Manage perceived e-learning quality in Egyptian context

Abstract

With the rapid growth of e-learning around the globe, it is becoming increasingly important to assess the perceived e-learning quality and its impact on learners’ satisfaction. Although e-learning is still a considerably young phenomenon in the Arab world, it is currently viewed by Arab government officials as a viable solution to their educational problems. This paper aims to suggest e-learning quality dimensions in Egyptian universities and investigate its impact on perceived e-learning quality and students’ level of satisfaction. The study sheds light on the importance of transferring traditional higher education into online education in order to enhance the effectiveness of higher education institutions as well as contributing to a better understanding of the role of quality in e-learning from the perspective of instructors and investigating its impact on perceived e-learning quality. Throughout the paper, the author focuses on the body of literature concerned with higher education, e-learning service quality and students’ satisfaction importance in universities; consequently, a set of hypothesised quality dimensions were introduced for Egyptian universities to measure and understand perceived e-learning quality and its influence on students’ satisfaction.

Full text

Manage perceived e-learning quality in Egyptian context
Riham Adel∗
College of Management & Technology, The Arab Academy for Science Technology & Maritime
Transport, PO Box 1029, Alexandria, Egypt
With the rapid growth of e-learning around the globe, it is becoming increasingly
important to assess the perceived e-learning quality and its impact on learners’
satisfaction. Although e-learning is still a considerably young phenomenon in the
Arab world, it is currently viewed by Arab government officials as a viable solution
to their educational problems. This paper aims to suggest e-learning quality
dimensions in Egyptian universities and investigate its impact on perceived
e-learning quality and students’ level of satisfaction. The study sheds light on the
importance of transferring traditional higher education into online education in order
to enhance the effectiveness of higher education institutions as well as contributing
to a better understanding of the role of quality in e-learning from the perspective of
instructors and investigating its impact on perceived e-learning quality. Throughout
the paper, the author focuses on the body of literature concerned with higher
education, e-learning service quality and students’ satisfaction importance in
universities; consequently, a set of hypothesised quality dimensions were introduced
for Egyptian universities to measure and understand perceived e-learning quality and
its influence on students’ satisfaction.
Keywords: quality; service; higher education; e-learning; students’ satisfaction
Introduction
Due to rapid technological changes, traditional universities are facing new challenges.
However, technological changes and implementations within higher education are far
too slow (Anon, 2012). Therefore, a renewed interest in the concepts of sustainable e-
learning practices has been acknowledged (Stepanyan, Littlejohn, & Margaryan, 2013).
E-learning emerged as an imperative paradigm of modern education unrestricted by
time or place, offering new personalised and flexible learning experience to students.
There is a growing interest in e-learning initiatives within the Arab world such as
Egypt, Saudi Arabia, Jordan, Lebanon, Bahrain, Palestine, United Arab Emirates, and
Yemen over the recent years. E-learning in the Arab states when compared to the more
established e-learning in the Western world is still considered in its infancy stage.
Despite the significant importance of higher education quality highlighted in the literature,
e-learning has been often addressed in isolation from quality assurance and quality
improvement issues in higher education. There are limited research, knowledge, and
understanding of how the Arab academic community truly views e-learning and defines
e-learning quality at the Arab regional level. However, there have been perception and atti-
tudinal studies on specific universities such as Saudi Arabia’s King Saudi University
(Alferaihi, 2003), as well as a broader study on several universities in Lebanon regarding
how the academic community perceives e-learning (Nasser & Abouchedid, 2000). Yet, the
literature on perceptions about e-learning quality in the Arab world is very limited. This
#2015 Taylor & Francis
∗Email: rehamadel@gmail.com
Total Quality Management, 2015
http://dx.doi.org/10.1080/14783363.2015.1103174

gap of knowledge has motivated the author to identify e-learning quality antecedents and
its impact on e-learning perceived quality and students’ satisfaction within Egyptian
higher education context by addressing the following objectives: (1) the potential chal-
lenges that Egyptian higher education institutions may encounter when attempting to
implement e-learning quality initiatives. (2) Identification of the e-learning quality
aspects within Egyptian higher education institutions and its impact on perceived e-learn-
ing quality and learners’ satisfaction.
Literature review
Bates (2010,2011,2012) stated that technology will be a powerful tool for creating new
kinds of universities. He stresses that structural and cultural changes are crucial changes in
universities and will play a supporting and prominent role.
Consequently, traditional universities are facing new challenges in order to be com-
petitive, not only in educational, social, managerial, and technological aspects, but also
it is argued that universities have to collaborate in a globally sustainable environment
and to compete to retain its competitive edge. Hence, e-learning is currently viewed by
Arab government officials as a viable solution to their educational problems (Aldhafeeri
& Almulla, 2006; Plotkin, 2010).
But the lasting success of e-learning initiatives becomes a growing concern for edu-
cational institutions, as there is a knowledge gap regarding the integration of quality
success factors in e-learning into the quality assurance system within higher education
(Shelton, 2011). Therefore, renewed interest in the concepts of e-learning quality
and finding practical solutions to improve e-learning quality have been acknowledged
(Stepanyan et al., 2013).
Higher education service quality
It was noted that the service sector has grown considerably since the 1970s and services are
now playing an increasingly important role in the economy of many nations (Abdullah,
2005). In conjunction to this trend, the construct of service quality has become an extre-
mely important issue within the services literature (Baron, Harris, & Hilton, 2009).
The provision of good service quality is commonly associated with increased profit-
ability, customer satisfaction, customer loyalty, customer retention, customer attraction,
and positive word of mouth (Abdullah, 2005; Abdullah, 2006a; Voss, Gruber, &
Szmigin, 2007; Nadiri, Jay, & Kashif, 2009). In consideration of these apparent relation-
ships, it is not surprising that there is great interest in the measurement of service quality
due to services’ unique characteristics including intangibility, inseparability, and lack of
ownership (Palmer, 2011).
Over the last three decades, a range of conceptual frameworks have been proposed in
an attempt to measure service quality. The most popular scales of measuring service
quality are the service quality SERVQUAL named also the gap model and the perform-
ance-only SERVPERF measure of service quality (Cronin & Taylor, 1994; Parasuraman,
Zeitham, & Berry, 1994; Fogarty, Catts, & Forlin, 2000; Rodrigues, Barkur, Varambally,
& Motlagh, 2011).
According to Oldfield & Baron (2000), not only higher education is seen as a pure
service, but also educational services fall into the field of services marketing (Gruber,
Fub, Voss, & Glaser-Zikuda, 2010). Thus, higher education exhibits all the characteristics
of a service provider. It is intangible and heterogeneous; it meets the criterion of
2R. Adel

inseparability by being produced and consumed at the same time, and assumes students’
participation in the delivery process. The concepts of service quality are, therefore,
directly applicable to higher education.
Nevertheless, higher education institutions are increasingly attracting more attention to
service quality initiatives mainly due to the social requirement for quality evaluation in
education and the competitiveness in higher education marketplace. The earliest
researches on service quality in higher education emphasised academic more than admin-
istration, concentrating on effective course delivery mechanisms and the quality of courses
and teaching (Cuthbert, 1996; Herstein & Gamliel, 2006; Houston, 2008; Ruiqi & Adrian,
2009; Sultan & Wong, 2012).
Generic measures (e.g. SERVQUAL and SERVPERF) of service quality may not be
totally suitable for assessing perceived quality in higher education; therefore, the need
for a specific instrument to the higher education sector has emerged. Abdullah (2006b)
developed the HEdPERF model which is an adaptation of the standard SERVPERF
model adopting a perceptions-only approach.
Furthermore, he emphasised that evaluating service quality dimensions and under-
standing how these dimensions impact service quality can enable higher education insti-
tutions to efficiently design the service delivery process. In today’s competitive
environment, higher education institutions’ performance is attached to the quality of
service provided to the students. Thus, delivering service quality has become an important
goal for most higher education institutions in order to attract and retain students (Emanuel
& Adams, 2006; Smith, Smith, & Clarke, 2007; Kwek, Lau, & Tan, 2010).
Although several researchers differ in their definitions of quality, its dimension, and
measurements, they agree that defining characteristics of quality in higher education is
a prerequisite for the measurement process. Reviewing the literature, many authors
attempted to define and understand different ‘Quality Dimensions’ in order to explain
quality in higher education. Table 1 compiles various quality dimensions suggested for
higher education.
Reviewing the suggested dimensions of service quality in higher education, it was con-
cluded that although different terminologies are used, all authors agreed upon core ideas
which are the teaching and learning methods that include the curriculum content, pro-
gramme design, course structure, instructors, as well as the teaching and learning environ-
ment that includes facilities, assessment, feedback, and students’ and instructors’
interaction.
E-learning quality
Universities need to take into consideration the importance of integrating new technol-
ogies into education. Besides online colleges, there are many traditional higher education
institutions that offer their students both face-to-face and online courses together.
This dual-mode system provides flexibility particularly for working students (Ruth &
Conners, 2012). E-learning and the use of new technology, social media and open edu-
cational resources will open up entirely new methods of education, and for this reason, uni-
versities need to undergo structural and innovative changes (Richter & McPherson, 2012).
As discussed earlier, quality has always been the prime concern in higher education and
numerous studies have been conducted to investigate higher education quality all across
the world.
However, Jackson & Helms (2008) highlight that there is an increase in concern with
e-learning quality. Quality in e-learning is defined by Chapman & Henderson (2010)asan
Total Quality Management 3

Table 1. Literature quality dimensions in higher education.
Authors Quality dimensions
Parasuraman et al. (1994) Reliability
Tangibles
Responsiveness
Assurance
Empathy
Kwan and Ng. (1999) Course content
Medium of instruction
Concern of students
Facilities
Assessment
Holdford and Patkar (2003) Resources
Interpersonal behaviour of faculty
Faculty expertise
Communication
Administration
Sohail and Shaikh (2004) Personnel
Physical evidences
Reputation
Responsiveness
Access to facilities
Curriculum
Joseph, Mehenna, and George (2005) Staff
Campus environment
Reputation
Cost
Rojas-Mendez, Vasquez-Parraga, Kara,
and Cerda-Urrutia (2009)
Instructors
Programme
Service attitude
Competence development
Tsinidou, Gerogiannis, and Fitsilis (2010) Academic staff
Administration services
Library services
Curriculum structure
Location
Infrastructure
Career prospects
Agariya and Singh (2012) From Learners’ Perspective:
Course content
Design structure
Collaboration
Industry acceptance
Value addition
From Faculty Perspective:
Course content
Design structure
Transparency in assessment
Technical know-how
Value addition
(Continued)
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evaluation process that ‘judges, measures, or assesses the quality of the development and
delivery of online courses/learning environments focused on appropriate design and best
practice, and is aimed at self-improvement ensuring quality instruction in a non-threaten-
ing way’. Measuring quality in e-learning has always been an important issue, and a
limited number of studies addressed this problem (Chapman & Henderson, 2010).
In evaluating the effectiveness of e-learning, researchers have focused on different
aspects, such as technology and human factor, while Frydenberg (2002) defined nine
quality areas including (1) executive commitment, (2) technological infrastructure, (3)
student services, (4) design & development, (5) instruction & instructor services, (6) finan-
cial health, (7) program delivery, (8) legal and regulatory requirements, and (9) pro-
gramme evaluation to assess quality in e-learning.
Another study have identified five primary aspects in evaluating e-learning effective-
ness, including quality of the system, learner attractiveness, instructor attitudes, service
quality, and supportive issues (Wu & Hwang, 2010).
On the other hand, Tseng, Lin, and Chen (2011) pinpointed a fuzzy evaluation model
with four aspects which are (1) system quality, (2) information quality, (3) service quality,
and (4) website quality factors. Furthermore, Khan (2010) developed an e-learning frame-
work comprising eight dimensions, namely, pedagogical, technological, interface design,
evaluation, management, institutional, resource support, and ethical.
This e-learning framework offers a platform that enhances the success of the learner’s
experience once completely embraced by higher education institutions. Wong and Huang
(2011) claim that obtaining a comprehensive e-learning solution model will enable insti-
tutions to focus on the three parts of e-learning including technology, content, and service.
Additionally, Agariya and Singh (2012) assert that e-learning quality is the discrepancy
between learners’ experience with services offered and their expectations about these
services.
E-learning quality is considered a multifaceted concept that may be viewed differently
by various stakeholders and can be measured by a range of factors such as the student, the
curriculum, the instructional design, the technology used, and the characteristics of the
faculty (Jung, 2010). However, it is often argued that quality is measured by end users’
perceptions since it is important to satisfy students, who consequently will recommend
the service to other prospective students; thus, when satisfied, more likely the relationship
with the service provider will continue (Farahmandian, Minavand, & Afshardost, 2013).
Therefore, it is important to fulfil the learners’ needs more effectively and understand
the impact of the perceived e-learning quality on students’ satisfaction. Several authors
focused on students’ satisfaction with teaching and learning process, performance of the
Table 1. Continued.
Authors Quality dimensions
Prasad and Jha (2013) Physical aspects
Reliability
Competence
Personal interaction
Course structure
Policy
Total Quality Management 5

educational process, and results of online course evaluation (Swan et al., 2000; Hong, Lai,
& Holton, 2003). Yet the findings of these studies imply that satisfaction with e-learning is
explained by numerous factors that are mostly related with the issues of courses’ content,
instructors, students, technology, support services, and learning environment. Table 2
illustrates a summary for factors that affect satisfaction with e-learning.
Most of the studies conducted on students’ satisfaction have highlighted that the most
important factors influencing students’ satisfaction are related to the perceived service
quality that is measured by the students’ perceptions of academic courses, learning experi-
ence, and interaction with peers and instructors.
Research results
E-learning in higher education differs from traditional higher education. Although a
review of related literature provided a wide variety of issues surrounding integrating tech-
nology into instruction, it was found that not only e-learning has been often addressed in
isolation from critical quality assurance factors and quality improvement in higher edu-
cation instead of integrating e-learning into the higher education quality assurance
Table 2. Factors that affect satisfaction with e-learning.
Authors Students’ satisfaction factors
Yang and Cornelius (2004) Flexibility
Cost-effectiveness
Electronic research availability
Ease of connection to the internet
Easy navigation of online class interface
Familiarity with the instructor
Reisetter, LaPointe, and Korcuska (2007) The instructor
Personal interactions
Multisensory learning
Accessibility
Structure of website
Feedback
Abou Naaj, Nachouki, and Ankit (2012) Instructor
Technology
Course management
Interactivity
Instruction
Courses
Culture
Seng and Ling (2013) Instructors
Learning resources
Academic courses
Assessment
Student engagement
Lee and Lee (2014) Students’ attitudes
Faculty activities
Learning environment
Learning content
Interactions
Class participation
Perceptions of the course
6R. Adel

framework so no generic framework or model for sustainable e-learning quality was ident-
ified. But also, studies in e-learning are increasing in number, but few empirical researches
have tested it from the perspective of instructors, as an essential determinant for any suc-
cessful implementation (Chen & Tseng, 2012).
Finally, to date e-learning literature concerns their focus exclusively on developed
countries, with a greater predisposition towards the Internet, while the worldwide
growth of e-learning has shown the need to extend this research to other developing
countries (Ahmed, 2010). Therefore, the researcher is challenged to explore the
problem in order to stimulate further research in e-learning quality within the Egyptian
higher educational institutions in order to fill the gap in the current body of literature by
developing and validating an empirical-based model identifying quality factors influen-
cing instructors’ intention to participate in e-learning and impacting perceived e-learning
quality and students’ satisfaction.
Thus, it is proposed to tackle the problem by addressing the following questions: (1)
what are the challenges facing e-learning quality in Egyptian higher education insti-
tutions? – This question studies the potential challenges that Egyptian higher education
institutions may encounter when attempting to implement e-learning quality initiatives.
(2) What are the proposed e-learning quality aspects in Egyptian higher education insti-
tutions? – This question attempts to identify the e-learning quality dimensions suggested
to be taken into consideration when assessing perceived e-learning quality in Egyptian
higher education institutions. (3) How to improve e-learning quality practices in Egyptian
higher education institutions? – This question suggests the potential areas of improve-
ments to be taken into consideration to improve e-learning quality practices to attain
higher students’ satisfaction.
With respect to the purpose of this study and in accordance with the stated research
problem, the researcher adopted an exploratory research to obtain data about the most
influential quality dimensions in e-learning identified from previous studies and to study
the relationship between these variables in order to determine how to cultivate positive
faculty efficacy and sustainable e-learning quality practices into Egyptian higher edu-
cation institutions.
This type of research was chosen since it provided the researcher with a quantitative
description of teaching staff perceptions regarding e-learning. Quantitative research is
most effective when research is intended to measure variables and to test the impact of
the variables on a defined outcome (Rubin & Babbie, 2010). The conceptual model
depicted in Figure 1 suggests that the three independent variables including (1) creative
classrooms measuring (technology, social networks, networking, and innovation manage-
ment); (2) teaching Practices measuring (instructor, innovative timetable, multiple modes
Figure 1. Research model.
Total Quality Management 7

of teaching, and course design), and (3) learning practices measuring (learning outcomes,
course delivery, assessment, and formal and informal learning) have a direct effect on the
moderator variable perceived e-learning quality and an indirect effect on the dependent
variable students satisfaction.
The creative classrooms: refers to creative and innovative learning environment and
facilities that fully utilise the basic technological structures and provision of information
technology services, whereas learners can access services rapidly, conveniently, with
flexibility.
Teaching process: refers to instructional design that must always be improved, focus-
ing on up-to-date teaching methods, besides teachers and learners who should take part in
curricular improvement/development to meet the needs of learners.
Learning Practices: refers to learner’s experience with e-learning, thus concerned with
course delivery process and assessment that should place the importance on individuals’
learning differences and learners’ motivation by using flexible and engaging learning prac-
tices to meet students’ needs and enable self-regulation as well as peer learning.
The survey instrument used in this study was divided into four sections, the first col-
lects demographic information. Closed questions were used to assess the respondents’
familiarity with e-learning tools in the second section. Participants from the academic
staff were asked to indicate their level of agreement with items measuring the hypoth-
esised model’s dimensions using a five-point Likert scale in the third section.
An open-ended question to collect the respondents’ opinions of advantages and disad-
vantages of e-learning implementation was included in the final section. Participants for
this study were randomly selected from five colleges in a private Egyptian higher edu-
cation institution. A total of 170 questionnaires were distributed, yielding 17.22%
response rate. Table 3 shows the sample size of academic staff taken from different
colleges.
In order to confirm the appropriateness of the questionnaire, it was important to test the
reliability of the questionnaire. The coefficient of internal consistency Crobach’s (
a
)is
highly statistically significantly reliable and equals to 97.3% for the total number of 56
questions. ‘This gets over the percent of 60%, which is an extra good value for the internal
consequence of the conceptual construction of the investigated scale’ (Anastasiadou &
Anastasiadis, 2011).
From the inferential analysis of the survey results, the instructors who participated in
the study showed a high level of willingness to adopt e-learning. It was found that their
perceived e-learning quality is strongly affected by the three quality antecedents included
in the research model; these three variables were correlated and have a direct positive
effect on perceived e-learning quality service and an indirect effect on student
Table 3. Population and sample size.
Colleges Population Distributed sample Actual sample size
Engineering and technology 285 50 30
Maritime transport and technology 102 25 22
International transport and logistics 74 35 18
Management and technology 164 40 31
Language and communication 37 20 13
Total 662 170 114
Population % 25.67% 17.22%
8R. Adel

satisfaction. In order to address the research questions, the researcher tested the follow-
ing hypotheses:
H1: The interactive creative classroom, teaching, and Learning practices are correlated
H2: The creative classrooms will positively affect the perceived e-learning quality
H3: The teaching process will positively affect the perceived e-learning quality
H4: The learning process will positively affect the perceived e-learning quality
H5: The perceived e-learning quality impacts student satisfaction
Pearson correlation was used to test the hypothesis and measure the direction and strength
of the variables. It was found a positive relationship of 0.653 between creative classrooms
Table 4. E-learning implementation’s advantages vs. disadvantages.
Advantages Disadvantages
Students can be disengaged and feel isolated
from the instructor and classmates if the
e-learning professionals fail to create
meaningful, motivating, and highly engaging
learning experiences
Delivery costs for e-learning are considerably
cost effective, it reduces participants’ time and
travel costs and instructors’ cost
Without the routine structures of a traditional
class, learners with low motivation, limited
computer skills, and bad study habits may fall
behind, get lost or confused about course
activities and deadlines
Online learning cannot fully replace the
relationships that develop in a group of
students and the personal contact with the
instructor
Students’ accessibility to online resources, in
different formats wherever and whenever they
want
Self-paced learning modules allow students to
work at their own pace and achieve work – life
balance
E-learning is completely dependent on
technology and thus creates inadequate
computers and slow Internet connections can
lead to frustrated learners and negative
perception of e-learning quality service
Flexibility to join discussions in the bulletin
board threaded discussion areas at any hour, or
visit with classmates and instructors remotely
in chat rooms
E-learning requires extensive use of computers
and related devices that may contribute to
repetitive physical problems related to
workplace ergonomics
E-learning increases interaction between
students better than traditional classrooms
Selecting inappropriate e-learning delivery
methods that simply does not match the
content of the courses thus impacts the
effectiveness of the programmes
E-learning materials can accommodate different
learning styles and can be regularly updated
with ease by incorporating new digital
elements that will benefit the learners
Wasting time with technical and security
problems. On the other hand, e-learning can
be a daunting and demotivating experience
especially for learners who are not too
comfortable using software and computers
Successfully completing online or blended
learning programmes encourages interaction
among learners, builds self-confidence, helps
better plan for their study, and enhances the
ability of students to network more effectively
Total Quality Management 9

and teaching practices; a positive relationship of 0.735 between creative classrooms and
learning practices, and a positive relationship of 0.865 between teaching practices and
learning practices at significance level less than 0.01, thus accept the hypothesis which
indicates a significant relationship.
Creative classrooms, the teaching process, and the learning process have, respectively,
a positive relationship of 0.672, 0.872, and 0.862 and with perceived e-learning quality
with significance level less than 0.01. The R
2
coefficient of determination gives indication
of the strength of the relationship. R
2
value respectively 45.2, 75.9, and 74.4 means that
45.2% of the variation in perceived e-learning quality can be explained by ‘creative class-
rooms’; 75.9% of the variation in perceived e-learning quality can be explained by ‘teach-
ing process’; and 74.4% of the variation in perceived e-learning quality can be explained
by ‘learning process’. Thus accept hypotheses 2, 3, and 4. There is a significant positive
relationship between perceived e-learning quality and students’ satisfaction where the cor-
relation coefficient is 0.889 at a level significantly less than 0.01, where perceived e-learn-
ing quality yielded 79% of the total change in students’ satisfaction with a significant level
of 0.01, which leads to accept hypothesis 5.
It was found that e-learning is arising as a new paradigm of advanced education with a
growing rate of 36.5% in the market, but still failures exist. Although the concept of
e-learning has been widely studied, many researchers agreed that e-learning still has
strengths and weaknesses; therefore, it is important to know exactly what are e-learning
advantages and disadvantages. Therefore, participants were asked to respond to an
open-end question identifying what drives them to accept or reject the implementation
of e-learning, and a list of advantaged and disadvantages was extracted from responses
(Table 4). However, results showed that most of the participants accept the implemen-
tation of the e-learning system and only 11 participants rejected e-learning. Through
reviewing the responses of the participants, the researcher was able to list a number of
advantages and disadvantages (Table 4).
Conclusion and recommendations
E-learning is changing the methods of teaching and learning, and thus challenges the tra-
ditional university. It is crucial to point out the impact on instructors and students’ learning
as e-learning can be viewed as an alternative to face-to-face teaching methods or as a
complement to traditional teaching. In all cases it is evident that e-learning usually
allows the students a greater choice as well as responsibility for their own learning
(Oye, Salleh, & Iahad, 2011; Dehghani & Peyman, 2014). It was clear that higher edu-
cation experts prefer to combine aspects of online learning and traditional face-to-face
learning in the so-called blended learning, rather than shifting completely into online
learning.
Interactive classroom setting promotes open exchange of ideas, accessibility, interac-
tivity between learners and instructors, as well as interactivity between learners and peers.
It promotes two levels of socialisation among students via group discussions, team pro-
jects, and peer evaluation and between students and instructors via lectures, seminars,
and discussions. Hence students become both active listeners and participants in the learn-
ing environment. On the other hand, the instructors continually observe students for clues
about their level of comprehension, and respond to difficulties with a wide range of strat-
egies. They can engage the students in an endless variety of individualised and cooperative
learning activities in order to attend to students’ motivation and to maintain their interest
and enthusiasm.
10 R. Adel

Traditional Egyptian universities aiming to transform from on campus and face-to-face
teaching into e-learning will have to ensure the following:
.Accessibility and flexibility: refers to flexible access and use of information and
resources at a time, place, and pace that are suitable and convenient to individ-
ual learners rather than the teacher and/or the educational organisation. This
could include accessing teaching resources online, communication tools,
online assessment and classroom technologies, electronic voting system, and
immediate feedback. E-learning supports the idea of continuity in learning
and the transfer of learning outside the walls of the university, so it is clear
that there is a link between e-learning and self-learning, each one being essen-
tial to the other.
.Added value service: offering quality content and developing teaching approaches
will keep learners fully engaged and motivated to learn. Regular feedback is top
of the list in students’ priorities for a good academic experience. On the other
hand, including information that is general and not specific will not bring any
added value to the e-learning course, and may even make the learner question the
value of the e-learning course as a whole. So, stay on-topic and always ensure
that you offer information that will help them to improve their knowledge base
and learn or improve upon a desired skill set in order to enhance their employability.
The key to finding what is relevant for your interactive online courses is to not
simply include what you think is important, but include what you believe the
learner may find valuable. Develop an e-learning strategy that provides the most
benefit for everyone involved.
.Learners-centred approach: it is essential for e-learning quality to design teaching
and learning environment with focus on learners to improve e-learning quality and
increase learners’ satisfaction with outcomes. Additionally, facilitate and motivate
students to play an active role in gaining new competencies and constructing their
knowledge. Students should be engaged in authentic learning activities and tasks
that encourage analysis and develop the learners’ capabilities rather than recalling
concepts and information.
Furthermore, the researcher recommends Egyptian higher education institutions to have a
sustainable e-learning quality practice which is referred to as the ‘three pillars’ of sustain-
able development. These three pillars are categorised into three domains: (1) Resource
Management domain that focuses on the cost of e-learning; many strategies and
approaches were adopted by institutions to improve cost-effectiveness, efficiency
gains, and economies of scale and scope. (2) Educational Attainment is another
domain that focuses on measures of student achievement, retention rates, skill acqui-
sition, personal development, as well as evidence of benefits, perceptions of quality,
usability of new technologies, and student performance. Finally, (3) Professional Devel-
opment and Innovation domain that views sustainability as a commitment to continuous
improvement and adaptation to a constantly changing environment; this domain focuses
on strategies for adapting to change, teacher training and development, institutional trans-
formation, and educational leadership (Stepanyan et al., 2013). Therefore, it is suggested
that each domain allows the integration of a range of competing factors influencing sus-
tainable e-learning quality practice in Egyptian higher education institutions.
Total Quality Management 11

Disclosure statement
No potential conflict of interest was reported by the author.
References
Abdullah, F. (2005). HEdPERF versus SERVPERF: The quest for ideal measuring instrument of
service quality in higher education sector. Quality Assurance in Education,13(4), 305 – 328.
Abdullah, F. (2006a). Measuring service quality in higher education: HEdPERF versus SERVPERF.
Marketing Intelligence and Planning,24(1), 31–47.
Abdullah, F. (2006b). The development of HEdPERF: A new measuring instrument of service
quality for the higher education sector. International Journal of Consumer Studies,30(1),
569–581.
Abou Naaj, M., Nachouki, M., & Ankit, A. (2012). Evaluating student satisfaction with blended
learning in a gender-eegregated environment. Journal of Information Technology
Education: Research,11, 185–200.
Agariya, A., & Singh, D. (2012). E-Learning quality: Scale development and validation in Indian
context. Knowledge Management & E-Learning: An International Journal,4(4), 500–517.
Ahmed, H. (2010). Hybrid e-learning acceptance model: Learner perceptions. Decision Sciences
Journal of Innovative Education,8(2), 313–346.
Aldhafeeri, F., & Almulla, M. (2006). Teacher’s expectations of the impact of e-learning on
Kuwait’s public education system. Social Behavior and Personality,34(6), 711 – 728.
Alferaihi, F. (2003). The perception of undergraduate students toward utilizing online courses at
King Saud University, Riyadh, Saudi Arabia. Athens: Ohio University.
Anastasiadou, S., & Anastasiadis, L. (2011). Reliability and validity testing of a new Scale for
mesuring attitudes toward electronics and electrical constructions subject. International
Journal of Applied Science and Technology,1(1), 1 – 10.
Anon. (2012). The NMC horizon report: 2012 higher education edition, the new media consortium,
Austin. Retrieved December 2014, from http://www.nmc.org/pdf/2012-horizon-report-HE.pdf
Baron, S., Harris, K., & Hilton, T. (2009). Services marketing: Text and cases (3rd ed.). Basingstoke:
Palgrave Macmillan.
Bates, T. (2010). Understanding web 2.0 and its implications for e-learning. In M. Lee and
C. McLoughlin (Eds.), web 2.0 based e-learning: Applying social informatics for tertiary
teaching (pp. 21–42). Herschey, PA: Idea Group.
Bates, T. (2011). 2011 Outlook for online learning and distance education. Retrieved December 2014,
from http://provost.ncsu.edu/governance/task-forces/distance-education/2011/documents/
2011-outlook-for-online-learning-and-de.pdf
Bates, T. (2012). E-learning outlook for 2012: Will it be a rough ride? Retrieved December 2014, from
http://www.tonybates.ca/2012/01/02/e-learning-outlook-for-2012-will-it-be-a-rough-ride/
Chapman, B., & Henderson, R. (2010). E-learning quality assurance: A perspective of business teacher
educators and distance learning coordinators. The Delta Pi Epsilon Journal,52(1), 16 – 31.
Chen, H., & Tseng, H. (2012). Factors that influence acceptance of web-based e-learning systems for
the in-service education of junior high school teachers in Taiwan. Evaluation and Program,
35(3), 398–406.
Cronin, J., & Taylor, S. (1994). SERVPERF versus SERVQUAL: Reconciling performance-based
and perceptions-minus-expectations measurement of service quality. Journal of Marketing,
58(1), 125–131.
Cuthbert, P. (1996). Managing service quality in HE: Is SERVQUAL the answer? Part 2. Managing
Service Quality,6(3), 31–35.
Dehghani, M., & Peyman, N. (2014). On the investigation of efficacy of e-learning on higher edu-
cation academic achievement. Basic Research Journal of Education Research and Review,
3(4), 29–34.
Emanuel, R., & Adams, J. (2006). Assessing college student perceptions of instructor customer
service via the quality of instructor service to students (QISS) questionnaire. Assessment &
Evaluation in Higher Education,31(5), 535 – 549.
Farahmandian, S., Minavand, H., & Afshardost, M. (2013). Perceived service quality and student
satisfaction in higher education. IOSR Journal of Business and Management (IOSR-JBM),
12(4), 65–74.
12 R. Adel

Fogarty, G., Catts, R., & Forlin, C. (2000). Identifying shortcomings in the measurement of service
quality. Journal of Outcome Measurement,4(1), 425– 447.
Frydenberg, J. (2002). Quality standards in e-learning: A matrix of analysis. The International
Review of Research in Open and Distance Learning, 3(2), 4–11.
Gruber, T., Fub, S., Voss, R., & Glaser-Zikuda, M. (2010). Examining student satisfaction with
higher education services using a new measurement tool education services using a new
measurement tool. International Journal of Public Sector Management,23(2), 105 – 123.
Herstein, R., & Gamliel, E. (2006). The role of private branding in improving service quality.
Managing Service Quality: An International Journal,16(3), 306 – 319.
Holdford, D., & Patkar, A. (2003). Identification of the service quality dimensions of pharmaceutical
education. American Journal of Pharmaceutical Education,67(4), 1 – 11.
Hong, K., Lai, K., & Holton, D. (2003). Students’ satisfaction and perceived learning with a web-
based course. Educational Technology & Society,6(1), 116– 124.
Houston, D. (2008). Rethinking quality and improvement in higher education. Quality Assurance in
Education,16(1), 61–79.
Jackson, M., & Helms, M. (2008). Student perceptions of hybrid courses: Measuring and interpreting
quality. Journal of Education for Business,84(1), 7–12.
Joseph, M., Mehenna, Y., & George, S. (2005). An educational institution
`s quest for service quality:
Customers
`perspective. Quality Assurance in Education,13(1), 66–82.
Jung, I. (2010). The dimensions of e-learning quality: From the learner’s perspective. Retrieved
December 2014, from http://apuedtech.com/520/Research/e-learning.pdf
Khan, B. (2010). The Global E-Learning Framework. Retrieved December 2014, from https://
webserver.ignou.ac.in/institute/STRIDE_Hb8_webCD/Chapter%205.pdf
Kwan, P. Y., & Ng, P. W. (1999). Quality indicators in higher education-comparing Hong Kong and
China’s students. Managerial Auditing Journal, 14(1/2), 20–27.
Kwek, C., Lau, T., & Tan, H. (2010). Education quality process model and its influence on students’
perceived service quality. International Journal of Business and Management,5(8), 154 –165.
Lee, S., & Lee, H. (2014). Analysis of the influence of factors related to student satisfaction with
web-based university courses:comparison between 2005 and 2014. Retrieved December
2014, from http://onlinepresent.org/proceedings/vol59_2014/17.pdf
Nadiri, H., Jay, K., & Kashif, H. (2009). Students’ perceptions of service quality in higher education.
Total Quality Management,20(5), 523–535.
Nasser, R., & Abouchedid, K. (2000). Attitudes and concerns towards distance education: The case
of Lebanon. Online Journal of Distance Learning Administration,3(4), 1–10.
Oldfield, B., & Baron, S. (2000). Student perceptions of service quality in a UK university business
and management faculty. Quality Assurance in Education,8(2), 85– 95.
Oye, N., Salleh, M., & Iahad, N. (2011). Challenges of e-learning in Nigerian university education
based on the experience of developed countries. International Journal of Managing
InformationTechnology,3(2), 39–48.
Palmer, A. (2011). Principles of services marketing (6th ed.). Maidenhead: McGraw-Hill.
Parasuraman, A., Zeitham, V., & Berry, L. (1994). Alternative scales for measuring service quality:
A comparative assessment based. Journal of Retailing,70(3), 201 – 230.
Plotkin, H. (2010). Free to learn: An open educational resources policy development. Retrieved
December 2014, from https://wiki.creativecommons.org/images/6/67/FreetoLearnGuide.pdf
Prasad, R., & Jha, M. (2013). Quality measures in higher education: A review and conceptual model.
Journal of Research in Business and Management,1(3), 23–40.
Reisetter, M., LaPointe, L., & Korcuska, J. (2007). The impact of altered realities: Implications of
online delivery for learners’ interactions, expectations, and learning skills. International
Journal On E-Learning,6(1), 55–79.
Richter, T., & McPherson, M. (2012). Open educational resources: Education for the world?
Distance Education,33(2), 201–219.
Rodrigues, L., Barkur, G., Varambally, K., & Motlagh, F. (2011). Comparison of SERVQUAL and
SERVPERF metrics: An empirical study. The TQM Journal,23(6), 629 – 643.
Rojas-Mendez, J., Vasquez-Parraga, A., Kara, A., & Cerda-Urrutia, A. (2009). Determinants of
student loyalty in higher education: A tested relationship. Latin American Business Review,
10(1), 21–39.
Rubin, A., & Babbie, E. (2010). Research methods for social work. Belmont, CA: Cengage/Brooks
& Cole.
Total Quality Management 13

Ruiqi, Z., & Adrian, P. (2009). Using SERVQUAL to measure the service quality of travel agents in
guangzhou, south China. Journal of Services Research,9(1), 87 – 107.
Ruth, D., & Conners, S. (2012). Distance learning in a core business class: Determinants of success
in learning outcomes and post-course performance. Academy of Educational Leadership
Journal,16(1), 123–131.
Seng, E., & Ling, T. (2013). A statistical analysis of education service quality dimensions on
business school students’ satisfaction. International Education Studies,6(8), 136– 146.
Shelton, K. (2011). A review of paradigms for evaluating the quality of online education programs.
Online Journal of Distance Learning Administration, 14(1). Retrieved from http://eric.ed.
gov/?id=EJ921847
Smith, G., Smith, A., & Clarke, A. (2007). Evaluating service quality in universities: A service
department perspective. Quality Assurance in Education,15(3), 334–351.
Sohail, M., & Shaikh, N. (2004). Quest for excellence in business education: A study of student
impression of service quality. International Journal of Educational Management,18(1),
58–65.
Stepanyan, K., Littlejohn, A., & Margaryan, A. (2013). Sustainable e-learning: Toward a coherent
body of knowledge. Educational Technology & Society,16(2), 91–102.
Sultan, P., & Wong, H. (2012). Service quality in a higher education context: An integrated model.
Asia Pacific Journal of Marketing and Logistics,24(5), 755 – 784.
Swan, K., Shea, P., Fredericksen, E., Pickett, A., Pelz, W., & Maher, G. (2000). Building knowledge
building communities: Consistencies, contact and communication in the virtual classroom.
Journal of Educational Computing Research,23(4), 359 – 383.
Tseng, M., Lin, R., & Chen, H. (2011). Evaluating the effectiveness of e-learning system in uncer-
tainty. Industrial Management & Data Systems,111(6), 869 – 889.
Tsinidou, M., Gerogiannis, V., & Fitsilis, P. (2010). Evaluation of the factors that determine quality
in higher education: An empirical study. Quality Assurance in Education,18(3), 227 – 244.
Voss, R., Gruber, T., & Szmigin, I. (2007). Service quality in higher education: The role of student
expectations. Journal of Business Research,60(9), 949–959.
Wong, W., & Huang, N. (2011). The effects of e-learning system service quality and users’ accep-
tance on organizational learning. International Journal of Business and Information,6(2),
205–225.
Wu, W., & Hwang, L. (2010). The effectiveness of e-learning for blended courses in colleges:a
multi-level empirical study. International Journal of Electronic Business Management,
8(4), 312–322.
Yang, Y., & Cornelius, L. (2004). Students’ perceptions towards the quality of online education: A
qualitative approach. Retrieved December 2014, from http://files.eric.ed.gov/fulltext/
ED485012.pdf
14 R. Adel