TYPE
Original Research
26 October 2022
10.3389/frsus.2022.841643
PUBLISHED
DOI
REVIEWED BY
Quantitative validation of a
proposed technical
sustainability competency
model: A PLS-SEM approach
Bogdan Fleacă,
University POLITEHNICA of
Bucharest, Romania
Denise Voci,
University of Klagenfurt, Austria
Nasiru Mukhtar1,2 , Yusri Bin Kamin1* and
Muhammad Sukri Bn Saud1
*CORRESPONDENCE
1
OPEN ACCESS
EDITED BY
Larisa Ivascu,
Politehnica University of
Timişoara, Romania
Yusri Bin Kamin
p-yusri@utm.my
Department of Technical and Engineering Education, Universiti Teknologi Malaysia, Johor Bahru,
Malaysia, 2 Department of Science and Technology Education, Bayero University, Kano, Nigeria
SPECIALTY SECTION
This article was submitted to
Modeling and Optimization for
Decision Support,
a section of the journal
Frontiers in Sustainability
22 December 2021
12 September 2022
PUBLISHED 26 October 2022
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ACCEPTED
CITATION
Mukhtar N, Kamin YB and Saud MSB
(2022) Quantitative validation of a
proposed technical sustainability
competency model: A PLS-SEM
approach. Front. Sustain. 3:841643.
doi: 10.3389/frsus.2022.841643
COPYRIGHT
© 2022 Mukhtar, Kamin and Saud. This
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The use, distribution or reproduction
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or reproduction is permitted which
does not comply with these terms.
The demand to enact sustainability into higher education so as to optimistically
shape the wider society and biosphere has been stressed by United Nations
Educational, Scientific and Cultural Organization (UNESCO). One of the
approaches is through rethinking and revising education at all levels to
capture obvious forms of present and imminent societies on the development
of sustainability knowledge, skills, perspectives and values. Several Higher
Education Institutes (HEIs) have started to implement a number of facets
to that effect, such as signing a climate commitment, working towards
plan to make their campuses climate-neutral, and making sustainability
their guiding principles and top priorities. However, analogous modifications
to the curriculum are lagging behind. As a consequence, this study is
set to quantitatively validate the technical sustainability competency model
suitable for incorporation into Higher National Diploma electrical/electronic
engineering curriculum in Nigeria. The authors used findings of their earlier
work to develop a questionnaire for collecting data from 168 respondents
in the study area, and consequently subject the data to descriptive and
inferential statistics with the aid of PLS-SEM approach. The study discovered
competencies suitable for incorporation into the curriculum. This includes
cognitive skills in Eco-design and Life-Cycle Assessment; Research; Modeling,
Simulation and Optimization; and Recycling/Renewable Resources. The study
also found suitable psychomotor skills in Sustainable production, Use of
modern engineering software tools, Operation/troubleshooting of electrical
machines and devices, Communication/Information and Communication
Technology, and waste-to-energy technology. Appropriate attitudes/values in
Engineering ethics, Occupational safety and health, and Inter-generational
equity are also discovered. This research is purely quantitative in nature
carried out through administering questionnaires to respondents in one geopolitical zone of the country. Thus, conclusions derived from these sources
rely on the genuineness of the information provided by the participants. The
findings offer accreditation body as well as curriculum developers in Nigerian
polytechnics with a validated model of technical sustainability competences.
This could be useful in the events of curriculum upgrade or renewal to integrate
sustainability.
KEYWORDS
Higher National Diploma, incorporation of sustainability, PLS-SEM approach,
technical sustainability, competency model
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Introduction
development into all features of education and learning. This
development warrants Higher Education Institutes (HEIs) to
begin to mount sustainability programmes, and the field has
already got significant institutional impetus over the years (Wiek
et al., 2011). Moreover, Louw (2013) stated that several HEIs
have started to implement a number of facets to that effect,
such as signing a climate commitment, working towards plan to
make their campuses climate-neutral, and making sustainability
their guiding principles and top priorities. (Tilbury, 2011)
stated that curriculum and pedagogy are at the heart of
higher education experiences which require to be transformed
if HEIs are to make a significant contribution to sustainable
development. This is because HEIs have a range of possibilities
to take on and promote sustainable human development.
However, Elder (2009) posited that analogous modifications to
the curriculum are lagging behind. Bauer et al. (2021) stated
that: “In the face of current sustainability crises, the survival
of global society depends on competencies that have so far
been of little relevance due to longstanding ignorance of the
consequences of our exploitative economic system” (p. 1).
In line with this development, this paper therefore, validated
technical sustainability competencies that were investigated in
the earlier work (Mukhtar et al., 2020) conducted by the
researchers, using both qualitative (document analysis and
semi-structured interview), and quantitative (modified Delphi
survey) methods with a fewer participants. The present study
used the earlier findings to develop a questionnaire that
was administered to a larger sample of the population, and
subsequently used a Partial Least Square-Sequential Equation
Modeling (PLS-SEM) approach in order to quantitatively
validate the competencies. A model of proposed technical
sustainability competences for integration into the Higher
National Diploma (HND) electrical/electronic engineering
curriculum in Nigeria was later formulated. Sufficient inclusion
of technical sustainability competencies such as eco-design,
life-cycle assessment, sustainable production, waste-to-energy
technology, recycling, engineering ethics, and Occupational
Safety Health (OSH) among others, into the said curriculum
will help the graduates to be fully prepared to work in the
manufacturing industries, and contribute in the uplifting of such
industries in realizing their sustainability goals and that of the
society and the country at large.
The world’s geometric population growth, the advent of
industrial transformation, new standards of lifestyle preoccupied
with growing earnings, ill-defined distribution of world’s
resources, and several other human factors have jointly
contributed to the stressed earth’s ecosystem. Chu et al.
(2013) stressed that yearly CO2 secretion climbs to more
than 30.6 gigatonnes worldwide. Africa, in particular, faces
numerous challenges that cause negative environmental impacts
including increased climate change susceptibility, desertification
of arid areas, deforestation, rapid urbanization, degeneration
of biological resources, degradation of coastal and marine
habitats, intensified water shortage and stumpy quality,
prevalent poverty, pitiable economic performance, ineffective
trade policies unfavorable toward peace and development,
defective technology base to meet existing demand, occurrences
of civil conflicts, and escalation in unlawful trade in minerals
and other natural resources (Lotz-Sisitka et al., 2015). Most
of these problems have complex roots and drivers and are
related to insufficient sustainability education as a driver for
sustainable development and durable ecosystems. The human
race and other living species have, therefore, plunged into an
entangled calamity with respect to the environmental, economic,
social, and technical facets of life, referred to as sustainability
challenges. Sustainability researchers, such as Doppelt (2012)
believed that these devastating problems continued to exist
not because we lack efficient energy, technology, or policy
guidelines, but because of our huge paucity of thinking in
relation to human history. Our thinking, decisions, and actions
will create either more scarcity and suffering or a future
of greater abundance and higher quality of life. Human’s
“Take-Make-Waste” thinking as coined by Doppelt (2012), has
aggravated atmospheric greenhouse gasses to a deadly echelon
and guided the earth to the precipice of catastrophe.
Responding to these scary phenomena, sequence of
conferences were organized while a number of charters and
declarations were made, and outcomes were announced and
published in form of action plans and policies. The salient
among these is the World Commission of Environment and
Development, also known as Brundtland Report which proffer
a viable solution to these problems. The report coined a term
“sustainable development,” and was defined as “development
that meets the needs of the present without comprising the
ability of the future generations to meet their own needs.”
A common vital feature identified by the commission was
education which was emphasized as a decisive instrument for
advancing the sustainable development, as well as improving the
ability of populace to tackle sustainability issues (United Nations
Educational Scientific Cultural Organization, 2006; Cheah et al.,
2012; Lozano et al., 2013). Accordingly, the United Nations
(UN) pronounced 2005–2014 as the “UN decade for education
for sustainable development” (DESD). The main object was to
incorporate the philosophies, ideals and practices of sustainable
Frontiers in Sustainability
Literature review
The literature review is discussed under three (3)
subsections. First, we described the concept, emergence,
and relevance of technical sustainability in engineering
education. Second, we argued that competencies (knowledge,
skills, and attitudes) in technical sustainability need to be
identified and infused into the engineering curricula to promote
manufacturing processes and industrial practices that are less
invasive or destructive to the environment and society. We also
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stressed that the development of the proposed model requires
being subjected to rigorous and diverse phases of validation
procedures including sequential equation modeling (SEM)
using the partial least squares (PLS) approach. Finally, we
provide a detail explanation of the origin of the research that
forms a clearly formulated research gap.
the environment to be the at the receiving end of the negative
impacts of engineering processes (Rosen, 2012).
Technical sustainability as viewed by Rosen (2012) is the
sustainable use of engineering in systems, which includes
processes and technologies for reaping natural reserves,
changing them to useful kinds, transportation and storage, and
the use of engineering products and processes to afford useful
services (p. 2,271). Hibbard (2009) provides us with six key
steps to make engineering more sustainable: optimizing the
use of fossil fuels, reducing or eliminating pollution, recycling,
recovering energy, and saving time. Therefore, for efficient
and sustainable engineering, industries and manufacturers alike
must device means to reduce, reuse, and recycle materials
and products. This is to say, wastes from one part of the
system should be used as inputs to other parts of the system.
Also, the extraction of mineral resources and the design of
products and processes should be modified and improved
to take the environment into consideration so as to avoid
the ever-increasing depletion of the ozone layer. In the same
vein, research on sustainable materials should be popularized
among material scientists to replace traditional ones which
help in reducing the environmental impact of their processing
and application. Similarly, Information and Communication
Technology (ICT) has the ability to change people’s job approach
and even their workplace, hence the nature of urban areas.
ICT is increasingly modifying the methods that business
and industrial ventures are run, which results in enhancing
the effectiveness of all transportation systems, among other
sectors of the economy. It is not the intention of this paper,
to examine the essential factors for achieving engineering
sustainability, but rather, the paper empirically investigates
the suitable competencies (KSA) in technical sustainability
that HND engineering graduates should acquire in order to
prepare them for assisting in providing technical solutions to
climate-related issues, and assessment of the relevance and
applicability of carbon management standards in industries and
manufacturing organizations.
The concept of technical sustainability
The concept of Sustainable Development (SD) generally
has its roots in the Brundtland Report where it was referred
to as “development that meets the needs of the present
without compromising the ability of future generations to
meet their own needs” (World Commission of Environment
Development, 1987, p. 43). While Mihelcic et al. (2003)
described sustainability as a design of human and industrial
systems to ensure that humankind’s use of natural resources
and cycles does not lead to diminished quality of life due to
either loss in further economic opportunities or adverse impacts
on social conditions, human health and the environment.
Three interlocking elements were also identified in the report
as major constituents of SD, viz, environment, society, and
economy. Several definitions, descriptions, and discussions on
SD among scholars and policy makers are conducted based
on the three pillar model of SD. A lot of researchers in nonengineering academic fields have advocated for the inclusion of
other dimensions into the SD discourse. This includes cultural,
institutional, judicial, and political sustainability (Spangenberg,
2002; Lähtinen and Myllyviita, 2015). However, researchers in
engineering sustainability such as Rosen (2012) and Sianipar
et al. (2013) have proposed a different pillar of sustainability
which is termed ‘technical sustainability’. This is due to
the inappropriateness of just 3 pillars of sustainability when
engineers attempt to develop sustainable and efficient products,
processes, and systems. Rosen (2012) argued that even though
technical sustainability was not identified as an independent
pillar of SD in the Brundtland Report, it is implicitly connected
to each one.
The development of technical sustainability is paramount
to adequately addressing climate and environmental problems
facing the entire globe. Technical sustainability addresses a wide
variety of mechanical and technical factors that constitute the
design and manufacture of products. It promotes manufacturing
processes and industrial practices that are less invasive or
destructive to the environment, society, and economy and yields
ideally, neutral or positive effects on these contexts. Kreith
(2012) is of the opinion that technical sustainability stands high
and that no subject is more vital to the engineering profession
or the wider world that we live in. The pursuit of technical
sustainability is imperative since its nature is worldwide. This
is because every country in the world makes use of engineering
services as well as exploits and consumes resources, which makes
Frontiers in Sustainability
The need for technical sustainability
competencies
Competency is a functionally linked complex of knowledge,
skills, and attitudes that enable successful task performance
and problem solving (Wiek et al., 2011). The United States
Department of labor defined competency as “a cluster of
related knowledge, skills, and abilities that affects a major part
of one’s job (a role or responsibility), that correlates with
performance on the job, that can be measured against wellaccepted standards, and that can be improved through training,
development, and experience.” This definition implies that every
job requires three-sided expertise for it to be accomplished.
These are the theoretical cognition of the job (knowledge), the
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stressed the importance of establishing the competency of an
individual and/or a competency model for an occupational role,
as it is becoming an increasingly versatile and powerful tool in
human resource management.
Sustainability challenges such as increase in CO2 emissions,
deforestation, persistent increase in fossil fuels and biomass
consumption, bushfires, use of inefficient technologies, water
shortages, ecosystem loss, ocean acidification and sea level
rise, disruption of food production and the food chain,
more extreme weather events, and the spread of diseases
occur as a result of normal systemic malfunction induced
by overly complex and high-risk technologies and production
systems. As a result, training the graduates to acquire
adequate competences in technical sustainability is inevitable for
minimizing the mentioned challenges. Nagel et al. (2011) and
Hidalgo and Arjona Fuentes (2013) stressed that implementing
changes in the curriculum to educate students in technical
sustainability through infusing requisite competences is essential
in order to produce graduates with higher-level cognitive
and critical as well as problem solving skills, to supply
sufficient solutions to complicated technical obstacles. Technical
sustainability competences will enhance HND graduates’
understanding of technical aspects of life through acquiring
requisite competencies. This understanding will help them
deal adequately with the future sustainability challenges in the
workplace and the broader society. This requires the upcoming
Twenty-first-century graduates of tertiary institutions to possess
technical sustainability competencies such as innovative skills in
problem-solving, and the ability for assessing the consequences
of their actions outside the immediate walls of their professions.
Most of these sustainability challenges listed above are
caused by the manufacturing industries that are the major
employers of HND graduates (in the area of the study) and
constitute the vast majority of businesses and form the economic
backbone of the area in terms of employment, investment, and
their overall contribution to GDP. Nevertheless, manufacturing
industries are beyond doubt, the major contributors to pollution
and climate change because they constitute mainly machines
and other electrical/electronic equipment for their operations,
and are driven or powered by fossil fuels and electricity. This
is a reason why they are regarded as part of structures that
contribute a lot to the emission of greenhouse gases which
leads to environmental degradation and other sustainability
problems. Furthermore, most of the natural resources used
by the manufacturing industries are uncontrollably explored
from the earth’s crust without care for the environment
and other life supporting systems. As such manufacturing
industries are under increasing societal pressure to become
more technically sustainable. One such approach is to equip
the graduates, who are to become the employee, with requisite
technical competences. For an HND graduate to be regarded
as sustainability-literate, they have to acquire competences in
technical sustainability that encourages, supports, and advances
manual dexterity of executing the job (skills), and the ethics
of the job (attitudes/values). It also implies that proficiency in
any competency is achieved via constant practice, and has to
be subjected to some standardized measurement procedures.
Therefore, competency can be seen as the knowledge base
(subject matter and content areas), the skills (techniques and
abilities), and attitudes (personal approach and motivation) used
in combination to perform a task.
Applied to sustainability, competency represents a complex
and integrated set of knowledge, skills, abilities, attitudes,
and values that people bring into play in different contexts
(society, education, labor, and family) to address situations
involving environmental, economic, social, and technical issues,
as well as to act upon and transform reality according to
sustainability criteria. For one to live sustainably, one requires
to build up capacities to bring together a range of qualities,
skills, knowledge, values, and dispositions which advance
sustainability actions in a given perspective. In view of this, Wiek
et al. (2011), define sustainability competencies as complexes
of knowledge, skills, and attitudes that enable successful
task performance and problem-solving with respect to realworld sustainability problems, challenges, and opportunities.
Moreover, technical sustainability concentrates on a broad
range of mechanical and technical issues that establishes the
design and manufacture of products (Pappas, 2012). These
include the scientific research and appropriate technology
corroborating product design, function, and development; ease
and efficiency of durable construction and use; maintenance
and functioning capabilities that meet the objectives for which
the product is designed; material selection and reduction,
recovery, and reuse or disposal of parts of unused materials
(Nagel et al., 2011). In view of this, competences that will
help in preparing and effectively equipping the students to
reasonably think and act in a sustainable manner, both in
his/her work place or broader society are here referred to as
“technical sustainability competences.” Technical sustainability
competencies are, therefore, knowledge, skills, values, and
dispositions about sustainable engineering, which is a practice
that encourages, supports, and advances among others, technical
sustainability via effective resource utilization, reduced emission
of greenhouse gasses, as well as thought of the effects of
novel technologies, procedures, and practices on the broader
society. International Society of Sustainability Professionals
(2010) reported that “technical expertise” came second in a
survey carried out to identify top skills that students would
need in order to be successful as sustainability professionals.
Identifying, establishing, and developing a competency model
has a long time root in human resource management (HRM).
This is because, with a competency model and appraisal tools
in place, corporations can clearly describe the expertises that
are essential for every job as well as trace and detect the skills
gaps within their employees, permitting the corporation to be
governed more professionally. In support of this, Collin (1997)
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deficiencies: Data were first collected through document
analysis, and then through semi-structured interviews involving
fewer participants. The quantitative section also used only
28 participants to collect data through three rounds of a
modified Delphi survey (The first round survey emanated
from the findings of the qualitative section). Perhaps the
greatest criticism of the Delphi technique is its lack of perceived
statistical rigor compared to purely quantitative research
methods that are systematized and experimentally confirmed
propositions of the natural sciences. Its lack of probability
sampling, the impossibility of accounting for unseen events,
and the absence of clearly defined procedures and processes
for conducting Delphi studies are just some of the features that
differentiate it from controlled scientific methodologies. In order
to strengthen and clear the model away from these anomalies,
there is a need to validate the findings of the earlier work. The
authors, therefore, went to the field again and collected data
from the larger sample of the respondents using a questionnaire
emanating from the findings of the earlier work for more
rigorous sequential equation modeling using Smart PLS 3.
The authors presented to the larger sample, the questionnaire
containing the competencies in technical sustainability as
screened, rated, and confirmed in the earlier work. These
larger samples were asked to go through the competencies,
rate them, and re-confirmed their appropriateness or otherwise
for inclusion into the HND electrical/electronic engineering
curriculum in Nigeria. The authors used PLS-SEM in the
analysis section primarily because the objective of the analysis
is predictive in the sense that this study attempts to explain or
predict the relationship between the exogenous and endogenous
constructs. Also, PLS-SEM was opted for in this study, since the
measurement philosophy in the model is by estimation with the
composite factor model using a total variance.
the technical context of sustainable development via effective
resource utilization, lessening emission of greenhouse gases, as
well as thought of the effects of novel technologies, procedures,
and practices on broader society. The graduate also requires
building up capacities to bring together a range of qualities,
skills, knowledge, values, and dispositions which advance
sustainability actions in a given perspective. Unfortunately,
these challenges would continue to prevail in our societies
unless necessary actions are taken from the grassroots, by way
of ensuring that knowledge, skills, and attitudes (values) in
technical sustainability are adequately entrenched in every level
of the educational curricula.
As a prerequisite for tomorrow’s electrical/electronic
engineers to be able to work toward a sustainable future, they
must be thoroughly trained in sustainable engineering through
the acquisition of technical sustainability competencies, and this
ultimately leads to sustainable thinking. Sustainable engineering
education should be able to educate future engineers to think
flexibly and to be adjustable because it is doubtful that their
prospective careers will require them to work in one realm
(Segalas et al., 2010; Nagel et al., 2011). Engineering is an
innovative, resourceful, and integrated discipline; however, it
is only in the last two decades that there has been a prevalent
understanding of the philosophical and emergent effect
engineering has on all sectors of society. Nagel et al. (2011)
observed that it has come to be understood that the utmost
and most urgent sustainability tribulations humanity faces are
linked to our relationship with the natural world. As engineering
transforms into an ever more assimilated field, engineers and
engineering programs are expected to verify the suitable
incorporation of sustainability into the curriculum. Sustainable
engineering education is training that encourages, supports,
and advances technical contexts of sustainability via effective
resource utilization, lessening emission of greenhouse gases, as
well as thought of the effects of novel technologies, procedures,
and practices on the broader society. Engineering education
takes up a very important task in dealing with those challenges as
engineers provide relatively innovative technological solutions.
This is an important reason why every electrical/electronic
engineering student should not be left out in the training and
acquisition of technical sustainability competencies.
The objective of the present study
The authors, in 2020, carried out and published
an article titled “Conceptual Model of Technical
Sustainability for Integration into Electrical/Electronic
Engineering Programme in Nigerian Polytechnics.” This
was published by IEEE in volume 8 of the 2020 publication
(doi: 10.1109/ACCESS.2020.3002579). The earlier study
was carried out through mixed-method adopting sequential
exploratory design where data was first collected through
document analysis and interview, and secondly using threerounds of modified Delphi survey technique. As such, this study
was delimited as only 28 participants were used in the collection
of the quantitative data which was not subjected to rigorous
data analysis.
The objective of this study, therefore, was to validate the
earlier findings by using a structured questionnaire emanating
from the said findings to collect data from more (at least 170)
Research gap
Enormous literature exists that is devoted to sustainable
education in Nigeria, including the empirical study that
developed a conceptual model for integrating technical
sustainability into Higher National Diploma (HND)
electrical/electronic engineering curriculum by the present
authors (Mukhtar et al., 2020). Although the data collection
procedure for the developed model was carried out through
both qualitative and quantitative methods, it still suffers certain
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respondents in both academia and industry. The data were
subjected to a more rigorous analysis using a PLS-SEM approach
to validate the earlier findings.
questionnaires having omitted value (s) or obvious errors were
removed via skewness and kurtosis with the help of Smart PLS
3.0. Descriptive and inferential statistics were used to analyze
the quantitative data. In particular, path modeling (PM) and
structural equation modeling (SEM) with the aid of smart PLS
3.2.8 was used in analyzing the data.
Methodology
This study builds on the earlier study (Mukhtar et al., 2020)
carried out by the researchers with respect to the development of
a conceptual model of technical sustainability, in which mixedmethod research was used through sequential exploratory
study. In the earlier study, the researchers collected data first
through document analysis and interviews with a smaller
sample of the population; and second, using a survey through
three-rounds of modified Delphi technique with yet fewer
participants. In the current study, the identified competencies
(i.e., the findings of the first paper), were used to form a
structured questionnaire and administered to a larger sample
(172 subjects) of the population selected through a simple
random sampling technique (Krejcie and Morgan, 1970). The
development of the questionnaire in the study was streamlined
by the objective of the research. Specifically, the questionnaire
was constructed based on the findings of the earlier work
conducted by the authors (i.e., Mukhtar et al., 2020), and
consisted of 87 competencies (knowledge, skills, and attitudes)
in technical sustainability (Refer to Appendix). Section A of the
questionnaire solicited the personal status of the respondents.
In Section B, which has 33 items (competencies), respondents
were asked, based on their perceptions, to indicate the suitability
or otherwise of the Technical Sustainability Knowledge (TSK)
for inclusion into the curriculum. Section C contains 38
Technical Sustainability Skills (TSS), and respondents were
asked to indicate those that are suitable for inclusion in
the curriculum. Finally, Section D comprises 16 Technical
Sustainability Attitudes (TSA), from which respondents were to
indicate suitable competencies for inclusion in the curriculum.
Six experts (electrical engineers with at least 15 years of
work experience from both academia and industry) validated
the questionnaire by checking the face and content validation.
The reliability of the instrument was established via a pilot test.
The researchers administered the questionnaire to 36 experts
in academia and industry in Bauchi state, Nigeria (not part
of the study area). The research instrument’s reliability was
computed with the aid of SPSS statistical software version 20,
using Cronbach’s Alpha method to ascertain the extent of the
homogeneity of the items. The results obtained show that the
reliability coefficients for the sub-sections B–D were 0.852,
0.799, and 0.901, respectively. On the whole, the reliability
coefficient of the questionnaire is 0.850 which indicates that
the items in the questionnaire were internally consistent in
measuring what was intended to be measured for the study.
In establishing the extent of accuracy of the data collected,
the researchers carried out a data screening exercise, where
Frontiers in Sustainability
Results
Data collected was analyzed using descriptive and inferential
statistics. We use descriptive statistics only to determine the
demographic information considered in this study, i.e., the
career of the respondents, which indicated that from the
realized sample (n = 168), ninety (90) were lecturers in the
polytechnics, while seventy-eight (78) were industry workers. All
the respondents were graduates of electrical engineering with at
least 10 years of work experience. Moreover, inferential statistics
were also used with the help of smart PLS 3.2.8 in testing the
hypothesized path relationships in the model.
Measurement model evaluation
To start with, the authors checked the data reliability using
SPSS statistical software v.20. Usually Cronbach’s Alpha is used
to establish the reliability of survey data, and values vary
between 0 indicating no reliability, and 1, indicating perfect
reliability (Bryman, 2008). Alpha values of 0.897, 0.849, and
0.916 were obtained for Sections B–D respectively, whereas, an
alpha value of 0.887 was obtained for the overall questionnaire
indicating that the data is internally reliable. In addition, we also
checked the univariate and multivariate normality of the data
using skewness and kurtosis tests (https://webpower.psychstat.
org/models/kurtosis). The results for the univariate normality
showed that the ranges of skewness values for all variables are
−0.7724 to −0.4833. While the ranges of kurtosis values for all
variables are −0.8415 to +0.3497. However, the most important
for this all is the multivariate normality. The researchers
used Mardia’s multivariate skewness and kurtosis to assess
the multivariate normality. The results showed that Mardia’s
multivariate skewness and kurtosis are 6.006 and 41.000,
respectively, which are above the cut-off point of Skewness ±
1; and Kurtosis ± 20. Therefore, the data in this study does not
satisfy the assumptions of univariate and multivariate normality.
Since the data does not meet the multivariate normality of
Skewness ± 1; and Kurtosis ± 20 (Mardia, 1970), the researchers
decided to use the smart PLS 3.0 for the regression (Hair et al.,
2012).
Besides, we also checked the common method variance
(CMV) of the data usually caused by self-reported biasness
which Conway and Lance (2010) supposed to exaggerate
relationships between variables. The researchers performed the
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FIGURE 1
Partial least squares (PLS) algorithm showing indicators’ loadings, paths’ coefficients, and coefficient of determination (R2 ).
“Harman one-factor-test” using SPSS to ascertain the degree
of biasness in different proportion distributions of the items
(Barker and Ong, 2016). Podsakoff and Organ (1986) infer that
CMV is challenging if a single latent factor would account for
the majority of explained variance (i.e., 50%), The researchers
used un-rotated factor analysis and found that the one-factor
Frontiers in Sustainability
accounted for 42.304% of the total variance; hence, the CMV was
not a grave risk for the data. Factor analysis here compelled all
the measurements into one single factor, and it emerges to be
<50%, implying that CMV is not a drawback. This paved the
way for the researchers to continue with the development of the
measurement model as shown in Figure 1.
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Convergent validity
values approaching 1 signifying a high-level of reliability and
vice-versa. Hair et al. (2017) suggested values of composite
reliability (CR) between 0.7 and 0.9 as satisfactory to ascertain
internal consistency. Table 1 shows the CR and rho A values
of the constructs implying good internal consistency reliability
in the constructs. The three exogenous constructs—knowledge
skills and attitudes have CR and rho A values of 0.961 and 0.958,
0.966 and 0.964, and 0.890 and 0.848, respectively. Furthermore,
the target endogenous construct in the model has CR and rho A
values of 0.981 and 0.989, respectively.
Wong (2016) refers to convergent validity as the model’s
ability to explain the indicator’s variance. It is the extent to which
a measure correlates positively with alternative measures of the
same construct (Hair et al., 2017). Metrics that include outer
loadings of the indicators, the indicators’ reliability, and the
average variance extracted (AVE) are mostly the considerations
in establishing convergent validity.
Indicator loadings and reliability
Indicator loadings are the first metric to be evaluated to
ascertain the validity of the model. We verify the indicator
loadings and reliability to be certain that the associated
indicators have much in common that is encapsulated by the
latent construct (Wong, 2016). Hair et al. (2018) suggest that
loading below 0.708 should be removed unless its removal will
affect the content validity of the linked latent construct, or
will not improve the AVE of the construct. Table 1 shows that
37 (75.51%) of the indicators surpassed the more strict cutoff verge (0.708) which means that more than 50% (0.7082 )
of the variance in the observed latent variable is assigned in
the construct, while 12 (24.49%) of the indicators had loadings
below 0.708, and the researcher decided to retain them in the
study because Hulland (1999) recommends items’ loadings of 0.4
and higher for exploratory study, coupled with their conceptual
importance in the measurement model.
Discriminant validity
Discriminant validity is the extent to which a construct is
realistically distinct from another construct in the structural
model (Hair et al., 2018). If discriminant validity is proved in
a model, it suggests that a construct is distinctive and depicts
phenomena that are not depicted by other constructs in the
model. The researchers assessed the discriminant validity in the
model using HTMT and Foenell-larcker criteria as shown in
Tables 2, 3 below.
As shown in Tables 2, 3 above, the discriminant validity of
the constructs is established. All the constructs in this study are
considered conceptually similar. The researchers used a repeated
indicator approach in the model estimation, which undoubtedly,
makes some constructs have a value higher than the suggested
threshold value.
Average variance extracted
The AVE remains the only common measure to establish
convergent validity on the construct’s level. Hair et al. (2014),
stated that the AVE is the grand mean value of the squared
loadings of a set of indicators and is equivalent to the
communality of a construct. Bagozzi and Yi (1988), recommend
values of AVE to be 0.50 as a threshold level to provide evidence
of convergent validity. An AVE of 0.50 or higher indicates
that the construct explains 50% or more of the variance of the
indicators that make up the construct (Hair et al., 2018). Table 1
shows the various AVEs values for the exogenous constructs
involved in the path model. As can be seen in the table, the
exogenous constructs of knowledge, skills, and attitudes have
AVE values of 0.577, 0.534, and 0.619, respectively. Furthermore,
the target endogenous construct in the model has an AVE
value of 0.517. The researchers, therefore, concluded that the
measures of all the endogenous constructs in the path model
have significant levels of convergent validity.
Structural model evaluation
The fit of the model was established by evaluating the
following five metrics:
Collinearity issues (VIF) of the structural model
Hair et al. (2018) suggest that a value of VIF higher than
five signifies likely collinearity issues among the predictor (or
exogenous) constructs. The researchers assessed the collinearity
issues by validating the VIF values of the exogenous constructs
as shown in Table 4 below.
The significance and relevance of the structural
model relationships
Following the running of a PLS algorithm, the path
coefficient approximates are made available. These approximate
correspond to the hypothesized relationships relating to the
constructs. Path coefficient values are standardized on a range
from −1 to +1, with coefficients closer to +1 denoting robust
positive relationship and coefficients closer to −1 signifying
vigorous negative relationship. Hair et al. (2017) stressed that
even though, values near +1 or −1 are often statistically
Internal consistency reliability
Composite reliability and rho A values were used to
establish the internal consistency reliability in the model. Rho A
represents an estimated precise measure of construct’s reliability,
and mostly lies between Cronbach’s alpha and composite
reliability. Composite reliability varies between 0 and 1, with
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TABLE 1 Internal consistency reliability, convergent, and discriminant validity.
Latent variable
Indicators
Convergent
validity
Loadings Indicator
reliability
>0.70
>0.50
Technical sustainability
Knowledge
Skills
Attitudes
Frontiers in Sustainability
TSK1
0.694
0.481
TSK2
0.692
0.478
TSK3
0.767
0.588
TSK4
0.772
0.595
TSK5
0.793
0.628
TSK6
0.789
0.622
TSK7
0.705
0.497
TSK8
0.714
0.509
TSK9
0.780
0.608
TSK10
0.782
0.611
TSK11
0.736
0.541
TSK12
0.747
0.558
TSK13
0.700
0.490
TSK14
0.799
0.638
TSK15
0.761
0.579
TSK16
0.787
0.619
TSK17
0.809
0.654
TSK18
0.824
0.678
TSS1
0.691
0.477
TSS2
0.667
0.444
TSS3
0.622
0.386
TSS4
0.708
0.501
TSS5
0.682
0.465
TSS6
0.713
0.508
TSS8
0.815
0.664
TSS9
0.785
0.616
TSS10
0.716
0.512
TSS11
0.726
0.527
TSS12
0.686
0.470
TSS13
0.780
0.608
TSS14
0.763
0.582
TSS15
0.680
0.462
TSS16
0.775
0.600
TSS17
0.717
0.514
TSS18
0.633
0.400
TSS19
0.779
0.606
TSS20
0.743
0.552
TSS22
0.779
0.606
TSS23
0.771
0.594
TSS24
0.735
0.540
TSS25
0.787
0.619
TSS26
0.732
0.535
TSS27
0.741
0.549
TSA1
0.797
0.635
TSA2
0.863
0.744
TSA3
0.811
0.657
TSA6
0.703
0.494
TSA7
0.751
0.564
Internal consistency Discriminant
reliability
validity
HTMT confidence interval
does not include 1?
>0.50
0.60–0.90
0.60–0.90
0.517
0.981
0.980
0.577
0.961
0.958
Yes
0.534
0.966
0.964
Yes
0.619
0.890
0.848
Yes
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The coefficient of determination (Level of R2 )
TABLE 2 HTMT criterion showing the discriminant validity among the
constructs.
Attitudes
Knowledge
A vital element of structural model assessment is the
estimation of the coefficient of determination (R2 ). Hair et al.
(2017) affirmed that “this coefficient is a measure of the model’s
predictive accuracy and is calculated as the squared correlation
between a specific endogenous construct’s actual and predicted
value” (p. 174). Hair et al. (2017) avowed that the R2 -value varies
from 0 to 1, with 1 implying absolute predictive accuracy and
larger explanatory. The coefficient of determination, R2 , for the
target endogenous construct (Technical sustainability) is 1.00.
This implies that the three exogenous constructs (TSK, TSS, and
TSA) linked to it, extremely explained 100% of the variance in
the context of sustainability.
Skills
Attitudes
Knowledge
0.911
Skills
0.943
0.925
TABLE 3 Fornell larcker criterion showing the discriminant validity
among the constructs.
Attitudes
Attitudes
Knowledge
Skills
0.787
Knowledge
0.821
0.760
Skills
0.851
0.892
The f2 effect size
0.731
When a particular exogenous construct is removed from a
model and a PLS-SEM algorithm is run, the R2 -value for the
target endogenous construct changes. This change in R2 -value
can be used to assess whether the removed construct has a
meaningful impact on the endogenous construct (Hair et al.,
2017). This measure is termed the f2 effect size and is calculated
as f2 = R2 included -R2 excluded /1–R2 included
where: R2 included and R2 excluded are the R2 -values of the
endogenous construct when a particular exogenous construct
is included in or excluded from the model. The effect sizes of
the endogenous constructs were assessed as a result of the PLS
algorithm and are shown below in Table 6.
Diagonals (in bold) represent the square root of the AVEs of the latent variables.
TABLE 4 Lateral collinearity of the latent variables.
Latent constructs
Technical sustainability
TSA (Attitudes)
3.885
TSK (Knowledge)
4.260
TSS (Skills)
4.228
relevant, a standard error must be acquired using bootstrapping
to test for significance. The bootstrap standard error allows
calculating the empirical t-value. If the empirical t-value is
greater than the critical value (in this study = 1.96 at p < 0.05,
two-tailed), we conclude that the coefficient is significant at a
5% probability error. Figure 2 below shows the results of the
PLS algorithm and the bootstrap results using 5,000 samples.
Similarly, Table 5 shows the hypotheses testing for all the path
relationships in the model.
Figure 2 and Table 5 show the hypothesized path
relationships among the constructs in the model. Specifically,
Table 5 reveals that the hypothesized path relationship between
TSK and Technical Sustainability (H1) is statistically significant
with a t-value of 28.228 and p < 0.05 at 0.376 and 0.431,
with 95% confidence intervals for lower and upper levels,
respectively. Similarly, the hypothesized path relationship
between TSS and Technical Sustainability (H2) is found
to be significant statistically. The t-value is 39.400 and p
< 0.05 at 0.498, 95% confidence intervals for lower level,
and 0.551, 95% confidence intervals for upper level. In the
same vein, the path relationship was found to be significant
statistically between TSA and Technical Sustainability (H3).
The t-value was found to be 28.125 and p < 0.05 at 0.102
and 0.118, with 95% confidence intervals for lower and upper
levels, respectively.
Frontiers in Sustainability
The predictive relevance Q2 and q2 effect size
The researchers evaluated the cross-validated redundancy
measure, otherwise known as Stone-Geisser’s Q2 -value, which is
evidence of the model’s predictive relevance. The Q2 -represents
a measure of how well-observed values are reconstructed by
the model and its parameter estimates (Chin, 1998). The
blindfolding technique is used to get the Q2 -value for a specified
omission distance; D (in this case, D = 9). Table 6 above shows
the predictive relevance of the endogenous constructs in the
model which are all well above Cohen’s suggestions for strong
predictive relevance. We noted, as explained by Rigdon (2014)
that, while comparing the Q2 -value to zero is indicative of
whether an endogenous construct can be predicted, it does not
say anything about the quality of the prediction. As such, Hair
et al. (2018) stated that similar to the f2 effect size method for
evaluating R2 -values, the relative effect of predictive relevance
can be compared by means of the measure to the q2 effect.
Table 6 above shows that TSK has the largest q2 effect size of
0.027, TSS has the second largest q2 effect size of 0.041, and
lastly, TSA has the least q2 effect size of 0.001.
Consequently, the researchers formulated a validated model
of the technical sustainability competences as shown in
Figure 3 below.
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FIGURE 2
Bootstrapping results showing the weight of indicators and empirical t-values using 5,000 samples.
TABLE 5 Structural model hypothesis testing.
Hypotheses relationship
Std beta
Std error
t-value
p-value
95% CI LL
95% CI UL
Decision
H1
TSK → Technical sustainability
0.402
0.014
28.228
0.00
0.376
0.431
Supported
H2
TSS → Technical sustainability
0.526
0.013
39.400
0.00
0.498
0.551
Supported
H3
TSA → Technical sustainability
0.110
0.004
28.125
0.00
0.102
0.118
Supported
Multi-Group analysis
Sarstedt et al. (2011) observed, for several practical purposes,
this belief of homogeneity is not viable, since people are liable
to be heterogeneous in their opinions, understandings, and
assessment of latent constructs. The researchers performed a
multi-group analysis to uncover if there is a difference between
Partial Least Square-Sequential Equation Modeling
commonly functions upon the belief that the data being
examined originate from a single population. However, as
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the groups of respondents with respect to hypothesized path
relationships in the model as shown below.
The bootstrapping result shown in Table 7 reveals that all the
hypothesized path relationships in the model are also significant
when data for each group is considered separately. To discover
whether there is a significant difference between coefficients, one
requires running a PLS-SEM multi-group analysis, which is a set
of different methods for comparing PLS model estimates across
groups of data. It is generally employed to examine variations
between path coefficients in the inner model. The three sets of
tests for multi-group analysis are shown below in Table 8.
Table 8 below shows all three tests for the multi-group
analysis. The PLS-MGA test reveals that the hypothesized
path relationships (H1, H2, and H3) are not significant. The
parametric test shows that the hypothesized path relationship
between TSA and Technical Sustainability (H1) is significant,
while the hypothesized path relationships (H2 and H3) are not
significant. Furthermore, the Welch-Satterthwait test confirmed
the parametric test indicating a significant path relationship in
H1 and no significant path relationships in H2 and H3.
Discussions
The objective of this study was to validate identified
competencies in technical sustainability suitable for
incorporation into HND electrical/electronic engineering
curriculum in Nigeria. The competencies were investigated
in the earlier research conducted by the authors using
both qualitative (document analysis and interview), and
quantitative (Delphi survey) means, with fewer participants.
This study then, administered questionnaires developed
from the findings of the earlier research to a larger
TABLE 6 f2 effect sizes and Q2 predictive relevance of the
endogenous constructs.
f2 effect sizes
Q2
q2 effect size
TSK
0.021
0.481
0.027
TSS
0.032
0.474
0.041
TSA
0.001
0.494
0.001
Endogenous constructs
FIGURE 3
Proposed model of technical sustainability for integration into HND electrical/electronic engineering curriculum in Nigeria.
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TABLE 7 Multi-group analysis—bootstrapping results for groups 1 and 2.
Hypotheses
relationships
Path coefficients Path coefficients
STDEV
STDEV
t-values
t-values
p-values
p-values
(Industry pers.)
(Lect.)
(Industry pers.) (Lect.) (Industry pers.) (Lect.) (Industry Pers.) (Lect.)
TSA → Tech. sustainability
0.111
0.111
0.006
0.005
20.065
20.405
0.000
TSK → Tech. sustainability
0.399
0.405
0.020
0.019
19.883
21.108
0.000
0.000
0.000
TSS → Tech. sustainability
0.529
0.523
0.019
0.019
28.582
26.908
0.000
0.000
TABLE 8 Results of multi-group analysis.
Hypotheses
relationships
PLS-MGA
Parametric test
Welch-Satterthwait Test
Path
p-value
Path
t-value
p-value
Path
t-value
p-value
coefficients- (lecturers vs. coefficients- (lecturers vs. (lecturers vs. coefficients- (lecturers vs. (lecturers vs.
diff
industry
diff
industry
industry
diff
industry
industry
(|lecturers— personnel) (|lecturers— personnel)
personnel) (|lecturers— personnel)
personnel)
industry
industry
industry
personnel|)
personnel|)
personnel|)
TSA –>
0.000
0.503**
0.000
0.004
0.997*
0.000
0.004
0.997*
0.006
0.423**
0.006
0.194
0.846**
0.006
0.194
0.847**
0.006
0.589**
0.006
0.229
0.819**
0.006
0.229
0.819**
Technical
susainability (H1)
TSK –>
Technical
sustainability
(H2)
TSS –> Technical
sustainability
(H3)
Bias-Corrected confidence intervals
2.5% (Industry personnel) 97.5% (Industry personnel)
TSA –>
2.5% (Lecturers)
97.5% (Lecturers)
0.099
0.122
0.100
0.122
0.362
0.439
0.373
0.450
0.492
0.572
0.482
0.559
Technical
sustainability
TSK –>
Technical
sustainability
TSS –> Technical
sustainability
* S, Significant; ** NS, Not significant.
Discussion of findings of knowledge
aspect of technical sustainability
sample of the population. Consequently, the authors
used PLS-SEM to validate the findings and formulate a
more robust model of technical sustainability. Hence, the
discussions of the findings are presented based on the three
domains of learning a competency, i.e., knowledge, skills,
and attitudes.
Frontiers in Sustainability
The findings of the study on knowledge of technical
sustainability revealed a lot of competencies in this domain for
inclusion in HND electrical/electronic engineering curriculum
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inculcating cognitive competencies in Eco-design and LCA to
HND graduates will get them fully prepared to work in the
manufacturing industries, whose focus now is on sustainable
design and production. Their contributions as technicians
and/or technologists will help in uplifting such industries
and will manifest in societal growth and development. This
indicates that there is a need for the HND electrical/electronic
engineering curriculum developers in Nigeria to incorporate
cognitive competencies in Eco-design and LCA in order to
accelerate the achievement of sustainable development goals in
the country.
The findings also revealed that the respondents agreed
with the inclusion of cognitive competencies in modeling,
simulation, and optimization (MSO) of electrical/electronic
products, processes, and systems. Modeling is the understanding
and predicting the functioning and performance of individual
components of a system or the overall system behavior.
Simulation involves solving the set of equations of mathematical
models in order to determine the unknown variables so
as to obtain key insights into the system’s behavior. While
optimization is determining the conditions of optimal system
performance with respect to a particular objective which
may be economical, environmental, social, or a combination
of the three (Subramanian et al., 2018). This finding is in
line with the study outcome of Vehmaa’s et al. (2018) who
emphasize the need to incorporate into engineering education
competencies that include the use of certain software and
modeling skills, as well as Geographic Information systems.
The findings are also in agreement with Bielefeldt (2013)
who maintained that the use of specialized software tools
can be a valuable way to help students analyze technical
sustainability aspects by assisting them in quantifying the
various factors that relate to the sustainability of a project.
It is with no doubt that acquiring adequate competency
in using relevant software tools will enhance the HND
electrical/electronic engineering graduates’ understanding of
modeling, simulation, and optimizing electrical/electronic
products, processes, and systems. This will also help in
equipping them with the necessary dispositions for working
adequately in manufacturing industries and especially electrical
energy companies. Effective understanding of modeling,
simulation, and optimization of the energy system will aid in
the sustainable production, transmission, and distribution of
electrical energy to teeming end users and therefore, improve
the living standards of the people, and also make society a
better place.
Furthermore, the respondents in this study accepted
competencies in research for inclusion in the curriculum of
HND electrical/electronic engineering. This finding is not
coming as a surprise because Carter et al. (2016) discovered
that engineering students who engage in undergraduate
research tend to report higher skill levels such as academic
skills, knowledge of science, and research processes. Consistent
in Nigeria. These are discussed under the following: Eco-design
and Life-Cycle Assessment, Research, Modeling, Simulation,
and Optimization (MSO), and Recycling/Renewable resources.
The findings indicated that the experts stressed the
importance of cognitive competencies in Eco-design and LifeCycle Assessment for inclusion in the HND electrical/electronic
engineering curriculum. Eco-design is the integration of
environmental aspects into product design and development,
with the aim of reducing adverse environmental impacts
throughout the product life cycle (ISO 14006, 2011). This
finding is consistent with who stated that eco-design has
been recognized as a promising technique that is able to
brace and reinforce the knowledge, skills, and attitudes
of students in higher education, and therefore, evaluated
whether eco-design related topics are fused in higher
education courses and degree programs in Germany and
some other countries. Furthermore, Favi et al. (2019) stated
that eco-design methods needed to be more evident in the
academic programs and scientific literature, lamenting the
difficulty of its effective implementation within the technical
departments in the industry. This finding also agrees with
Pigosso and Leroy (2017) who reported that “Educating
students (on Eco-design) seems to be more promising
than changing industrial habits.” As such, Kattwinkel et al.
(2018) concluded that a key success factor in integrating
eco-design into the product development practice is the
development of related competences among employees
and designers through training and education. Romli et al.
(2015) also supported this finding by stressing the benefits
of competences in eco-design which include understanding
of reducing the environmental impact and cost for the whole
product life cycle. Konig (2021) also, stated that in the face of
civilization’s complex and existential sustainability challenges,
there are urgent demands on science to be at the service
of society.
Life-Cycle Assessment (LCA), on the other hand, is an ecodesign tool that is able to assess the product’s environmental
performance through a life cycle perspective. Our findings
matched the findings of Roure et al. (2018) who maintained
that LCA is one of the sustainability concepts that can be
integrated into many engineering programs to leave the “end
of pipe” approach and enter a more pollution-prevention and
holistic approach. This finding is concise with Bielefeldt (2013)
who viewed LCA as a method of assessing the environmental
impacts associated with a product or process from cradleto-grave including raw material extraction and processing,
manufacturing, transportation, use, upkeep, and disposal. In
support of this, Corporation and Curran (2006) developed
a guiding document to provide an introductory overview of
LCA and describe the general uses and major components
of LCA for the benefit of academia in learning how to
incorporate environmental performance based on the lifecycle concept into their programs. This is good evidence that
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Discussion of findings of skills aspect of
technical sustainability
with this finding is the study of Seymour et al. (2004)
in which they stressed the benefits of undergraduate
research as having a positive impact on students’ interest
in engineering majors, career preparation, critical thinking,
self-efficacy, and self-confidence. They describe undergraduate
research as “powerful affective, behavioral and personaldiscovery experiences whose dimensions have profound
significance for their emergent adult identity and sense
of direction” (p. 531). The literature is rich with works
suggesting that undergraduate research affects cognitive
skills, and as such has become a bedrock of academic
activity in colleges and universities (Carter et al., 2016). This
finding stresses the need for HND electrical/electronic
engineering graduates in Nigeria to acquire adequate
dispositions in sustainability research and developments
to enable them to match the requirements of industries
and companies. These are dynamic organizations that rely
on research and development for the ever-changing needs
of technology, machines, materials, products, processes,
and systems.
Moreover,
the
findings
revealed
that
HND
electrical/electronic engineering curriculum needs to
incorporate cognitive competencies in the aspect of recycling
and renewable resources. This finding confirms the assertion of
Gupta et al. (2011) who stated that there are millions of green
jobs in the labor market, but there are not enough workers who
can design and build green buildings, design renewable energy
systems, install and maintain solar panels and windmills, and
make processes more efficient. For these reasons, they advocated
for greening the engineering curricula. Supporting this finding
are Behboodi et al. (2016) who emphasized the need for an
accelerated step toward greening the engineering curricula by
embedding competencies in renewable resources. This finding
is also consistent with the study of Rajan et al. (2019) that found
and reported that many higher education institutions have
incorporated topics related to recycling and waste management
into their curricula at different levels to increase awareness
as well as to develop new recycling technologies. This is so
important because recycling waste is a vital technique for
addressing the crucial concerns associated with environmental
pollution arising out of dumping waste into the municipal
solid waste stream. Electrical/electronic engineering curriculum
developers in Nigeria need to consider reviewing the curriculum
to incorporate competencies in aspects of recycling and
renewable resources because of the intense global focus on the
rising costs of non-renewable energy sources and the negative
impacts that our societies have on the global environment. This
finding if implemented will help in cutting costs, mitigating
risks, opening up new competitive and revenue opportunities,
driving innovation, and improving employee development and
retention, as well as helping Nigeria in achieving the sustainable
development goals.
Frontiers in Sustainability
The findings of the study on skills in technical sustainability
showed a lot of competencies are accepted by the research
participants for inclusion in HND electrical/electronic
engineering curriculum. We, therefore, discuss these
competencies under the following: Communication/ICT;
Sustainable production; Application of modern engineering
software tools; Operating and troubleshooting of electrical
engineering machines, devices, processes, and systems; and
Skills in waste-to-energy technology.
The findings of the study revealed that communication/ICT
competencies are accepted by the respondents for inclusion in
HND electrical/electronic engineering curriculum. This finding
corroborates the claims of Carter et al. (2016) who affirmed
that in engineering, written, oral and graphic communication
skills are inevitable because they are regarded as components
of students’ training for engineering practice. They stressed that
technical communication courses should concentrate on the
development of these skills and students frequently practice
these skills in design courses through presentations to peers,
faculty, and industry representatives. The finding is also in
conformity with the study outcome of Kolmos et al. (2016)
in which they reported that communication skills were highly
recommended by engineering employers and graduates for
inclusion in the new sustainability curriculum. The employers
emphasize the need for engineering graduates to communicate
effectively, listen, observe, speak, draw, and write; communicate
results qualitatively, quantitatively, graphically, electronically,
and textually; communicate processes of thinking and reflection
including giving constructive feedback. Vehmaa’s et al. (2018)
study also justify this finding, because their discovery showed
that soft skills, and in particular, communication skills are
considered essential in an engineer’s early career, and this
includes information and communication technology (ICT)
skills that make them good communicators. This point to
the fact that integrating communication/ICT skills in the
HND electrical/electronic engineering curriculum in Nigeria
will help in preparing the students to meet up with the job
requirements of the industries, and therefore assist in realizing
the sustainability goals of the industries, the society and the
country in large.
The study also found that competences in sustainable
production are unanimously agreed upon by the participants for
inclusion in HND electrical/electronic engineering curriculum
in Nigeria. This finding is strengthened by the work of Raoufi
et al. (2017) who noted that in view of the rising relevance
of the need for sustainable production in manufacturing
industries, engineering programs must educate students as the
next generation of engineers by providing appropriate types
of education. In line with this, Raoufi et al. (2018) said that
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10.3389/frsus.2022.841643
of skilled technical manpower for the development and
sustenance of the national economy. HND electrical/electronic
engineering program in the polytechnics was designed to
produce higher technicians in electrical/electronic engineering
for the manufacturing, assembling, and service industries,
instrumentation and control, power generation, transmission,
distribution, and utilization industries. This finding is also
positively related to the study of Mukhtar (2014) whose findings
revealed that psychomotor competencies in constructing,
installing, assembling, testing, and maintaining electrical
machines, devices, systems, and equipment are approved by
industry managers for inclusion in bachelor of engineering
electrical/electronic curriculum in Nigeria. If this finding is
implemented, the graduates will be conversant with the actual
rigors of carrying out practical activities so that they help
industries in the development, manufacture, and operations of
a wide variety of electrical devices, circuits, systems, products,
and equipment. This will, in turn, influence societal and national
growth and development technologically, economically, socially,
and environmentally.
Competencies in waste-to-energy technology were also
identified by the respondents as suitable for inclusion in HND
electrical/electronic engineering curriculum. This finding is not
coming as a surprise due to Rada’s et al. (2017) claim that globally
1.3–1.9 billion tones of solid waste is collected per year, and
only 19% is recycled, 11% is used as energy recovery, and the
rest ends up in landfills or dumps. Nevertheless, Alawin et al.
(2016) identified a lack of awareness and shallow knowledge
about renewable energy technologies among senior students
in faculties of engineering. As a result, Robinson et al. (2018)
called on higher education institutions to increase their effort
in playing an influential role in providing technical solutions
to climate-related issues, and assessment of the relevance and
applicability of carbon management standards. This is an
obvious indication that the inclusion of the competencies in
waste-to-energy technology into the HND electrical/electronic
engineering curriculum in Nigeria is paramount, and will help
in preparing the graduates to be well-equipped with state-ofthe-art expertise such as modern incineration and anaerobic
digestion. This will yield environmental benefits, promotes
financial savings, and increases competition.
engineering accreditation bodies were challenged to focus on
the changes in the undergraduate curricula that would support
sustainable production. The finding is also in harmony with
the work of Blume et al. (2015) who stressed the significance
of acquiring useable competencies in sustainable production
engineering, which depends on a deep understanding of the
fundamental principles as well as on practical skills. Hence
engineering education directed at these complex topics needs
adequate didactic measures and learning environments, or else
the students barely accumulate factual knowledge. Adequate
inclusion of competencies in sustainable production engineering
in the HND electrical/electronic engineering curriculum will
help the graduates with broad skills in sustainable production
engineering to be able to assist manufacturers in achieving
appropriate and lasting sustainable products and processes.
Furthermore, the findings of the study indicated that
appropriate competencies in the application of engineering
software tools are suitable for incorporation into HND
electrical/electronic engineering curriculum in Nigeria. This
finding is concise with the Networked European Software and
Services Initiative (NESSI) that recommends all European
universities modernize and meet the demands for basic
and advanced software engineering skills and competencies
(Bellavista, 2014). The white paper reported that engineering
curricula across Europe need to address emerging technology
trends, including cloud-based, data-intensive, CPS-oriented,
and/or service-oriented systems through adequate software
tools. Hussain and Hamid (2017) augmented this finding
by maintaining that, for smooth entry into the Malaysian
industries, engineering graduates are expected to be conversant
with certain fundamental software tools needed in the
industries. They stated that competency in using modern
engineering tools and software is crucial in the working
environment to ensure quality standards and to meet
engineering specifications. Sarwar (2018) listed some of
the electrical/electronic engineering software for graduates
to be acquainted with. This includes MATLAB, Simulink,
Pspice, Multisim, ETAP, Power World Simulator, PSCAD,
PSS/E, LabVIEW, and Keil uVision to mention but a few. It is
obvious that the inclusion of competencies in the application
of electrical engineering software tools in the Nigerian HND
electrical/electronic engineering curriculum is eminent because
software tools have become ubiquitous in today’s digital world.
Industries and Companies are in dire need of employees with
the requisite competencies to embed software in almost all kinds
of modern products and services, since it is the key enabler
for innovation.
The findings of this study also include the incorporation
of competencies in operations and troubleshooting of electrical
engineering machines, devices, processes, and systems into the
HND electrical/electronic engineering curriculum in Nigeria.
This finding is in line with the mission of the National Board for
Technical Education NBTE (2001) of promoting the production
Frontiers in Sustainability
Discussion of findings of affective/values
aspect of technical sustainability
Attitudes/Values are defined as favorable students’
perspectives of sustainability issues (Stubbs, 2013). The findings
of the study on attitudes toward technical sustainability
demonstrated that values needed for integration into
HND electrical/electronic engineering curriculum comprise
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10.3389/frsus.2022.841643
Engineering ethical awareness, Occupational and safety health
(OSH), and Inter-generational equity (Biasutti and Frate, 2017).
The finding of this study disclosed that affective values in
engineering ethical awareness need to be captured into the HND
electrical/electronic engineering curriculum. This finding is in
cognizance with the work of Ali and Sinha (2016) who pointed
out that the world presently is in a complete state of conflict
and confusion, hatred and violence, war and rebellion, mainly
due to the serious negligence of ethical values, which have not
been adequately incorporated into education curricula. This is
perhaps the reason why the Accreditation Board for Engineering
and Technology (ABET) in the US requires engineering
students to “acquire an understanding of professional and
ethical responsibility” as well as other competences related to
appreciating the engineer’s role in society, and engineering’s
impact in the wider world (Newberry et al., 2011). The finding
is also consistent with Biasutti and Frate (2017) who realized
the importance of sustainability attitudes in higher education,
and therefore, developed and validated a quantitative scale
for measuring sustainable development attitudes based on
four dimensions consisting of environment, economy, society,
and education. Engineering ethics is the study of moral
issues and decisions confronting individuals and organizations
engaged in engineering. Incorporating it appropriately into
HND electrical/electronic engineering curriculum will facilitate
the transformation of the students into sustainability-literate
graduates and contribute to increased professionalism, increased
awareness of engineering’s societal context, and thus allowing
them to make educated, sustainability-informed decisions on the
overall welfare of the public.
The findings also revealed that the respondents stressed
the importance of embedding competencies in occupational
safety and health (OSH) into the HND electrical/electronic
engineering curriculum. This is perhaps due to the frequent
work-related deaths caused by work place accidents and
occupational diseases. Integrating competencies in OSH will
save the industry millions of dollars in workers’ compensation,
medical costs, and work efficiency. In line with this, Tureková
and Bagalová (2018) stressed that educational organizers must
ensure occupational safety and hygiene, since this has an
economic impact and educational attainment, in addition to
humanistic nature. This is also consistent with Endroyo et al.
(2015) who believed that to guard against industrial accidents,
it becomes essential to enhance the knowledge, skills, attitudes,
and habits of the people involved by adequately embedding
safety education in the school curriculum. Daud et al. (2010)
agreed with this finding and saw the need to, and subsequently
identified threshold and differentiating competencies needed by
OSH professionals for administrating and enforcing legislations
related to OSH in Malaysia.
Findings of the study also showed that affective
competencies related to intergenerational equity are worthwhile
for integration into the HND electrical/electronic engineering
Frontiers in Sustainability
curriculum. This finding is strongly supported by the
World Commission of Environment Development (1987)
report in which the concept of intergenerational equity was
popularized: “. . . without compromising the ability of future
generations to meet their own needs. . . ” This implies equitable
distribution of bio-spherical compatible improvements
in human wellbeing both today and tomorrow (Van der
Bank, 2014). This finding also coincides with the view of
Stazyk et al. (2016) who stated that organizations (higher
education institutions inclusive) striving to be socially and
environmentally responsible would be well-served by treating
sustainability as a form of intergenerational social equity or
fairness. As such, when sustainability is conceptualized in
intergenerational social equity, it is easier to determine what
socially and environmentally responsible organizations look
like in practice. Equity is a vital social notion in sustainable
development discussion and is believed to be the nucleus of
sustainability. As a result, when HND electrical/electronic
engineering curriculum is adequately entrenched with values
in intergenerational equity, the students will acquire skills that
render them the opportunity to work and help industries in
achieving their sustainability goals.
Conclusion
In consideration of the United Nations’ appeal to higher
institutions of learning to build systems for environmental
and development education, provides cross-disciplinary
courses to all students, and elevate quality and superiorities
in interdisciplinary research and education, this study
quantitatively validated technical sustainability competencies
for incorporation into HND electrical/electronic engineering
curriculum in Nigeria. Appropriate technical sustainability
competencies which are adequately validated can undoubtedly
be used to formulate a model for incorporation into the
engineering curriculum. This will then ensure adequate
production of the requisite and vital manpower to hasten the
technological, environmental, and socio-economic growth
and development of the nation, which will serve as a tool for
societal transformation as well as economic development. The
study found that cognitive competencies in Eco-design and
Life-Cycle Assessment; Research; Modeling, Simulation, and
Optimization (MSO); and Recycling/Renewable resources are
suitable for incorporation into the curriculum. The study also
discovered that skills in Communication/ICT; Sustainable
production; Application of modern engineering software
tools; Operating and troubleshooting of electrical engineering
machines, devices, processes, and systems; and Skills in
waste-to-energy technology are suitable for incorporation into
the curriculum. Similarly, the study uncovered that affective
values related to Engineering ethical awareness, Occupational,
and safety health (OSH), and Inter-generational equity are
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Mukhtar et al.
10.3389/frsus.2022.841643
suitable for incorporation into the curriculum. Therefore,
the electrical/electronic engineering curriculum developers in
Nigerian polytechnics and appropriate accreditation bodies
should organize and coordinate the processes of implementing
the validated model into the said curriculum. This will help the
upcoming twenty-first-century engineers to possess positive
sustainability thinking, innovative skills in problem-solving,
and the ability for assessing the consequences of their actions
outside immediate engineering walls.
results for both measurement and structural models. MS was
responsible for the discussions of the findings as well as
organizing and rearranging the references using EndNote.
All authors contributed to the article and approved the
submitted version.
Funding
This work was funded by UTM Encouragement Research
Grant Reference No: PY/2021/01612; Cost Center No:
Q.J130000.3853.20J37.
Data availability statement
The original contributions presented in the study are
included in the article/supplementary materials, further
inquiries can be directed to the corresponding author/s.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Ethics statement
Ethical review and approval was not required for the study
on human participants in accordance with the local legislation
and institutional requirements. The patients/participants
provided their written informed consent to participate in
this study. Written informed consent was obtained from the
individual(s) for the publication of any potentially identifiable
images or data included in this article.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed
or endorsed by the publisher.
Author contributions
Supplementary material
NM was responsible for the development of the introductory
and methodology aspects of the articles as well as the actual
field collection of the quantitative data. YK was responsible
for the data analysis which involves the effective running
of the software (SmartPLS), as well as interpretation of the
The Supplementary Material for this article can be
found online at: https://www.frontiersin.org/articles/10.3389/
frsus.2022.841643/full#supplementary-material
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