its own sampling requirement
– a purely quantitative research design was conducted. Quantitative research employs descriptive and
inferential statistics to test the veracity of the hypotheses using real-life information. For this research,
a trend analysis was used, followed by a questionnaire analysis. Trend analysis is a technique whereby
historical trends of a given variable are studied to determine the future movement of that variable. A
trend is generally defined as the “direction the variable is taking during a specified period of time”.
A trend can be both upward and downward.
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Table 1: Data collection framework (secondary data)
Research phase
Data collection
Data analysis
Methodology
Process
Reports from the Mauritius Examination Syndicate
were examined, and data related to the enrolment
figure and performance of boys/girls opting to study
IT were extracted.
MES Annual Reports
The data on enrolment/performance were either
graphed or represented in tables. The underlying
trends were then discussed.
Graphical representation
“Quantitative Research uses measurable data to formulate facts and uncover patterns in research. It
is used to quantify the problem by way of generating numerical data or data that can be transformed
into useable statistics” (Sanders et al., 2009, pg125). The main goal of Phase I was to assess the
perception of women working in the ICT sector of their current working conditions to understand
if the latter were perceived as gender biased. Understanding the current state of play is essential for
future policy-making. It helps the researcher understand what is working and what is not working in
the sector and thus offers more insight into the areas where improvements are needed.
Table 2: Data collection framework (primary data)
Research phase
Methodology
Remark
Filters included:
Sampling method
Purposive sampling
•
•
Gender (only female)
Job preference (currently working in IT sector or
have IT-related jobs)
N = 135
Initially 175 questionnaires were distributed to the target
population, of which only 135 were received back,
resulting in a return rate of 77.14%. The sample consisted
of participants from both the main private ICT companies
in Mauritius and public officers from several ministries
and parastatal bodies.
Data collection
Structured
questionnaires
Structured questionnaires were used to collect data. The
questionnaire was administered both face-to-face and
online via Google Forms. The majority of questions in the
questionnaire were in the format of five-point Likert-scale
questions.
Data analysis
Descriptive and
inference statistics
Both descriptive (measure of location, dispersion, etc.)
and inference/hypothesis testing (non-parametric mean
tests) were used.
Sample size
Reliability test of the structured questionnaire
The Cronbach alpha test is used to assess reliability/internal consistency when a set of items is used
to measure a variable during a survey. The reliability of any given measurement refers to the extent
to which it is a consistent measure of a concept. The threshold to decide what makes a “good” or
“bad” alpha coefficient is arbitrary and depends on the way the particular variable is measured.
Conventional wisdom in statistics recommends that an alpha coefficient between 0.65 and 0.8 (or
higher in many cases) is a “good coefficient”, whereas a figure less than 0.5 is termed as unacceptable.
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The table below shows the Cronbach alpha coefficient for the data obtained from questionnaire 1 on
each of the variable/constructs under study. All the alpha coefficients were well above 0.5, meaning
that the data were of “good” quality to go ahead with further analysis.
Table 3: Variable/construct
Variable/Construct
Cronbach’s Alpha
No. of Items
Job Characteristics
0.731
12
Career Opportunities
0.642
7
Gender Bias
0.538
8
Influence Factors
0.788
13
Health and Safety
0.854
4
Job Perception
0.753
6
Individual Differences
0.650
7
Ethical issues
Ethical considerations were attended to in the study. First, it was important to assure the anonymity
and confidentiality of respondents so that they did not hesitate to provide truthful and accurate
answers. Respondents were assured that their responses would be kept confidential and anonymous
and would not be revealed to any irrelevant party. They were also told that the questionnaire would
be used for academic purposes only. Moreover, to assure anonymity, respondents were not required
to write their names anywhere on the questionnaire. The cover letter attached also explained the
purpose of conducting the survey, and the personal details of the researcher were provided to
respondents so that they could contact the researcher in case they had any queries. Moreover,
participants were informed that their responses would be used for aggregation purposes and that they
could withdraw from the project whenever they wanted to.
ANALYSIS OF PRIMARY DATA
Before taking stock of the opinions of women who had not opted for an ICT career, this research
sought to compare the number of boys and girls actually studying Computer Studies in our schools.
Analysis of data collected from the Mauritius Examinations Syndicate shows that for four consecutive
years, the percentage of boys studying Computer Studies at the School Certificate level was higher
than for girls (table 4). Around 1 000 more boys studied that subject at School Certificate level,
although, overall, there were more girls in our schools. Table 4 also shows that the percentage of boys
studying Computer Studies kept increasing from 47.3% (2015) to 53.8% (2018), whereas the
percentage of girls for the same period remained around 30%. The rippling effect was that less girls
studied the subject at the Higher School Certificate level. Hence, less girls could opt for higher studies
in ICT, with the result that less of them would be eligible for an ICT job. This trend will certainly
account for a shortage in the number of women holding ICT positions and if not addressed, it will
over the coming years aggravate the situation. Matters are even worse in the UK, whereby females
now make up less than one tenth of Computer Science students (Sumner, 2018). Girls still perceive
that Computer Studies is a difficult and boring subject meant mainly for “nerdy” boys. Therefore,
they go for the more traditional “female” subjects such as history, languages, and the arts. But it was
worth noting that girls performed better than boys, given the higher pass rate over the years (table 5).
This information could certainly have an impact on girls’ perception that ICT is a male-dominated
sector.
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There is thus a need for urgent action from relevant authorities to reverse the situation and channel
more girls into IT-focused education by helping more women become Computer Studies teachers.
The National Computer Board in collaboration with other organisations and ministries could launch
projects like “Girls in IT Excellence Awards” to help promote successful female role models and
encourage more women onto this career path. It is also important to further encourage girls to study
STEM subjects like Computer Studies, otherwise, this might represent a loss of potential talent in the
computing workforce.
Figure 1: Percentage of girls and boys taking Computer Studies at School Certificate level
Pass Rate for Computer Studies at SC Level
79.07%
80%
78%
76%
73.71%
72.64%
74%
72%
73.42%
70.15%
70%
68%
69.95%
68.78%
66%
68.14%
64%
62%
2015
2016
2017
Boys
2018
Girls
Figure 2: Pass rate for Computer Studies at School Certificate leve
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Table Error! No text of specified style in document.: Total number of candidates who opted for computer studies at School Certificate level
TOTAL NUMBER OF CANDIDATES WHO OPTED FOR COMPUTER STUDIES AT SC
2015
2016
2017
2018
Total
No/(%)
Total
No/(%) who
Total
Examined
who opted
Examined
opted for
Examined opted for
Examined opted for
at SC
for
at SC
Computer
at SC
at SC
Computer
Studies
No/(%) who
Computer
Total
Studies
No/(%) who
Computer
Studies
Studies
BOYS
6 931
3 280
47.3%
6 824
3 506
51.4%
6 617
3 457
52.2%
6 488
3 488
53.8%
GIRLS
8 137
2 382
29.3%
7 984
2 522
31.6%
8 069
2 562
31.6%
8 111
2 442
30.1%
TOTAL
15 068
5 662
37.6%
14 808
6 028
40.7%
14 686
6 019
41.0%
14 599
5 930
40.6%
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Table 5: Pass Rate for School Certificate examination (Computer Studies)
PASS RATE FOR SCHOOL CERTIFICATE EXAMINATION (COMPUTER STUDIES)
2015
Examined
Pass
2016
Pass rate Examine
(%)
d
Pass
2017
Pass rate
(%)
Examined
Pass
2018
Pass
rate (%)
Pass rate
Examined
Pass
(%)
BOYS
3 280
2 256
68.78%
3 506
2 389
68.14%
3 457
2 418
69.95%
3 488
2 561
73.42%
GIRLS
2 382
1 671
70.15%
2 522
1 859
73.71%
2 562
1 861
72.64%
2 442
1 931
79.07%
TOTAL
5 662
3 927
69.36%
6 028
4 248
70.47%
6 019
4 279
71.09%
5 930
4 492
75.75%
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ANALYSIS OF SECONDARY DATA
This section of the report presents an analysis of the data collected during the first questionnaire
administered to women already working in the ICT sector in both private and public companies. This
phase of the project aimed to assess if working conditions in the ICT sector was gender biased.
Next, a summary is provided of the demographic profile of the 135 respondents who participated in
the survey. Demographic data are often used in research to help identify certain key characteristics of
the target group, such as age, gender, et cetera. This enables researchers to judge whether the sample
is representative of the population under study. Demographic information also helps segment
respondents into different market profiles.
Demographic profile of the respondents
Data (figure 3) shows that around 73% of the respondents were young adults (18–35 years) who held
various positions in their organisation, varying from managerial to operational through technical and
administrative.
Age Distribution
40%
35%
30%
25%
20%
15%
10%
5%
0%
37%
36%
18%
9%
18-25 years
26-35 years
36-45 years
≥ 46 years
Figure 3: Age distribution
The survey also showed that 78.5% of the participants held post-HSC qualifications: 14.7% had a
diploma; 47.4% had an undergraduate degree; and 16.4% a master’s degree. It was also observed that
around 35.3% of the respondents who worked in the sector had never study ICT at the secondary
school level; however, these participants were mainly involved in administrative (8.6%) and
operational (15.5%) duties in the sector.
Job characteristics and working conditions in the ICT sector
At a time of rapid digitalisation of its economy and growth in its ICT sector, Mauritius is facing two
major problems: first, a shortage of specialists to work in the ICT sector, especially at the technical
level; and second, an under-representation of women in the sector. This slows the objective of local
authorities to “end all forms of discrimination against all women everywhere” as part of their
commitment to SDG 5. While women around the world are, on average, pursuing higher levels of
education than their male counterparts, it was found that only about 17% of them end up following a
STEM profession (EIGE, 2017). Dana et al. (2006) observed that unexpected obstacles and risky
situations often hinder women’s careers. Timms et al. (2008) identified factors such as good social
image, flexible working hours, among others, as key determinants of a woman’s choice to embark on
a career in the ICT sector.
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Respondents answered a set of questions inspired from the above studies and sought responses related
to job characteristic and working conditions in the ICT sector. The results obtained are summarised
in figure 4:
Flexitime
Worklife Balance
7.0%
12.5%
8.6%
14.1%
Maternity Leave 2.4%5.6%
Safe for Pregnant Women
Hygiene Facilities
Holidays
Well-Defined Schemes of Duties
Job Security
7.8%
28.1%
30.5%
38.3%
23.8%
27.3%
38.1%
10.9%
32.0%
7.0% 7.0%
8.7%
34.6%
15.6%
31.5%
26.0%
3.9% 7.9%
18.8%
36.7%
15.7%
11.7%
30.2%
30.5%
33.6%
5.5% 7.9%
21.9%
43.3%
33.9%
29.9%
9.4%
17.3%
24.4%
Flexible Hours 3.1% 8.6%
19.5%
44.5%
24.2%
Shift Systems 3.1% 7.8%
21.1%
43.8%
24.2%
High Pressure
4.7% 5.5%
Strongly Disagree
21.1%
Disagree
46.1%
Neutral
Agree
22.7%
Strongly Agree
Figure 4: Job characteristics and working conditions
Work–life balance policies include, for instance, various rights relating to care-related leave and care
services, but also working arrangements that would allow employees to find a suitable balance
between their work responsibilities and their family and other responsibilities. The results show that
more than 70% of respondents agreed with the statement that working in the ICT sector in Mauritius
was equivalent to working under high pressure. Even though most companies in the sector had shift
systems and flexible hours, only around 54.3% of women agreed with the statement that there was
job security in the sector, while the other half were either undecided or literally disagreed with the
statement. In addition, only around 39% of the respondents agreed with the statement that the ICT
sector in Mauritius catered for a proper work–life balance. Figure 5 below summarises the answers
obtained from the respondents regarding their perception of whether the working conditions in the
ICT sector was women friendly. Around 54% of the respondents agreed with the latter statement.
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Perception of Working Conditions
Agree
39%
Strongly Agree
15%
Strongly Disagree
4%
Disagree
15%
Neutral
27%
Figure 5: Perception of working conditions
Career opportunities and job retention
The second set of questions in the first questionnaire was to investigate the perception of female
workers of their career opportunities in the ICT sector in Mauritius and to understand the reasons why
these women kept working in the sector.
Overall, the results presented in figure 6 show that as regards career opportunities, female respondents
were unanimous about the fact that opportunities existed in the ICT sector in Mauritius for personal
development. Around 59% believed that holding a job in that sector was associated with future
promotional prospects and high socio-economic status. However, it is important to note that women
(more than 83.6%) thought that more incentives needed to be provided for women to choose a career
in the ICT sector. Generally, when prompted about opportunities to take up managerial positions, a
significant percentage of respondents (44%) agreed with the statement.
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19.5%
18.9%
20.3%
22.0%
23.4%
46.9%
22.0%
40.9%
39.8%
32.0%
53.9%
33.1%
36.7%
26.6%
35.2%
30.7%
16.4%
10.2%
3.9%
Promotional
Prospects
12.5%
0.8%
3.1%
8.7%
00.8%
7.8%
1.6%
Personal
Development
High Socio
Economic
Status
Strongly Disagree
Neutral
2.4%
Gender Neutral
High
Adverts
Probability for
Management
Position
More
Incentives for
Women
Disagree
20.5%
6.3%
3.1%
Agree
Strongly Agree
Figure 6: Career opportunities
Figure 7 shows the various reasons that kept respondents from working in the ICT sector. The two
main reasons were job satisfaction (34.6%) and the nature of the sector (25.9%). Around 13.6% and
11.5% selected work environment and reward, respectively, as the main reasons that kept them
working in that sector. Women also valued the social image associated with working in the ICT sector.
Job Retention
35.0%
30.0%
25.0%
20.0%
34.6%
15.0%
25.9%
10.0%
5.0%
11.5%
13.6%
11.1%
3.3%
0.0%
Reward
Job Satisfaction
Social Image
Work
Environment
Love the Sector
No Choice
Figure 7: Job retention
Gender bias
James et al. (2006) conducted a study commissioned by the Embassy of Finland as part of a larger
study to investigate mechanisms for stimulating the increased participation of women in high-level
ICT skills in South Africa. The authors found that women were still discriminated against vis-à-vis
men to take up management positions (only 18–20%), and they still earned less than men. There were
many barriers that kept women from being promoted to management and executive positions. Most
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were related to misconceptions that women did not show leadership potential and behaved differently
from traditional male leaders in ways that would be detrimental to themselves and an organisation. In
line with the above, a series of questions were posed to respondents to gauge their perception of the
level of gender bias in the Mauritian ICT sector.
Figure 8 shows that women in general believed the ICT sector was gender biased being male
dominated. Respondents pointed out that it was very difficult for them to aspire to senior positions or
technical positions when in competition with their male counterparts: 43.7% agreed that it was
difficult for them to move up the career ladder. When asked questions about gender bias in the
Mauritian ICT sector, 56.3% of the participants agreed that the sector was male dominated, and 60.9%
opined that senior positions in the sector were occupied by male. A majority of respondents, however,
did acknowledge that their male co-workers were quite supportive in their daily activities. These
findings are in line with those of a recent study conducted by the European Institute for Gender
Equality (EIGE) in 2018 that highlighted that the gap between men and women securing a job in ICT
was widening every year.
5.5%
no dressing restriction
7.8% 10.9%
senior positions occupied by men
7.0%
industry male dominated
8.3%
handle heavy equipment
Disagree
18.8%
37.5%
21.9%
17.3%
35.4%
28.1%
34.7%
17.4%
Neutral
28.8%
34.4%
32.3%
6.3% 8.7%
supportive male coworkers
Strongly Disagree
14.8%
25.0%
35.9%
20.3%
20.8%
5.6% 10.4%
same chances to join technical positions
23.4%
21.9%
32.8%
16.4%
Agree
10.9%
32.8%
28.1%
14.8%
13.3%
difficulties move up career ladder
12.5% 6.3%
43.0%
27.3%
10.9%
recruitment and selection favours women
11.6%
Strongly Agree
Figure 8: Gender bias
Gender bias in the private sector only?
In this section of the paper, using the same data collected on women already working in the ICT
sector, an attempt is made to investigate whether the gender bias identified above was specific to the
private sector, or whether it can be generalised to the public sector as well. In the public sector, things
are expected to be a bit different, as pay schemes and conditions of service are regulated by the PRB
(2016). Hence, the following hypothesis was proposed:
•
•
H0: There is no difference in the perception of gender discrimination in the public and private
sectors.
H1: There is a difference in the perception of gender discrimination in the public and private
sectors.
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The Mann-Whitney (MW) test is used to compare variation between the recorded responses from two
independent groups when the dependent variable study is not normally distributed. The MW test
statistics are provided in table 6 and 7.
Table 6: Ranks
N
Mean rank
Sum of
ranks
Public
35
62.84
2199.50
Private
90
63.06
5675.50
Total
125
Type of Company
Male dominated
Table 7: Mann-Whitney U test statistics
Male dominated
Mann-Whitney U
1569.500
Wilcoxon W
2199.500
Z
-.031
Asymp. Sig. (2-tailed)
.975
The significance value of the MW-U test statistic is given by 0.95, which is greater than the
benchmark level of 5%. Hence, it can be concluded that there was no difference in the perception of
gender bias from respondents in the public and private sectors. This result is in line with recent
findings by Ahmed and Nasser (2015) who discovered that gender discrimination faced by females
at work does not happen in the private sector only but is also present in public organisations.
Is the perception of gender bias age related?
In addition to the above, it was also explored whether the age group of respondents might have had a
confounding effect on the perception of respondents of gender bias in the sector. As such, a second
hypothesis was tested as follows:
•
•
H0: There is no difference in the perception of gender discrimination among the different age
groups of respondents.
H1: There is a difference in the perception of gender discrimination among the different age
groups of respondents.
The KW test statistics are provided in table 8 and table 9 below:
Table 8: Ranks
Male dominated
18–25 years old
26–35 years old
36–45 years old
≥ 46 years old
Total
N
46
49
26
Mean rank
52.46
72.88
73.31
11
80.73
132
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Table 9: Kruskal Wallis test statisticsa, b
Male dominated
Chi-Square
10.647
df
Asymp. Sig.
3
.014
a. Kruskal Wallis test
b. Grouping variable: Age group
The significance value of the KW test statistic is given by 0.014, which is less than the benchmark
level of 5%. Hence, it can be concluded that there was a difference in the perception of gender
discrimination among the different age groups. This result corroborates the finding of Sanders (2005),
who reported that gender differences in attitudes and behaviour were relatively small at younger ages
but increased as people became older.
Influential factors
Studies such as that of Adya and Kaiser (2005) and Turner et al. (2002) pinpointed the huge influence
that parents have on young women’s choice to take up employment in the sector. Out of the sample
of women interviewed, Adya and Kaiser (2005) observed that around 73% of respondents identified
their fathers as strong influencers in their career choice. In the same vein, a similar set of questions
were administered to women already working in the ICT sector to investigate the influence of family,
schools/teachers and authorities on their choice to take up a career in the sector. Figure 9 below
summarises the responses obtained. Respondents generally agree that parents (45.7%), teachers
(39.4%), siblings (69.3%) and having a role model in the field (67.5%) tended to influence their
choice of choosing a career in the ICT sector.
14.2%
Percentage
31.5%
11.8%
32.3%
13.4%
22.8%
33.9%
11.8%
11.9%
27.6%
25.4%
29.1%
13.4%
18.9%
8.7%
7.9%
6.3%
18.9%
13.2%
9.1%
24.8%
27.3%
18.9%
5.0%
19.2% 14.9%
33.9%
52.8%
46.5%
32.3%
3.1%
15.7%
37.0%
44.1%
34.1%
38.8%
42.1%
15.7%
15.7%
7.4%
5.8%
48.3%
48.8%
24.2%
18.2%
7.5%
13.2%
33.1%
34.6%
18.9%
16.5%
3.1%
18.9%
7.1%
4.7%
4.7%
Strongly Disagree
19.8%
22.0%
8.7%
6.3%
Disagree
22.8%
7.9%
4.7%
Neutral
7.9%
Agree
Strongly Agree
Figure 9: Summaries of respondents
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Table 10 shows that two thirds of the respondents (neutral responses were ignored) acknowledged the
encouragement provided by their parents to choose a career in the ICT sector. The relevant authorities
should, therefore, take necessary measures to organise information campaigns for parents to
encourage girls to pursue an ICT job.
Table 10: Parents encourage girls to take up an ICT job
Frequency
11
18
40
21
90
Strongly disagree
Disagree
Valid Agree
Strongly agree
Total
Per cent
12.2
20.0
44.4
23.3
100.0
Individual differences
Individual differences are defined in the literature as “enduring psychological characteristics that
distinguish one person from another”, which is extremely useful to demarcate between each person's
individuality. The most common types of individual differences used in research are:
i.
ii.
iii.
intelligence
personality traits
values.
Women tended to give up on STEM careers because they perceived that such type of jobs were not
meant for them. A set of questions related to individual differences were administered to the survey
participants. The diagram below summaries the results:
100.0%
10.2%
9.4%
28.1%
28.9%
8.6%
90.0%
80.0%
35.9%
70.0%
60.0%
50.0%
40.0%
28.9%
44.5%
50.8%
30.0%
20.0%
10.0%
20.3%
11.7%
7.8%
3.1%
5.5%
6.3%
0.0%
Personality
Strongly Disagree
Innate Aptitudes
Disagree
Neutral
Lack of Technical Capability
Agree
Strongly Agree
Figure 10: Ease of women to cope with ICT jobs
It was observed that 38.3% of the women who were interviewed agreed with the statement that “the
personality of women make them suitable for the ICT sector; 38.3% thought that “[w]omen have
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innate aptitude for ICT-related jobs”; and 44.5% were of the opinion that women lack the necessary
technical skills to work in ICT-related jobs.
CONCLUSION
The aim of this study was to investigate the opinion of women about ICT-related jobs and the factors
hindering them from embracing a career in the ICT sector. First, analysis of secondary data from the
MES reports showed that despite a higher girl population in schools and their ability to perform better
than boys in Computer Science, there were significantly lesser girls taking this subject at the School
Certificate level. Over the years, the percentage of boys studying Computer Science kept increasing,
while the percentage of girls remained nearly the same. Therefore, there is a need to encourage more
girls to study Computer Science at school and thus be more prepared to choose ICT as a career. Girls’
ability to perform better than boys in Computer Science means that encouraging more girls to follow
an ICT-related career would contribute to strengthening human capital in our ICT sector.
A questionnaire was designed and administered to 135 working women in the ICT sector. It was
observed that around 70% of the participants acknowledged that the ICT sector required working in
shift systems and thus under high pressure. Two out of every three women agreed that working in the
ICT sector did not offer a balanced work life. Only a minority of the respondents (11.8%) opined that
there was not enough job security in the sector. Women in general (59%) believed that working in
that sector offered promotional prospects and was associated with high socio-economic status.
However, according to them, there was a need to provide more incentives to encourage women to opt
for an ICT career. In general, it can be said that women enjoyed working in the ICT sector.
Analysis of a set of items dealing with gender bias revealed that women felt discriminated against in
ICT-related jobs. They opined that the sector was mostly male dominated, and career opportunities
and promotions at work were restricted for them. However, younger women were less concerned with
gender bias, hence showing that the younger generation might be equally at ease as their male
counterparts in that sector. Another set of items helped to understand the factors that influenced
women in their choice of an ICT career. In addition to parents and teachers, the influence of siblings
already working in this sector and women role models in the field were reported as significant
signposts directing girls/women in their choice.
RECOMMENDATIONS
This study revealed that there is definitely a digital divide favouring men for ICT-related jobs. The
first phase of the study gathered women working in the ICT sector for a group discussion. The
participants opined that access and opportunities to jobs in the ICT sector were influenced by
numerous factors. Moreover, companies should give women the same opportunity as men to climb
the ladder and be promoted to higher-level jobs in the ICT sector. It is also recommended that
stakeholders provide appropriate training in the field of ICT to attract a number of women to the
sector to meet the increasing demand for skilled IT professionals.
The conclusions drawn from the study and recommendations were as follows:
Girls outperform boys in Computer Studies, but there is still a higher percentage of boys doing
Computer Studies in our schools.
Recommendation 1: Schools should provide wider access to girls to Computer Studies through
awareness programmes. This subject should form part of the different subject combinations offered
at school.
Opinions about gender bias for ICT-related jobs persist and discriminate against girls.
Recommendation 2: Sensitisation programmes should be conducted in schools by female role
models to help dissipate misconceptions about ICT jobs.
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Cultural and societal attitudes do influence girls opting for an ICT job and women working in that
sector. This is closely related to the perception that ICT jobs are more for men, given both the nature
of jobs and working conditions.
Recommendation 3:
(a) A number of video programmes can be produced showing women successfully and happily
working in the ICT sector. Frequent broadcasting of such videos on our TV channels and in our
schools is recommended.
(b) ICT organisations should provide a conducive working environment that would attract more
women to the sector.
There is a feeling that while promotional prospects exist in the sector, males are more apt to aspire to
higher posts.
Recommendation 4: While awaiting more women to join that sector, organisations might introduce
a dose of positive discrimination when promoting employees to higher posts by reserving a quota for
women. A “Women Excellence Award” can be organised at different levels, including one at the
national level to acknowledge and reward women who have excelled in the sector.
Recommendation 5: Stakeholders should provide appropriate training in the field of ICT and attract
a number of women to the sector to meet the increasing demand for skilled IT professionals.
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A STUDY OF MOOC LEARNERS’ LEARNING EXPECTATIONS,
LEARNING ENGAGEMENT AND SATISFACTION
Mahesh H. Koltame
PVDT College of Education for Women,
SNDT Women’s University, Mumbai (mahesh.koltame@pvdt.sndt.ac.in)
Abstract
In this study, the researcher analyzed learners’ expectations of massive open online courses
(MOOCs), their learning engagement, and satisfaction. This paper reports the findings of a study of
the relationships between learners’ learning engagement and their satisfaction with their overall
performances in an online course. This study was conducted with 224 participants who had
successfully completed a 90-hour, four-credit School Leadership Capacity Building (SLCB) MOOC
(first offering from 07 September to 20 December 2020). The researcher collected data by means of
a pre-course survey, learning engagement analytics, and a post-course learner satisfaction survey.
Data were coded and analyzed both quantitatively and qualitatively. After the data analysis with
descriptive statistics, the researcher found most MOOC learners expected simple but more interactive
learning activities and reading material in small chunks. Also, the research showed there was a
significant correlation between learners’ confidence in their pre-ICT skills and their learning
engagement, and the association between satisfaction and engagement was significant and positively
correlated. Furthermore, there was a weak but positive significant correlation between satisfaction
and engagement with their overall performances. In this course, the researcher found that those
learners who were connected with each other in their small groups (maybe the groups were based on
country or institute) engaged more and performed well in the course. The blending of a few
synchronous interaction sessions boosted learners’ confidence and interest in the MOOC, and it
helped to sustain their motivation in the course.
Keywords: MOOC, learning expectations, learning engagement and learning satisfaction
INTRODUCTION
The nature of the 21st-century world is dynamic and digital. The impact of technology on 21st-century
education is very high. Since technology is rapidly evolving and needs specialists to deliver highquality e-learning, a vibrant ecosystem must be encouraged to create solutions that not only solve
India’s challenges of scale, diversity and equity but also evolve in keeping with the rapid changes in
technology whose half-life reduces with each passing year (NEP, 2020). Technology in education is
a journey, not a destination (NEP, 2020).
Massive open online courses (MOOCs) are rapidly emerging as the high standard of lifelong learning
in 21st-century education. It has opened the door to high-quality global learning. It has the potential
to make education more equitable and inclusive through open educational resources (OERs). MOOCs
could well replace some forms of traditional teaching (such as large lecture classes). However,
MOOCs are more likely to remain an important supplement or alternative to other conventional
education methods. They are not on their own a solution to the high cost of higher education, although
MOOCs are and will continue to be an important factor in forcing change (Dousay, 2015). In this
pandemic, the whole world is engaged in remote learning practices. Among these practices, online
modalities and MOOCs have become popular, although there are ongoing debates about MOOCs
regarding the perspective of learners’ expectations, patterns of their learning engagement, and their
learning satisfaction.
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To comprehend “MOOC” (or massive open online courses), “massive” means a platform that is
designed for the public at large. “Open” means the course/platform being free or being given out at a
very nominal charge, giving them access to different societal sections and different demographics and
economic strata. “Online” implies that the courses are omnipresent – easily accessed anywhere
(Kumar et al., 2020). Thus, they are defined as something online that has an option of free and open
registration, along with a shared curriculum and pedagogy with public and open outcomes (Macleod
et al., 2014; McAuley et al., 2010).
As per the UGC concept note on the blended mode of teaching–learning, MOOCs aim to provide
real-time education online with the help of various features like videos, study materials, quizzes, and
online exams. MOOCs also try to make it more efficient than real-time education in classrooms by
removing time constraints and location constraints. Also, MOOCs provide interactive discussion
sessions for the user through interactive discussion forums that help to build a community for students
and professors (UGC, 2020).
There are currently major structural limitations in MOOCs for developing deep or transformative
learning or for developing the high-level knowledge and skills needed in a digital age (Dousay, 2015).
The more massive the course, the more likely participants are to feel overload, anxiety and a sense of
loss if some instructor, intervention, or structure is not imposed (Knox, 2014). Firmin et al. (2014)
have shown that when there is some form of instructor “encouragement and support of student effort
and engagement,” results improve for all participants in MOOCs.
MOOCs tend to attract those who already have a high level of education; however, wide access and
high dropout rates are some of the major concerns of MOOCs. Therefore, it is necessary to understand
the factors that affect the learning satisfaction of learners. In this regard, several investigations have
already been conducted, and some factors have been identified, like level of interaction, networking
opportunities, course pedagogy, course content, assessment features, the presence of technology, and
feedback-sharing mechanisms (Kumar & Kumar, 2020).
A learner satisfaction survey is one of the important instruments to investigate the reasons of
discontinuance of an online course. Detailed analysis of a learner satisfaction survey would help
educators understand learners’ expectations of the course, and they can work on these factors, which
may lead to increased learner satisfaction with MOOCs, thereby addressing high dropout rates (Pande
& Mythili, 2021).
In this study, the researcher analyzed learners’ expectations of MOOCs, their learning engagement
and satisfaction and reports on the findings of a study of the relationships between learners’ learning
engagement and their satisfaction with their overall performances in an online course.
RESEARCH QUESTIONS
i.
ii.
iii.
iv.
What are learners’ expectations of MOOCs?
What factors affect learners’ learning engagement?
What is the level of learners’ learning satisfaction?
Is there any relation between learners’ learning engagement and their satisfaction?
METHODOLOGY
Quantitative and qualitative research methods – that is, a survey and content analysis – were used in
this study. The researcher collected data by means of a pre-course survey, learning engagement
analytics, and a post-course learner satisfaction survey, along with the content analysis of learners’
reflective learning diaries. In the course, the learners were assigned a reflective learning diary and
some descriptive questions in feedback after each module. The reflective learning diary contained
responses to questions like: What is the driving force to complete these learning activities? How do
these activities support my knowledge, skills, and attitudes to capacity building as a school leader?
What do you like most in this module, and why? What are you expecting from the next module?
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Responses to all these questions were analyzed using an analysis chart. For analysis, eight key MOOC
learning engagement factors were considered: 1. course content; 2. pedagogy; 3. expert intervention
in the discussion forum and synchronous discussion sessions; 4. freedom; 5. flexibility; 6. continuous
formative assessment; and 7. continuous communication and support by mentors. Data were coded
and analyzed with the use of descriptive statistics like percentage, mean and correlation.
Participants
The study included 224 participants who had successfully completed a 90-hour, four-credit School
Leadership Capacity Building (SLCB) MOOC that was offered by PVDT College of Education for
women, SNDT Women’s University, Mumbai, from 07 September to 20 December 2020.
Table 1: Learner demographics
Gender
Characteristics
Male
Female
Age group
< 20 Years
20-29 Years
30-39 Years
40-49 Years
50-59 Years
60 >Years
Primary spoken language
English
Hindi
Marathi
Tamil
Spanish
Malayalam
Odia
Telegu
Bangla
Swahili
Punjabi
Kiswahili
Kinyarwanda
Gujarati
Konkani
Geographic Region
Africa
America
Asia
Central America
Job profile
Headmaster/Principal
Vice Principal
Supervisor
Teacher
Teacher educator
Pupil teacher/research
scholars
Others
Frequency
%
82
142
36.60
63.39
05
35
86
68
27
03
2.23
15.62
38.39
30.35
12.05
1.33
84
28
38
14
09
09
09
03
09
03
03
06
03
03
03
37.5
12.5
16.96
6.25
4.01
4.01
4.01
1.33
4.01
1.33
1.33
2.67
1.33
1.33
1.33
36
12
167
09
16.07
5.35
74.55
4.01
27
16
08
68
51
36
20.05
7.14
3.57
30.35
22.76
16.07
18
8.03
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Research Q 1: What are the learners’ expectations of MOOC?
Instruments and data analysis
To study students’ learning expectations, the researcher collected quantitative and qualitative data
through an online pre-course survey and student feedback after completing each module. Along with
the feedback, students were asked a descriptive question regarding what they were expecting of the
next module.
The pre-course survey was designed with a five-point Likert scale (strongly agree, agree, neutral,
disagree, strongly disagree). The scale consisted of 25 statements related to the seven major aspects
(structure, content, pedagogy, sharing and discussions, assessment, expert intervention and learning
support, and ICT use) of the MOOC.
Table 2: Shows the percentage of learner expectations of MOOCs
Aspects of
MOOC
Expectation statements
Course
structure
There should be no due dates for
learning activities and
assignment.
I should be able to choose
learning activities as per my
interest.
The course should be
multilingual.
All course content and learning
activities should be completely
open without any prerequisites.
Downloadable text material
should be available
Engaging video and animation
should be given
I feel Infographics and pictorial
content would be facilitate my
learning
Video, text, graphics should be
interactive.
Case studies, scenarios should be
used for a realistic experience
It should contain useful learning
activities to make the learning
experience centered.
There should be diversity in
Learning activities.
There should be learning
activities that can practice skills
in the real field.
I love to learn from short,
engaging presentations followed
by reflection
I should be able to communicate
with all co-learners
There should be scope for the
sharing of ideas and experiences
with co-learners.
Course
content
Course
pedagogy
Sharing &
discussions
Strongly
agree (%)
Agree
(%)
Neutral
(%)
80
14
03
03
70
10
00
12
08
26
38
02
29
05
73
11
03
13
00
75
23
00
02
00
69
31
00
00
00
68
12
07
13
00
57
23
00
08
12
79
21
00
00
00
88
12
00
00
00
77
23
00
00
00
66
27
00
07
00
66
16
06
10
02
59
35
00
06
00
44
48
02
06
00
119
Disagree
(%)
Strongly
disagree
(%)
0%
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Course
assessment
Expert
intervention,
feedback and
learning
support
Use of ICT
In the discussion forum, the
mentor or facilitator should
remain neutral.
Quizzes should be included to
promote and direct the learning.
Assignment should be easy.
26
16
00
20
38
91
06
0
02
00
60
40
0
0
0
Assessment should be done
through learning activities
final exam should be conducted
for a fair assessment
A mentor should intervene as
expert in discussion forums.
Synchronous sessions should be
organized for resolving doubts
and contextualizing content
A mentor should be constantly
active and support my learning
MOOC should use simple ICT
tools that are accessible to all.
I believe that advanced ICT tools
will be more helpful for my
learning.
Should provide basic training
before the course start on how to
use LMS.
71
09
0
14
06
17
08
03
26
46
77
13
00
10
0
34
18
10
32
06
26
07
0
59
08
89
06
0
04
01
12
06
0
74
08
85
11
0
03
01
CONTENT ANALYSIS
Content analysis is the process of summarizing and reporting written important content of any data
(Onah, 2015). According to some authors (Flick, 1998; Mayring, 2004; Krippendorp, 2004), content
analysis is a systematic procedure for the rigorous analysis, investigation and “verification of the
contents of a written data”. They refer to it as “a research technique for making replicable and valid
inferences from texts” to the context of their usage.
In conjunction with the quantitative analysis, MOOC learner expectations are studied through
qualitative analysis. Accordingly, the learners’ descriptive answers and their reflective learning
diaries were analyzed using content analysis methodology. The learners’ expectations were
categorized into seven categories: 1. Flexibility; 2. Freedom; 3. User-friendly ICT integration; 4.
Interactive course content; 5. Learner-centered pedagogy; 6. Continuous assessment; 7. Expert
intervention and learning support.
In the flexibility category, the analysis indicated that 68% of the respondents wished to learn at their
own pace; 91% of the respondents believed that there should be no due date for any assignment and
any learning activity; 59% of the respondents indicated that there should be no prerequisite for any
course content exploration or learning activity; 20% of the respondents felt that there should be a
facility to submit assignments in their local language; and 54% of the respondents believed there
should be no insistence on spending five to six hours per week.
In the freedom/openness category, the analysis indicated that 86% of the respondents wished to
download study material so they could use it in offline mode; 91% of the respondents indicated that
there should be no compulsion to complete all activities; 69% of the respondents indicated that there
should be freedom to choose learning activities according to learners’ interest; and 84% of the
respondents felt there should not be too much workload.
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In the ICT integration category, the analysis indicated that 89% of the respondents believed MOOCs
should use simple ICT tools that are accessible to all; 59% of the respondents expected basic training
before the course as to how to use LMS and other ICT tools; and only 30% of respondents believed
that advanced ICT tools would be more helpful for their learning.
In the interactive course content category, the analysis indicated that 91% of the respondents
expected downloadable interactive text handouts that could be easily read anytime, anywhere; 84%
of the respondents expected interactive video tutorials, pictures, and infographics; 83% of the
respondents expected handouts in small chunks; and 73% of respondents expected case studies,
scenarios in text, and videos for a realistic experience.
In the learner-centered pedagogy category, the analysis indicated that 90% of the respondents
expected useful learning tasks to make learning experience-centered; 89% of the respondents
expected a learner-centered collaborative learning design; 64% of the respondents expected learning
activities that could practice skills in the actual field; and 62% of the respondents expected diversity
in learning activities.
In the continuous assessment category, the analysis indicated that 96% of the respondents expected
practice quizzes to speed up and direct learning; 88% of the respondents expected field-based
assignments for developmental assessment; 61% of the respondents expected assessment through
learning activities; and 58% of the respondents expected a course end exam.
Finally, in the expert intervention and learning support category, the analysis indicated that 70%
of the respondents expected synchronous sessions for expert support; and 83% of the respondents
expected mindful expert intervention by course mentors to solve doubts or to clarify misconceptions.
RESULTS
Based on the data analysis and interpretation, the following common expectations of MOOC learners
of an MOOC were as follows:
•
•
•
•
•
•
•
•
To gain new knowledge skills of school leadership and earn a course completion certificate
was the initial motivation of the learners.
MOOC learners expected more flexibility in the course structure.
MOOC learners expected more freedom in the choice of what to learn, how to learn, and when
to learn.
MOOC learners expected the use of ICT tools in MOOCs should be simple and user-friendly.
Also, learners expected pre-orientation to LMS and other ICT tools used in the course.
MOOC learners expected interactive, engaging and scenario-based course content in small
chunks.
MOOC learners expected a learner-centered, experience-based collaborative learning design.
MOOC learners expected continuous developmental assessment through quizzes, field-based
assignments, learning activities, etcetera, instead of end-of-course exams or tests.
MOOC learners expected mindful expert intervention by course mentors for doubt solving or
clarification of misconception and learning motivation.
Research Q 2: What factors affect learners’ learning engagement?
Learner learning analytics
One way to identify learners’ expectations, motivations and understand their learning engagement
online is through learning analytics. De Liddo et al. (2011) analyzed a learner analytics dataset to
shed light on individual or group learning patterns and learner activities in the course at different
stages (Breslow et al., 2013) or learners’ ability to proceed to the end successfully or fail and drop
out (Barber et al., 2012). According to Kizilcec et al. (2013), these learner analytics presented a
method of classifying MOOC learners by grouping them into levels of engagement.
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Learners’ learning engagement has been assessed mainly through LMS statistics, like time spent on
LMS; the number of posts or replays in discussion forums; number of submissions for assignments;
number of peer assessments done by a learner; engagement in interactive content; and participation
in synchronous discussion sessions. It is classified further into three levels: high (80% and above); 2.
moderate (60–79%); and 3. low (below 60%).
Table 3: Level of learners’ learning engagement with course content
Factor
Nature of content
Interactive
course
content
Experience
centered
learning
activities
Discussion,
sharing and
co-creation
Assessment
Text content with embedded quizzes/ reflective
questions
Video tutorials with embedded reflective
spots/questions
Interactive ppt presentations
Puzzles, games
Field based activities’
Scenario/ case-based discussion
Reflective discussion with focused questions
Sharing forums and walls
Graded quizzes
Practice quizzes
Assignments
Learner engagement level
High
Moderate
Low
68%
19%
13%
29%
35%
36%
62%
93%
48%
24%
6%
50%
14%
1%
02%
62%
72%
59%
98%
88%
30%
23%
19%
14%
2%
06%
70%
15%
09%
27%
0%
06%
0%
In this study, 68% of the learners were highly involved in embedded text content with quiz/reflective
questions; 62% of the students were highly involved in interactive presentation; and 36% of the
learners showed lower engagement in interactive tutorials. This means interactive text content and
presentation is highly engaging in comparison to interactive video tutorials.
Moreover, 93% of the learners were highly involved in puzzles and games, and 48% learners were
highly involved in field-based activities. This means experience-centered micro-learning activities,
such as puzzles and games, were highly engaging in comparison to field-based activities.
Also, 72% of the learners were highly involved in reflective discussion with focused questions; 62%
of the learners were highly involved in scenario/case-based discussion; 59% in sharing forums and
walls; and only 45% of the learners showed moderate engagement in groupwork. Thus, reflective
discussion with focused questions was highly engaging in comparison to groupwork.
Finally, 98% of the learners were highly involved in graded quizzes; 88% of the learners were highly
involved in practice quizzes; and only 70% of the learners showed moderate engagement in graded
assignments. This means that reflective discussion with focused questions was highly engaging in
comparison to group work.
Table 4 shows the descriptive statistics at the level of learning engagement of students. According to
this, 65% of the learners were highly engaged in learning and had completed 80–100% of their
assigned learning activities; 24% of the learners were moderately engaged in learning, and 60–79%
of assigned learning activities had been completed; and 11% of the learners were less engaged in
learning and had completed below 60% of the assigned learning activities.
Table 4: The percentage of overall learner engagement level in an MOOC
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Content analysis
To gain a deeper understanding of learning engagement in this study, content analysis of learners’
reflective learning diaries was done. Content analysis revealed seven key factors that drove learners’
learning engagement in MOOCs: 1. Course content; 2. Pedagogy; 3. Expert intervention in the
discussion forum and synchronous discussion sessions; 4. Freedom; 5. Flexibility; 6. Continuous
formative assessment; and 7. Continuous communication and support by mentors.
Level
Learners %
High
145 (65%)
Moderate
54 (24%)
Low
25 (11%)
Results
Through the descriptive analysis of LMS statistics, four course content-related factors were identified:
Interactive course content
•
•
•
Experience centered micro-learning activities
Scope for discussion, sharing and co-creation
Use of graded and non-graded quizzes for continuous assessment
And through content analysis of learners, reflective learning diaries and their descriptive feedback,
three more factors were identified. Course structure and support-related factors were identified as:
•
•
•
Flexibility and freedom
Use of ICT tools
Continuous communication and support by course facilitators.
Research Q 3: What is the level of learners’ learning satisfaction?
To study the MOOC learner’s learning satisfaction, a post-course learner satisfaction survey was
conducted. The various factors adopted in this study were taken from other research on MOOC
satisfaction and retention (Kumar & Kumar, 2020). The scales were changed according to context of
SLCB MOOC, and some more factors were brought to add to its relevancy (i.e., course structure,
support system and learners’ learning engagement). The scale included 21 attributes on a five-point
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scale, ranging from “Not at all satisfied” to “Completely satisfied” in various components related to
SLCB MOOC.
Table 5: The percentage of learners in respect of the level of their learning satisfaction
Completely
satisfied
(Level 05)
Satisfied
(Level 04)
Satisfied
somewhat
(Level 03)
Not
satisfied
(Level 02)
Not at all
satisfied
(Level 01)
183 (81.69%)
179 (79.91%)
41 (18.30%)
45 (20.08%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
169 (75.44%)
50 (22.32%)
0 (0%)
0 (0%)
176 (78.57%)
42 (18.75%)
0 (0%)
0 (0%)
Scenarios and case studies
170 (75.89%)
52 (23.21%)
0 (0%)
0 (0%)
Interactive video tutorials
169 (75.44%)
50 (22.32%)
0 (0%)
0 (0%)
Practice learning activities
163 (72.76%)
56 (25%)
0 (0%)
0 (0%)
Sharing and discussion
Discussion forum
05
(2.23%)
06
(2.67%)
02
(0.89%)
05
(2.23%)
05
(2.23%)
163 (72.76%)
55 (24.55%)
0 (0%)
0 (0%)
Sharing walls (Padlet)
169 (75.44%)
50 (22.32%)
0 (0%)
0 (0%)
Pedagogy
Course alignments
Learner-centricity
06
(2.67%)
05
(2.23%)
183 (81.69%)
172 (76.78%)
41 (18.30%)
50 (22.32)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
Game based interactive
learning activities
Assessment and grading
Practice quizzes
188 (83.92%)
32 (14.28%)
0 (0%)
02
(0.89%)
02
(0.89%)
02 (0.89%)
0 (0%)
190 (84.82%)
29 (12.94%)
0 (0%)
0 (0%)
Graded final quizzes
163 (72.76%)
55 (24.55%)
0 (0%)
0 (0%)
Graded final assignments
145 (64.73%)
65 (29.01%)
0 (0%)
0 (0%)
Instructor intervention
and feedback
Synchronous sessions
02
(0.89%)
06
(2.67%)
14
(6.25%)
170 (75.89%)
47 (20.98%)
02 (0.89%)
0 (0%)
Clarifying doubts
188 (83.92%)
32 (14.28%)
02 (0.89%)
0 (0%)
Feedback
181 (80.80%)
38 (16.96%)
0 (0%)
0 (0%)
Technical support
181 (80.80%)
39 (17.41%)
05
(2.23%)
02
(0.89%)
05
(2.23%)
04
(1.78%)
0 (0%)
0 (0%)
190 (84.82%)
26 (11.60%)
3 (1.33%)
0 (0%)
145 (64.73%)
60 (26.78%)
02
(0.89%)
14
5 (2.23%)
0 (0%)
Components of MOOC
Course structure
Flexibility
Freedom/openness
Course content
Quality of text resources
(Self-learning Handbooks)
Quality of video tutorials
Use of ICT
LMS/ICT orientation
module
Integration of ICT tools
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Overall satisfaction level
179 (79.91%)
43
(19.19%)
(6.25%)
02
(0.89%)
0 (0%)
0 (0%)
Results
•
•
•
•
•
•
•
•
Overall, 80% of the learners were completely satisfied; 19% of the learners were satisfied;
1% were somewhat satisfied; and no one was dissatisfied with SLCB MOOC.
As regards course structure, 81% of the learners were completely satisfied; 19% of the learners were satisfied; and no one was dissatisfied.
Concerning course content, 75% of the learners were completely satisfied; 25% of the learners were satisfied; and no one was dissatisfied.
Regarding sharing and discussion activities, 74% of the learners were completely satisfied;
23% of the learners were satisfied; 3% of the learners were somewhat satisfied; and no one
was dissatisfied.
With regard to course pedagogy, 81% of the learners were completely satisfied; 18% of the
learners were satisfied; 1% of the learners were somewhat satisfied; and no one was dissatisfied.
As regards assessment and grading, 75% of the learners were completely satisfied; 22% of
the learners were satisfied; 3% of the learners were somewhat satisfied; and no one was dissatisfied.
Regarding instructor intervention and feedback, 80% of the learners were completely satisfied; 17% of the learners were satisfied; 2% of the learners were somewhat satisfied; 1% of
the learners were not satisfied; and no one was completely dissatisfied.
Lastly, 76% of the learners were completely satisfied; 19% of the learners were satisfied; 3%
of the learners were somewhat satisfied; 2% of the learners were not satisfied; and no one was
completely dissatisfied with course use of ICT in course.
Research Q 4: Is there any relation between learners’ learning engagement and their
satisfaction?
To answer this question, data were analyzed with descriptive statistics like mean, standard deviation
and correlation coefficient.
The researcher investigated the relationships between learning engagement and learning satisfaction
using the correlation coefficient (r).
Table 6: Correlation between learners’ learning engagement and their learning satisfaction
Variables
Level of learning engagement
Level of learner satisfaction
N
224
224
M
4.06
4.71
SD
1.37
0.47
Correlation coefficient
r = 0.75
(r = 0.434117, ρ < .01)
Result
The r-value was r = 0.75, ρ < .01 – so, it was found that correlations between learning engagement
and learning satisfaction were significant and substantially strong.
DISCUSSION
The dropout rate in MOOCs is high due to several reasons, of which one is the MOOC itself. Often,
MOOCs look like digital versions of existing distance learning material and practices. They do not
consider the different expectations of learners, different learning styles, differences in their personal
professional contexts, and differences in the digital learning environment. This study found that
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MOOC learners expect more autonomy and flexibility regarding what to learn, how to learn, and
when to learn. They expect the learning to be easy, with hassle-free, user-friendly technology. As per
the expectation of the learners, if there is enough choice in the learning activities and materials, it
would fulfill their interests and needs and would make learning meaningful. Moreover, MOOC
learners expect interactive, engaging and scenario-based course content in small chunks, along with
joyful micro-learning activities. Such content and learning activities and developmental assessment
strategies increase their learning engagement and facilitate their learning. Regarding MOOCs, we
must develop a learner-centered, experience-based collaborative learning design to make learners
satisfied with learning. Also, for doubt solving or clarification of misconceptions and learning
motivation, mindful expert intervention by course mentors is useful to sustain learners in the course.
This study supports previous research that has identified the central role of interactive curriculum
content in students’ learning engagements and their satisfaction.
CONCLUSION
This study examined learners’ expectations and factors that influence their learning engagement and
their satisfaction with MOOCs. After the data analysis and interpretations, the following conclusions
were drawn:
•
MOOC learners expect more flexibility and freedom in course structure, content, pedagogy
and assessment.
• MOOC learners expect that the use of ICT tools in MOOCs should be simple and userfriendly. Also, learners expect pre-orientation to LMSs and other ICT tools used in the course.
• Also, they expect scope for connectedness through discussion, sharing with fellow learners
and course mentors or facilitators.
• MOOC learners expect engaging, interactive course content in small chunks.
• MOOC learners expect a learner-centered, experience-based collaborative learning design.
• This study also found that learners’ learning engagement can be increased through joyful,
interactive course content and learning activities.
• Learners’ learning engagement and their learning satisfaction are positively correlated with
one another.
This study supports the central role of interactive course content in learners’ learning engagement and
their satisfaction.
RECOMMENDATIONS
The following recommendations are made:
•
•
•
•
•
•
Every MOOC developer should keep in mind learner expectations as MOOC design principles
at the designing and deployment stages.
MOOCs should maintain flexibility, freedom and learner centricity in their structure, content,
pedagogy, assessment and alignment through sufficient learning choice for learners, minimal
restrictions and prerequisites, formal and non-formal discussion forums, and collaborative
learning opportunities.
The use of ICT tools in MOOCs should be simple and user-friendly.
Every MOOC should offer technical support through LMS and ICT orientation modules as
pre-course activities.
This study also suggests that providing more engaging and interactive course content can increase learning engagement and the overall satisfaction of learners.
MOOCs should provide mindful expert intervention by course mentors for doubt solving or
clarification of misconceptions and learning motivation.
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NOMSA Open Up and Connect 2021
•
MOOCs should use continuous developmental assessment through quizzes, field-based assignments, learning activities, peer assessment, et cetera, instead of end-of-course exams or
tests.
Acknowledgements
I am extremely grateful to the UNESCO-UNEVOC, Boon Germany, for their financial support under
the first UNESCO-UNEVOC OER grant programme 2020.
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Krippendorp, K. (2004). Content analysis: an introduction to its methodology. Sage.
Kumar, P., & Kumar, N. (2020). A study of learner’s satisfaction from MOOCs through a mediation
model. Procedia Computer Science, 173(July), 354–363.
https://doi.org/10.1016/j.procs.2020.06.041
M. Liu, J. Kang & E. McKelroy (2015) Examining learners’ perspective of taking a MOOC:
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http://dx.doi.org/10.1080/09523987.2015.1053289
Macleod, H., Haywood, J., Woodgate, A., & Alkhatnai, M. (2014). Emerging patterns in
MOOC's: Learners, course designs and directions. Tech Trends, 56-63.
McAuley, A., Stewart, B., Siemens, G., & Cormier, D. (2010). The MOOC model for digital
practice. Retrieved from http://www.elearnspace.org/Articles/MOOC_Final.pdf
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Rob Firmin, Eva Schiorring, John Whitmer, Terrence Willett, Elaine D. Collins & Sutee
Sujitparapitaya (2014) Case study: using MOOCs for conventional college coursework,
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UGC. (2020). Blended mode of teaching and learning: concept note
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FLIPPED-CLASSROOM APPROACH IN THE DIGITAL POSTCOVID-19 ERA: AN EFL BLENDED LEARNING SCENARIO
THAT PROMOTES HEALTHY EATING HABITS
Athanasia Kakali
Junior High School of Dionysos, Attica, Athens, Greece (prima25vera@yahoo.gr)
Abstract
The COVID-19 crisis has had a substantial effect on teenagers’ dietary profiles, since adolescents
are prone to acquiring unhealthy eating habits that can further lead to diseases, such as obesity and
diabetes (Ruiz-Roso et al., 2020). The main objective of this study is to address this problem through
formal education in an EFL context. The flipped-classroom approach is proposed with the aim to
promote healthy eating habits in the post-COVID era. First, the key concept of flipped classroom is
elucidated. The study builds on previous research, published in relevant conferences and journals, on
the flipped-classroom approach and its impact. The next part of the study focuses on a blendedlearning scenario that favors a flipped classroom and is developed to satisfy students’ needs. This
scenario fosters 21st-century skills (critical thinking, collaboration, communication, and creativity)
by exploiting technology and a wide range of Web 2.0 tools. It consists of three phases. Initially,
students access new knowledge while studying nutrition vocabulary in an asynchronous mode (Phase
I). Then they deal synchronously with tasks that provide practice and consolidation of the new
knowledge (Phase II). Not only do they reflect on teenagers’ eating disorders, giving advice, but they
work in teams to create healthy menus according to the needs of certain teenagers. The scenario
culminates asynchronously (Phase III). In the last phase, students undertake tasks and writing
assignments to apply the newly acquired knowledge. They come up with their own ideal healthy menu
and then evaluate the whole learning process. Finally, the article concludes by suggesting that
teachers should move beyond traditional teaching practices, integrating the flipped-classroom
approach into the EFL classroom to adapt to the needs of the constantly changing 21st century and
reap rewards.
INTRODUCTION
Technological advances have an impact on teaching, since they bring about new methodological
approaches that revolutionize traditional instruction (Gómez-García et al., 2020). Teaching delivery
modes now range from face-to-face to virtual and blended ones. Teaching has been traditionally
delivered through the face-to-face mode, whereas the virtual classroom environment is a totally
opposite medium of delivery. Blended teaching is the approach that combines both modes of delivery
– face to face and virtual (Slomanson, 2014). Prior to the COVID-19 pandemic, secondary school
teachers in Greece used to have all their classes face to face and hardly ever delivered lessons in a
blended mode. During the pandemic, teachers across Europe undertook the hard task of using distance
learning to provide support to teenagers who underwent difficulties and had to deal with the
management of their own learning and cope with feelings of anxiety in the COVID-19 environment
(Katić et al., 2021).
The teacher decided to integrate a pedagogical approach of blended learning in her EFL teaching
practices based on the encouraging results of relevant research worldwide. In more concrete terms, a
considerable number of empirical studies revealed that learners’ performance in online teaching
environments can outweigh the performance of peers who are taught face to face only (Means et al.,
2010). Besides, the teacher sought to motivate learners through innovation. The need for teaching
English in an innovative way by exploiting Web 2.0 tools and integrating a flipped classroom is a
21st-century demand (Anwar, 2020).
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In addition, the teacher used the particular scenario as a means of intervention, supporting teenagers
and promoting healthy eating patterns. Relevant studies conducted in Europe during school closure
reported a correlation between psychiatric disorders, such as increased anxiety levels and social
isolation (Katić et al., 2021). Adolescents’ dietary profiles have been influenced by confinement due
to the pandemic. Teenagers are prone to acquiring poor eating habits, especially after the outbreak of
the pandemic, which caused tremendous changes in everyday practices (Gómez-García et al., 2020).
Adolescence is a crucial stage in one’s life, as it signifies the transition from childhood to adulthood
(Gómez-García et al., 2020). Healthy eating is crucial and protects against the acquisition of several
diseases, such as obesity, diabetes, and cardiovascular concerns (Gómez-García et al., 2020).
Confinement is associated with less physical activity and changes in daily life and eating routines
(Gómez-García et al., 2020). In the post-COVID era, adolescents still experience the consequences
of the confinement and live under the anxiety of a new outbreak of the pandemic. Consequently, the
teacher is implementing the current scenario to promote healthy eating habits among adolescents and
prevent eating disorders deriving from increased levels of stress in the post-COVID-19 era.
LITERATURE REVIEW
Flipped-classroom approach
The flipped classroom – also called the inverted classroom – has been very popular recently in both
K-12 and higher education (Milman, 2014). The flipped-classroom approach is an innovative model
of teaching that has been exploited extensively recently (Sohrabi & Iraj, 2016). It is widely recognized
as one of the most effective approaches within the EFL educational community (Al-Naabi, 2020). It
is a type of blended learning instruction where learners acquire new knowledge online through videorecorded lessons (Milman, 2014; Nwosisi et al., 2016). Traditionally, learners are expected to study
and do their homework at home (Nwosisi et al., 2016). In this method, there is a shift in the
implementation mode regarding teaching in various phases. Traditional class time activities, such as
presentation of new knowledge, are implemented at home, whereas homework and projects are
completed during class time (Nwosisi et al., 2016; Sohrabi & Iraj, 2016). Thus, in the flipped
classroom, teacher time is allocated in a different way. Students do not struggle at home to get work
done by themselves (Nwosisi et al., 2016). Teachers devote classroom time, offering help to learners
who need it to complete tasks successfully (Nwosisi et al., 2016). This instructional strategy also
involves formative and summative assessment activities (Milman, 2014). This approach gained
popularity, as it promotes student-centered learning. That is, in the flipped classroom, there is a shift
of focus from educators to learners who become responsible for their own learning (Sohrabi & Iraj,
2016). Teachers act mainly as facilitators of the learning process rather than instructors of the
traditional teaching environment (Sohrabi & Iraj, 2016; Anwar, 2020). Therefore, learning is regarded
as part of a constructive process, where learners take steps to construct their knowledge (Sohrabi &
Iraj, 2016).
Therefore, the flipped-classroom approach is not merely a lecture delivered online (Slomanson,
2014). Students become responsible for their own learning in a student-centered environment. That
is, they can have access to additional teaching material, or they may use differentiated educational
technologies compared to the ones chosen by the teacher; they can ignore some elements provided
by the educator and take benefit by combining activities in a unique, individualized way (Ritella &
Loperfido, 2021). Technology tools provide additional resources that explain students’ tasks step by
step, or offer solutions to common problems that arise in a particular learning context (Nwosisi et al.,
2016). Instructors may exploit advanced learning management systems (LMSs), such as Moodle and
Blackboard, to aid learners to interact with each other before the class about the content of the videos
uploaded by the teacher (Al-Naabi, 2020).
Regarding the use of the flipped classroom, this approach can be employed by instructors to introduce
a new topic and for remedial instruction as well (Nwosisi et al., 2016). Even though the flipped
classroom supports procedural knowledge the best, the other three types of knowledge according to
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Bloom’s taxonomy – that is, factual, conceptual, and metacognitive – can also be taught utilizing this
approach (Milman, 2014). Although the flipped classroom has been mainly used in physical sciences,
it recently attracted the attention of educators from all disciplines (Ozdamli & Aşıksoy, 2016).
Nutritional education is one field in which the flipped-classroom approach can be successfully
implemented. Bearing in mind that the flipped classroom promotes learner autonomy, this teaching
method can be considered appropriate for addressing effectively nutritional habits of teenagers in the
post-COVID-19 era. That is, the promotion of learner autonomy through a flipped classroom can help
learners understand better the importance of a balanced diet and become more responsible towards
their own eating routines, which may lead to a healthy lifestyle (Gómez-García et al., 2020). Thus,
teenagers can benefit in this regard and avoid the bad eating habits acquired during the quarantine.
As a result, nutritional education can confront teenagers’ risk of obesity, sedentarism and eating
disorders, such as anorexia nervosa, bulimia, and compulsive eating. The effectiveness of the flippedclassroom approach in nutritional education has been confirmed by several relevant studies (GómezGarcía et al., 2020). In general, nutritional education should be incorporated into the curriculum
through technology so that learners receive knowledge that can be applied in their everyday lives in
an attractive and dynamic way (Gómez-García et al., 2020).
Even when a flipped classroom is partly employed in classroom practices, the educational profit can
be considerable. A study on college students revealed that flipping the content of a course for 30%
can aid learners, since it facilitates student-to-student as well as student-to-teacher interaction. Thus,
this approach is considered effective, since it yields better learning results (Nwosisi et al., 2016).
Another study on EFL learners showed that learners were able to understand and use English grammar
more effectively (Al-Naabi, 2020), whereas a study on Saudi Arabian EFL students indicated
improvement in the skill of speaking (Al-Ghamdi & Al-Bargi, 2017). Similarly, a study on Indonesian
EFL learners classified benefits of using a flipped classroom into three main categories: providing
flexibility; encouraging discussions among students; and enhancing learner readiness (Lestari &
Sunadri, 2021). According to recent research, a flipped classroom also yields satisfactory learning
outcomes in remote instruction (Heiss & Oxley, 2021).
Despite the positive impact of the flipped-classroom approach, negative aspects can also arise. First,
learners may lack motivation in the beginning and come to lessons unprepared (Ozdamli & Aşıksoy,
2016). Moreover, some teachers may be discouraged from using flipped-classroom approaches, since
content creation required in blended learning can be a time-consuming process (Heiss & Oxley, 2021).
Creating and integrating class activities in the flipped-classroom approach can also be difficult
(Ozdamli & Aşıksoy, 2016). However, material can be prepared by several instructors and once
prepared, it can be shared and used by all instructors, making preparation for future delivery of flipped
classes less time-consuming (Heiss & Oxley, 2021). A last negative aspect that must be taken into
consideration is related to technology. Access to technology equipment can be a problem among
remote-area students or those from a low-income background (Anwar, 2020).
Twenty-first-century skills
It is imperative for the educators to use innovative strategies and modern learning technologies to
infuse cognitive and social skills in the acquisition of knowledge and reinforce student participation
(Alismail & McGuire, 2015). Incorporating 21st-century skills in schools requires meticulous
planning (Erdem, 2019). Teachers, through their work, form part of this planning. In this sense, they
take up the important role of aiding students to develop 21st-century skills through practices that
empower students and strengthen their abilities (Alismail & McGuire, 2015).
Problem-based learning is an educational approach that boosts both knowledge acquisition and
growth of 21st-century skills that bring students in contact with real life (Alismail & McGuire, 2015).
In this approach, students raise their concerns and discuss subjects related to the real world. Moreover,
when students are asked to find a proper solution, they deal with problems by investigating, providing
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explanations, coming up with ideas, analyzing data, and making evaluations. At the same time,
students enhance their participation in class and exercise critical thinking using higher-order thinking
patterns to solve problems. Lastly, through critical thinking, students learn to overcome thinking
obstacles and obtain 21st-century skills (Alismail & McGuire, 2015).
Another core element of 21st-century skills is co-operative learning. According to this approach,
students are divided into different teams that vary in interests and capabilities. Co-operation makes
students more creative, since all student skills and talents are combined in a single team with the
objective to reach the desirable goal. Consequently, co-operation enhances student motivation. Cooperative learning is encouraged through projects, problem-solving situations and tasks based in
inquiry learning (Alismail & McGuire, 2015).
Finally, technology plays a significant role in 21st-century skills development. First, it supports
problem-solving, critical thinking and co-operative learning and strengthens student motivation.
WebQuests, Wikis, Google sites, digital storytelling, blogs, and e-portfolios are some indicative
technological tools. Furthermore, multimedia tools broaden deeper understanding and promote
higher-order thinking skills that lead to successful activity completion. Technology helps students
come closer to information and knowledge in an autonomous way. Moreover, technology facilitates
co-operation, dissemination of information, organization of ideas through projects, or internet
research. Thus, technology can prepare learners to learn how to collect information deriving from a
wide range of internet resources (Alismail & McGuire, 2015).
LEARNING SCENARIO
The current learning scenario focuses on teenagers and was created to help them cope with a common
problem they shared – the changes that the COVID-19 crisis brought about in their lives and
nutritional habits. Indisputably, adolescents’ dietary routines changed during the pandemic; the
acquisition of new eating habits with higher sugar consumption due to anxiety and boredom caused
by confinement can lead to health issues in the near future (Ruiz-Roso et al., 2020). Thus, the current
scenario sought to act as an intervention to motivate students curb unhealthy eating habits. Recent
studies proved valuable to learning that is supported with meaningful activities developed on purpose,
such as scenarios focusing on everyday life (Semilarski et al., 2021).
Target group profile
This learning scenario is addressed to all teenagers globally who, due to the COVID-19 crisis, have
acquired unhealthy eating habits. Currently, it is being implemented and presented to 60 Greek
students at the Junior High School of Dionysos in the northern suburbs of Athens. Most students have
a good socio-economic background. The scenario is implemented through blended learning via
synchronous and asynchronous teaching sessions that favor the flipped-classroom approach.
The scenario is interdisciplinary and combines the teaching of English, ICT and Home Economics.
According to the Common European Framework of Reference (CEFR) for languages, learners are
expected to be independent users of English Threshold B1 level (Council of Europe, 2001). ICT
competence and prior use of Web 2.0 tools are also prerequisites for a better learning experience.
Digital literacies are also important on the part of the teacher who undertakes the scenario’s
implementation. Moreover, students must have some prior experience in blended learning scenarios.
Otherwise, the teacher should devote some time to initiate students into similar activities.
The scenario covers approximately 90 minutes of teaching and consists of three phases:
•
•
•
Phase I: Non-synchronous: Students access new knowledge and study (20΄)
Phase II: Synchronous: New knowledge consolidation activities (40΄)
Phase III: Non-synchronous: Acquired knowledge application and evaluation stage (30΄).
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Aim
Teenagers are guided to understand and value the importance of following a healthy diet. As a result,
they are expected to acquire a healthy lifestyle that can prevent diseases related to bad nutrition, such
as diabetes and obesity. At the same time, the scenario aspires to change in a significant positive way
learners’ perceptions of self-efficacy towards 21st-century skills.
More specifically, by the end of the learning scenario students are expected to:
•
•
•
•
•
•
cope with post-COVID-19 feelings of anxiety that can lead to eating disorders;
acquire knowledge related to nutrition (healthy diet, junk food, etc.);
distinguish between healthy and unhealthy food;
provide advice on a healthy diet;
design a healthy diet menu;
practice 21st-century skills, namely creativity, critical thinking, co-operation, and new literacies.
Phase I
The first part of the scenario (20΄) is delivered asynchronously. The teacher chooses to use the learning
management system (LMS) of open e-class, because it is an open-source software that is distributed
for free. The teacher devotes approximately 1–2 hours to organize the lesson in the open e-class. They
exploit the glossary tool to introduce vocabulary related to the thematic field of nutrition and eating
disorders. They upload a text about Teen Eating Disorders and the link of a short video about Teens’
Nutrition and create an exercise to check comprehension. Lastly, the teacher activates the forum tool
where students are asked to upload vocabulary related to nutrition, the thematic core of the scenario.
The teacher uses the tool announcements to inform students about the learning goals and the lesson
content and to explain the learning steps students must take before the synchronous meeting of Phase
II. To cater for all learning styles, the teacher uses the Screencast-o-Matic Web 2.0 screen recorder
tool to create a short video with the learning goals and the lesson content. They record their voice on
relevant PowerPoint slides. Learners appreciate listening to their teacher’s voice and develop a sense
of closeness and greater intimacy to each other despite the lesson’s distance feature. Later, the teacher
uploads the video in the open e-class using the multimedia tool.
Learners visit Open e-Class, read the announcement and follow the guidelines. First, they study the
glossary on the thematic field of nutrition (5΄). Then, they read the relevant text, watch the video and
complete the closed-type activity (multiple choice, true–false, matching) (10΄). After completing the
task, students receive immediate feedback of their progress and use the forum tool to upload new
vocabulary (5΄).
Phase II
The second part of the scenario takes place synchronously using the web-conferencing tool of Webex.
The teacher welcomes students in the synchronous lesson. The teacher presents the lesson’s goals,
making a connection between the asynchronous Phase I and the current one. The tool known as
Polling of Webex is used to check vocabulary comprehension and prepare learners for the activities
to follow. Students answer the Polling questions and submit their answers. The teacher provides
feedback based on students’ answers. After the Polling activity, the teacher initiates students in a
skimming and scanning activity by sharing a new text and asks them to use the annotate tool to mark
the answer on the following questions that are delivered orally:
•
•
•
•
How important is nutrition?
What is a balanced diet?
Which What are the common types of eating disorders?
Which What is the best advice for having a healthy diet?
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Then, the teacher presents the profiles and nutritional habits of five teenagers and asks students to use
the chat to report any possible eating disorders accompanied by a piece of advice to the teenager
regarding their eating habits. The next activity is a collaborative one and focuses on teenagers’ healthy
diet. The teacher uses the breakout session tool and divides students randomly into teams of four to
five. Then, the teacher exploits the broadcast message tool and sends a different teenager’s profile to
each team, asking them to prepare a healthy menu that caters for the needs of the particular teenager.
The teacher acts as a facilitator of the learning process. They enter all team rooms one by one to make
sure everything is on the right track. They offer their support when asked. Students collaborate with
each other and keep notes to come up with the proper healthy diet suitable for the teenager’s profile
they have been given. They take up different roles and decide on the person who will undertake the
task to present the menu in the plenary. Presentation takes place, and the rest of the teams use chat to
comment, make additions or express disagreement with something (peer feedback). The teacher also
provides feedback.
Phase III
Phase III is delivered asynchronously (30΄). Learning takes place through new knowledge
consolidation and application, reflection and assessment. The teacher exploits open class tool
exercises to create a short activity of summative assessment that students access and submit within
the predefined time limits. Alternatively, the teacher can use the ready-made activities of Web 2.0
tools Quizizz and Liveworksheets for formative assessment.
Then, the teacher uses the tool assignment to ask students to hand in an assignment. They must
describe the ideal healthy diet that caters to their own profiles, justifying their answers. Students
upload their assignments, and the teacher provides feedback. Last, the students consider the teacher’s
feedback, make the last modifications in their assignments, and keep them in their portfolios in either
a digital or print-out form.
CONCLUSION AND FURTHER SUGGESTIONS
Undoubtedly, traditional instruction is not enough to keep learners stimulated and meet the
instructional demands of the post-COVID-19 era. Therefore, teaching should be adapted to the needs
of the 21st century. Flipped classroom is an approach that promotes all 21st-century skills – that is,
creativity, critical thinking, communication, and technology. Considering all of the above, teachers
should move beyond conventional instruction and integrate the flipped classroom into their teaching
practices to help learners benefit and cope with the anxiety caused by the pandemic.
Flipped-classroom integration into the curriculum can yield promising results and be challenging for
teachers worldwide. For the effective incorporation of flipped learning, teachers must be digitally
competent. Teachers’ technological competence is a prerequisite for the efficient integration of flipped
classroom into the curriculum (Al-Ghamdi & Al-Bargi, 2017). Recent research claims that teachers
who are highly motivated to use technology in their instructional practices tend to exploit the flipped
classroom approach widely (Ozdamli & Aşıksoy, 2016). Moreover, teachers who employ flipped
classroom in their teaching practices must acquire special skills in designing materials (Ozdamli &
Aşıksoy, 2016). Recently, there has been an increase in flipped-classroom approach research
(Ozdamli & Aşıksoy, 2016). Future research can go even further and investigate the correlation
between learners’ level of linguistic competence, age and gender and the flipped-classroom approach
(Al-Naabi, 2020).
REFERENCES
Al-Ghamdi, M., & Al-Bargi, A. (2017). Exploring the application of flipped classrooms on
EFL Saudi students' speaking skill. International Journal of Linguistics, 9(4), 28–46.
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Alismail, H.A., & McGuire, P. (2015). 21st century standards and curriculum: Current research and
practice. Journal of Education and Practice, 6(6), 150–154.
Al-Naabi, I.S. (2020). Is it worth flipping? The impact of flipped classroom on EFL students'
grammar. English Language Teaching, 13(6), 144–155.
Anwar, Ch. (2020). Flipped Classroom and Digital Literacy in EFL Learning. In N.F. Sudaryanto &
O. Zefki (Eds.) Bulir-bulir kajian linguistik terapan (pp.11–23). Indonesia,Yogyakarta: CV
MARKUMI.
Council of Europe. (2001). Common European framework for languages: Learning, teaching,
assessment. Cambridge: CUP.
Erdem, C. (2019). Introduction to 21st century skills and education. In C. Erdem, H. Bağcı & M.
Koçyiğit (Eds.) 21st century skills and education (pp. 1–14). Cambridge Scholars Publishing.
Gómez-García, G., Marín-Marín, J. A., Romero-Rodríguez, J.-M., Ramos Navas-Parejo, M., &
Rodríguez Jiménez, C. (2020). Effect of the flipped classroom and gamification methods in
the development of a didactic unit on healthy habits and diet in primary education. Nutrients,
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Heiss, E.M, & Oxley, S.P. (2021). Implementing a flipped classroom approach in remote
instruction. Analytical and Bioanalytical Chemistry, 413(5), 1245–1250.
Kakali, A. (2021). To eat or not to eat healthy! Retrieved December 5, 2021, from
https://demo.openeclass.org/courses/DEMO-A1977/
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COVID-19 pandemic: a comparison between European countries. Education Sciences, 11(10),
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Lestari, I.W., & Sundari, A. (2021). Indonesian EFL students’ experiences in a flipped classroom.
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Practices in Online Learning: A Meta-analysis and Review of Online Learning Studies. U.S.
Department of Education: Washington, D.C.
Milman, N.B. (2014) The flipped classroom strategy: What is it and how can it best be used?
Distance Learning, 11(4), 9–11.
Nwosisi, Ch., Ferreira, A., Rosenberg, W., & Walsh, K. (2016). A study of the flipped classroom and
its effectiveness in flipping thirty percent of the course content. International Journal of
Information and Education Technology, 6(5), 348–351.
Ozdamli, F., & Aşıksoy, G. (2016). Flipped classroom approach. World Journal on Educational
Technology, 8(2), 98–105.
Ritella, G., & Loperfido, F. F. (2021). Students’ self-organization of the learning environment
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Ruiz-Roso, M. B., de Carvalho Padilha, P., Mantilla-Escalante, D. C., Ulloa, N., Brun, P., AcevedoCorrea, D., Arantes Ferreira Peres, W., et al. (2020). Covid-19 Confinement and changes of
adolescent’s dietary trends in Italy, Spain, Chile, Colombia and Brazil. Nutrients, 12(6), 1807.
Semilarski, H., Soobard, R., & Rannikmäe, M. (2021). Promoting students’ perceived self-efficacy
towards 21st Century Skills through everyday life-related scenarios. Education Sciences,
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514–524.
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THE RELATIONSHIP BETWEEN ONLINE PROFESSIONAL
LEARNING COMMUNITIES AND TEACHING PRESENCE
Vusi Maseko
South West Gauteng College (masekovj@swgc.co.za)
Abstract
COVID-19 shut down most schools and colleges globally, but collaboration among educators
persisted. Whilst COVID protocols ruled out physical meetings among teachers, collaboration has
gone online. The objective of this research was to offer a comprehensive yet concise assessment of
the link between teaching presence (TP) and online professional learning communities (OPLCs). The
survey used in this study was based on a four-point Likert scale, and respondents were asked to pick
one option that best matched their point of view. This study also used factor analysis, correlations,
regressions and structured equation modelling (SEM) to establish the relationship between TP and
OPLCs. There were 112 respondents from diverse countries of origin. There is a strong correlation
between TP and OPLCs; in fact, TP significantly predicted OPLCs. SEM was used to test and evaluate
multivariate causal relationships. More respondents were required to fully establish the full extent of
the relationship between TP and OPLCs. Educator innovations have implications for everyday
practice. Comprehending the multidimensional relationship would assist educators to ensure that
teaching and learning continue even in COVID times. Furthermore, decisions that affected working
arrangements taken by management modulated the respondents’ perceptions. These results suggest
that teaching presence is one of the most important factors in building community for online learning
to occur.
INTRODUCTION
The COVID-19 pandemic forced all Technical and Vocational Education and Training (TVET)
colleges in South Africa to close abruptly. Owing to COVID-19’s disruptive nature, educators could
not meet and discuss students’ educational challenges. Implementing the social distancing protocols
forced educators to stop large group teaching and even halted peer collaborations, resulting in
lecturers losing hundreds of collaborative learning hours. Continuing professional development
(CPD) for educators through professional learning communities (PLCs) is a well-researched and wellestablished technique that transforms much-needed training
(Brown et al., 2018). PLCs support
continuous, job-embedded learning by bringing together a group of lecturers who often interact to
ensure continued school success
(Brown et al., 2018). The PLC group gathers (Brown, Horn, &
King) to share and critically analyse their practices and learn new and more effective techniques to
improve learning and networking with other educators. However, COVID-19 stopped all
collaborative activity despite it being an excellent collaborative period. Because of COVID-19,
educators and students must start learning in a new normal. Educators should start using online
professional learning communities (OPLCs) to transform learning from brick and mortar to clicks
using OPLCs.
The role of the teacher in an online learning context is to create an effective online educational
community that involves three critical components: cognitive presence, social presence, and teaching
presence (Garrison et al., 2000). This study focused on teaching presence. The term “teaching
presence” refers to the effort made to teach both before and during the course. It encompasses all
aspects of course design and preparation, as well as hands-on instruction in leading and assisting
learners during the course’s delivery. The presence of the instructor is evident in the course materials,
which include the syllabus, assignments, readings and conversations. One’s teaching presence is
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shown via all one does to lead, encourage and influence one’s students’ learning experiences. A
teaching presence creates clear expectations and provides beneficial guidance.
The professional learning community (PLC) has been considered as a strong professional
development strategy and a potent instrument for school reform and continual improvement. The
notion of continual improvement is a crucial principle held by members of a PLC. When one uses
information communication technologies to host a PLC online, it becomes an online PLC (OPLC).
The OPLC broadens knowledge by using computer-mediated communication and global resources.
This kind of community also allows individuals to make, acquire and engage with knowledge and
ideas provided by others in ways that are appropriate for their needs. As a result, we can define OPLCs
as a group of autonomous, independent individuals who are drawn together by shared values, goals
and collaboration using the Internet as a medium.
OPLCs are also based on Hord’s (1997) PLC model with the following: (1) a shared mission, vision,
values, goals (SM); (2) collaborative teams focused on learning (CT); (3) collective inquiry (CI); (4)
action oriented (AO); (5) commitment to continuous improvement (CC); and (6) results orientation
(RO).
METHODOLOGY
For this study, an e-survey was used to ascertain respondents’ opinions by eliciting their level of
agreement or disagreement with a specific issue or statement. Frequencies and percentages were
calculated for gender, qualification, status, country, age range, work location, designation, race,
working arrangements, and hierarchical level. Summary statistics were calculated for the six
components of the OPLC to confirm the existence of a PLC.
A Pearson correlation analysis was conducted among innovation in teaching and learning (ITL),
professional learning communities (PLC) and teaching presence (TP). Cohen’s standard was used to
measure the strength of the relationships, where coefficients between .10 and .29 reveal a little impact
size, coefficients between .30 and .49 represent a moderate effect size, and coefficients over .50 imply
a large effect size (Cohen, 1988). Next, a linear regression analysis was done to see whether TP and
ITL significantly predicted PLC. Finally, an SEM model was conducted to evaluate whether the latent
variables (OPLC, TP, and ITL) adequately describe the data. Maximum likelihood estimate was done
to determine the standard errors for the parameter estimations.
RESULTS
Bar plot of gender:
Figure 1: Gender
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The most frequently observed category of gender was female (n = 64.57%). Most respondents had a
post-matric qualification (n = 58.52%) and were employed (n = 86.77%). The vast majority of the
respondents were based in South Africa (n = 74.66%). The millennials age range (26–44) (n =
51.46%) had the highest number of respondents. Most respondents were college-based (n = 63.56%),
of whom lecturers were in the majority (n = 40.36%). The sample had more people of African descent
(n = 64.57%). Working arrangements at most workplaces were on a rotational basis (n = 44.39%).
They were mostly frontline workers like lecturers or class teachers (n = 51.46%). Respondents with
a post-matric qualification (n = 58.52%) were in the majority of the sample.
Table 1: OPLC summary statistics table for interval and ratio variables
M
SD
n
SEM
Min
Max
Skewness
Kurtosis
SM
2.87
0.72
112
0.07
1.00
4.00
-0.32
-0.39
CT
2.87
0.76
112
0.07
1.00
4.00
-0.35
-0.50
CI
2.91
0.67
112
0.06
1.00
4.00
-0.50
-0.10
AO
3.12
0.74
112
0.07
1.00
4.00
-0.86
0.45
CC
3.00
0.75
112
0.07
1.00
4.00
-0.68
0.02
RO
3.07
0.73
112
0.07
1.00
4.00
-0.74
0.32
Variable
Note. ‘-’ indicates the statistic is undefined due to constant data or an insufficient sample size.
Assigning Likert scale values to Dufour’s Professional Learning Community Continuum Rubric
(2008) yielded table 2.
Table 2: PLC Continuum
Developmental Stage
Mean
SM
CT
CI
AO
CC
RO
Average
Pre-initiation
1.01 – 1.99
Initiation
2.00 – 2.49
2,973
Developing
2.50 – 2.99
2.87
2.87
2.91
Sustaining
3.00 – 3.99
3.12
3.00
3.07
An SM value of 2.87 indicates that teachers were aware of the learning outcomes expected of their
students. They developed strategies to evaluate student mastery of these outcomes, monitor the results
and attempt to intervene with non-learners. A CT value of 2.87 is indicative of the fact that
periodically, teachers met in work groups to complete tasks such as reviewing intended outcomes and
coordinating calendars. Furthermore, having a CI value of 2.91 means that individual teachers and
teaching teams collected data that enabled the identification and monitoring of individual and team
objectives. An AO mean of 3.12 implies that action research topics were derived from the school’s
shared vision and objectives. Staff members viewed action research as an integral part of their
professional obligations. Furthermore, as educators attempted to learn from the research of their
colleagues, there were frequent discussions regarding the implications of the findings. The CC mean
of 3.00 shows that all educators in the school participated in a continuous cycle of systematic data
collection and analysis to identify gaps between actual and desired results, goal setting to reduce the
gaps, strategy development to achieve the goals, and monitoring of improvement indicators. A mean
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of RO above 3.00 implies that the teams of educators were hungry for results data. They collected
pertinent data and used the data to identify improvement goals and track progress towards those goals.
Based on the proceeding, we can therefore conclude that a critical mass of educators supported
OPLCs. To implement OPLCs, educators are beginning to modify their thinking and behaviour. To
align with OPLCs, structural adjustments are being made.
The outcome of the correlations was assessed using the Holm correction to compensate for multiple
comparison tests depending on an alpha value of 0.05. A significant positive correlation was
discovered between IT and PLC (r = 0.72, p < .001, 95% CI = [0.61, 0.80]). The correlation value
between IT and PLC was 0.72, suggesting a large impact size. This correlation implies that as IT
increased, PLC tended to increase. A significant positive correlation was established between IT and
TP (r = 0.58, p < .001, 95% CI = [0.44, 0.69]). The correlation coefficient between IT and TP was
0.58, also indicating a large effect size. Accordingly, this correlation indicates that as IT increases, TP
tends to increase. A significant positive correlation was observed between PLC and TP (r = 0.75, p <
.001, 95% CI = [0.66, 0.82]). The correlation coefficient between PLC and TP was 0.75, indicative
of a large effect size, indicating that TP tends to increase as PLC increases. Table 3 presents the results
of the correlations.
Table 3: Pearson correlation results among IT, PLC and TP
Combination
r
IT-PLC
0.72
IT-TP
0.58
PLC-TP
0.75
Note. p-values adjusted using the Holm correction.
95% CI
[0.61, 0.80]
[0.44, 0.69]
[0.66, 0.82]
n
112
112
112
p
< .001
< .001
< .001
The results of the linear regression model were significant – F(3,108) = 79.85, p < .001, R2 = 0.69 –
indicating that approximately 69% of the variance in PLC is explainable by TP and IT. TP
significantly predicted PLC, B = 0.59, t(108) = 3.58, p < .001. This indicates that on average, a oneunit increase of TP will increase the value of PLC by 0.59 units. IT significantly predicted PLC, B =
0.43, t(108) = 2.09, p = .039. This indicates that on average, a one-unit increase of IT will increase
the value of PLC by 0.43 units. The interaction between TP and IT did not have a significant effect
on PLC, B = -0.02, t(108) = -0.38, p = .705. Based on this sample, a one-unit increase in TP does not
significantly affect the relationship of PLC on IT. Table 4 summarises the results of the regression
model.
Table 4: Results for linear regression with TP, IT, and TP:IT predicting PLC
Variable
B
SE
95% CI
β
t
p
(Intercept)
0.11
0.50
[-0.89, 1.10]
0.00
0.21
.834
TP
0.59
0.16
[0.26, 0.91]
0.57
3.58
< .001
IT
0.43
0.20
[0.02, 0.83]
0.51
2.09
.039
-0.02
0.06
[-0.14, 0.10]
-0.13
-0.38
.705
TP:IT
Note. Results: F(3,108) = 79.85, p < .001, R2 = 0.69
Unstandardized Regression Equation: PLC = 0.11 + 0.59*TP + 0.43*IT - 0.02*TP:IT
The results of the linear regression model were significant – F(1,110) = 22.97, p < .001, R2 = 0.17 –
indicating that approximately 17% of the variance in PLC is explainable by those institutions that
have made the decision to go “online”. Online significantly predicted PLC, B = 0.28, t(110) = 4.79,
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p < .001. This indicates that on average, a one-unit increase of online will increase the value of PLC
by 0.28 units. Table 5 summarises the results of the regression model.
Table 5: Results for linear regression with online predicting PLC
Variable
(Intercept)
Online
B
2.22
0.28
SE
0.17
0.06
95% CI
[1.88, 2.55]
[0.16, 0.39]
β
0.00
0.42
t
13.20
4.79
p
< .001
< .001
Note. Results: F(1,110) = 22.97, p < .001, R2 = 0.17
Unstandardized Regression Equation: PLC = 2.22 + 0.28*Online
The results of the linear regression model were significant – F(2,109) = 7.58, p < .001, R2 = 0.12 –
indicating that approximately 12% of the variance in PLC is explainable by COVID-19 working
arrangements. The “I go to my institution on a rotational basis” category of COVID-19 work
arrangements did not significantly predict PLC, B = 0.10, t(109) = 0.75, p = .455. Based on this
sample, this suggests that moving from the “I work or study from Home” to “I go to my institution
on a rotational basis” category of COVID-19 work arrangements does not have a significant effect
on the mean of PLC. The “I am still on a normal shift as I used before COVID-19” category of
COVID-19 work arrangements significantly predicted PLC, B = -0.45, t(109) = -3.00, p = .003. Based
on this sample, this suggests that moving from the “I work or study from Home” to “I am still on a
normal shift as I used before COVID-19” category of COVID-19 working arrangements will decrease
the mean value of PLC by 0.45 units on average. Table 6 summarises the results of the regression
model.
Table 6: Results for linear regression with COVID-19 working arrangements predicting PLC
Variable
B
SE
95% CI
β
t
p
(Intercept)
3.05
0.10 [2.86, 3.25]
0.00
31.19 < .001
COVID-19, I go to my institution on a
[-0.17,
0.10
0.13
0.07
0.75
.455
rotational basis
0.37]
COVID-19 I am still on a normal shift as I
[-0.75, -0.45
0.15
-0.33
-3.00
.003
used before COVID-19
0.15]
Note. Results: F(2,109) = 7.58, p < .001, R2 = 0.12
Unstandardised regression equation: PLC = 3.05 + 0.10*COVID-19 I go to my institution on a rotational
basis - 0.45*COVID-19 I am still on a normal shift as I used before COVID-19
The results of the linear regression model were significant – F(1,110) = 5.61, p = .020, R2 = 0.05 –
indicating that approximately 5% of the variance in PLC is explainable by implemented online
learning. The “No” category of implemented online learning significantly predicted PLC, B = -0.39,
t(110) = -2.37, p = .020. Based on this sample, this suggests that moving from the “Yes” to “No”
category of implemented online learning will decrease the mean value of PLC by 0.39 units on
average. Table 7 summarises the results of the regression model.
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Table 7: Results for linear regression with implemented online learning predicting PLC ff
Variable
(Intercept)
Implemented online learning No
B
SE
95% CI
β
t
p
3.03
0.06
[2.91, 3.16]
0.00
46.71
< .001
-0.39
0.17
[-0.73, -0.06]
-0.22
-2.37
.020
Note. Results: F(1,110) = 5.61, p = .020, R2 = 0.05
Unstandardised regression equation: PLC = 3.03 - 0.39*implemented online learning “No”
First, the reliability of the analysis was tested based on the sample size used to construct the model.
Next, the results were evaluated using the Chi-square goodness of fit test and fit indices. Lastly, the
squared multiple correlations (R2) for each endogenous variable were examined. The correlations
between the latent variables are presented in table 8.
Table 8: Correlation table for the latent variables
Variable
OPLC
TP
ITL
OPLC
1.00
0.80
0.72
The node diagram is shown in figure 2.
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TP
-1.00
0.63
ITL
--1.00
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Figure 2: Node diagram for the SEM model
Evaluating sample size. Factor analysis requires a large sample size to construct repeatable and
reliable factors. A variety of authors suggest different benchmarks to determine sufficient sample size
for SEM. Some authors use benchmarks based on overall sample size. A common rule of thumb for
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determining sufficient sample size is 300 observations (Comrey & Lee, 2013; Tabachnick & Fidell,
2019). Other authors use the ratio N:q of the overall sample size to the number of free parameter
estimates (latent variable, indicator, variance, covariance or any regression estimates) included in the
model. Kline (2015) recommends that the N:q ratio should be about 20:1. Schreiber et al. (2006)
suggest that the consensus for a sufficient N:q ratio is 10:1. On the lower end of the ratio, Bentler and
Chou (1987) suggest that an acceptable N:q ratio is 5:1. The participant-to-item ratio for this analysis
was approximately 3:1, where the sample size was 112 and the number of variables included was 36.
Model fit. There are a variety of ways to measure if the SEM model adequately describes the data.
The Chi-square statistic is the most popular statistic used to measure-model fit. Besides the Chisquare statistic, fit indices are also used to help researchers determine if the factor analysis model fits
the data properly. Along with the Chi-square goodness of fit test, the following fit indices were used
to assess the model fit: root mean square error of approximation (RMSEA); comparative fit index
(CFI); Tucker-Lewis index (TLI); and standardised root mean square residual (SRMR).
Fit indices. The TLI was less than .95, TLI = 0.88, which is indicative of a poor model fit (Hopper,
Coughlan, & Mullen, 2008). The CFI was between .90 and .95, CFI = 0.90, suggesting that the model
is not mis- specified and the fit is acceptable (Hooper et al., 2008). The RMSEA index was greater
than .10, RMSEA = 0.13, 90% CI = [0.12, 0.15], which is indicative of a poor model fit (Hooper et
al., 2008). The SRMR was greater than .08, SRMR = 0.22, implying that the model fit the data poorly
(Hooper et al., 2008). The fit indices are presented in Table 9. To determine whether a model fits data,
researchers typically use CFI and TLI thresholds greater than 0.90 and RMSEA less than 0.08.
Goodness of fit test. A Chi-square goodness-of-fit test was conducted to determine if the SEM model
fit the data adequately. It is standard practice for SEM to include the Chi-square test. However, this
test is sensitive to sample size, which causes the test to almost always reject the null hypothesis and
indicate a poor model fit when the sample size is large (Hooper et al., 2008). The results of the Chisquare goodness-of-fit test were significant – χ2(84) = 253.29, p < .001 – suggesting that the model
did not adequately fit the data. However, the Chi-square model fit criterion is sensitive to sample size,
and as sample size increases (normally above 200), the Chi-square statistic indicates probability
values that are not statistically significant.
Table 9: Fit indices for the SEM model
NFI
TLI
CFI
RMSEA
0.86
0.88
0.90
0.13
Note. RMSEA 90% CI = [0.12, 0.15]; -- indicates that the statistic could not be calculated.
SRMR
0.22
Squared multiple correlations. The regressions in the model can be assessed by examining the R2
value of each endogenous variable. The R2 value identifies how much the regressions explain the
endogenous variable in the model. An R2 value ≤ .20 suggests the endogenous variable is not
adequately explained by the regression(s) in the model, and all regressions for that endogenous
variable should be considered for removal from the model (Hooper et al., 2008). There were no
endogenous variables with R2 values ≤ .20. The R2 values and the error variances for each
endogenous variable are presented in table 10.
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Table 10: Estimated error variances and R2 values for each endogenous variable in the SEM
model
Endogenous Variable
Standard Error
OPLC
SM
CT
CI
AO
CC
RO
CD
FD
DI
IT1
IT2
IT3
IT4
IT6
Note. -- indicates the statistic could not be calculated.
0.08
0.22
0.21
0.07
0.11
0.10
0.13
0.07
0.04
0.13
0.45
0.31
0.22
0.18
0.22
R2
0.72
0.56
0.59
0.84
0.79
0.83
0.76
0.82
0.92
0.70
0.54
0.61
0.75
0.70
0.71
DISCUSSION AND CONCLUSION
Typical of millennials’ intuitive knowledge of technology, there were more responses from them in
the sample. The regressions were examined based on an alpha value of 0.05. ITL significantly
predicted OPLC, B = 0.27, z = 3.90, p < .001, indicating a one-unit increase in ITL would increase
the expected value of OPLC by 0.27 units. TP significantly predicted OPLC, B = 0.54, z = 5.96, p <
.001, indicating a one-unit increase in TP would increase the expected value of OPLC by 0.54 units.
The PLC continuum rubric suggests that PLCs were formed online, meaning that online PLCs were
present in the sample. Regression analysis indicates that teaching presence significantly predicts the
existence of OPLCs. By utilising OPLCs, educators can learn how to utilise PLCs to enhance their
professional development. This result, therefore, suggests that educators can have their CPD online
during the COVID-19 pandemic.
The correlation between teaching presence and OPLCs was 0.75, implying a large effect size,
meaning the relationship between these bivariate variables is strong.
REFERENCES
Bentler, P., & Chou, C. (1987). Practical issues in structural modeling. Sociological Methods &
Research, 16(1), 78–117. https://doi.org/10.1177/0049124187016001004
Brown, B. D., Horn, R. S., & King, G. (2018). The effective implementation of professional
learning communities. Alabama Journal of Educational Leadership, 55–59.
Cohen, J. (1988). Statistical power analysis for the behavior sciences. West Publishing Company.
Comrey, A. L., & Lee, H. (2013). A first course in factor analysis. Psychology Press.
https://doi.org/10.4324/9781315827506
Garrison, D.R., Anderson,T., & Archer, W. (2000). Critical inquiry in a text-based environment:
Computer conferencing in higher education. The Internet and Higher Education 2(2–3): 87–105
Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: guidelines for
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determining the model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
Hord, S. M. (1997). Professional learning communities: Communities of
continuous inquiry and improvement. Austin, TX: Southwest Educational
Development Laboratory.
Kline, R. B. (2015). Principles and practices of structural equation modeling. Guilford
Publications.
Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural
equation modeling and confirmatory factor analysis results: A review. The Journal of
Educational Research, 99(6), 323–338.
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics. Pearson Education.
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TECHNICAL SUPPORT NEEDS OF DISTANCE STUDENTS TO
PARTICIPATE IN ONLINE COURSES AT THE CENTRE OF OPEN
AND LIFELONG LEARNING
Mildred Juliana Besser
Namibia University of Science and Technology (mbesser@nust.na)
Aletta Mweneni Hautemo
Namibia University of Science and Technology (ahautemo@nust.na)
Abstract
The premise of this study was to investigate the technical support needs of online students at the
Centre for Open and Lifelong Learning (COLL). The aim was to establish effective ways to resolve
the technical support needs of students and to enhance their optimal participation in online distance
education. A descriptive case study design was used for this investigation, which relied on a
quantitative research approach. Random sampling was used to recruit 60 online students, three online
instructors, and five student support officers (SSOs) as research participants. Data were collected
using questionnaires and were analysed thematically. The study found that sufficient technical
support is hampered by the absence of a technical support team to attend to technical issues on time.
A lack of an orientation course to introduce the students to the online platform crippled the students’
knowledge and skills to navigate and use the Moodle platform effectively. It is recommended that the
institution considers technical support training for both faculty and students and harnesses operative
communication channels between COLL and online students. Lastly, the provision of affordable and
easy payment structures for data and online devices can decrease the technical problems for online
students, as they create easy access to service and eliminate frustration posed by technology.
Keywords: constructivism, technical support, open and distance learning, cognitivism, online
learning
INTRODUCTION
The concept of traditional education has changed radically and as a result, the process of sitting in a
classroom and studying is not regarded as a sole learning option. The rise of internet technologies
emphasises the importance of online learning and the critical role it plays in people’s lives (Babson
Survey Research Group, 2020). Internet technologies make online learning and e-Learning a sensible
choice of learning, allowing people to study whenever and wherever they are. The use of different
technological tools, such as laptops, smartphones and the Internet, among others, influence the modes
of study in open and distance education (ODL). De Pryck et al. (2018) noted that information and
communication technologies (ICT) formed the basis of ODL systems, which emphasises that
technical support is an essential determining factor in online learning. Consequently, ODL institutions
should be realistic with the amount of support available for students and decide whether additional
technical support systems would be required to cope with the increased ICT burdens in education.
With the rapid growth in technology and ICT, which have become a part of everyday life, online
learning is emerging as a growing trend in Namibia.
The Centre for Open and Lifelong Learning (COLL) at the Namibia University of Science and
Technology provides learning to students who could not study full-degree programmes on a full-time
basis. Owing to the eruption of COVID-19, the mode of learning for all students at the centre moved
to online (hybrid for fewer courses, and full-fledged for many others), using the Moodle platform and
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virtual conferencing tools such as MS Teams. The main concern observed as a threat to successful
online learning has been the lack of technical support. Technical support becomes vital due to more
students partaking in online ODL education at the institution as all courses were converted to online.
Further, COLL has 10 regional centres equipped with a library and computer laboratories with
wireless internet facilities. However, students still find it hard to upload their assignments and struggle
to participate in online activities due to a lack of technical skills or sufficient technical assistance
provided by the institution.
Challenges have been observed regarding students’ accessibility to e-Learning. The latter is a paced
weekly way of studying cooperatively with the tutors and students, utilising a virtual classroom that
provides a variety of technology-enhanced learning tools, such as electronic text, images, animations,
streaming video, and audio. The reality of the matter is that students in Namibia struggle with poor
internet connectivity, expensive data, lack of electricity, low proficiency in technology, and
unavailability of study devices, among others. Kamati (2020, April 01) stated that the Students Union
of Namibia (SUN) requested Namibian universities to reconsider their decision to offer online
learning due to poor internet connectivity in villages and informal areas.
With the emergence of COVID-19 in early 2020, with the commencement of education, the National
Unity Democratic Organisation (Nudo) expressed their concern that Namibia was not equipped to
ensure that students all over the country would be able to enrol in online learning platforms or that
they would have the necessary devices and secure internet. They suggested that the infrastructure be
improved so that the entire country could access the Internet (Beyer, 2020). Wantulok (2015)
maintains that for students to survive online learning, they must know technology and get adequate
technical support. The success of any online course starts with students who can access the online
learning environment. A lack of access and unsolved technical support may lead to a dropout of
students or exclude students from online learning at COLL and they may become disappointed and
frustrated during their online studies. This study attempted to determine the importance of technical
support needs to ODL students due to the rapidly growing trend in online learning worldwide.
The following research questions guided the study:
•
•
•
What types of online technical support does COLL offer to online students?
What can COLL do to detect technology problems for online students?
How can COLL provide adequate technical support to online students?
THEORIES FOR DISTANCE EDUCATION
This section discusses two theories that could be used to assist with the design and implementation
of an effective online learning environment.
Constructivist theory
Constructivists view learning is a process in which the learner actively engages in new ideas through
collaborative grouping situations, and active participation of students in problem-solving and critical
thinking given authentic problems (Carwile, 2007; Lamon, 2020). Constructivism acknowledges the
impact of technology in online learning by emphasising the advantage of the technological tools
available to monitor students’ interaction and manage time wisely to overcome technical challenges
(Higley, 2018). The constructivist theory could be used to harness the effective use of ICT, depending
on greater access to information and communication to create an urge for technical support (Carwile,
2007). ICT helps more people to educate themselves and learn at a flexible time (Nawaz, 2010). Thus,
the success of online learning depends on the skills and quality of technical support to end-users.
Without proper technical support and maintenance of even the most current and sophisticated
hardware and software, the ability of teachers and students to access and use technology is severely
at risk (Valdez et al., 2004). From a constructivist view, online students can successfully collaborate
with others, consult with online instructors, and share knowledge resources if they have the know146
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how of technology. Critical to collaboration is an orientation to online courses and platforms.
UNESCO (2002) recommends that technical support should start with an orientation at the beginning
of the course. Estrada et al. (2013) posit that new student orientation programmes can reduce anxiety,
improve online class attendance, and social and online autonomy, which impact on successful online
learning and planning. Orientation is crucial for the smooth running of the course, as it introduces the
students to all collaboration tools to use in the learning management system (LMS).
Cognitivist theory
Alzahrani and Woollard (2013) explained that cognitive learning theories permit online students to
learn through interaction, construct knowledge and share knowledge-building experiences with the
online instructor. Students acquire knowledge and information through the cognitivist theory, which
facilitates the process of information acquisition (Kelly, 2012). Thus, the student actively seeks ways
to process the information received and relate it to the knowledge already stored in their memory.
Carwile (2007) posits that online students retain knowledge more effectively because of increased
engagement and collaboration. Owing to distance and time constraints, the online instructor finds it
challenging to observe how online students interact with the online learning environment. As a result,
course designers and online lecturers should tailor online content to meet online learners’ cognitive
abilities (Arshavskiy, 2018). Tinio (2002) emphasised that ICT has a remarkable impact on education,
as both online instructors and students attain and absorb knowledge; this calls for ICT to be included
as part of the curriculum to enhance the learning and teaching process. Raja and Nagasubramani
(2018) argued that a university or institution with improper ICT systems never grows in today’s
world; hence, using technology in teaching and learning processes is beneficial for the future learning
direction, since online learning is here to stay.
ICT NEEDED FOR TECHNICAL SUPPORT
It is vital to infuse technical support with online course development and facilitation to enable
students and online instructors to interact with ease. Technical teams can integrate practical
technology tools and resources to support interaction and information-sharing effectively. Research
shows that students perceive more significant social interaction when creating and sharing in-depth
messages (King, 2002). Technical support teams should be equipped with the necessary technical
knowledge to assist in developing online students’ critical thinking skills and to learn with technology
at their own pace (Hara et al., 2000). ICT provides powerful technology tools to support group work
and enables groups to share online information and suggestions to enhance collaborative teaching and
learning (Filipatali, 2013). Consequently, effective online learning requires appropriate ICT support
systems, such as infrastructure, hardware and software.
The integration of ICT as an instructional online learning tool in academic courses has escalated
rapidly (Becker, 2000), resulting in the continued use of Moodle as an LMS at COLL. Research shows
that Moodle as an LMS has a positive impact on online students’ performance. According to MartínBlas and Serrano-Fernández (2009), students who use Moodle obtain better results than those who
do not. King (2021) indicated that self-technical support assistance on Moodle is available through
the “Moodle Help for Students” and Moodle demo site. These sites are considered suitable for training
students on the use of Moodle. Unfortunately, many universities, like NUST, are unaware of the
support these Moodle sites provide.
Challenges in technical support
Nawaz and Khan (2012) argue that technical support is crucial for both the online instructor and the
online learner. Online instructors need technical support to ensure the availability of resources and
skills necessary for technology integration. They also need technical support to help them acquire the
knowledge and skills to fulfil their unique curriculum requirements. Below are some technical support
needs that challenge effective online learning.
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Inability to use the LMS
The proper functioning of ODL depends on a robust technical support system to manage technical
issues continually. According to Nawaz and Khan (2012), digital-age technology is changing fast.
Compatibility and flexibility to adapt to different devices, and platforms are essential issues in the
infrastructure of the online institution. They further argue that the reliability of equipment means that
technical support staff can spend less time on maintenance and more time on training teachers and
students in the use of the software. Resistance to change makes it difficult for online students to adapt
to the online environment. According to Kumar (2015), students with a traditional mindset find it
challenging to adapt; however, they need to accept the new learning circumstances. Students struggle
to upload assignments and do not know the difference between a discussion and a chat (Career Guide,
2020). Providing students with the opportunity to collaborate, share and create learning resources
would increase the use of various technologies and enhance students’ e-Learning experience (Clark
& Mayer, 2011). Most people assume that students have the technical knowledge or are computer
literate (Kumar, 2015). However, computer illiteracy is a significant issue among students. Students
struggle to operate basic programs such as Microsoft Word and PowerPoint and are thus not able to
fix fundamental computer problems through troubleshooting. This highlights the importance of
technical proficiency to be able to use an LMS effectively. Kumar (2015) stated that technical
proficiency enables students to manage their assignments and courseware without struggling. He
further mentioned that introductory courses in computer literacy enhance students’ knowledge and
could help them to participate effectively in online learning.
Lack of technical staff
Simpson (2000) asserts that technical staff capacity is one of the neglected support systems at ODL
institutions. A lack of technical staff contributes to students’ struggle in online courses. Many
institutions do not have qualified staff to handle technical issues related to ICTs in education and most
especially the use of LMSs. Some institutions appoint student support officers (SSOs) and
instructional designers, who are more knowledgeable in providing administrative support and content
development-related support but may lack the ability to provide technical support. Therefore, ODL
institutions should recognise the importance of technical support by assigning technical support staff
to each department.
No induction or orientation programme
The effective use of the online LMS stimulates learning that is enacted through an induction
programme for online learning. However, ODL institutions lack the availability of induction or
orientation programmes to introduce students to the effective use of the LMS. Many online students
drop out of their courses since they find it difficult to navigate and study online. Anderson and Dron
(2011) reveal that technology failure, instructor feedback and lack of technical support contribute to
online student dropout. Online students tend to become frustrated when technology does not function
well or when they do not know what to do in the online course. Thus, without induction into the
learning programme, online students become frustrated and lose confidence in their studies.
RESEARCH DESIGN AND METHODOLOGY
A descriptive case study research design was employed to gain concrete, contextual, in-depth
knowledge about real-world problems of technical support in ODL. This design kept the study
focused and manageable because of the limited time and shed new light on the research problem. The
target population consisted of 118 online students, three online instructors and five SSOs who
participated in two full-fledged online courses at COLL in the year 2020. The probability sampling
technique (Saunders et al., 2019) was compatible with the quantitative study. Simple random
sampling, in which each population element had an equal chance of being selected, was used. The
sample population was 60 online students randomly selected from two online courses, three online
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instructors and five student support offices from COLL. Survey questionnaires were administered to
online students, SSOs and online facilitators in two online courses.
The table below indicates the response rate of participants.
Table 1: Response rate of participants
Participants
Online students
Student support officers
Online instructors
Total
Questionnaires
distributed
60
5
3
68
Number
responses
26
3
2
31
Response rate in
Percentage
43%
60%
66.6%
43%
Google Doc Forms were used to collect and analyse all quantitative data. Google Forms is a powerful
tool within Google Drive for creating online survey forms and collecting and analysing data that
support necessary data validation (Kumar & Naik, 2016). The advantage of using Google Forms was
to receive feedback for quick responses, analysis and storage (Kumar & Naik, 2016). Google Forms
was integrated with Google spreadsheets, which provided access to a spreadsheet view and created
graphs and tables to quickly analyse the data. Data were analysed in percentages and structured into
grids and graphs to make it easier for the readers to understand the results.
For ethical consideration, permission to conduct the research was sought from and granted by the
acting Registrar of NUST and acting Director at COLL. Participants were informed of the nature and
importance of the study and their rights to participate. Participant’s personal information remained
anonymous. Willing participants were required to sign an informed consent letter.
DATA PRESENTATION AND ANALYSIS
The findings are presented in four sub-sections below.
Part A: Technical skills of online students
1. The type of electronic device students use for the online course
The research results showed that 42% of the respondents used laptops, 12% used desktop computers,
and 46% used smartphones. The findings revealed that online students who used smartphones
experienced difficulties typing assignments and downloading huge files and videos. Fewer students
used their phones for effective learning. Students indicated that they mostly used cell phones for
reading, downloading documents and watching videos on social media platforms such as Twitter,
Facebook, WhatsApp, Instagram, etc. The findings also revealed that students were more confident
using laptops as learning devices. Students commented that smartphones had small screens which
were not suitable for typing assignments; however, some students downloaded PDF and Microsoft
Office documents to read offline. According to Darko-Adjei (2019), students use their cell phones for
playing games and other leisure activities more than for learning.
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Electronic devices used by students
Laptop
desktop computer
Laptop
42%
Smartphone
46%
Smartphone
desktop computer
12%
Figure 1: Electronic devices used by students
The participants were asked to rate their level of confidence using a laptop, computer, or smart device
for online learning. The results established that 64% of the respondents could confidently use a laptop,
computer, or smartphone; 24% of the respondents were somewhat confident, and 12% were not
confident. In the same vein, the study also showed that 12% of the respondents still needed to learn
how to use a laptop or computer and were not computer literate. Although the findings indicate that
more than 50% of the respondents could confidently use an electronic device, there is still a need for
training on the effective use of electronic devices for learning.
Figure 2: Confidence using electronic devices for online learning
Further, the participants were asked to rate their level of confidence to do logins and surf the Internet.
The study findings revealed that 48% of the participants could confidently log into the Internet and
surf the Web; 40% had somewhat confidence, and 12% were not confident to log in and serve the
Web. Thus, students should get support to familiarise themselves with the Internet and surfing the
Web.
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Confidence to log in and surf the Internet
Not confident
12%
Confident
Confident
48%
Somewhat confident
Not confident
Somewhat
confident
40%
Figure 3: Confidence to log in and surf the Internet
2. Compatibility of the electronic software with the course e-Learning platform
The findings show that 77% of the respondents had compatible software on the electronic devices
used. This means these respondents could download different document formats such as PDF and
Microsoft Office documents. The data also shows that 23% of the respondents found it difficult to
download certain documents from the online platform. The study revealed that a lack of regular
software upgrades may hinder the working of the online device. This implies that even a PDF and
Microsoft Word document can be difficult to view and download because of a lack of regular
upgrading and interrupts the smooth working of the electronic device used for online learning
(Thomas, 2019).
Not able to
download PDF
and Microsoft
documents
23%
Compatible software
Able to download PDF and
Microsoft documents
Not able to download PDF
and Microsoft documents
Able to download
PDF and
Microsoft
documents
77%
Figure 4: Compatible software
3. Confidence to work on the LMS (Moodle)
The participants were asked to rate their level of confidence in using Moodle LMS. The study findings
(figure 5) show that 56% of the participants could confidently use Moodle; and 44% were not
confident, thus, possibly needing training.
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Confidence to use Moodle
not confident
Confident
44%
Confident
not confident
56%
Figure 5: Confidence of online students to use the LMS, Moodle
The ability to use Moodle can be attributed to the fact that most of the respondents were first-year
students. This highlights the importance of training on Moodle at the beginning of the course.
According to Cook and Sonneberg (2014), the implementation of e-Learning through Moodle
improves effectiveness and efficiency in education.
4. Confidence to upload and download course assignments and documents
The study findings presented in figure 6 show that 57% of the participants could confidently upload
assignments/documents, save their work and print documents; 29% were somewhat confident, and
14% were not confident. Thus, more training is needed on how to upload assignments/documents,
save work and print documents. The study also revealed that students uploaded their assignments as
a draft after failing to complete the entire submission process. These are some minor technicalities
that prevented the students from submitting their assignments successfully.
Confidence to upload assignments and print eBooks and documents
Not confident
14%
Confident
Somewhat confident
Not confident
Somewhat confident
29%
Confident
57%
Figure 6: Confidence of online students to upload course assignments and documents
Further, the participants were asked to rate their level of confidence to read and download online
content for their online learning. The results established that 68% of the respondents could confidently
read and download online content; 24% were somewhat confident, and 8% were not confident to read
and download content.
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5. Confidence to send and receive e-mails on the LMS
The participants were asked to rate their level of confidence to send and receive e-mails as well as to
attach documents to e-mails. The study findings (figure 7) showed that 68% of the participants could
confidently send and retrieve e-mails and attach documents to their e-mails; 28% were somewhat
confident, and 4% could not send and retrieve e-mails. Thus, online students need training on the use
of e-mails.
Sending and receiving e-mails and attachments
Not confident
4%
Somewhat confident
28%
Confident
68%
Confidetn
Somewhat confident
Not confident
Figure 7: Confidence of online students sending and retrieving e-mails
6. Confidence in partaking in online discussions and quizzes
The participants were asked to rate their level of confidence to participate in online discussions. The
results established that 35% of the respondents could confidently partake in online discussion forums.
Forty per cent (40%) of the respondents were somewhat confident, and 25% were not confident about
partaking in online discussions.
Confident in participating in online discussions
Not donfident
25%
Confident
35%
Confident
Somewhat confident
Not donfident
Somewhat
confident
40%
Figure 8: Online students’ confidence to partake in discussion forums
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The participants were also asked to rate their level of confidence to take online quizzes. The research
results established that 65% of the respondents could confidently take online quizzes, and 35% were
somewhat confident to take online quizzes. Thus, online students need assistance in attempting online
quizzes.
Confidence in taking online quizzes
Not confident
0%
Somewhat
confident
35%
Confident
Somewhat confident
Not confident
Confident
65%
Figure 9: Confidence in taking online quizzes
7. Confidence to change profile, passwords and access grades
The participants were asked to rate their level of confidence to change their profiles and passwords
and access their grades. The findings (figure 10) show that 54% of the respondents could confidently
change their profiles, and passwords and access their grades; 34% were somewhat confident, and
12% were not confident. Thus, orientation sessions are needed on changing profiles and passwords
and accessing grades.
Change profile, password and view grades
60
54
50
40
34
30
20
12
10
0
Confident
Somewhat confident
Not confident
Figure 10: Online students’ confidence to change profiles, passwords and access to grades
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8. Confidence to communicate with the instructor and online friends
The participants were asked to rate their level of confidence to communicate with their online
instructors and friends. The findings in figure 11 show that 65% of the participants could confidently
ask questions and communicate with their online instructor or online friends, and 35% were not
confident.
Confidence to communicate online
Not confident
35%
Confident
Not confident
Confident
65%
Figure 11: Confidence to ask questions and communicate with the instructor and friends
Part B: Technical support for online students
Part B presents the results from the survey questionnaires to analyse the technical skills of online
students in two online courses at COLL.
1. Communication with online students at the beginning of the course
The participants were asked to confirm if they had been contacted at the beginning of the online to
get information on their shortcomings in the course. The chart (figure 12) indicates that 96% of the
respondents were not contacted, and 4% were contacted. This can reflect badly on the institution, and
online students may lose their trust in the institution.
The online institution contacted online learners
No
No; 96%
Yes
Yes; 4%
0
20
40
60
80
100
120
Figure 12: Online students contacted at the beginning of the course
2. Training provided to online students
The findings established that 58% of the participants received training to navigate the online course
and submit discussions and quizzes. Moreover, the online students received training on how to change
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their profile and login details at the beginning of the course so that other students could not use their
login credentials. The results showed that the majority (68%) of the participants knew how to change
their profile and login details. A smaller percentage of 32% indicated that they did not know how to
change their profile and login details. This could be the result of a lack of training for teachers and
management. The findings indicate that COLL provided training as a method of technical support.
However, 42% of the online students did not receive training; thus, these online students lacked
technical support and lost out on certain techniques to navigate their online courses. Mir (2016)
further suggested grouping the type of challenges received from online students to indicate the total
queries pending.
3. Provision of affordable data and online devices
The participants were asked to indicate whether COLL had provided affordable online devices and
data to students who did not have any electronic devices, laptops, or computers. The research results
(figure 13) showed that the majority (92%) of the respondents indicated “no” – the online institution
did not provide online devices and data to students, and online students need an online device and
affordable data. Students had a choice to indicate on their Namibia Students Financial Assistance
Fund (NSFAF) application forms if they wanted to take out a loan for electronic devices such as a
laptop and data devices; however, only 8% indicated that they took the loan.
Provision of affordable data and online devices
Institution did not
provide
affordable data
and devices
8%
Institution provide affordable
data and online devices
Institution did not provide
affordable data and devices
Institution
provide
affordable
data and
online devices
92%
Figure 13: Provision of affordable data and electronic devices to online students
The lack of data and online devices created new technical issues, such as missing submission dates
of assignments, discussion forums and students falling behind with their studies (Bingimlas, 2009).
The majority of the online student respondents indicated that they needed an essential device, and
some students used their cell phones as technical device devices for their studies. Students revealed
that the screens of their cell phones were too small for studies and that cell phones were not effective
for typing assignments. Thus, COLL should consider the provision of affordable data and technical
devices that meet the needs of online learners. It is recommended that students make use of the loan
system of NSFAF to buy online devices and data devices.
4. Handling of technical problems experienced by online students
The results presented in figure 14 show that 64% of the respondents said that the online institution
did not deal immediately with their technical problems. Thirty-six per cent of the online students
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indicated that the institution dealt immediately with their technical problems. This may be the result
of negligence in technical support.
Institution dealt immediately with technical problems of
online learners
Yes
36%
Yes
No
No
64%
Figure 14: Handling of technical problems experienced by online students at COLL
5. The level of interaction and motivation of online classmates
The research results in figure 15 show that 8% of the responses indicated that the participation and
motivation of online friends were poor and 63% were satisfactory. However, 29% indicated there was
good interaction between online students on the Moodle platform.
Interaction between online students on Moodle
Poor
8%
Good
29%
Poor
Satisfactory
Good
Satisfactory
63%
Figure 15: Interaction and motivation of online classmates
6. Online support provided by the e-Tutor throughout the e-Learning course
The research results (figure 16) show that 25% of the respondents indicated that they received poor
online support, and 46% indicated that online support was satisfactory. Thus, there is a need for
effective and more online learning support on the part of the e-Tutor. Only 29% indicated that online
support was good on the part of the e-Tutor.
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e-Tutor online support
Poor
25%
Good
29%
Poor
Satisfactory
Good
Satisfactory
46%
Figure 16: Online support by the online instructor to online students
7. The assistance provided by the student support officer
The participants were asked to rate the assistance provided by the student support officer for their
online problems. The results (figure 17) showed that the majority (71%) of the respondents said they
were not happy with the support provided by SSOs. The other 29% received effective support from
the SSOs. SSOs were overloaded with other work and did not provide effective student support.
Support provided by student support officers (SSOs)
Effective
technical support
provided
29%
Effective technical support
provided
No effective technical data
provided
No effective
technical data
provided
71%
Figure 17: Assistance provided by student support officers to online students
8. Provision and completion of the course evaluation survey
The research results (figure 18) show that the majority (71%) said they completed a survey at the end
of the course to measure their technical problems during the online course. Twenty-nine per cent
(29%) indicated that there was no survey at the end of the course to measure their technical problems.
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Provision and completion of the course evaluation survey
Yes
No
29%
No
Yes
71%
Figure 18: Provision and completion of online course evaluation surveys
According to Mir (2016), the success of online students depends on the level and various forms of
ICT support services available. He further indicated that a comprehensive technical student support
system that integrates with the queries of students and provides effective solutions to online students
is a necessity for any institution. A total of 96% of online students indicated that COLL did not provide
technical support. This is an indication that technical challenges were experienced by online students
at COLL. Common technical challenges included a lack of data, error messages, continuous loading
of online notes, uploading the wrong assignment and high similarity rates, and the use of cell phones
as a technical device for studies. These challenges can be eliminated immediately by a technical team
who would attend to student queries and not repeat themselves.
Part C: The response rate of the student support officers
This section presents the results on the technical support provided by the SSOs to online students.
Three SSOs out of a sample of five participants responded to the survey questionnaires, thus a
percentage of 60%. The visual presentation of data in graphs in percentages enabled the researcher to
offer an analytical description and interpretation of data employing descriptive statistical procedures.
The results from the survey to rate the technical support services provided by SSOs at COLL are
presented in the following subsections.
1. Satisfaction with technical support services provided
The findings show that the majority of respondents (66.7%) confirmed that the online technical
services provided were comparable and at the same level as those services offered in the traditional
learning mode. Further, 33.3% revealed that there was a difference in the technical support offered to
online students and those in the traditional methods. The results further show that all student support
officers provided technical support after hours from 16H30. This could benefit online learners, since
more students were online after hours because of work responsibilities or during lunchtime when they
were free. The study findings established that 66.7% provided immediate technical support to online
students. The rest (33.3%) indicated that they did not provide immediate technical support.
The research results show that all SSOs indicated that they knew how Moodle worked and could
assist with other technical criteria the institution used; thus, they could provide technical support to
online students. However, they indicated that they were reluctant to offer extra support to students
who were doing full-fledged online courses, as it put pressure on their workload. This indicates that
students may suffer in silence with their technical problems, which could reflect badly on the online
institution and technical support system.
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2. The functionality of the Moodle platform
The SSOs were asked if they had experienced any problems with the functionality of the Moodle
platform. The findings in figure 19 established that 67% of the respondents experienced no problems
with the functionality of Moodle at COLL. Further, 33% of the respondents indicated that they had
experienced minor technical problems with the LMS (Moodle). Thus, online students experienced
challenges with Moodle. These challenges could hamper learning and submission of assessments.
Immediate attention is needed to make sure the LMS functionality is effective.
Functionality of the Moodle platform
Minor problems
experienced
33%
Problems experienced
Minor problems experienced
Problems
experienced
67%
Figure 19: Challenges experienced by online students on Moodle
Moreover, 66.7% indicated that SSOs referred online students with technical challenges to the IT
department since they were not comfortable with technical issues. This emphasises the importance of
a technical support unit at online institutions.
3. Provision of training for student support officers
Student support officers SSOs were asked to indicate if they had received training from the online
institution on how to deal with the technical problems of online students. The findings established
that 66.7% of the respondents did not receive training on how to deal with technical issues. This could
be an obstacle because, in the absence of training, the institution would not be able to provide efficient
technical support. SSOs can be an asset to online institutions and online students. The provision of
technical support by SSOs, instructional designers, and online instructors, whether they have the
technical knowledge or not, could lessen the tension among online students. It is evident that SSOs
refuse to provide technical support because of a lack of technical skills and, as a result, this has a
repelling effect on students to work efficiently online and on their appreciation for the opportunities
that online learning has to offer.
Part D: The response rate of online instructors
This section presents the results from the survey questionnaires to analyse the online instructors’
technical support provided to online students. Two online facilitators responded to the survey
questionnaire. The visual presentation of data in graphs in percentages enabled the researcher to offer
an analytical description and interpretation of the data, employing descriptive statistical procedures.
The findings are presented in the following subsections.
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1. Provision of technical support by online instructors
The study findings established that 50% indicated that technical support to online students was only
provided at the beginning of the course. Thus, 50% of the online students did not get technical support
during the year, which may be bad for their online experience.
2. Monitoring of online students
Online instructors were asked if they monitored their online courses and students’ work weekly, and
50% of the respondents indicated that they monitored their online students weekly and continually
sent out reminders. The remaining 50% did not monitor their students and did not go into students’
activities to see how they were faring in the course. This is not a good reflection on the online course,
since it may result in online students falling behind and losing out on important assessments. The
tutors were asked to indicate whether they had sent out reminders every week to students reminding
them of the week’s tasks. The research results showed that all respondents who took part in the study
sent out reminders to remind online students about learning activities due for the week.
3. Assisting online students with technical challenges
Tutors also reflected on their willingness to assist students with any technical problems and to work
out solutions to solve the problem immediately. The research results showed that all the respondents
who took part in the study were willing to assist online students with technical problems and found
immediate solutions for these technical difficulties. All respondents indicated that they understood if
online students had internet difficulties and gave online students extensions for the submission of
assignments and other online tasks/activities.
4. Provision of effective feedback
When asked to reflect on the provision of feedback for effective learning to online students, all
respondents indicated that they did provide effective feedback to their online students. This is an
advantage for every student, and it assists online students with their learning. The tutors explained
why it was important for one to provide marks to online students within two weeks. One tutor
reflected that:
Timely grading of student’s work and the provision of feedback is regarded as stimulants for
students to be motivated for future submissions. It also guides students to avoid making the
same mistakes as indicated by the lecturer.
About checking when the students submitted their assessments and marking them immediately, the
results showed that 50% of the respondents checked constantly when students submitted assignments
and marked them immediately. The other 50% did not check constantly and did not mark assignments
immediately. This can be a bad reflection on the institution because prompt feedback is essential for
any online course.
5. Managing the online courses independently
Online instructors were asked if they managed the online course on their own and needed a little help
from instructional designers and technical support officers. Fifty per cent needed assistance, and the
other 50% did not need assistance. The results also showed that all respondents could reply
immediately to online students’ problems and re-question. This is a good reflection, and technical
support is provided immediately. Continued research on technical challenges would reduce technical
issues (Bingimlas, 2009). Instructional designers, SSOs, online instructors, and ICT experts can work
in collaboration to overcome the technical challenges of online learners.
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DISCUSSION OF THE FINDINGS
The findings indicated that online students at COLL need effective electronic devices. Students used
their cell phones as technical device devices for their studies, and they experienced challenges to type
assignments on their cell phones. It is also difficult to read on the screen of a cell phone. Cook and
Sonneberg (2014) stated that online education and students change continuously, as is the case with
technological innovations, the Internet, and computer software; thus, it is vital to consider the changes
in approaches to online development and devices. Effective online learning should create a mobilefriendly framework that allows for comprehensive viewing of all online environments. Using
collaborative tools and devices could allow online instructors and students to connect at anytime,
anywhere. Therefore, COLL should provide affordable data and devices as part of its technical
support to students.
The research findings indicated that COLL did not conduct an evaluation surveying the technical
issues of online students after the completion of courses. Research and development are vital in online
learning and can identify online challenges experienced by students to develop operational strategies
that improve teaching and learning. Another barrier that affects technical support is the effectiveness
of communication. The study found that there was a lack of confidence to communicate with the
institution, online instructors, and online students. Through effective communication, ODL
institutions can acquire numerous information on online students’ challenges. COLL should create an
effective communication structure online to communicate with online students. According to Isman
et al. (2003), eliminating communication barriers in online learning is a step to overcoming
difficulties and is necessary to get meaningful communication to restore online problems.
Mir (2016) states that the success of online students depends on the level and various forms of ICT
support services available. The author further indicated that a comprehensive technical student
support system that integrates with the queries of students and provides an effective solution to online
students is a necessity for any institution. The majority of online students indicated that COLL did
not provide technical support. Common technical challenges – such as the lack of data, error
messages, continuous loading of online notes, uploading the wrong assignment and high similarity
rates, and using cell phones as a technical device for studies – are experienced at COLL. According
to the SSOs, there was a lack in the provision of technical training at COLL. Technical training is an
important component of effective technical support. The workload of SSOs makes it impossible for
them to provide technical training and, therefore, the SSOs referred students to the IT department for
support. SSOs had more knowledge about administrative and academic support but lacked technical
skills. These challenges could be eliminated immediately by recruiting a technical team who would
attend to students’ and tutors’ queries.
The provision of technical support by SSOs, instructional designers, and online instructors – whether
they have the technical knowledge or not – can reduce the tension among online students. The study
indicates that SSOs lack the confidence to provide technical support because of a lack of technical
skills. According to Kumar (2015), students with a traditional mindset find it challenging to adapt;
thus, changing the mindset of online students by interacting with online students and creating a
collaborative, caring online environment may strengthen their love for online learning. Yang and
Cornelius (2004) stated that when online students have technical challenges, they need someone to
help them immediately. The first person they think about for assistance is their online instructor rather
than SSOs. However, tutors felt that they were not fully equipped to provide technical support to
online students.
All SSOs indicated that they had the necessary knowledge to work on the Moodle platform. This was
a great achievement for COLL. This knowledge should be communicated to online students through
essential technical support. This calls for the implementation of operative strategies, such as that
COLL, to ensure that continuous monitoring of the online platform is in place. Factors that demotivate
students in online learning, such as delayed feedback and unavailable technical support, should be
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dealt with through proper training of the staff members and faculty. Lastly, the implementation of
technical training to SSOs and online instructors at COLL is suggested.
CONCLUSION
The study reveals that technical support is an essential aspect of online learning and should be part of
any ODL structure. COLL only concentrates on academic and administrative support and neglects
technical support. As the number of online students is increasing, the study concludes that COLL
should establish technical support systems. Common challenges that are experienced by online
students at COLL can be addressed immediately with the help of a technical team. The provision of
affordable data and electronic devices is one strategy of technical support. Another strategy to
decrease the technical challenges of online students at COLL is training to navigate the online
platform, assignment submissions, and the use of Turnitin to test similarity rates.
More research on online challenges at COLL should be conducted. This would create awareness of
the necessity of technical support. An operative communication channel between COLL and online
students should be established. The traditional mindset of online students should be changed to create
a love for online learning. Operative strategies should be in place to enhance the effective use of
technical tools with online students. COLL can provide adequate technical support by continuously
upgrading and testing the Moodle platform. The provision of affordable and easy payment structures
for data and online devices can decrease the technical problems of online students. It is concluded
that the implementation of technical training for online instructors and SSOs should be a necessity at
COLL. The provision of training on how to minimise similarity rate, submit assignments and navigate
the Web should be introduced to online students. It is recommended that COLL offers a compulsory
orientation programme for all online courses on offer.
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EXPLORING MOBILE TECHNOLOGIES AS MITIGATING
TOOLS FOR ONLINE LEARNING CRISIS
Michael Agyemang Adarkwah
Smart Learning Institute of Beijing Normal University, 12F, Block A, Jingshi Technology Building, No. 12
Xueyuan South Road, Haidian District, Beijing, 100082, China (adarkwahmichael1@gmail.com)
Samuel Amponsah
Department of Distance Education, School of Continuing and Distance Education, College of Education,
University of Ghana, Legon, Ghana
College of Education, University of South Africa, Sunnyside, Pretoria
Yohana Kifle Mekonen
Faculty of Education, Southwest University, No. 2 Tiansheng Road, Beibei District, Chongqing, 400715, P.
R. China
Edna Pambour Agyemang
Department of Geography, Resource Development, and Department of Economics, University of Ghana, P.O.
Box LG50, Legon
Abstract
Some educators seem to dwell on the popular belief that mobile devices have a disruptive influence
on education. In the COVID-19 pandemic crisis, during which the abrupt disruption of education had
forced many institutions to embrace online learning, those in developing countries such as Ghana
faced unique challenges. A phenomenological qualitative inquiry approach involving tertiary
students (n = 20) from three institutions was used to problematize the online instruction in Ghana
and to present the integral role of mobile technologies in education. The paper reinforces the need to
adopt mobile technologies to mitigate “challenge-ridden” online learning, as participants perceived
m-learning as a pedagogical arsenal to battle the disruption in education. The researchers report
that handheld mobile devices can be adopted as an effective learning tool for both online and offline
or blended instruction during and after the COVID-19 pandemic. Educators should integrate mobile
technologies in education to aid struggling institutions with limited physical space to enrol more
students and continue the online instruction to achieve lifelong education. Future studies should focus
on the learning outcomes of m-learning in this pandemic era and how they can be used as a crisismanagement tool post-pandemic.
Keywords: mobile technologies; online learning; e-learning; m-learning; COVID-19
INTRODUCTION
Many educational institutions in low-income countries were reluctant to embrace online learning until
it was prompted by the COVID-19 crisis (Adarkwah, 2020, 2021a). Although COVID-19 primarily
affects health, its spillover effect on other aspects of human life led to a disruption to the status quo
for education delivery. Since the discovery of the COVID-19 disease in Wuhan City of China in
December 2019 (Karasmanak & Tsantopoulos, 2021) and its declaration as a global pandemic on 11
March 2020
(WHO, 2020), almost all human activities, including education, have been suffering
from its devastating effect. The lockdown and social distancing norms implemented to curb the virus
led to the sudden closure of schools in 188 countries, affecting the education of over 91% of the
student population globally (UNESCO, 2020). Online learning emerged as a panacea for the complete
paralysis of education caused by the COVID-19 pandemic
(Adarkwah, 2020; Pokhrel & Chhetri,
2021). However, the emergent nature of the transition from traditional face-to-face (F2F) delivery to
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the online modality of instruction meant that many schools, teachers and students were unprepared.
Concerns about the weakness of online learning are widespread in most developing countries (Bhagat
et al., 2020). In Ghana, online instruction was labelled as “challenge ridden” by the National Union
of Ghana Students (NUGS) (Adarkwah, 2020, 2021b). In Nigeria, the challenge of procuring ICT
tools negatively affected online learning (Oyediran et al., 2020). The high cost of internet served as a
barrier to the effective implementation of online learning in Ethiopia
(Mengistie, 2020). Though
online learning has saved education institutions from collapsing amid the COVID-19 pandemic, its
expensive nature is a real challenge. Consequently, many education institutions are looking for costeffective ways to instruct students online.
Technological applications offer learning opportunities in the form of virtual classes, m-learning and
online learning. Hence, technologies for mobile learning (m-learning) have become an important
approach for most schools to be at the forefront of progressive education in this pandemic era. The
role of technology in revolutionizing education has been highly acknowledged. Mobile technologies,
such as tablets and smartphones, are interwoven into the fabric of life and are more affordable for
teaching and learning (France et al., 2020). The ubiquitous spread of mobile tools such as iPads,
smartphones, tablets, and mobile applications such as Skype, Facebook, Twitter, YouTube, et cetera,
demonstrate our digital dependency and have also provided a new landscape for digital learning to be
realized. The significance of mobile technologies in education cannot be underrated, as teachers can
instruct and students can self-study online
(Razzaque, 2020), surf for new knowledge and take
snapshots/screenshots online without time and space limitations due to their mobility, unlike
laptops/desktops that limit physical mobility because of their bulky nature
(Churchill, 2020).
As many countries experienced a second and probably a third wave of the virus, even with the
prospect of a potent vaccine
(Mahase, 2020), online learning as the “new normal” for instruction
is likely to persist for a long time. The challenges that have fraught schools in low-income countries
like Ghana and the possibility of reclosing schools because of increasing COVID-19 cases in the
country calls for alternative solutions to ensure the educational careers of students are not in jeopardy.
Thus, the authors attempt to position mobile technologies for m-learning as a cost-effective,
innovative and novel means to continue the online modality of instruction in low-income countries
such as Ghana. In Ghana and other developing countries, mobile technologies can help address the
digital divide that poses a threat to online learning in the COVID-19 crisis. The following principal
question led this research: What are the challenges of online learning in Ghana, and how can these
challenges be mitigated through the adoption of mobile technologies?
THE PRESENT STUDY
Statistical data show that in West Africa, Ghana has the highest mobile penetration
(Omondi,
2020). As of the end of 2019, Ghana had a mobile adoption rate of 55%, which is higher than the
Sub-Saharan Africa regional average. Consequently, a considerable number of people (e.g., teachers
and students) can be served via digital technology in the country. The failure of many promulgated
ICT policies in Ghana such as the “one child, one laptop” policy (Adarkwah, 2020) and the failure of
online instruction in this pandemic era, which may not die out soon, invite alternative solutions such
as the use of mobile technologies to advance education.
As projections show Ghana has a lot of mobile users (figure 1), mobile technologies with their
affordances can serve as an alternative route to ensure the success of the online mode of teaching and
learning. The present study acknowledges the failure of online learning in Ghana with empirical
evidence and demonstrates how mobile technologies can be a game-changer and long-term plan for
institutions that have limited physical space for F2F instruction and are struggling to instruct students
online.
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Figure 1: Mobile users in selected countries in Sub-Saharan Africa. Source (GSMA
Intelligence)
LITERATURE REVIEW
Online learning
Online learning occurs over the Internet, either synchronously or asynchronously, and is associated
with the use of technology, which connotes that interaction between teachers and students and among
students is mediated by technology. The ability to stay at home and study, concerns about health
associated with daily commuting and physical contact with people, family obligations and
convenience are some of the main reasons why students prefer online instruction in higher education
(Landrum et al., 2020).
Hussein et al. (2020) also added that online learning is considered as the choice of instruction for
learners with financial constraints, older people with more familiar duties and those with work-related
responsibilities who are unable to study on campus. Some of the popular applications used for online
instruction during the COVID-19 pandemic were Zoom, Google Classroom, Coursera, Blackboard
Learn, Future Learn, TED-Ed, ClassMate, and Classwize (Mishra et al., 2020).
M-learning
M-learning is a multifaceted terminology that has different meanings to different people (Cowan &
Butler, 2013). Crompton (2013, p. 83) defines mobile learning as “learning across multiple contexts,
through social and content interactions, using personal electronic devices”. Simply, m-learning is any
type of learning that occurs with the use of mobile technologies or devices. Cowan and Butler (2013)
and Kumar (2018) acknowledge that m-learning is closely linked to e-learning. Thus, m-learning can
be both an indoor (offline) and outdoor activity (online). Accordingly, m-learning is considered as a
new platform for e-learning in the field of digital education (Wang et al., 2020). Students can use
mobile learning applications on their mobile devices to access learning materials irrespective of their
geographical location or time (Kuadey et al., 2020). Thus, the flexibility of m-learning allows
teaching and learning to happen without any limit to a specified location or time (Kumar, 2018).
Moreover, m-learning can increase the learning experience and academic outcomes of students
(Kumar, 2018). One key advantage of m-learning is its mobility and its efficiency in leading to better
learning experiences. Mobile learning systems offer users high levels of constant interactivity,
intercity and easy communication with different learners, enable users to make use of sensor data,
and bring out learning content depending on the education setting (Jagušt & Botički, 2019). Some
of the negative effects of m-learning are that it can create isolation among learners and high
dependency on online platforms for learning content
(Kumar, 2018). Also, small screen size of
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mobile devices, small keyboards, and the possibility of distraction contribute to the undesirable side
of m-learning. Despite the shortfalls identified with m-learning, Diao and Hedberg (2020) estimated
that it constitutes around 57% of all learning technologies. The authors estimate that the inroads mlearning keeps making on the education front amid the COVID-19 pandemic seem to establish it as
key to the redefinition of instruction even beyond the crisis.
Mobile technology mitigate the challenges of online learning
In this digital age, most learners have access to mobile technologies that are more robust and have a
better connection than conventional desktop computers (France et al., 2020). Mobile technologies as
handy information technology devices comprise hardware (i.e., devices), software (i.e., interfaces and
applications), and communication systems (i.e., network services). Mobile technologies have
powerful technical features that allow new forms of learning to take place in diverse educational
contexts (Xue, 2020). Thus, mobile devices possess omnipresent features that allow instruction to
happen beyond traditional spaces and foster convenient, personalized and customized learning using
mobile applications
(Diao & Hedberg, 2020).
Moreover, mobile technologies such as tablets and smartphones are portable and multifunctional in
nature and possess a wide array of applications that aid students in learning (France et al., 2020).
These technologies can be used by students for online activities on any learning platform. The unique
characteristics of mobile technologies, including their wireless communication ability, can aid
teachers to instruct their students online via m-learning during the COVID-19 pandemic. Kim and
Padilla (2020) also mentioned that mobile technologies such as cellphones and tablets could be used
for educational purposes during the COVID-19 era. Irrespective of the geographical location of
learners, they can surf for content online and access three-dimensional virtual platforms using their
mobile devices (Wang et al., 2020). In Ghana, an increasing number of students at the university level
have mobile devices that can help them to access massive open online courses (MOOCs), which may
also extend access to learning for students in rural areas (Kuadey et al., 2020).
THEORETICAL FRAMEWORK
This study adopted France et al.’s (2020) pedagogical framework for mobile technology integration
(see figure 2) to demonstrate how mobile technologies can be effectively incorporated into teaching
and learning (France et al., 2020). The framework suggests that to integrate mobile technologies into
a course or assessment, there are two crucial components to consider: 1) the pedagogical basis and
the reason for implementation; and 2) technological considerations and perceived issues to be
encountered. According to progenitors, the two components should be treated independently as
demonstrated in the diagram (figure 2) – pedagogical framework (P) and technological consideration
(T) – which ultimately results in effective use of mobile technologies at the center of the diagram.
The pathway consists of a set of guiding questions for educators and researchers to ponder about the
effect on instruction of incorporating mobile learning into the curriculum. Moving through the
guiding questions in the pathway, any “no” answer has a short guiding statement to be followed. The
principal constructs that should underpin the planning and implementation of mobile technologies in
the classroom include personalization (enables student to engage in learning tasks and allows
instructors to customize learning), authenticity (mobile technologies should not make learning
complex but fluid by allowing for adaptive learning spaces and should be familiar to students), and
collaboration (mobile technology should foster conversation and allow for data sharing). The theory
proved to be a useful lense to guide the current researchers to problematize online instruction in Ghana
and present the integral role of mobile technologies in education.
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Figure 2: Pedagogical framework for mobile technology integration into course or assessment
(France et al., 2020)
METHOD
Qualitative inquiry was used for the purpose of this study. Liamputtong (2019) states that qualitative
inquiry involves an examination of social circumstances of people based on the assumption that
researchers can unearth what people see, hear and feel. The phenomenological design that aligns with
the interpretive paradigm guided the process of inquiry. A phenomenological research design provides
a description of “phenomena as they manifest in our experience, of the way we perceive and
understand phenomena, and of the meaning phenomena have in our subjective experience” (Neubauer
et al., p. 92). Participants in this study faced challenges in their attempt to study online during the
COVID-19-engineered sudden shift to online learning and needed a space to share their experiences.
Liamputtong (2019) highlights that the value of qualitative inquiry cannot be underestimated when it
comes to amplifying the voices of the marginalized. In the light of the above, the current study sought
to problematize online instruction in Ghana and present the integral role of mobile technologies in
education through the voices of the study participants.
Qualitative data were gathered by the researcher from 15 tertiary students who experienced online
learning in Ghana, and their views were used to problematize online learning. These 15 students
comprised nine males and six females. Ten of the participants were from a public university; three
were pre-service teachers being trained in a college of education at the time; and the remaining two
were undergoing training in a nursing training college. Fifteen participants were recruited – first,
because of their involvement in online learning during the COVID-19 lockdown period and second,
because of their agreement to participate by their own volition.
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Sampling of these institutions was based on judgement sampling, as they had found ways of resuming
teaching and learning during the lockdowns between April and May 2020. Two research assistants
(RAs) trained to help in the fieldwork distributed permission letters to the management of selected
institutions between July and August. Upon receipt of acceptance from the institutions to commence
fieldwork, the RAs informally engaged with students to establish contact with those who had learned
online; this also led the RAs to other students who had done same. The RAs collected the phone and
WhatsApp contact details of the participants and agreed on convenient dates for the interviews. This
selection criteria positioned us to get access to information-rich cases for an in-depth study of the
challenges Ghanian higher education students faced while learning online (Patton, 2015).
A semi-structured interview guide developed by the researcher based on extant literature was used to
solicit information from the participants on the challenges to online learning. The interview guide
was structured into three sections. The first section sought information on the biographical
information of the participants. The second section elicited responses on their experience during the
COVID-19-engineered online learning, and the last section solicited reactions on their perception of
mobile technologies for m-learning. The structure of the interview guide permitted the researcher to
ask open-ended questions to enable participants to elaborate more their experiences. The instrument
was screened individually and collaboratively by the researchers to ensure there were no errors in
formatting, structure and construction and that it would elicit responses for the purposes of the study
aim.
A day before each interview, based on the agreement made beforehand between the participants and
RAs, an introductory letter was sent to the participants via WhatsApp that explained the purpose of
the study and also formally sought their consent to participate in the study. All interviews were
conducted in English via WhatsApp video calls. The interviews were conducted between July and
August 2021. On average, each interview lasted 30 minutes. The researchers downloaded the
interview data from the WhatsApp storage and transcribed each interview verbatim using the
Microsoft Office (MS) Word tool. All transcriptions were sent to the participants to validate before
the analysis was done. None of the participants had any queries about the transcribed data we sent to
them.
In analyzing the collected data, the transcript was imported to the NVivo 11 software. Using the Node
option, a coding table was generated based on the main categories outlined during the literature
review (challenges to online learning and mobile technologies for m-learning). Following the
stepwise approach of Colaizzi (1978), new nodes were created under the two main categories for all
emergent themes. The rigorous and robust data analysis framework by Colaizzi (1978) ensured
reliability and credibility of the research findings. The first step was reading and re-reading the
transcripts to help the researchers obtain a thorough understanding of the phenomenon. The second
step was extracting key statements from participants. In the third step, the extracted statements from
each of the participants was aggregated to generate interconnected themes. Seven interconnected
themes were formulated under the first category (challenges of online learning), while six themes
emerged under the second category (mobile technologies for m-learning). As discussed in the next
section, a comprehensive description of the identified themes was provided. Finally, participants were
requested to validate the research findings by sending a copy of the analyzed result to them through
WhatsApp. Participants agreed that the results of the study reflected their experiences and
perceptions.
DISCUSSION AND RESULTS
The results of this study are discussed in the context of the study participants’ views, the literature
review, and the theoretical framework to determine the challenges confronting online learners in
Ghanaian HEIs and how best m-learning can be deployed to assuage the challenges.
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Challenges of online learning in Ghana during the COVID-19 pandemic
The COVID-19 pandemic revealed the cracks as regards the digital divide among learners in various
institutions in Ghana, as it came to light that not every student was able to participate in online
learning for various reasons, including inadequate access to the Internet, high cost of the online
learning process (data bundles), limited access to electricity, lack of ICT facilities/tools, geographical
location, and glitches in the online learning system.
As regards internet access, a respondent mentioned that “the poor in the village have already paid
school fees but are unable to have good internet for the online learning. We also have bad networks.”
A study conducted on online learning in HEIs in Ghana found that students lamented difficulties
associated with accessing the Internet due to financial unpreparedness (Adarkwah, 2020). Some of
the students who enrolled in online learning also resided outside network coverage areas and were,
therefore, unable to engage in online instruction. This challenge affected communication and social
interactions. As one respondent said “the intercommunication between lecturers and students is very
poor. Communication is not good. You will be having a class and then the network starts
misbehaving.” Thus, problems with internet connectivity affected social interactions/communication
between instructors and students. In science-related courses, such as mathematics and physics,
missing a key word in an instructor’s speech can affect a student’s ability to comprehend succeeding
lessons.
Additionally, students were unable to submit their assignments on time. A respondent stated that “[f]or
the online learning, sometimes you are given a test like mathematics with 24 questions and then the
system takes 15 minutes to submit.” In their study on the impact of COVID-19 on education, OwusuFordjour et al. (2020) reported that a high percentage of their respondents found the online learning
platform ineffective.
Students also lamented the high cost of purchasing bundles to access teaching content and submit
their assignment. According to the students, coupled with the expensive cost of data bundles is the
lack of ICT tools, primarily laptops and desktops computers, which were more aligned with accessing
online learning platforms. For example, one respondent mentioned: “the school does not provide us
with ICT tools. If you don’t have these ICT tools, you have to share that of a friend.”
Access to electricity was also a major problem both for students in urban and rural areas due to power
instability in the country. However, for some students in remote areas, they were yet to get electricity
supply to their vicinities, which meant they were cut off from learning online. Those with electricity
power supply also experienced frequent power outages, which made the learning process frustrating.
A respondent stated, “electricity is another impediment, since it’s not stable.”
Although some students acknowledged that they were able to download study materials on time from
the online platforms, they lamented the lack of orientation on the usage of the online platforms. For
instance, one participant said, “we couldn’t have any orientation on how to engage in e-learning.” All
of these challenges reveal the plight of students regarding online learning.
4.2The integral role of mobile technologies in mitigating the challenges of online learning
The main themes that emerged under this category were social media education; communication
pathways in using mobile devices; the cost-effective nature of mobile technologies; how mobile
devices can be utilized for blended learning; the hampering nature of mobile devices on selfregulation; and creating an e-learning platform that is mobile friendly.
Most of the participants agreed that social media was a space where they could access educational
content in line with their programs of study. Some of the participants owned more than one mobile
device on which all social media applications were installed. One participant expressed the following:
I join several Facebook groups. Some of them has to do with education and even how to apply
for further studies abroad. Sometimes, I get insight on some general concepts from some of
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these groups. Also, sometimes when I don’t understand anything thought in class, I visit
YouTube to watch videos. They are all helpful.
The ubiquitous usage of social media platforms by university students can be used as an educational
advantage, especially in this pandemic crisis where the sudden migration from conventional
classroom teaching to online learning is fraught with challenges. Instructors can create educational
groups, pages, or channels where students can receive education. Xue and Churchill (2020) found
that social media platforms as educational tools can create a motivating environment for learners,
serve as a place for resource sharing, and provide room for evaluation and feedback. Additionally,
one affordance of mobile technologies is their use as a communicative tool. This feature of mobile
devices was reiterated by some of the participants.
It was observed that some of the students used their phones for text messaging and casual
communications. For example, one participant said:
“Oh, almost every day I chat with a lot of friends. Some are my course mates. But we talk about
other things not necessarily about school. But there are times when my friends explain some
parts of some lessons to me. I needed a brief explanation to write my exam.
The statement is a testament to how mobile devices are often used as a communicative channel. As
regards teaching and learning, updates on class sessions, course contents, and assignments can be
shared in created groups/pages for educational purposes. With just a text or voice recordings,
instructors are able to convey salient information to their students.
As reviewed in the literature above, participants echoed the cost-effective nature of mobile
technologies as opposed to laptops. Some of the participants believed that they could equally use their
mobile devices to learn just like laptops:
Sure! My Android phone has enough space to install many educational applications. If our
school is ready to develop an application for us to learn and take quizzes there, I can use my
phone to do that. Personally, I have answered some online quizzes on the Internet using my
phone.
An added advantage is the mobility and cost of mobile devices over laptops. The Government of
Ghana can save money for other important educational projects by supplying mobile technologies for
m-learning instead of laptops of which the cost far outweighs most mobile devices.
The students also mentioned how mobile technologies could help in education delivery in case a
blended mode of teaching and learning be adopted. In the first quarter of 2021, some public
universities experimented on a Multi-Track Year-Round Education (MT-YRE) system, popularly
known as the “double-track” system in Ghana. This approach separated the students into two groups:
the first group had physical classroom teaching and were replaced by the second group of students
who stayed at home during the academic year. This approach was adopted because of the lack of
physical space in the universities. Some of the participants highlighted how mobile technologies
could be used for blended learning where all groups of students learn, be it at home or on the school
premises. One student opined:
…[t]he double-track method was not effective for me. Sometimes, you are not able to get
clarifications to all your questions. Supposing we use our mobile phones, the other group can
also study online while we are here. This will at least reduce the pressure on us.
Appropriately, blended learning is 80% online and 20% offline (Adarkwah, 2021c; Anthony et al.,
2020). This means both groups of students experimented on in the MT-YRE system could learn
concurrently instead of one group idling at home.
In the current study, an ample number of the students did not shy away from the disruptive effect of
mobile technologies. Some of the respondents acknowledged that mobile devices had the tendency
to affect their self-regulation. In a typical case, one participant shared the following statement:
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“Sometimes, when watching an educational video, you get notifications which can takes your mind
from what you are learning. But I think we can still use our mobile phones to learn.” In integrating
mobile technologies for m-learning, France et al.’s (2020) framework should be followed. This would
help in enhancing the self-regulation of learners. Mobile technologies for learners can be customized
in such a way that they support only educational applications with some added restriction on accessing
some sites.
Finally, students called for a mobile-friendly e-learning platform (learning management system). In
the COVID-19-inspired online learning, some students experienced difficulties accessing the elearning system when there were assignments and exams. This is expressed in the response of one
participant:
Formerly, when we studied at home online, there were instances where the e-learning system
will ‘jam’ (experience a glitch) when you are taking a quiz or uploading your assignment.
Sometimes, you get anxious about your grade at the end of the semester. If we will use a mobile
device to study, I suggest that the platform for course assignment and exam be one that works
on the phone.
It can be observed that the majority of the respondents believed mobile technologies for m-learning
could be a pedagogical arsenal to battle “challenge-ridden” online learning in developing countries
such as Ghana, Sub-Saharan African, and other developing economies. However, students were also
concerned with the mode of implementation of mobile technologies. We believe that the framework
of France et al. (2020) is tested and valid to promote m-learning. With the emergence of new COVID19 variants, integrating mobile technologies into education is an alternative to avert another disruption
in education while avoiding the exacerbation of the spread of the virus through human contact. Mobile
technologies for m-learning can be a crisis management tool against COVID-19 and subsequent
emerging variants.
CONCLUSION AND RECOMMENDATION
This phenomenological qualitative inquiry sought to problematize online instruction in Ghana and
present the integral role of mobile technologies in education. Findings from the study reveal that the
relatively poor infrastructure of universities, the lack of ICT tools, inadequate internet accessibility
and erratic electric power supply (called “dumsor” in Ghana), lack of proper orientation and glitches
in the online platform negatively affected online instruction in Ghana. Hence, there is a clear need to
introduce a novel and innovative method of instruction to replace or enhance traditional onsite
instruction and foster online learning in Ghana. Mobile technologies can be used for both online and
offline learning environments and have shown to be a positive predictor of student academic
achievement.
The qualitative inquiry attested that the students were eager to embrace m-learning. Specifically, they
perceived integrating mobile technologies for m-learning as one way by which they could use their
social media platforms for educational purposes, improve social interactions through effective
communication, and foster blended learning. The use of mobile devices can be an innovative and
cost-effective way to enhance learning through asynchronous and synchronous approaches to
instruction. The supply of conventional laptop and desktop computers to teachers and students for
online instruction can be a great challenge for developing countries like Ghana. To defray the cost of
expensive laptops for online instruction, mobile devices such as cellphones and tablets can be used
to achieve the same goal as indicated in the pedagogical framework for mobile learning. As students
are mostly used to cellphones and other handheld devices, they would be comfortable to engage in
online learning at any time and in any place due to the portability of said devices. Students would be
able to listen to podcasts, watch videos, download presentations and access other instructional
materials on their mobile devices.
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Potential setbacks such as reduction in self-regulation of learners and e-learning systems incompatible
with mobile devices can be addressed during the stage of implementation. To this end, the researchers
call on policymakers in educational institutions and other significant stakeholders to integrate mobile
technologies in education in Ghana, especially in this COVID-19 pandemic era where the educational
careers of most students are in jeopardy because they are unable to participate in the ongoing
instruction. The researchers recommend that future researchers focus on teachers and students’
acceptance of or attitudes to mobile technologies for instruction and how they can be successfully
implemented. Also, researchers can focus on the instructional methods and learning outcomes of
mobile technologies. The abrupt shift to online learning presented a limitation to this study in that
faculty and school administrators were too overwhelmed with work to share their useful insights into
the experiences of online instruction and plans for adopting m-learning in their institutions. This, in
turn, limits the generalizability of the study results. However, insights from extant literature of topical
importance and the pedagogical framework for mobile learning were used to somewhat compensate
for this deficit.
Acknowledgements
Our sincere thanks to Professor Jako Oliver and all the reviewers. We thank Wishwell Mensah, Robert
Kyei, and Sir Kwegyir Aggrey of Ghana Education Service for assisting in this study.
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LECTURERS’ RECOMMENDATIONS ON HOW LEARNING
MANAGEMENT SYSTEM TRAINING AND SUPPORT CAN
IMPROVE THE IMPLEMENTATION OF BLENDED LEARNING
IN A HIGHER EDUCATION INSTITUTION
Jackalyn Appalsami
The Independent Institute of Education, Varsity College Nelson Mandela Bay, Port Elizabeth, South Africa
(jackalyn.abrahams@gmail.com)
Abstract
The 2020 COVID-19 pandemic has disrupted almost every sphere of our daily lives. Even businesses
and educational institutions were forced to shut down so that the spread of the virus could be
contained. To rescue the academic year, many higher education institutions (HEIs) made the switch
to online learning. The sudden shift put immense pressure on the IT infrastructure and more
importantly, on lecturers and students. Many lecturers were not equipped to teach and facilitate
online learning and were unable to use a learning management system (LMS). In 2018, a study
conducted on lecturers’ teaching strategies in the use of an LMS at an HEI made recommendations
on how system training and support can improve teaching strategies through the implementation of
a blended learning approach. A qualitative, exploratory single case study design was undertaken by
conducting semi-standardised interviews, observations, and the analysis of log files. This article
focuses on the responses from the interviews with lecturers regarding recommendations on training
and support that are still relevant to this day. The results suggest that the promotion of training and
lecturer support is beneficial; hence, blended learning in higher education will be better
implemented, which will lead to an improvement in student performance and success.
Keywords: learning management system (LMS), COVID-19 pandemic, blended learning
INTRODUCTION
The COVID-19 pandemic has caused many educational institutions to shut down and resort to online
learning, as parents, teachers and children had to stay at home (Hung & Wati, 2020). The closure of
schools and higher education institutions (HEIs) led to a loss of teaching time (Ramrathan, 2020).
While some private schools and higher institutions could switch to online teaching and learning, many
public schools did not have the infrastructure and capable staff to make the switch. Pete and Soko
(2020) iterate that switching from face-to-face classes to online learning can be disruptive if the
teachers, learners and school are not ready for it. The adoption of learning management systems
(LMSs) in education has become a trend to facilitate the teaching and learning process in an online
environment (Martin et al., 2010). Martin (2008) defines an LMS as online educational software that
supports and manages teaching and learning material provided by the lecturer. Gani (2013) describes
an LMS as a support tool to carry our administrative and academic tasks. Examples of academic tasks
are providing access to learning material, hosting online assessments or activities, such as online tests,
quizzes, and discussion forums or blogs (Gani, 2013). Examples of administrative tasks are providing
automated or immediate feedback on assessments, tracking and monitoring of student activity on the
LMS (Gani, 2013). However, there are many challenges that students and lecturers face when
adopting an LMS, for example, they lack computer skills and skills for teaching with technology (AlBusaidi & Al-Shihi, 2010). In another study, Gani (2013) revealed that lecturers lacked experience in
teaching with an LMS, which left them discouraged. Thus, it is necessary for lecturers to feel
supported, well-trained and heard on how to improve training.
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LITERATURE
Need for training lecturers on an LMS
Digital immigrants refer to people who were not born in the era of technology but then adopted
technology into their lives (Prensky, 2001). Presently, teachers and instructors are considered digital
immigrants, as they grew up without technology. The latter presents a problem since these digital
immigrants must teach in the Fourth Industrial Revolution (4IR) where their students rely on
technology in every part of their lives. For example, students in this era use the Internet to learn
through videos, sound, and web 2.0 applications (Sharma, 2019). Educational tools such as LMS,
school management systems and communication tools are used in education in the 4IR (Sharma,
2019). These instructors lack computer skills and knowledge on how to integrate technology in their
teaching strategies (Al-Busaidi & Al-Shihi, 2010). Bervell and Umar (2020) express that the lack of
LMS usage and online presence by instructors has resulted in a hindrance of successful online
teaching and learning. Gani’s study revealed that instructors had time constraints on learning how to
use an LMS (Gani, 2013).
How to train lecturers on how to use an LMS
In the 21st century, lecturers should be required to have the necessary competencies to teach online.
Bates (2015) recommends that lecturers undergo training on how to use an LMS and strategies of
teaching in a digital age. Furthermore, Bates (2015, p. 488) suggests that the following training be
offered:
The use of technology needs to be combined with an understanding of how students learn, how
skills are developed, how knowledge is represented through different media and then processed,
and how learners use different senses to learn.
Bowen (2012) suggests that education institutions should focus on training lecturers on how to design
learning experiences and how to make learning engaging for students. Educational institutions should
employ education technologists to train lecturers on the technical aspects of using an LMS, but more
importantly, training on how to design lessons must be emphasised so that blended learning can be
better implemented (John & Wheeler, 2008). Desimone and Garet (2015) revealed in their study that
teachers preferred individual support so that their training needs could be met. HEIs should provide
IT support services to lecturers and students so that they can equip them with technical and
pedagogical skills (Mtebe, 2015).
Blended learning and LMS
Harpur (2013) describes blended learning as a combination of face-to-face teaching and online
teaching that are facilitated on online educational platforms. Blended learning is aimed at creating an
effective learning environment by offering various modes of teaching (Harpur, 2013, p. 28). For
example, face-to-face teaching and online teaching are offered. Blended learning allows for
flexibility, as students can access the course material online anywhere, at any time (Protsiv et al.,
2016). The use of technology in blended teaching and learning allows for traditional face-to-face
teaching to continue (Grabinski et al., 2015). Many HEIs use LMSs to facilitate the blended teaching
and learning approach (Makara et al., 1997).
THEORETICAL FRAMEWORK
Garrison and Vaughan (2008) designed a framework to support lecturers and instructors on how to
implement blended teaching and learning on an LMS. This framework is called Community of
Inquiry (CoI) whereby the lecturer is expected to create a social, cognitive and teaching presence
(Garrison & Vaughan, 2008). Each presence is interdependent and they overlap with each other so
that effective online teaching and learning is created. Garrison et al. (2000, p. 13) define social
presence as “the ability of participants in a community of inquiry to project themselves socially and
emotionally, as ‘real people’, through the medium of communication being used”. Thus, lecturers
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need to create a safe and non-threatening environment so that students can feel free to express their
ideas and opinions. Moreover, Garrison et al. (2000, p. 10) define cognitive presence as “the extent
to which learners are able to construct and confirm meaning through sustained reflection and
discourse”. Lecturers must create and design opportunities on the LMS for students to develop critical
thinking and an understanding of the content. Garrison and Arbaugh (2007) suggest that cognitive
presence can be achieved by creating an opportunity for students to explore and apply content material
through using LMS tools such as online tests, blogs, and discussion forums. Teacher presence is
defined as the “design, facilitation and direction of cognitive and social processes for the purpose of
realising personally meaningful and educationally worthwhile learning outcomes” (Garrison &
Arbaugh, 2007, p. 163). For example, lecturers can create a teaching presence by focusing on the
design of their lesson and then continue through to the facilitation phase so that students can
accomplish the learning outcomes of the lesson online (Vaughan, Cleveland-Innes, & Garrison,
2013). Aghili et al. (2014) suggest that a high level of teacher presence on an LMS makes
communication between students and the content material easier, which, in turn, develops a better
CoI.
METHODS
The researcher conducted an exploratory case study to achieve the aim of this study. The aim of this
study was to impart the recommendations provided by lecturers on LMS training and support to
improve the implementation of blended learning in an HEI. According to Luo (2011, p. 8), an
“exploratory case study is used to explore situations in which the intervention being evaluated has no
clear, single set of outcomes”. Such a case study is conducted within the sphere of the qualitative
approach, which is defined by Creswell (2012) as an approach that allows one to explore the problem
and gain an understanding from the participants. Seven participants were purposefully selected as
they were defined by their participation in the LMS training and its implementation. A purposive
sampling technique was adopted because the researcher worked at the research site and thus spoke to
the relevant stakeholder to identify appropriate participants to partake in this study. These participants
were lecturers who had started using an LMS for blending teaching and learning. The participants
lectured in various disciplines.
The data collection instruments used in this study were semi-standardised interviews. The researcher
conducted the interviews in person. The use of semi-standard interviews was deemed appropriate for
the study because predetermined questions were asked which were then followed up by relatable
questions so that in-depth data could be acquired. The participants’ responses were audio-recorded
and later transcribed for analysis. Consent was received from all the participants to audio-record the
interview and take notes during the interview.
Creswell (2012) suggests that inductive reasoning should be used when analysing qualitative data.
Thus, the data were organised, and themes were identified. Measures of trustworthiness were
promoted by adopting Lincoln and Guba’s strategies, namely credibility, transferability, dependability
and confirmability (Baxter & Jack, 2008, p. 555). The researcher ensured confidentiality and
concealment of the participants personal details.
RESULTS AND DISCUSSION
The findings revealed themes from the recommendations provided by the lecturers on how to improve
LMS training and support. From discussions with the participants, some recommendations were made
on how to improve the training and support offered on the LMS. The following themes emerged from
the results, which are expanded further in the subheadings below.
LMS training and support provided
Training was provided on how to navigate the LMS and illustrate what LMS tools were available.
The training was facilitated on campus and by an educational technologist. Participants shared that
they had received technical support on how the LMS worked. However, one participant felt that
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training was required on how to teach with the LMS. One of the participants felt that too much training
was provided. Another participant felt that the training was overwhelming because she did not know
which LMS tool to use. There were many workshops throughout the year on the LMS; however, one
participant was unable to attend all the workshops, and this resulted in self-study on how to use the
LMS independently. Some participants preferred one-on-one training so that specific training needs
could be met.
Training should be focused on subject-specific modules
Participants expressed that they had received significant training on how to use the LMS; however,
they would have appreciated subject-specific training on how to integrate lessons on the LMS more
effectively. One participant suggested that training should be provided on what LMS tools to use
when lecturing a theory module versus a numerical module.
Support documentation should be provided after the training workshop
One participant suggested that once training has been provided, it should be supplemented with
additional resources – such as the recording of the training, or how-to guides, or user-friendly
diagrams – so that lecturers could refer to these resources if they get stuck. Furthermore, the
participant suggested that there should be a central online location to access these additional
resources. It emerged from the recommendation that the participants wanted additional support
documentation so that they could develop their competence in using the LMS.
Training students on the LMS
Another participant noted that training of lecturers was extensively provided, but training of students
should be emphasised. For example, students should receive refresher workshops at the beginning of
the first semester on how to use the LMS. In addition, training on how to download the LMS mobile
application should be provided so that students could learn how to navigate the application on their
smartphones. This would assist students to comfortably navigate the LMS and would, as a result,
build student competence.
Additional people should assist educational technologists
One participant praised the educational technologist for providing how-to guides on how to use
certain LMS tools after the workshops. However, another participant felt that the educational
technologist was not easily accessible to support his needs. This participant recommended that an
educational technologist should be available during lecture times so that they can freely assist if
assistance is required. The aforementioned recommendation supports the work of Bates (2015, p.
499), who suggests that learning technology support units are necessary for effective training and
support to be offered.
Training on LMS for groupwork and peer assessments
Another participant recommended that training should be provided on how to use group work and
peer assessments on the LMS. This would enhance peer-to-peer learning and create a social presence
on the LMS. Furthermore, training is requested on how to plan an entire lesson on the LMS. Garrison
and Arbaugh (2007, p. 158) support this recommendation, as they suggest that for effective online
learning to occur, the lecturer must design collaborative online activities.
CONCLUSION
The study was aimed at exploring how LMS training and support can improve the implementation of
blended learning in higher education by considering recommendations by lecturers. From the results,
the researcher could deduce that even though lecturers received extensive training on how to use an
LMS, more training is required on how to integrate teaching strategies in blended learning with the
use of an LMS.
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Mhlanga and Moloi (2020, p. 4) assert the COVID-19 pandemic acted as a “motivating factor towards
digital transformation in the education sector during the lockdown”. The pandemic caught the world
off guard, as many education institutions and lecturers had to make the sudden shift to online. Thus,
education institutions need to be proactive and train lecturers on how to adapt to such unforeseen
changes. On the other hand, Bates (2015) suggests that personal professional development should be
emphasised. For example, lecturers must upskill themselves in learning technologies and skills
required to teach online (Bates, 2015). Van Der Merwe et al. (2015, p. 11) concur that professional
development is a vital component in the success of blended learning.
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