International Journal of Technology and Design Education
https://doi.org/10.1007/s10798-021-09680-8
ORIGINAL RESEARCH ARTICLE
Exploring the role of situational flow experience in learning
through design in 3D multi‑user virtual environments
Dilek Doğan1
· Ömer Demir2
· Hakan Tüzün3
Accepted: 5 June 2021
© The Author(s), under exclusive licence to Springer Nature B.V. 2021
Abstract
This study aims to examine the situational flow experiences of students creating 3D
designs in 3D multi-user virtual environments. This time series quasi-experimental study
included 40 volunteer junior students who studied at the Computer Education and Instructional Technology department and had taken the elective course of “Instructional Design”.
The participants in the role of a designer created 3D designs in the OpenSimulator application throughout the process. They worked in groups to solve authentic problems. At the
end of each session, the students were applied a flow experience scale individually. As a
result of the study, it was concluded that the participants’ flow experience did not differ by
gender and overall grade point average. Autotelic activity and disappearance of self-consciousness were the highest components of flow experience indicating that the designers
felt immersed in the 3D design activities throughout the 15-week implementation process.
Considering flow experience by weeks, it was found that conveying theoretical information to the students diminished their flow experience owing to lack of the concentration,
control and feedback components, whereas giving feedback after letting them present what
they worked on fostered their flow experience by increasing the clear goals and immediate
feedback components. The results highlighted the importance of flow experience in design
education.
Keywords Three-dimensional multi-user virtual environments design education · Learning
through design · Flow theory · Collaborative learning problem-based learning approach
constructionism
* Dilek Doğan
dilek.dogan@ankara.edu.tr
Ömer Demir
omerdemir@hakkari.edu.tr
Hakan Tüzün
htuzun@hacettepe.edu.tr
1
Department of Computer Education and Instructional Technology, Ankara University, Ankara,
Turkey
2
Department of Computer Technologies, Hakkari University, Hakkari, Turkey
3
Department of Computer Education and Instructional Technology, Hacettepe University, Ankara,
Turkey
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D. Doğan et al.
Introduction
Three-dimensional multi-user virtual environments (3D MUVEs) are platforms structured
with three-dimensional (3D) objects, where users can navigate effectively with the help of
an avatar (Doğan & Tüzün, 2017). In these environments, users can interact with different objects and avatars which are their own representational characters and perform many
actions such as walking, running, flying, jumping and dancing (Doğan et al., 2018). In
the 21st century, 3D MUVEs are mentioned alongside concepts such as simulations and
games. However, although the reflection of the authentic world may be designed in a virtual environment, since a real process involving defined relationships between objects cannot be imitated in any system, it would not be accurate to call this a simulation. Besides,
since these environments do not have specific goals or specific rules to achieve a goal in
their use, it would not be accurate to call them games (Doğan & Tüzün, 2017).
In 3D MUVEs, the properties of objects and users can be presented in different ways
based on many different situations. These environments, therefore, can be used in many
different fields from entertainment to education, trade to socializing. Among these fields,
education in particular draws attention. The main reasons for the increased use of these
environments in education may be listed as follows: offering interactive and collaborative
environments, supporting different learning approaches, giving learners an opportunity to
use their creativity, presenting the reflection of the outside world virtually without cost
and eliminating dangerous situations, and allowing authentic tasks to be created. Moreover,
communication is reinforced in 3D MUVEs due to fast and rich interaction, the ability to
change the characters in line with determined strategies and goals and the control of the
communicated information (van der Land et al., 2011).
Over time, 3D virtual environments have become customizable with designs in line
with user requirements. The design of 3D virtual environments is a long process, and
since the design of these environments requires a variety of higher-level learning skills,
such as virtual environment design, creativity, problem-solving skills and spatial thinking, it is also associated with pedagogical approaches. One of these approaches is learning through design. Regarding this approach, it is known that people acquire new information as a result of their relationships with the world, especially while trying something
new (Resnick, 1996). Having focused on how information is shaped and defined according
to contexts and environments and how information is processed in people’s minds, Papert and Harel (1991), while observing students who were creating sculptures out of soap
using their hands, realized that their students were more engaged than dealing with abstract
things such as solving a math problem. This realization stresses the importance of learning through design, which is a constructionist approach. On this matter, multimedia software may be used since it supports activities that engage students in knowledge construction through active, constructive, collaborative, intentional, conversational, contextualized
and reflective learning (Jonassen, 1995). According to Csikszentmihalyi (1991), design
is one of the important processes that provide flow experience, which is defined by the
same author (1991) as becoming immersed in an activity mentally and/or physically. With
design processes via multimedia software such as games and 3D MUVEs, tasks on different challenge levels are created for learners. These tasks require learners to use their relevant skills to overcome specific challenges. The balance between the challenge level of the
task and skill level of the learners determines the learners’ flow and engagement experiences (Ramondt, 1998). When this balance is achieved, students’ motivation increases. The
relationship between constructionism, learning through design and flow is shown in Fig. 1.
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Exploring the role of situational flow experience in learning…
Fig. 1 Relationship between constructionism, learning through design and flow (adapted from Ramondt,
1998)
It goes without saying that the skill of spatial thinking is crucial for design education,
especially for 3D designs. Regarding this issue, it is known that the mental rotation and
3D visualization skills of males are higher than those of females (Maeda & Yoon, 2013;
Medina et al., 1998). In this respect, gender might be affecting what designers experience
in 3D design process over the difference in spatial skills. Moreover, the balance between
challenge and skill is a component of flow experience (Csikszentmihalyi, 1996), and
designers’ Overall Grade Point Averages (OGPA) might, in part, represent their overall
design skills. In fact, the sample of this study had studied “instructional design”, so, they
had taken several courses about instructional design, as well as computer programming.
Consequently, OGPA might be related to flow experience. In light of this information, this
study aims to investigate the flow experiences of designers who concretely create educational environment designs in 3D MUVEs by working in groups. In the time-series study
conducted with 40 university students in the role of instructional designers, the flow experiences of the participants during a 3D MUVE design process were examined throughout
weeks. Furthermore, the effects of gender and OGPA were also investigated. In this context, firstly, the concepts of Learning through Design, Flow Theory, Flow Experience in 3D
MUVEs and the Zone of Proximal Flow were explained, respectively.
Learning through design
Although it is emphasized that there is a strong relationship between the constructionism
approach and design and learning, and rich content should be presented in the learning
process due to its various activities such as production, construction and programming,
design and learning have not been seen as close concepts. Design and learning approaches
have different origins. Traditionally, design theorists have focused on the resulting product
and argued that constraints affect product designs. Learning theorists, on the other hand,
have been more concerned with the process than the product. In recent years, both learning and design approaches consider meaning-making as a basic process. In this regard, this
process involves creating the relationship between design, designer and objects. Designers
reveal what objects mean to both themselves and others and whether the properties of the
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object and the context in which it is used are consistent. The relationships that designers
obtain about objects and situations form the focus of design theories. Design, therefore, is
considered as a process since it involves creating not only the object but also its meanings
in the context.
Design theories and constructionism approaches overlap since they focus on meaningmaking. At the same time, more attention has been paid to the roles of the product and
work through learning approaches. Papert’s Constructionism (Papert & Harel, 1991) goes
beyond Piaget’s Constructivism Learning Theory (Piaget, 1976) and focuses on products.
In this approach, it is emphasized that sharable products developed by students make it
easier for these students to make meanings. This process is named learning through design.
Unlike traditional problem-solving processes and unlike solving the problem created by
the teacher or given to the student, in this approach, students are expected to create designs
involving development of goals and problems. The problem to be solved is determined by
the students, not by the teachers or by experts. In learning through design processes, defining the problem and developing goals in problem-solving are a part of the curriculum. The
actions performed during the process are more important than the resulting product. In
other words, although students’ final projects might be unsatisfying, learning occurs since
the students participate in the process (Kafai, 1996). On the other hand, the issue of what
students feel has importance in learning through design processes.
Flow theory
Being defined as a holistic feeling that individuals have in their behavior with all their
interests, flow has been suggested to explain the concept of internal motivation in a broader
manner (Csikszentmihalyi, 2000). Therefore, flow is a subjective situation like motivation (Csikszentmihalyi, 2005). Flow experience may occur while playing computer games
(Kara & Çağıltay, 2013), playing chess (Abuhamdeh & Csikszentmihalyi, 2009), writing
introductory computer programming codes (Demir & Seferoğlu, 2021a; 2021b) and during
other activities depending on the individual’s interest. In flow experience, a high level of
attention is achieved almost effortlessly (Csikszentmihalyi & Nakamura, 2010).
Flow is often defined by the compatibility between an individual’s skill and the challenge of the work one performs. It is the expected result that the skill of the individual is
compatible with the challenge of the work one performs. The individual, thus, enters the
zone of flow. In the zone of flow, enjoyment is experienced on the highest level. If the skill
of the individual is higher in comparison to the demand of the work one performs, the
individual starts to get bored. In the exact opposite situation, in other words, if the demand
of the work is higher than the skill of the individual, then tension begins. In both cases, the
individual leaves the zone of flow (Csikszentmihalyi, 1991; 2000). In this case, the individual cannot have enjoyment. However, this model of flow is criticized on the grounds that it
only makes a three-channel examination. In models suggested later, flow was divided into
eight channels by the balance between the challenge and the skills of the individual. At this
point, the channels of getting bored and tension take different names by division within
themselves. Besides, in this model, challenges and skills are discussed on an intermediate
level. The 8-channel flow model, on the other hand, was criticized for the following issues:
focusing on the balance between the challenge of the work and the skill of the individual
by more than what is adequate, ignoring the other components by flow, and the fact that it
is problematic to determine what it means to have a moderate challenge/skill in the model.
In parallel with these criticisms, it is seen that the concept of flow is generally discussed
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Exploring the role of situational flow experience in learning…
in a multi-dimensional manner (Moneta, 2012). Another discussion at this point is how
many components the concept of flow has. Nevertheless, here, it is observed that in general
that the dimensions specified by Csikszentmihalyi are being embraced (Özkara & Özmen,
2016). Csikszentmihalyi (1996) shows the balance between challenge and skill, disappearance of self-consciousness and change of time perception as a prerequisite for flow experience and emphasizes that there should be a total of nine conditions:
1.
2.
3.
4.
5.
6.
7.
8.
9.
clear goals
immediate feedback
balance between challenge and skill
merging of action and awareness
exclusion of distractions from consciousness
no worry of failure
disappearance of self-consciousness
distortion of sense of time
autotelic activity
The aforementioned conditions can occur independently of each other (Tozman et al.,
2015). Another important point to be mentioned about flow is whether flow is dispositional/trait flow or situational flow. Flow that is experienced independently of personal
situations is named dispositional/trait flow, while flow resulting from the interaction of the
individual with the situation/context is named situational flow (Jackson et al., 2001). The
expression of situational flow is preferred within the scope of this study.
Flow experience in 3D MUVEs
3D MUVEs, which enable learners to discover and use their creativity, contribute to the
learners in learning by experiencing the outcome of an event with applied activities (Faiola
et al., 2013; Koffman & Klinger, 2007). Through features such as controllability, arousing
curiosity, aiming at individual interests and enabling users to experience a sense of presence, virtual worlds allow users to experience flow in 3D virtual environments. In virtual
worlds, learners can control their movements and the viewpoint of their characters. Being
also perceived as a game-based learning environment, virtual worlds stimulate users’ sense
of wonder about using the system. Additionally, the internal motivation of users increases
as they feel that they can find a new and an enjoyable way in the learning process. If they
are not motivated to apply the necessary effort, they cannot learn in these environments
(Tüzün et al., 2019). The immersive nature of 3D virtual worlds also makes users feel like
they are inside the environment (Hassell et al., 2012). However, they use 3D virtual worlds
not to experience flow or feel the sense of being there but for fun and becoming immersed
(Bartle, 2007). Huang et al. (2010) determined that users’ flow experiences during navigation in 3D MUVEs were associated with skills, challenges, interactivity and telepresence.
The interaction of avatars with each other in these environments, as well as the interaction
with objects while navigating and structuring the 3D environment, affects the users’ flow
experience (Hoffman & Novak, 2009). In these environments, how users process the information acquired through these environments in their cognitive processes also affects their
flow experience (Goel et al., 2013). In 3D virtual environments, through the tasks given,
users are facilitated to engage more, and immediate feedback based on user performance
increases users’ flow experience (Pagano, 2013). In their study investigating the effect of
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D. Doğan et al.
environmental features on flow experience in learning through virtual worlds, Choi and
Baek (2011) concluded that the factors of interactivity and representational fidelity predict
flow.
The zone of proximal flow
To enable student learning in 3D MUVEs, Lambropoulos and Mystakidis (2012) presented
a novel pedagogical framework, entitled the “Zone of Proximal Flow”, which integrates
Vygotsky’s (1978) Zone of Proximal Development Theory and Scaffolding Theory with
Csikszentmihalyi’s (2000) ideas about Flow. The zone of proximal flow is defined as the
area where flow takes place in the zone of proximal development. Therefore, to ensure the
optimal flow, groups should consist of individuals with different skills, and there should
be in-group assistance. In this regard, unlike flow experience, the zone of proximal flow
is defined as a social variable rather than an individual variable. On the other hand, this
seems to be more appropriate to the nature of 3D MUVEs.
The purpose of the study and research questions
This study aims to investigate the flow experience of participants in the role of instructional designers in 3D MUVEs in the process of learning through design by performing
group activities. In light of this information, in the study, answers to the following research
questions were sought.
When university students in the role of instructional designers create designs in 3D
MUVEs to solve authentic problems within the framework of learning through design,
1. Do their flow experiences show a statistically significant difference by a) gender and b)
overall grade point averages (OGPA)?
2. How does the flow that they experience change over weeks by components?
3. Does the flow that they experience show a statistically significant difference over weeks?
Method
Research design
This study was carried out with a time series design as a quasi-experimental method. The
time-series design involves performing repetitive measurements at certain times before and
after the intervention (Fraenkel et al., 2012, p. 276). In this research process, the data were
collected eight times from the same group at different times using the same measurement
tool.
Study group
The sample of the study consisted of 40 junior university students in total, who studied at
the Computer Education and Instructional Technology department at a public university
in Turkey. The students were enrolled in a 15-week elective course related to 3D MUVE
design. Most of them were female students (N = 22, 55%), whereas the male students were
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Exploring the role of situational flow experience in learning…
in the minority (N = 18, 45%). The ages of students ranged from 20 to 30 (M = 22.18,
SD = 1.693). Table 1 shows the demographic information of the sample.
As seen in Table 1, in terms of gender, the participants showed an almost homogeneous distribution. However, regarding overall grade point average (OGPA), an accumulation
between 3.00 and 3.25 (N = 19, 47.5%) and a decrease in 3.26 and above (N = 8, 20%) drew
attention. Additionally, the overwhelming majority of the sample did not use 3D environments. When we examined the daily average internet usage times, most of the participants
were found to use the internet for 4–6 hours per day (N = 22, 55%). Finally, it was noteworthy that close to three-quarters of the participants played computer games to some extent
(N = 25, 62.5%). To summarize the characteristics of the sample, it was a group familiar
with the internet and PC games but unfamiliar with 3D environments. This information
was used to create the design groups homogeneously.
Setting
The implementations were carried out in a computer laboratory with 40 identical all-inone computers on which the required software such as OpenSimulator was installed. The
official lecturer of the course in which the data were collected was also one of the authors
of this study. The students were already familiar with the computer laboratory and the lecturers since they had taken a course from them in the laboratory. All students, designing
instructional 3D virtual environments in the role of instructional designers in the study, had
taken the course "Instructional Design" in previous semesters, and so, they knew the basics
of instructional design.
Data collection instruments
A “Personal Information Form” was used to collect the personal information of the students, while the “Flow Scale” was used to identify their situational flow experience levels.
Table 1 Characteristics of the sample
Variable
Category
N
Percentage (%)
Gender
Female
22
55
Male
2.99 and below
3.00–3.25
3.26 and above
Never used
Used before
1–3 hours
4–6 hours
7 hours and more
Never play
1–2 hours
3–4 hours
5 hours and more
18
13
19
8
34
6
9
22
9
15
8
8
9
45
32.5
47.5
20
85
15
22.5
55.0
22.5
37.5
20
20
22.5
Overall Grade Point Averages (OGPA)
Weekly 3D environment use
Average Daily Internet Usage
Weekly PC Game Play
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Personal information form
To determine the personal information of the participants, a 13-item questionnaire that
was developed by the researchers and consisted of three parts was used. The first part consisted of four items related to the participants’ name and surname, gender, year of birth
and OGPA, while the second part covered three items about the participants’ computer and
internet usage status, and the third part included six items about the participants’ use of 3D
MUVEs and computer games.
Situational flow scale
Within the scope of the study, to measure the participants’ levels of situational flow experience, the 7-point Likert-type Situational Flow Scale that was developed by Sahranç (2008)
was used after getting the necessary consent. The scale was developed and validated with
university students. The scale consists of seven items listed under a single factor. Each item
in the scale measures the following features: (1) Skill-challenge balance, (2) Clear goals,
(3) Immediate feedback, (4) Concentration and focus, (5) Control, (6) Disappearance of
self-consciousness, (7) Autotelic experience. One can get the minimum and maximum
scores of 7 and 49 in the scale. A high score indicates that the individual’s flow experience
is high. The Flow Scale explains 47.21% of the total variance. The Cronbach’s alpha reliability coefficient of the scale was reported as .80.
Implementation process
To examine the change in the participants’ flow experience in the 3D MUVE learning
through design process, longitudinal research was conducted. During the 15-week study,
the participants used the OpenSimulator application, an open-source 3D MUVE, for individual and group work. While the participants studied individually for the first 7 weeks, as
of the 8th week, they started their environment designs with group work. The groups were
formed by the lecturers of the course considering the diversity of the students in terms
of gender, overall grade point averages (OGPA), grades in programming and instructional
design courses which they took in previous semesters since the characteristics of the group
members would affect the flow experience (Demir & Seferoğlu, 2021b). In the implementation process that started with 43 people at the beginning, after the groups were formed,
3 students left the course. At the beginning, while 8 groups were formed based on the
course achievement levels and genders of the participants, including 5 groups of 5 people, and 3 groups of 6 people, after 3 people left, the number of members in one of the
5-person groups decreased to 3, and the number of members in one of the 6-person groups
decreased to 5. In the design process, the designers used “Problem-Based Learning (PBL)”
as a theoretical framework. Project topics that were previously determined with subjectmatter experts were distributed to the groups by lot. During the design process, the students and subject-matter experts stayed in touch with each other. The students focused only
on the 3D design process. The project topics of the participants are given below.
• Tree identification It was planned to introduce trees that exist in a certain ecosystem.
The target audience was university students.
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Exploring the role of situational flow experience in learning…
• Online course orientation in distance education An environment where basic Turkish words are taught to foreign students was designed through the distance education
center of a public university.
• Library orientation A library at a public university was modeled to be used in introductory trainings about the library for university freshmen.
• Hospital orientation A hospital at a public university was modeled to be used in introductory trainings about the hospital for university freshmen.
• Pharmacy It was designed for the teaching of the students of the faculty of pharmacy.
• Virtual patient (the topic was given to two different groups) It was designed for the
teaching of the faculty of medicine students.
• Dentistry It was designed for the teaching of dentistry students.
During the 15-week course, the flow scale was administered eight times at the end of
each session. The coverage of different topics was taken into consideration in selection
of the weeks when the scale was applied. The scale was applied in the paper-and-pencil
form. A short flow scale was preferred to minimize the practice effect (Fraenkel et al.,
2012, p. 276). Figure 2 summarizes the implementation process.
The weeks when the flow scale was applied and the topics covered in these weeks are
as follows:
(a)
Week 2: General terms related to 3D MUVEs were explained, how these environments
were going to be used in instruction was mentioned, and some 3D MUVE examples
were shown. Additionally, technical information about the OpenSimulator software was
introduced. The participants used this application both individually and in groups. In
the first weeks, the users were asked to experience the environment individually to get
used to the environment. For this reason, the installation of the necessary programs for
the operation of the environment on personal computers and their connections with the
database were explained.
Fig. 2 Implementation process
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(b) Week 5: The participants who started to get used to the interface of the OpenSimulator software and learn how to create 3D designs began to master how to customize
their designs by adding multimedia materials such as audio, video and images to the
environment. Information was given on properties added to objects and how lighting
and region/estate settings in the OpenSimulator could be made.
(c) Week 6: One of the elements increasing the interaction of users in the OpenSimulator
software is animations. Therefore, third-party programs were shown to the participants
in which they could prepare animations for OpenSimulator. Besides, how to import
these into the application and how to use them with the characters were explained.
(d) Week 7: In addition to the design in the OpenSimulator software, pedagogical
approaches underpinning design in OpenSimulator are also important. For this reason,
in the 7th week of the design process, theoretical information about the Problem-Based
Learning (PBL) approach was conveyed to guide the participants. In this context, wellstructured and ill-structured problem situations, projects on how to use these in 3D
MUVEs and previous examples were shown.
(e) Week 8: In the OpenSimulator software, codes called “Scripts” are written to enable
the participants to interact with objects. Although the participants were familiar with
programming languages, they did not have any information about the specific programming language called the Linden Script Language (LSL) used in the OpenSimulator
platform. Therefore, the participants were explained how to write code in LSL and how
to add these codes to objects.
(f) Week 9: The participants, who started the design process with their groups by putting
their designs on paper as of the 8th week, began working on the server in accordance
with the sketches on paper in this week. They worked as a group on an island devoted
to them on the server. Firstly, they started the design of the island by deciding on the
objects they needed. In this week, they also shared their first oral presentation to share
design ideas. The lecturers gave feedback to the design groups.
(g) Week 11: Although their purpose was clear before starting the design process, as the
design process progressed, the participants began to make changes in their goals and
scenarios. During the collaborative work on the server, they continued their design
process by adjusting the group dynamics and changing scenarios. In this week, they
shared the progress of their designs with the lecturers and other design groups.
(h) Week 13: The design groups made oral presentations to share information about the
progress of their designs. The lecturers gave feedback to the design groups.
Figure 3 shows the design examples of the participants in 3D MUVEs at the end of the
process.
Data analysis
First of all, the data were transferred to and arranged in the Excel 2016 spreadsheet software and imported to SPSS 24. The lost data were filled in by the linear trend at point
method. Afterwards, merges were made to avoid less than five observations in the categories with the purpose of avoiding large differences between the categories, leading to
unreliable results. The total flow experience points of weeks were obtained by averaging
the items of the Flow Scale of each week. Gender and OGPA were the independent variables, whereas situational flow experience was the dependent variable. Median, arithmetic
mean, standard error of mean, standard deviation, frequency and percentage were used to
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Exploring the role of situational flow experience in learning…
Fig. 3 Design examples in 3D MUVEs
describe the data. Finally, the normality of the distribution of the data was checked using
Shapiro–Wilk test for all variables. Since it was observed that the data did not show a normal distribution, among non-parametric tests, Mann–Whitney U and Kruskal–Wallis H
tests were used for the cross-sectional data, and Wilcoxon signed-rank test and Friedman
test were used for the longitudinal data. For the pairwise comparisons after a statistically
significant Friedman test, Wilcoxon signed-rank tests were performed as the post-hoc test
to reveal the directions of the differences. To control the inflation of type I error rate, Bonferroni p-value correction was applied (Armstrong, 2014), which yielded a padjusted value
of .05/28 = .00178. The threshold level of significance was determined as .05. If a statistically significant difference was reached as a result of the tests, Cohen’s d effect size was
calculated to determine the significance of this difference in practice. According to Cohen
(1988), an effect size between .1 and .3 means small, between .3 and .5 means medium and
higher than .5 means large effect.
Findings
In this section, the findings are presented in titles by the order of the research questions.
Comparison of flow experienced by designers in 3D MUVEs by gender and OGPA
Table 2 shows the findings obtained using Mann–Whitney U test for the first research
question. As seen in Table 2, the female participants (Median = 5.79, M = 5.72, SD = .87)
were found to experience flow on a significantly higher level than the male participants
(Median = 5.34, M = 5.04, SD = .88) in Week 8 (U = 101.500, p = .009, d Cohen = .912).
According to Cohen (1988), this effect size was on a large level. No significant difference
was found for the other weeks.
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Table 2 The change of flow experience over weeks by gender
Weeks
Gender a
Median
M
Week 2
Female
5.31
5.39
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
5.29
5.86
5.57
5.71
5.35
5.14
4.86
5.79
5.34
5.71
5.50
5.86
5.55
6.00
5.79
5.55
5.47
5.17
5.73
5.24
5.66
5.28
4.97
5.05
5.72
5.04
5.51
5.32
5.78
5.44
6.08
5.84
5.60
5.30
Week 5
Week 6
Week 7
Week 8
Week 9
Week 11
Week 13
Mean of Weeks
SD
Mean Rank
U
p
.55
21.30
180.500
.633
1.08
.41
1.04
.58
.79
1.04
.86
.87
.88
.86
.87
1.02
.71
.36
.49
.41
.60
19.53
22.50
18.06
23.23
17.17
21.27
19.56
24.89
15.14
21.52
19.25
23.11
17.31
23.52
16.81
23.11
17.31
154.000
.230
138.000
.101
181.000
.643
101.500
.009**
175.500
.539
140.500
117
131.500
.069
140.500
.118
Cohen’s d effect size of week 8 is .912 (large level)
**p < . 01
a
Female = 22, Male = 18
To analyze the comparison of the flow experienced by the participants in the 3D
MUVEs according to OGPA, the findings obtained using Kruskal–Wallis H test are presented in Table 3. As seen in Table 3, the flow experience of the participants in the 3D
MUVEs did not show a statistically significant difference based on the variable of OGPA.
Descriptive findings regarding change of flow experienced by designers in 3D
MUVEs over weeks by components
As seen in Table 4, a significant decrease was observed in the students’ flow experience in
the 7th week’s practice. However, an increase in the 8th week drew attention. This increasing trend continued in the 11th and 13th weeks. When the trends were analyzed on the
basis of the components, it was seen that the disappearance of self-consciousness and autotelic experience components were relatively high. The components of skill-challenge balance, concentration and focus, and control, on the other hand, were found to be relatively
low.
To better analyze the trends in the participants’ flow experience, Fig. 4 was plotted
based on Table 4. In Fig. 4, the skill-challenge balance plot indicated that the challenge
of the task encountered was higher than the skill level of the individual except for the 7th
week where theoretical information about PBL was conveyed to the participants. Especially when it came to the completion stage of the project, it was observed that the challenge of the tasks to be performed while completing the objects that were expected to take
13
Exploring the role of situational flow experience in learning…
Table 3 The change of flow experience over weeks by OGPA
Weeks
OGPA
Median
M
Week 2
2.99 and belowa
5.29
5.20
.98
19.19
3.00–3.25b
3.26 and abovec
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
2.99 and below
3.00–3.25
3.26 and above
5.43
5.20
6.00
5.57
5.86
5.71
5.61
5.57
4.86
5.14
4.57
5.38
5.54
5.86
5.86
5.41
5.86
5.57
5.71
5.71
5.86
5.86
6.00
5.50
5.50
5.52
5.31
5.24
5.64
5.38
5.63
5.43
5.46
5.57
4.88
5.24
4.45
5.10
5.51
5.68
5.42
5.19
5.94
5.62
5.64
5.38
5.88
5.95
6.16
5.40
5.46
5.51
.81
.54
.72
.94
.47
.64
.85
.33
1.06
.71
1.14
.82
1.09
.61
1.01
.80
.45
.64
.90
1.28
.42
.45
.43
.51
.56
.42
21.32
17.93
22.77
18.00
20.29
19.04
20.63
20.07
19.46
22.61
13.93
15.77
20.97
25.21
22.08
15.97
27.07
19.73
20.45
19.29
18.00
19.45
25.21
19.12
20.29
20.86
Week 5
Week 6
Week 7
Week 8
Week 9
Week 11
Week 13
Mean of Weeks
SD
Mean Rank
Chi-square (χ2)
p
.553
.758
1.367
.505
.152
.927
3.017
.221
3.402
.183
5.532
.063
.064
.968
1.931
.381
.130
.937
a ,b,c
The numbers of observations in the cells were 13, 19 and 8, respectively
place in the 3D design, animation, script writing, creating interactive menus and evaluation
process was higher than the skill levels of the individuals with the exception of the last
week of the semester. What the participants wanted to do started to become clear as of
the 8th week and reached its peak value in the last week. This increased the clear goals
component. The participants were provided with immediate feedback by the lecturers for
every question they asked about their tasks in all weeks. Therefore, there was a steady
increase in the immediate feedback component except for the 6th and 7th weeks. This component reached its peak in the 13th week. It was determined that the students had some
hardship in gathering their attention between the 7th and 9th weeks, especially in the 7th
week as a result of their passive status owing to theoretical information delivery. The 7th
week had a similar impact on the control component. Furthermore, the students seemed
to lose control to some extent in the last three weeks possibly due to their hurry to finish
the project on time. Possibly because of the same effect, it was seen that the participants
experienced a steady decrease in the disappearance of self-consciousness component in the
last three weeks. In general, they became immersed in the tasks during the design process.
13
D. Doğan et al.
Table 4 The change of flow experience over weeks by components
Week
Components of flow
Mean of weeks
1
2
3
4
5
6
7
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
Week 2
5.0 (.9)
5.3 (1.4) 5.0 (1.2) 4.9 (1.3) 5.0 (1.1) 6.2 (1.2) 5.7 (1.5) 5.3 (.8)
Week 5
Week 6
Week 7
Week 8
Week 9
Week 11
Week 13
Mean of components
5.1 (1.3)
5.4 (.8)
5.1 (1.1)
5.2 (1.2)
5.2 (1.2)
5.1 (1.5)
6.0 (.7)
5.2 (1.1)
5.3 (1.2)
5.4 (1.0)
5.0 (1.1)
5.4 (1.1)
5.5 (1.0)
5.8 (1.0)
6.2 (.6)
5.5 (1.0)
5.3 (1.0)
5.1 (1.1)
4.8 (1.2)
5.3 (1.4)
5.3 (1.0)
5.5 (1.2)
6.1 (.8)
5.3 (1.1)
5.4 (1.4)
5.4 (1.2)
4.4 (1.7)
5.0 (1.7)
5.0 (1.6)
5.6 (1.2)
6.0 (.8)
5.2 (1.4)
5.3 (1.2)
5.4 (1.1)
4.6 (1.3)
5.3 (1.4)
5.1 (1.4)
5.4 (1.3)
5.6 (.9)
5.2 (1.2)
5.9 (1.1)
5.9 (1.2)
6.2 (.9)
6.2 (1.0)
6.0 (1.2)
5.9 (1.3)
5.9 (1.2)
6.0 (1.1)
6.2 (1.0)
5.8 (1.1)
4.9 (1.5)
5.5 (1.3)
5.8 (1.1)
6.0 (1.1)
6.0 (1.0)
5.8 (1.2)
5.5 (.8)
5.5 (.7)
5.0 (1.0)
5.4 (.9)
5.4 (.9)
5.6 (.9)
6.0 (.4)
5.5 (.5)
Standard errors of the means are presented in “Appendix”
1 = Skill-challenge balance, 2 = Clear goals, 3 = Immediate feedback, 4 = Concentration and focus, 5 = Control, 6 = Disappearance of self-consciousness, 7 = Autotelic experience
Fig. 4 The change of flow experience over weeks by components
13
Exploring the role of situational flow experience in learning…
It is interesting to note that the disappearance of self-consciousness component showed an
opposite pattern compared to the other components of flow. Examining the autotelic experience component, it may be expressed that the participants were active not only physically
but also cognitively in the first and last weeks. To sum up, although a floating plot was
seen in all the components of the flow experience, it was evident that there was a slow but
steady upward trend towards the end of the semester. To ascertain whether these floating
plots showed statistically significant differences or not, the flow experiences of the designers in the 3D MUVEs were compared by the weeks.
Comparison of flow experienced by designers in 3D MUVEs by weeks
To answer this research question, first of all, Friedman test was performed with the flow
score means of each week to determine whether the flow experienced by the participants
differed by the weeks. For practical reasons, the general flow score means of the weeks
were compared rather than the means of the individual components. As a result of this test,
it was concluded that the flow experienced by the designers in the 3D MUVEs differed
significantly by the weeks (χ2 (7) = 37.425, p = .000). Wilcoxon signed-rank tests were conducted between the weeks to determine the direction of the differences. Table 5 presents
the results of the post-hoc Wilcoxon signed-rank tests.
As seen in Table 5, as a result of performing post-hoc Wilcoxon signed-rank tests with
Bonferroni correction, it was revealed that the flow experience measured in the 13th week
practice differed from 2nd (Z = 4.296, p = .000), 5th (Z = 3.311, p = .0009), 6th (Z = 3.420,
p = .0006), 7th (Z = 4.687, p = .000), 8th (Z = 3.507, p = .000) and 9th (Z = 3.604, p = .000)
weeks. The differences favored the 13th week. Moreover, the flow experienced in the
7th week practice was found to be lower than the practice in the 11th week (Z = 3.366,
p = .0008).
Results and discussion
Within the scope of this study, while the participants were asked to create instructional
designs in a 3D MUVE, it was aimed to analyze the change in the flow experience of the
participants by gender, OGPA, components and the weeks of the course.
Change of flow by gender and OGPA
According to the results of the study, the flow experience of the participants did not vary by
the variables of gender and OGPA. The only exception about gender was the finding that,
in the 8th week, the female participants had a higher flow experience level in comparison
Table 5 the results of comparison of flow experience by weeks using post-hoc Wilcoxon signed-rank tests
Weeks
2
5
6
7
8
9
11
13
*The difference
13
13
13
11, 13
13
13
7
2, 5, 6, 7, 8, 9
The direction
2 < 13
5 < 13
6 < 13
7 < 11, 13
8 < 13
9 < 13
7 < 11
2, 5, 6, 7, 8, 9 < 13
*As a result of Bonferroni correction, the p value was adjusted to .00178
13
D. Doğan et al.
to the male participants. In the relevant week, the participants had to interact with objects
in a 3D MUVE without knowing the syntax of the application’s unique programming language by writing programs with block-based programming tools. The Linden Script Language (LSL) has traditional code statements and complex syntax rules, so, it is difficult to
learn for students. However, block-based programming tools allow students to recognize
blocks instead of recalling syntax to support inexperienced used in their first programming
steps (Tumlin, 2017). Block-based programming eliminates syntax complexity as it uses
a drag-and-drop feature (Çınar et al., 2019). Additionally, block-based programming languages support constructionism by tinkering (Maloney et al., 2010) which helps female
users gain valuable information about the features of a novel environment and increases
their self-efficacy (Spieler, 2018). Considering all these, it may be asserted that the female
participants’ programming skills were more compatible with the challenge of the work in
comparison to the male participants. This may have caused the female participants to experience more flow. However, since there was no difference in flow experience in the other
weeks of measurement by gender, it may be concluded that gender does not have an overall
effect on flow experience during 3D designing in MUVEs.
It was noteworthy that there was no significant difference in flow experience according
to the variable of OGPA. In fact, flow experience is directly related to the skills of individuals (Csikszentmihalyi, 1991). However, it should be noted here that, OGPA measures
not only the skill of the individual but also a combination of intelligence, perseverance
and diligence in general. In this sense, the OGPA of the sample of this study might not
have been directly related to their design knowledge and skills in 3D MUVEs. Moreover,
the balance between challenge and skill is just one of many factors that form flow experience (Csikszentmihalyi, 1991). In this context, it makes sense that flow experience did not
change by OGPA.
Change of flow by components
When the participants’ flow experiences were analyzed by the components, it was concluded that the designers experienced every flow component in the design process to some
extent. In general, there was a continuous increase towards the end of the semester, notwithstanding fluctuations. On the other hand, it is known that there is no need for all components of flow to occur to achieve flow (Csikszentmihalyi, 1991). It was stated that, in
cases where the clear goals, skill and challenge balance and immediate feedback components of flow are present, the other components follow (Csikszentmihalyi, 2004; 2005).
One cannot become immersed into action without having any idea of the goal one must
accomplish (Csikszentmihalyi, 2014). Consequently, the lack of a clear goal for one’s
action hinders the emergence of a full flow experience (Guo, 2004). In this study, the clear
goal of the designers was to create a 3D MUVE through a group study. Aside from the
clear goal, challenging tasks that increase the individual’s skills to a certain extent reveal
the flow (Snyder & Lopez, 2007). At this point, the concept of over-learning in education is
another factor that plays a critical role in students’ skills to reach the flow. In over-learning,
the mind integrates actions and envisions them, instead of performing many actions (Csikszentmihalyi, 1991). Throughout the design process of this study, the participants faced
various challenges. To overcome these challenges, they acquired new information and
learned a new software every week. Nonetheless, flow experience does not occur only with
the balance between the challenge and the individual’s skill (Guo, 2004). One does not
have the opportunity to evaluate their own performance in the process (Csikszentmihalyi,
13
Exploring the role of situational flow experience in learning…
2014). In cases where one has not received feedback regarding the accuracy of their action
in the process, one moves away from having a mental flow experience and begins to worry
about whether their actions are correct or not (Guo, 2004). In short, continuous feedback
should be provided to focus the attention of individuals on higher-level tasks (Kiili, 2005).
In this study, the participants presented the environments they designed and received feedback from the lecturers and their peers. Furthermore, the questions asked by students to the
lecturers and vice versa during the design process had the characteristics of feedback. This
feedback helped them re-determine their goals.
Individuals do not enjoy doing the same thing for a long time. For this, activities should
lead to development and discovery to create flow (Csikszentmihalyi, 1991). In this study,
the participants completed a different task of designing a 3D environment each week. They
produced solutions to overcome challenges, and they implemented and evaluated these
solutions. In the process of learning through design, designers think closely about ideas
and concepts, and consequently, learn to produce the desired results (Mishra & Girod,
2006). In fact, design projects enable students to be active participants, and they offer
opportunities for collaboration, deep thinking and creative problem-solving. For this reason, the participants enjoyed the design experiences with different challenge levels, so they
became intrinsically motivated. That is to say, it is known that an individual with flow
experience has positive motivation to work (Kalaycı et al., 2011). Because of these matters,
the participants concentrated on design projects, felt that they were in control and lost selfconsciousness during the 3D MUVE design processes.
Change of flow by weeks
In the study, it was seen that the flow experience in the 7th week differentiated towards
a negative direction, while the flow experience in the 13th week differentiated in a positive way. This may have been due to the theoretical knowledge given to the participants
about PBL in the 7th week. It was especially noteworthy that the concentration and focus,
control and immediate feedback factors of flow were the lowest factors in the 7th week.
The more concentration a task requires in terms of attention and workload, the more it is
adopted by the individual (Sweetser & Wyeth, 2005). In this context, it may be considered
that there was a significant decrease in the flow experience of the participants due to the
low interaction, control and immediate feedback of the theoretical knowledge transferred.
On the other hand, regarding the 13th week, the fact that the participants introduced the
projects they were working on to the lecturers and their peers was effective. In this week,
the groups were given feedback by both the lecturers and theirs peers, leading the way for
them to improve their projects. It is well known that feedback on performance promotes the
flow experience (Pagano, 2013). In line with this, it was concluded that the clear goals and
immediate feedback factors of flow were the two highest factors in the 13th week.
Conclusion, recommendations and limitations
This study aimed to explore the role of situational flow experience in a 15-week design
education course where students in the role of instructional designers strived to find
design solutions to authentic problems by designing 3D MUVEs in groups drawing on
the constructionism, learning by doing, problem-based learning (PBL) approach and the
zone of proximal flow theoretical frameworks. Forty university students were enrolled
13
D. Doğan et al.
in the study. The novelty of this study was that it handled the situational flow experiences of designers studying in groups during 3D MUVE design tasks based on several theoretical frameworks to solve authentic problems across one semester. The results
revealed that gender and OGPA had no significant effect on the students’ flow experience. Moreover, the emergence of autotelic experiences and the disappearance of selfconsciousness during the design process led to an increase in the flow experience of
the students. However, the designers encountered various tasks on different levels of
challenge, and this caused fluctuations in their flow experiences. For instance, the participants creating designs in 3D MUVEs diverged from the flow experience due to lack
of feedback, control and concentration when theoretical knowledge was conveyed. Conversely, they experienced a relatively high level of flow thanks to clear goal and feedback when they presented their projects. In summary, transfer of continuous feedback
from the lecturers and peers to the designers, setting clear and realistic goals and adjusting challenge levels in the design process enabled the participants to focus on what they
were doing and not to lose control over their actions.
While it is stated that the flow experience of designers in 3D MUVEs varies over
weeks, it should be kept in mind that the mean value of the flow experience in the 7th
week, which was the week with the lowest flow experience level, was on a high level as
5 points. Another point to be noted here is that the difference between the weekly flow
means was minor. The mean value of the 13th week with the highest flow experience
was 6. This mean value was only 1 point higher than the mean value of the 7th week.
In this study, the individual flow experiences in the groups were examined. In future
studies, “group flow experience” rather than individual flow experience in groups might
be studied. In this context, the effects of variables such as group cohesiveness and
atmosphere on group flow experience may be investigated. Besides, researchers may
examine the impact of students’ group flow experiences on the quality of their designs.
As far as practitioners in the field of design education are concerned, practitioners
should make students more active by giving them control during classes and provide
frequent feedback to students’ projects so that the students can enter the zone of proximal flow. Additionally, researchers may adjust the challenge levels of learning tasks
based on the skill levels of students, and accordingly, set clear goals. This way, students
can focus on learning a task, have an autotelic experience and lose self-consciousness.
This study had several limitations. First, this study was carried out with 40 participants who were reached by the convenience sampling method. Therefore, the findings
of this study may only be generalized to samples that have characteristics similar to
this sample. In this study, each component of flow was measured with only one scale
item. The reason for this preference was to minimize a potential fatigue effect. For this
reason, the components of the concept of flow may be measured with more items in
future studies. Moreover, flow experience was measured using a scale since it was easy
to apply repetitively. In future studies, the authors recommend that flow may be handled
with physiological measurements such as heart rate and sweating.
Appendix
Standard error of the mean (SEM) of the flow experience over the weeks by the components
13
Exploring the role of situational flow experience in learning…
Week
Components of flow
Weeks
1
2
3
4
5
6
7
SEM
SEM
SEM
SEM
SEM
SEM
SEM
Week 2
.146
.215
.196
.202
.179
.183
.230
.131
Week 5
Week 6
Week 7
Week 8
Week 9
Week 11
Week 13
Components
.210
.126
.176
.197
.182
.239
.113
.174
.193
.163
.179
.179
.155
.151
.096
.158
.156
.180
.193
.219
.165
.192
.126
.174
.222
.192
.267
.271
.254
.198
.134
.221
.186
.177
.213
.213
.226
.198
.149
.190
.175
.188
.148
.159
.186
.198
.183
.174
.158
.169
.245
.204
.177
.177
.154
.190
.124
.111
.150
.147
.136
.142
.070
.080
1 = Skill-challenge balance, 2 = Clear goals, 3 = Immediate feedback, 4 = Concentration and focus, 5 = Control, 6 = Disappearance of self-consciousness, 7 = Autotelic experience
Declarations
Ethical statements We declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere. On behalf of the Co-Author, the corresponding Author
shall bear full responsibility for the submission.
Informed consent Informed consent was obtained from all individual participants involved in the study.
Conflict of interest We know of no conflicts of interest associated with this publication, and there has been
no significant financial support for this study that could have influenced its outcome.
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