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The Effectiveness and Potential of E-learning in
War Zones: An Empirical Comparison of Face-
to-Face and Online Education in Saudi Arabia
Khairan D. Rajab1, Member, IEEE
1Najran University, Najran, Saudi Arabia
Corresponding author: Khairan D. Rajab (e-mail: khairanr@ gmail.com).
The author would like to thank the E-Learning Committee at the College of Computer Science and Information System at Najran University for the weekly,
mid-semester, and final reports that ensured the proper activation of e-learning teaching during the academic year 2016. “ This work is supported by Najran
University [grant number NU/ESCI/064].”
ABSTRACT This study compares the effectiveness of e-learning and face-to-face education in the
previously neglected context of Saudi Arabia. This is done by examining Najran University‟s e -learning
experience after the institution suspended traditional course delivery due to the ongoing war between Saudi
Arabia, the Arab Coalition, and Yemeni rebel groups. The analysis also considers the potential benefits
offered by e-learning in crisis zones such as the southern border region of Najran, Saudi Arabia. The results
indicate that there is no statistical or practical difference between online and face-to-face learning with
respect to student performance. The study also demonstrated that e-learning is capable of delivering the
educational goals of higher learning institutions to areas wrecked by wars. E-Learning offers students a safe
learning environment, engaging platforms, and most importantly, a quality education. The findings of this
study contribute to a growing body of scholarship on the effectiveness and implementation of e-learning in
the Middle East.
INDEX TERMS Education in War Zones, E-learning, Evaluation of Face-to-Face Education, Information
Communications Technologies (ICTs), Online Education, Saudi Arabia
I. INTRODUCTION
The government of Saudi Arabia has increasingly coalesced
its efforts at implementing e-learning initiatives and
programsintothekingdoms‟highereducationsystemsince
April 2016, when the Council of Ministers endorsed the
2030 vision to “expand the scope of online education” in
the country. Authors [1] noted that the Saudi higher
education system was gradually shifting from a traditional
face-to-face classroom setting into a more web-based
system. While the number of e-learning courses and
programs has increased exponentially within Saudi
universities, it is still unclear whether online learning is an
effective educational model.
Research on the effectiveness of online education is both
extensive and inconclusive [2-8]. On the one hand, many
studies concluded that there is no statistical or practical
difference between the academic outcomes of online and
face-to-face courses [9-12]. On the other hand, many
studies have found that student performance and
satisfaction with online courses was better when compared
to traditional face-to-face classes [13-16]. Additionally, few
studies reported poor student performance in online classes
compared to traditional courses [16-17].
Despite a large number of studies comparing student
academic outcomes across various learning modes (such as
face-to-face, hybrid, blended, and online or distance
education), there has been no systematic evaluation of the
effectiveness of e-learning in Saudi universities [18-22].
Previous studies on e-learning in Saudi Arabia focused on
the types, breadth, future potential, and challenges of the
mode [23-27]. Despite an interest in e-learning throughout
the Kingdom, the effectiveness of it has not yet been
adequately evaluated. Do online students perform the same,
better, or worse than students who attend traditional classes
in Saudi universities? This study attempts to address this
question by comparing student performance in courses
taught both online and face-to-face at the same public
university in southern Saudi Arabia.
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While scholarship on e-learning has extensively outlined
the benefits of online education, it has failed to indicate that
e-learning can be used as an effective educational delivery
system in crisis areas [2, 5-6, 12, 26]. E-learning expands
the access of education to hard-to-reach groups, rural
populations, and female students in countries such as Saudi
Arabia as well as among non-traditional groups including
single parents, the less economically endowed, and the
chronically ill [18, 25-26]. The format also allows students
to learn, develop, and enhance their technical skills by
forcing them to utilize new educational tools [17, 27]. In
addition to such advantages, this paper highlights the
potential of e-learning in delivering intended educational
outcomes within crisis zones.
This research contributes to ongoing debates concerning
the effectiveness of e-learning in emerging educational
systems such as in Saudi Arabia. Many policymakers have
been hesitant in lending support for the expansion of e-
learning, citing its ineffectiveness in delivering desired
educational goals, unsuitability for students, lack of self-
direction among students, regulation and motivation,
institutional inexperience and inadequate technologies.
Findings of this research clearly indicate that e-learning is
an effective tool for achieving desired educational
outcomes in countries where online education is still
emerging, such as Saudi Arabia. It adds evidence to the
nascent scholarship establishing a positive correlation
between online education and better student outcomes in
the Middle East. This study provides policymakers with a
real success story demonstrating the effectiveness of e-
learning in unconventional areas, with a predominantly
conservative Arab constituency in Southern Saudi Arabia.
This research presents an efficient, accessible and timely
solution to suspended higher education due to natural
disasters, emergencies or civil wars. E-learning does not
require students to travel to a brick and mortar structure
where the lives of students are jeopardized due to air
bombardments, rocket shelling, earthquakes or flooding.
Students can access course materials remotely from a safe
haven. Faculty can offer collaborative and assisted learning
services to students using online platforms without
worrying about their safety. E -earning provides a
compelling educational solution that guarantees better
equity and access to high quality education in emergency
ridden areas around the world.
Distance education literature often neglects the connection
between e-learning, its benefits and its application in
unconventional contexts, sa hus war-zones. This research
extends the study of e-learning by testing its effectiveness in
war zones specifically. Evidence indicates that well-designed
e- learning initiatives allow universities to provide equitable,
high quality and efficient higher education to inaccessible
populations such as those prevented from attending face-to-
face courses due to wars or natural disasters. The concept of
implementing e-learning in war-zones is inadequately
investigated and needs to be developed further. This research
expands the horizon for further rigorous analyses on the
implementation of e-learning in natural disaster areas to
address inadequate access to high quality education in those
areas.
II. FACE-TO-FACE VERSUS ONLINE
Analyzing data from the same courses over a four-year
period, the authors [28] compared student performance with
respect to the medium of instruction, specifically face-to-
face versus fully online courses. Using a post-test design,
theauthorsconcluded that the “data suggested that student
learning outcomes were essentially the same for face-to-
face and fully online delivery.” This finding seems to be
pervasive in the literature comparing academic student
outcomes across different means of instruction.
Nevertheless, other studies found noticeable statistical and
practical differences in student achievement based on the
way that the courses were delivered [2, 7, 11, 14, 16, 29].
Therefore, the question remains whether online instruction
delivers the same academic results as traditional face-to-
face instruction. Despite the existence of hundreds of
studies which attempt to answer this question, none have
investigated it within the context of the Saudi educational
system.
The seminal work „There is No Significant Difference
Phenomenon‟,[30] concluded that there is no statistical or
practical difference in the student outcomes between
alternative modes of educational delivery. Russell‟s
analysis included over three-hundred and fifty-five articles,
reports, summaries, and related investigations which
indicated no significant difference in thestudents‟academic
and non-academic outcomes between face-to-face and
distance education forms of delivery. Despite the criticisms
Russell‟s work has received regarding its lack of
methodological rigor and inclusion criteria, a few meta-
analyses on the effect educational delivery modes have on
student academic and extracurricular outcomes found that
no tangible difference exists between face-to-face and
distance education delivery models such as hybrid, blended,
or fully online. In a meta-analysis investigation examining
the effects of traditional and distance education course
delivery on student achievement, attitudes, and retention
rates, utilizing one-hundred and fifty-seven studies, Hijazi,
et al. [31] found a slightly positive difference, suggesting
that distance education is actually more effective than face-
to-face delivery in respect to student achievement.
Nevertheless, there were no significant differences between
the various educational delivery systems in respect to the
student‟s attitude toward the courses. Similarly, a meta-
analysis conducted by Zhao, et al. [32] found no significant
difference in student outcomes when comparing courses
taught in traditional classroom settings and those taught in
any form of distance education. In a more recent study,
Dell, Low and Wilker compared student achievements in a
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human development graduate course and three educational
psychology undergraduate courses taught both online and
face-to-face at a large Midwestern United States university
and concluded that the “results suggest there were no
significant differences between the work submitted by
students from the online sections and from the face-to-face
students, and the methods of instruction are more important
thanthedeliveryplatform”[33].
In a study comparing cyber and traditional learners‟
academic performance and perceptions on an introductory
economics course, Navaro and Shoemaker [34] found that
the online learners performed as well as or better than the
traditional students with respect to their academic
performance after holding the effects of gender, ethnicity,
academic background, academic aptitude, and computer
skills constant. Furthermore, the study reported higher
satisfaction rates amongst the cyber-learners compared to
traditional students. Similarly, Harmon and Lambronis [35]
found that the likelihood of answering a question correctly
on an economics exam is significantly higher if the material
was instructed and covered online versus in-class
instruction. The authors continued to suggest that online
instruction results in better academic performance
compared to traditional face-to-face instruction in a
classroom. Comparing student performance in computer
science courses taught both on campus and online, Dutton,
et al. [29] found that the online learners performed better
than the on-campus students. One possible explanation
offered by Dutton is that the online learners tend to be
older, employed, have children, and are more serious,
experienced, and skilled in a variety of aspects compared to
the younger on-campus college students. In a study
comparing student achievement in management courses
taught online and on-campus, Wilson and Allen [36]
concluded that “the assertion that online students perfor m
poorly relative to face-to-face students wasnotsupported.”
Controlling for gender, prior math knowledge, and high
school grades, Brown and Liedholdm compared student
performance in macroeconomics by measuring test scores,
finding that the on-campus students performed better than
the online students [37]. Similarly, Coates, et al., compared
student achievement in the macroeconomics section, and
also concluded that after controlling for age, working hours,
and prior college experience, the face-to-face learners
outperformed their online counterparts [38]. In a recent
reporttitled“OnlineCourse-Taking and Students Outcomes
in California Community Colleges,” the results indicated
that the on-campus learners who received face-to-face
instruction outperformed those who opted to take online
classes across the state community college system. The
authors concluded that “whichever way we look at it, we
are finding consistently that students are performing better
in the face-to-face sections versus the online sections" [39].
The wide variation in the findings regarding the effectiveness
of online instruction when compared to face-to-face course
delivery is resultant of a number of methodological
problems. First, selection bias characterizes a large number
of the samples used in the above cited studies; namely, the
researchers have not randomly assigned students into online
or face-to-face courses [29, 33-34]. On the contrary, the
students self-selected the medium of instruction that best
satisfied their need or desire. This jeopardizes the
representativeness of the samples, especially when the
researchers are only comparing one or two courses, totalling
a small number of students. Second, few studies compared
more than two courses, making it difficult to generalize based
on the small samples [35-37]. Making bold inferences, such
as online learning being as good, better, or worse than face-
to-face instruction, requires a larger sample. Most studies
including online and face-to-face courses do not exceed one
hundred students combined [29, 32, 36, 38]. While
researchers tried to control for instructor differences, material
variation, and course variation by making these as uniform as
possible, small student samples when taking the same course,
at the same college, with similar academic and demographic
backgrounds jeopardizes the key element of any sample: its
representativeness. Third, most comparisons of online and
face-to-face instruction were conducted by researchers who
taught the courses themselves [34, 36-38]. This results in
inducing a certain degree of bias generated by the
participation of the researcher. Researcher bias in social and
behavioural research is unavoidable [40-41].Theinstructors‟
choices, interactivity levels, motivation, charisma,
instructional rigor, and other contextual factors are likely to
influence the comparison results and make the online
instructions appear more or less effective compared to the
face-to-face instructions [35, 38]. Most comparisons of the
course delivery methods do not provide sufficient
information on possible researcher biases that could
influence the inferences based on their findings.
III. BENEFITS OF E-LEARNING
In a report reviewing one thousand empirical studies, the
U.S. Department of Education noted that a greater number
of well-documented benefits resulted from e-learning.
First, e-learning allowed students to access the content of
the courses at any time and from any place [42-43]. E-
learning also focuses on offering options to students unable
to attend face-to-face settings or those who wish not to
partake in the same learning experiences as traditional
students [14]. In addition, e-learning allows for the
distribution of learning materials in a more cost-effective
manner [45-46]. Lastly, e-learning permits the instructors to
reach out to more students while maintaining equivalent
standards of learning quality [42, 44, 46].
In studying the benefits brought about by the adoption of
e-learning in developing countries, Olson, et al. [47],
concluded that students, teachers, and both the economies
and societies in such areas would be greatly improved with
the implementation of e-learning [47-49]. The report
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concluded that the use of laptops in student learning
experiences fosters team work qualities, independent
learning habits, the development of greater critical thinking,
and problem-solving skills in addition more time spent on
homework, thus enhancing the overall learning experience
[12, 17, 43]. E-learning also positively impacts the
performance of teachers who can utilize a variety of means
to motivate students, identify weaknesses to better target
student challenges, and become overall better teachers
through learning new technologies that are likely to
improve the quality of their teaching [50-51]. E-learning by
its very nature introduces both students and teachers to new
technologies, equipping both groups with the necessary
skills and knowledge essential for economic success in
today‟s world. E-learning generally enhances the overall
skillset of students as well as teachers, improving their
chances of obtaining and maintaining employment.
Studies of e-learning in Saudi Arabia have highlighted
the importance of such approaches in expanding
educational opportunities available for women and hard to
reach populations [18, 20]. First, the Saudi educational
system is based on Islamic tradition, where men and
women are not allowed to interact within the same
classroom [19, 21]. This requires universities to offer
equivalent versions of courses for each gender. E-learning
makes this process less expensive, and quality control is
better guaranteed by allowing the same instructors to teach
online or through an internally utilized system accessible to
both sexes [25]. Second, many areas of the Kingdom suffer
from limited access to universities. This population can be
more readily reached through the use of online education
conveyed wirelessly [26].
Additionally, e-learning could potentially be used as an
alternative model to traditional education in crisis and
disaster areas. Olson, et al. [47], concluded that e-learning
was a potential solution to the educational problems in
Libya following the February 14th revolution that resulted
in the death of Libyan leader Muaammar Al Gaddaffi. In
theauthors‟words
“E-learning appears to be a promising alternative.
It can provide learning opportunities anytime
anywhere. It enables students and instructors to use
a wide range of Internet based tools to communicate,
collaborate and share resources, and open up
accessible educational opportunities. ICT and e-
learning could be used (as reconstructive and
attractive measures) to support the affected learners
and instructors in Libya.”
The ongoing conflict between Saudi Arabia, its allies,
and the Houthi rebel group and supporters in Yemen has
resulted in the closure of schools in many areas of southern
Saudi Arabia along the border. E-learning has emerged as a
viable alternative for many institutions such as Najran
University, which closed its classrooms in 2015 for safety
concerns. With the institutionalization of e-learning as an
alternative to traditional face-to-face learning, Najran
University has overcome the political crisis by delivering
its educational mission and standards online.
This study aims to investigate whether there is a tangible
difference in the academic performance between students
attending face-to-face courses and those enrolled online.
Furthermore, the study explores whether e-learning can serve
as an effective system overcoming some of the challenges
brought on by man-made or human crises such as interstate
conflict. The case study analysed here is that of a large public
university located in southern Saudi Arabia where all of its
computer science courses were moved online due to safety
concerns.
IV. HYPOTHESES, DATA AND METHODS
This study hypothesizes that students‟ academic
performance does not differ based on the medium of course
delivery in higher education institutions in the Kingdom of
Saudi Arabia. Further, the research hypothesizes that e-
learning can fulfil educational outcomes in a comparable
fashion to face-to-face educational settings. Available data
from the Computer Science department at Najran
University in southern Saudi Arabia is utilized. Najran
University suspended on-campus learning due to ongoing
conflicts between the Arab Coalition led by Saudi Arabia
and Yemeni rebel groups spearheaded by the Houthi Group.
The Department of Computer Science at Najran University
has collected detailed information on students‟ enrolment,
withdrawal, passing, and course completion rates, allowing
the comparison between face-to-face and online learning.
Najran University was established only recently with a
royal decree from King Abdullah Bin Abdulaziz in 2005,
quickly becoming the largest public university in the
Kingdom with an 18-million square meters campus. The
university has two campuses, one for males and the other
for females, with fifteens and ten colleges respectively. The
university intended to accommodate 45,000 students and
currently has a total enrolment of 14,000 students in its
undergraduate and graduate programs.
This research tests the effectiveness of an e-learning
program developed by the Department of Computer
Science at Najran University based on Andrade‟s [52]
online teaching theoretical framework. The model depicted
in Figure 1 integrates three of the most widely theoretical
frameworks in the distance education literature: Self-
Regulated Learning Model, Transactional Model and
Collaborative Learning Practices Model. This model starts
with designing courses that compel learners to exercise
goal-setting, development and application of strategies,
review of the implementation of those strategies and
fulfilment of set educational objectives. In addition, the
course content, materials, syllabi and supporting services
are designed with organized channels of communication,
interaction and dialogue with students. Instructors are
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trained in fostering collaboration and harnessing help-
seeking practices among learners polishing off the
educational experience with a socially conducive
environment for collaboration and sustained learning. The
resulting e-learning program aimed at aggrandizing
learners‟ autonomy, self-direction and self-regulation to
support individual learning attitudes, behaviors and
improvement.
This framework suggests how distance education and e-
learning initiatives can blend transactional education
models, self-regulation learning models and collaborative
practices into a unified online delivery system. While the
model dimensions overlap and share few similar
characteristics such as structured, organized and facilitating
mediums of learning and instruction, each component is
distinctly fostering an independent pillar of distance
education. In the end, this increases learners‟ self-
regulation, structure, autonomy and educational
performance.
The data used in this study comes from two different
years, one taught traditionally in face-to-face instructional
settings and the other taught online using Learning
Management Systems (specifically Blackboard). All
students were tested on-site for final examinations
regardless of the medium of instruction. This analysis
excluded directed study, independent projects, and
graduation capstones because such courses are tailored to
one individual with a specific scope. Table 1 presents the
course names taught in all four semesters (two in the face-
to-face year and two in the online education year). Note that
courses taught in one semester but not in the other were
excluded in order to reduce non-comparable cases
Measures.
Thirty-six courses with a total enrolment of over 1,000
students over the four semesters are included in this
analysis. Each semester includes the same courses with
varying enrolment numbers. Face-to-face semesters
exhibited higher enrolments compared to online semesters.
Please not that this was the first time in the history of the
Saudi higher educational system, where a department
transferred all its courses from traditional settings to an e-
learning environment. Subsequently, there has been a
steady decrease in computer science courses at the
university and online enrolment is lower than that of face-
to-face courses. Note that students and courses included in
this analysis come from both the male and female campuses
at Najran University. Most students come from the city of
Najran, an urban area, and are enrolled in the undergraduate
curriculum of the department or other colleges around the
university. Most students are within the age range of 18 to
22 years old. Courses were taught by the same instructors in
TABLE I
COURSE NAME AND ENROLMENTS IN THE TWO SEMESTERS
Course Name
Visual Programming
Database Foundations
Information Systems Design and Analysis
Modern Approaches for Application Programming
Database Systems Architecture
Database Systems Administration
Database Systems Engineering
Database Systems Project Management
Computer Networks and Data Communication
Database Systems Strategies
Information Networks Administration
Electronic Business
Multi-medium Technologies
Internet Application Development
Decision Support Systems
Information Systems Security Administration
Computer Programming 1
Object Oriented Programming
Design and Analysis of Algorithms
Computer Organization and Collection Language
Unix Environment
Operating Systems
Theories of Computing
Computer Graphics
Human-Computer Interaction
Computer Architecture for CS Majors
User Interface Programming
Programming Engineering
Design and Construction of Translators
Artificial Intelligence
Foundations of Database Management Systems
Modern Topics in Computer Science
Computer Security
Social, Ethical and Professional Issues
Parallel and Distributed Systems
Internet Technologies
Total: 36
Fig.1. Adapted Online Teaching Theoretical Framework
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both semesters, decreasing the influence of instructional
rotationandinstructors‟interactivitylevels.
Themaindependent variable intheanalysisis students‟
academic performance. This outcome is measured using
various indicators to cross-validate results obtained from
the analysis. First, the number of passing students in each
course serves as a simple indicator of students‟
performance. The higher the number of passing students,
the higher students‟ performance in the course is
considered. Second, the percentage of passing students
(passing rates) is another indicator of student performance.
The higher the percentage among those who took the entire
course and final examinations (and were not terminated,
suspended,or withdrawn), the higher is a course‟slevelof
student performance. Finally, withdrawal rates are taken as
another indicator of student performance. The higher
withdrawal rates are in a course, the lower the rates of
students‟ performance are recorded. Note that the
correlations between the three variables are sufficiently
high as evident in Table 2 which prompts the conclusion
that all such indicators measure a latent construct, student
academic performance. Taking all these measures together,
analysts can better evaluate student performance in face-to-
face as well as online learning environments.
The primary independent variable in this analysis is the
course delivery medium, a categorical indicator coded 0 if
the course was taught online and 1 if the course was taught
face-to-face. This leads to the conclusion that the unit of
analysis in this research is the individual course.
Information about courses, however, informs stakeholders
on student academic performance. Since this research is
aimed at establishing the direction and strength of
relationships among course delivery method and student
academic performance, the appropriate research strategy
proves to be quantities correlational design.
To evaluate the proposed hypotheses, a simple
comparative analysis between the means of course passing
rates, passing students and withdrawn students in the face-
to-face learning environment and online learning semester
is carried out. Since the courses taught are the same in four
consecutive semesters, a paired sample exists. Therefore,
the analysis utilizes the paired samples t-test to evaluate the
statistical and practical significance of the mean differences
in student performance between face-to-face and online
learning settings, if existent. The paired t-test is a repeated
measure design that is more powerful compared to other
designs such as between group designs.
V. RESULTS
Table 3 displays all 36 courses with passing rates in each
year. Note the value for passing rate is an average for the
course across two semesters, considered for each
corresponding year. The right-hand column presents the
difference between face-to-face values and online learning
values. Note that passing rates refers to the percentage of
those students who passed the course from the total number
of students who were admitted into the final examination
phase. For instance, if ten students in a computer science
programming course were admitted into the final
examination period and all passed the passing rate would
equal 100. The table indicates that 26 online courses have a
passing rate of 100% compared to about 17 courses in the
face-to-face learning environment.
Face-to-face courses had a higher rate of passing
students, with 24 courses featuring a higher number of
passing students in a face-to-face environment compared to
about 8 courses having online courses surpass face-to-face
participation in terms of the number of passing students.
Twenty-seven courses had the same number of withdrawn
students regardless of the medium of instruction, and all
such cases had zero students withdrawn from classes. In
about 14 courses, the difference between passing rates in
face-to-face and online courses exceeded 10 points. In fact,
in 4 courses the passing rate exceeded 30 points of
difference. Thirteen courses had higher passing rates for
online courses compared to 9 face-to-face courses. Fourteen
courses had the same passing rate in both semesters. The
results show marked differences in passing rates and the
number of passing students dependent on the medium of
instruction. Simultaneously, the findings show no real
differences in terms of the number of withdrawn students
among the courses based on whether they were delivered
online or face-to-face. Those differences, however, are seen
on the individual course level and the inspection at the
aggregate level follows below.
Figure 2 displays a bar chart with the course delivery
mode, face-to-face versus online, on the x-axis while the
mean of passing rates for courses in the 4 semesters is on
the y-axis. Notice that in both years, the mean of passing
rates was about 90%. The bars show a little difference,
indicating that online courses had a higher rate compared to
face-to-face courses. Nevertheless, such a difference seems
to be negligible, 0.5 or half a point. Figure 3 displays a bar
chart depicting the mean of passing students on the y-axis
and course delivery mode on the x-axis. The figure shows a
difference of 2.3 students; 7.1 for face-to-face courses and
4.8 for e-learning courses. This difference is non-negligible
and may be partly due to the larger number of students who
attended face-to-face courses compared to online courses.
Figure 4 displays the mean of withdrawn students in face-
to-face courses and online courses. The findings indicate
that the difference is miniscule, 0.3. Such figures
demonstrate that face-to-face and online courses have
TABLE 2
MEANS OF PASSING RATES BY COURSE DELIVERY METHOD
Variable
Passing
Rates
Passing
Students
Withdrawn
Students
Passing Rates
1.0
0.83
-0.78
Passing Students
0.83
1.0
-0.82
Withdrawn Students
-0.78
-0.82
1.0
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similar passing rates and numbers of withdrawn students. Conversely, they differ with respect to the number of
passing students due to the larger student body size that
enrolled in face-to-face courses compared to online classes.
TABLE 3
COURSE NAME AND THEIR PASSING RATES
Course Name
Face-to-
Face
Enrolment
Online
Enrolment
Difference
Visual Programming
(88)
(100)
(-12)
Database Foundations
(88)
(100)
(-12)
Information Systems
Design and Analysis
(50)
(67)
(-17)
Modern Approaches for
Application Programming
(100)
(100)
(0)
Database Systems
Architecture
(89)
(100)
(-11)
Database Systems
Administration
(100)
(100)
(0)
Database Systems
Engineering
(71)
(50)
(21)
Database Systems Project
Management
(100)
(100)
(0)
Computer Networks and
Data Communication
(80)
(100)
(-20)
Database Systems
Strategies
(100)
(86)
(14)
Information Networks
Administration
(100)
(75)
(25)
Electronic Business
(95)
(91)
(4)
Multi-medium
Technologies
(89)
(71)
(18)
Internet Application
Development
(100)
(100)
(0)
Decision Support Systems
(92)
(100)
(-8)
Information Systems
Security Administration
(82)
(100)
(-18)
Computer Programming 1
(79)
(50)
(29)
Object Oriented
Programming
(31)
(100)
(-69)
Design and Analysis of
Algorithms
(89)
(100)
(-11)
Computer Organization
and Collection Language
(100)
(100)
(0)
Unix Environment
(67)
(100)
(-33)
Operating Systems
(89)
(100)
(-11)
Theories of Computing
(100)
(100)
(0)
Computer Graphics
(100)
(90)
(10)
Human-Computer
Interaction
(100)
(100)
(0)
Computer Architecture for
CS Majors
(100)
(100)
(0)
User Interface
Programming
(83)
(100)
(-17)
Programming Engineering
(71)
(0)
(71)
Design and Construction
of Translators
(100)
(100)
(0)
Artificial Intelligence
(86)
(50)
(36)
Foundations of Database
Management Systems
(91)
(100)
(-9)
Modern Topics in
Computer Science
(100)
(100)
(0)
Computer Security
(100)
(100)
(0)
Social, Ethical and
Professional Issues
(100)
(100)
(0)
Parallel and Distributed
Systems
(100)
(100)
(0)
Internet Technologies
(100)
(100)
(0)
Fig. 2 Passing Rates
Fig. 3 Quantity Passing
Fig. 4 Withdrawn students
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Table 4 displays the means, standard deviations, and
sample sizes for the number of withdrawn students, number
of passing students, and passing rates for face-to-face and
online courses. As previously indicated, results show little
difference between course means with respect to passing
rates and the number of withdrawn students. Further, the
means seem to differ significantly, which will be assessed
more below, with respect to the number of passing students.
Despite the mean differences regarding the number of
passing students, the distribution of the variable is similar
with respect to the standard deviation (3.7 for face-to-face
learning versus 3.5 for online learning), suggesting similar
distributional characteristics. This indicates that the likely
explanation for the mean difference is simply the larger size
of student enrolment in the face-to-face semester.
Table 5 presents the results of three paired sample t-tests
on passing rates, the number of passing students, and the
number of withdrawn students. Please note that each course
included in the analysis received two measurements, one is
the average for the two face-to-face semesters and one for
the two online learning semesters. This allows detecting the
statistical and practical differences in means among the
three variables. Results indicate that mean differences with
respect to passing rates and the number of students
withdrawn from courses are not statistically significant,
with p-values of 0.880 and 0.850 respectively. The
confidence intervals for both variables at the 95% level
contains zero in them, indicating that the mean differences
are not statistically significant. The slight difference in
means yields no practical significance in the two variables.
On the other hand, the p-value corresponding to the number
of passing students is 0.006 with a t-value of 2.93
indicating statistical significance. This result is consistent
with the large practical means‟ difference betweenface-to-
face and online courses with respect to the number of
passing students. This result may be due to the larger
number of students who registered in the face-to-face year
compared to the online learning year.
This research tested an integrated e-learning framework
based on self-regulation learning models, transactional
distance learning and collaborative practices. The model
presented in Figure 1 wassupportedbyNajranUniversity‟s
experience. Student academic performance in Computer
Science was found to be satisfactory and equal to that
obtained through face-to-face instruction. The department‟s
data indicated that the Computer Science faculty designed
well-structured courses that helped students in fostering
goal setting, applying helpful learning strategies and
monitoring their progress. Further, evidence indicates that
the level of interactivity between faculty and students, as
well as students with each other was high, fostering a
collaborativelearningenvironment.Finally,Najran‟sonline
experience provided evidence that well designed online
education fosters adequate learner autonomy capable of
improving student academic performance.
Figures 5-9 present findings based on an internal
departmental assessment of faculty performance throughout
the e-learning year. First, the department reported that there
was a high participation rate from the faculty teaching
online. Figure 5 shows that on average, 82% of the teaching
faculty have provided the department with information
about their courses throughout the 11-week long semester.
By the same token, Figure 6 displays the percentage of
content uploaded by faculty members throughout the
semester. The graph indicated that on average, 87% of
faculty members uploaded their materials online for
students to use throughout the semester. Figure 7 indicates
that faculty members heavily used the virtual classes,
resulting in a semester average of 83%. Figure 5 suggests
that on average, 18% of classes were missed due to
technical problems per week, and Figure 8 shows that the
faculty members experienced a moderate number of
TABLE 4
MEANS COMPARISON BETWEEN FACE-TO-FACE AND ONLINE COURSES
Delivery Mode
Withdrawal
Passing
Passing Rate
Face-to-Face
Learning
Mean
.3784
7.1081
89.4595
N
37
37
37
Std. Dev.
.82836
3.73262
15.37782
E-learning
Mean
.4054
4.8649
90.0000
N
37
37
37
Std. Dev.
1.01268
3.53681
21.55871
Total
Mean
0.3919
5.9865
89.7297
N
74
74
74
Std. Dev.
.91887
3.78350
18.59835
TABLE 5
PAIRED T TESTS RESULTS
Paired Samples Test
Paired Differences
t
df
Sig.
Mean
Std. Deviation
Std. Error Mean
95% Confidence Interval of the
Difference
Lower
Upper
Pair 1
Passing1 - Passing2
2.24324
4.6452
0.76367
0.6944
3.79204
2.937
36
0.006
Pair 2
Passing Rate1 - Passingrate2
-0.54054
21.613
3.55324
-7.7468
6.66577
-0.152
36
0.880
Pair 3
Withdrawl1 - Withdrawl2
-0.02703
0.8655
0.14230
-.31563
0.26158
-0.190
36
0.850
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technical issues while teaching online with an average of
almost 30% a week. Figure 9 shows that almost half of the
lectures were recorded through the Learning Management
System used by the department.
Those graphs indicate that faculty members were actively
engaged in utilizing the available resources for teaching
their assigned courses online. The high percentages of
faculty participation, low percentage of missed classes, and
the moderate number of technical issues coupled with high
rates of course accomplishment as outlined above, shows
that the e-learning experience within the department has
proved to be quite successful.
Results indicated that face-to-face and online learning do
not significantly differ. The paired t-test findings alluded
that the mean differences in passing rates and the number of
passing students were not statistically or practically
significant. With respect to the number of withdrawn
students, the difference in means was statistically
significant; however, the larger size of enrolment in the
face-to-face instruction semester may have generated such a
result. The internal departmental investigation has
established that faculty actively participated, delivered, and
evaluated learning outcomes during the e-learning semester.
This indicates that online education is as effective as face-
to-face instruction, yielding similar results.
VI. DISCUSSION AND CONCLUSION
This study supports the no significance hypothesis,
suggestingthatastudent‟sperformancedoes not differ with
respect to the educational delivery mode (face-to-face
versus online) [2, 4, 6, 8, 11]. While this research is novel
given its exploration of a new context (Saudi Arabia) and
breadth (inclusion of all courses offered by a large
computer science department), the findings of the study
confirm the earlier results by concluding that the course
delivery technique has little impact when it comes to
justifying the course passing rates. It is difficult to
generalize these findings across all Saudi universities,
departments, or Middle Eastern higher learning institutions,
though such findings should persuade opponents of e-
Fig.5. Overall faculty participation.
Fig.6. Overall faculty participation in uploading lectures
Fig. 9. Overall percentage of recorded lectures through BB collaborates
Fig. 8. Overall number of technical problems faced
Fig.7. Overall faculty usage of virtual class in the blackboard systems
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VOLUME XX, 2017 9
learning implementation by demonstrating that it carries the
same, if not better, results than traditional face-to-face
learning.
One of the main findings is that enrolment rates in the
online semester were significantly lower than the face-to-
face semester. This difference may be due to students‟
increased fears of taking online courses. Notice that Najran
University‟s experiment withonline teaching ist helargest
and first of its kind in the Kingdom. Students perceive
online courses as lacking in support, interactivity,
connectivity, and as more difficult academically. For such
reasons, Saudi students are likely to avoid registering in
online courses. University administrators should increase
student confidence levels in online education through an
awareness campaign showing the mechanics, logistics,
usefulness, accessibility, and interactivity of online courses.
University faculty should receive formal training in
delivering course contents through Learning Management
Systems and following best practices for teaching via
online platforms. While universities in Saudi Arabia are
expanding their online education programs, they still need
to do more work to harness students trust in e-learning.
This study‟s findings challenge popular perceptions
among educators as well as policy-makers in Saudi Arabia
and the Middle East about the effectiveness of e-learning.
These perceptions include: lower quality of education
offered by e-learning compared to face-to-face settings, the
lack of need given comprehensive on-campus programs,
insufficient knowledge about the nature, implementation, or
potential of e-learning, and the substantial bureaucratic
burdens associated with creating new e-learning programs.
Further, this study demonstrated that e-learning in Saudi
Arabia is capable of delivering the same, if not better,
educational quality as that provided by traditional delivery
settings. It has also shown that the implementation and
maintenance of e-learning courses and programs does not
involve the contracting of immense resources. Given the
outcomes, this research contributes to the efforts of
adopting and expanding e-learning initiatives across the
region.
In addition, this study has shown the power of
Information Communications Technologies (ICTs) in
overcoming challenges such as war or natural disasters by
delivering the educational mission and vision of higher
learning institutions remotely. E-learning has proven to be a
successful course delivery method at Najran University.
The Computer Science Department was able to engage its
faculty, staff, and resources to teach all of its courses online
while the university closed its doors for traditional learning
due to the worsening humanitarian conditions resulting
from the political crisis between Saudi Arabia and Yemen.
While the student evaluations of their online experience are
not well documented, the data obtained from the
department indicated high levels of success characterizing
the e-learning program at Najran University.
This research opens paths for future research on the
impact of e-learning on student performance in the Middle
East, an unexplored area of inquiry. It also encourages
future study on the applicability and potential of e-learning
in areas unraveled by political instability and conflict. E-
Learning is developing exponentially across the Kingdom
of Saudi Arabia and the Middle East generally. Therefore,
more concern should be devoted to its effectiveness,
implementation, and impact on students' academic and non-
academic outcomes.
Natural disasters in the form of hurricanes, wildfire,
floods, famines, or civil and interstate conflicts regularly
prevent millions of children, college students, and adult
learners from accessing brick and mortar schools, colleges,
or universities. E-learning can mitigate the magnitude and
severity of these impacts on education delivery. Refugees in
host countries may fully access wired computer labs
connected to university and school servers abroad. Thus,
access to education for vulnerable groups such as refugees
or those affected by natural disasters improves significantly
with the prospects of e-learning. The use of e-learning as an
alternative medium of education for all levels should be
seriously considered in areas suffering from emergencies
such as a number of Middle Eastern nations including
Syria, Iraq, Libya, Yemen, and Lebanon.
At best, E-learning costs less than constructing and
maintaining educational facilities. It also requires a lower
number of academic and administrative staff. E-learning
eliminates heavy dues and the hefty requirements of
running large educational facilities, proving to be a solution
for delivering basic educational curriculum to suffering
populations. It can also be administered from a long
distance, connecting the best brains available and desiring
to assist in lessening the hardships faced by affected student
groups. The best example can be offered by large Massive
Open Online Courses platforms such as Coursera. Despite
the shortcomings of any online educational medium, it can
at least be accessed by hard to reach populations who can
have access to the study material online and practice what
they learn using virtual machines from their homes, cafes,
designated learning labs, or anywhere connected to the
internet. For all such reasons, e-learning is an effective tool
in delivering educational goals in crises ridden areas such
as the southern borders of Saudi Arabia.
This research contributes to the efforts of making higher
education more accessible, efficient and sustainable in
Saudi Arabia as well as in other areas are affected by
disasters, natural or otherwise. Najran‟s university
experience provides compelling evidence that the university
curriculum, instruction and evaluation can reach more
students faster through its e-learning program than its brick
and mortar apparatus. Equity in education is defined by two
components: access and quality. Delivering educational
content by Saudi universities online can reach the same
desired population targeted through face-to-face
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VOLUME XX, 2017 9
approaches. Student performance rates in the computer
science department, one of the toughest areas of education
across the university, did not fall in the e-learning program.
On the contrary, in many courses, students‟ academic
achievement improved significantly. Faculty members
reported high levels of self-reported satisfaction with the
quality of courses delivered online at Najran university.
Informal assessments by the College, department and allied
staff exhibited high levels of approval with the statement,
“online courses provide equal if not superior quality
educationtotraditionalmethodsofinstruction.” Oneofthe
more increasingly used indicators to measure quality of
coursesisstudents‟satisfaction.
Detailed discussions with students who enrolled in both
sessions, the face-to-face and online phases, reported higher
satisfaction with the online delivery method. This is due to
the ease of access, processing and retrieval of course
materials posted on Blackboard. All in all, online education
seems to score higher on equity, access and quality than
face-to-face instruction. E-learning serves as a sustainable
form of education. It is cheaper to provide online courses
than on-campus courses. E-learning utilizes less material
resources, less human capital and is more agile compared to
face-to-face education. E-learning not only saves
universities undue costs to broaden the educational, service
or research endeavors of students and faculty, but also
delivers education and resources in a timely, easily tractable
and monitored fashion. Therefore, this paper supplies
higher education stakeholders in Saudi Arabia with telling
results that Najran university‟s experience with e-learning
presents Saudi students with more equitable, accessible,
quality and sustainable education compared to face-to-face
approaches.
This research does not only present an on-going extensive
debate on whether e-learning provides satisfactory
educational gains, but also tests the effectiveness of an e-
learning program in a previously neglected context: the Saudi
higher education system. It also outlines the potential
benefits offered by e-learning in war-ridden zones. This
research offers a real success story where e-learning
delivered efficient, equitable, accessible and high-quality
education to students who could not attend classes due to an
ongoing war. This is a novel research agenda attempting to
address an internationally forgotten crisis, inadequate access
to high quality higher education in hard to reach geographic
areas, war-zones, areas suffering from epidemics, natural
disasters, civil wars or other types of emergencies.
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Khairan D. Rajab (M‟06) is working as an Assistant Professor, Vice
Dean of E-learning and Distance Education and also the Head of Network
and Communication Engineering Department at College of Computer
Science and Information Systems (CSIS), Najran University, Najran,
Saudi Arabia. He received Ph.D. in Computer Science and Engineering
from the University of Southern Florida, United States under supervision
of Prof. Les A. Piegl. He also received his Masters from the University of
South Florida and his bachelor from the University of South Carolina,
United States. Dr. Rajab has published more than 16 research papers in
high impact factor journals and reputable conferences. He is also a
reviewer and editorial board of several research conferences and journals.
His research interests are geometric modeling, NURBS, data mining, and
network security, as well as cyber learning; in addition, he is a member of
IEEE and College Council at CSIS.
