WITH COMMENTS-Research Proposal - Impact of Students' e-Learning during Covid-19 (1).docx

Impact of Students' e-Learning during Covid-19
A Study focused on HEI's in Oman
By:
Student Name: Mohammed Alajmi
Student ID: 17214

Executive Summary:
At the point when Covid-19 was found to make broad frenzy due a few passings all through the
world, Higher Educational Institutions (HEIs) had to close and eliminate scholarly exercises from
study hall settings. Notwithstanding, since there isn't adequate space for the current understudies
in general, and their places should be provided by understudies from lower levels, online training
was made as an answer. The review's targets will be to decide the viability of e-gaining according
to the point of view of understudies in advanced education foundations, to find out about the
difficulties and chances of the e-learning environment, and to find the connection between key
factors, for example, understudy fulfillment and different e-learning devices. While conducting e-
learning activities in numerous learning organisations, the process has a variety of effects on
students that must be revealed in order for negative effects to be corrected for better results and
positive effects to be rewarded with more incentives for students' comfort and satisfaction while
completing their courses. The research will look at learning efficiency and satisfaction, e-learning
technology, student challenges and benefits, and the flexibility of e-learning for students who are
used to traditional classroom learning. Despite the fact that some schools had previously adopted
e-learning, but not for all courses or all students, the Covid-19 epidemic resulted in a significant
change in the learning environment for individuals who had never used online platforms. Main
data will be used as the primary source of information, and questionnaires will be used as the
primary research technique. A total of 150 students from various higher education institutions will
be selected at random for the research. To investigate the impacts of e-learning on students, both
qualitative and quantitative research methodologies will be employed throughout the study project.

Contents
Executive Summary:.....................................................................................................................2
1. Introduction:.........................................................................................................................5
1.1 Research problem:...............................................................................................................5
1.2 Research Background:.........................................................................................................6
1.3 Research Aim and Objectives: .............................................................................................7
1.4 Value of the Research: .........................................................................................................7
1.5 Practical Importance: ..........................................................................................................8
1.6 Academic Importance:.........................................................................................................8
2. Literature Review:.................................................................................................................9
2.1 e-Learning:..........................................................................................................................9
2.2 Pandemic – Covid-19:..........................................................................................................9
2.3 Methods ofe-Learning:......................................................................................................10
2.4 Challenges of e-Learning:..................................................................................................10
2.5 Opportunities ofe-Learning:.............................................................................................12
2.6 Resources:..........................................................................................................................13
2.7 Physical Learning Vs e-Learning:......................................................................................14
2.8 Other Research:.................................................................................................................15
2.9 Psychological Impact: ........................................................................................................16
3. Research Methodology:.......................................................................................................17
3.1 Introduction:......................................................................................................................17
3.2 Sources of Data:.................................................................................................................17
3.3 Sample Size:.......................................................................................................................17
3.4 Questionnaire: ...................................................................................................................18
3.5 Key Variables:...................................................................................................................18
3.6 Qualitative Analysis:..........................................................................................................19
3.7 Quantitative Analysis:........................................................................................................19
3.8 Approach to Data Analysis: ...............................................................................................20
3.9 Research Limitations:........................................................................................................20
4. Data Collection and Analysis:..............................................................................................21
4.1. Response Rate...................................................................................................................21
4.2. Demographic Profile:...................................................................................................21
4.3. Reliability Test:.................................................................................................................26

4.4. Descriptive Statistics: ...................................................................................................28
4.5. Linear Regression Assumptions:.......................................................................................29
4.6. Correlation Analysis:........................................................................................................31
4.7. Heteroscedasticity:............................................................................................................32
4.8. Histogram:........................................................................................................................32
5. Conclusion and Recommendations ......................................................................................34
5.1. Conclusion:.......................................................................................................................34
5.2. Recommendations:............................................................................................................34
Timeline......................................................................................................................................36
References...................................................................................................................................37

1. Introduction:
“COVID-19 has unprecedentedly hit the world and crippled many social and economic sectors,
including higher education (Tamrat 2020; Rahiem 2021). Thoroughly analysing the measures
taken by 20 countries worldwide, Crawford et al. (2020) found that universities have responded
differently to the staggering threats caused by COVID-19. The responses depended on the number
of students and the government’s structures. These measures included temporary campus closures,
the complete shift of education from face-to-face to online instruction, or classes offered on
campus with strict social distancing measures.
In Oman, the Covid-19 Supreme Committee announced the suspension of all classes in Higher
Education Institutions and asked the concerned to look for alternatives to face-to-face education
(Covid-19 Supreme Committee Holds First Meeting, 2020). Some HEIs took a more complicated
approach by completely shutting down, waiting for the new academic year to begin and starting
classes as usual. Nevertheless, as the pandemic continued to threaten people’s lives, students have
been unable to attend their colleges and universities until recently, necessitating the classes
delivery using various electronic platforms. This complete shift to e-learning was a new experience
that came with unforeseen challenges for students, teachers and administrators (Mohmmed et
al.,2020). Most of the HEI’s in Oman suspended all their classes at the end of March 2020 and
switch most exams into home assignments. For general foundation programme (GFP) students,
the decision to conduct final exams was delayed until the beginning of September 2020,
anticipating that the pandemic would be over. Then, the university administrations decided to rely
on the student’s continuous marks to determine their results. And by the end of September 2020,
the HEI’s in Oman announced that all classes would be online and that students should take the
necessary preparations to ensure their studies would not be disrupted during the semester.”
1.1 Research problem:
When Covid-19 was found in late 2019, it had an influence on operations, notably learning
processes, as students were able to study from home using e-learning portals, avoiding crowds.
Governments enforced a variety of restrictions, including a ban on meetings, which might help
Covid-19 spread. To comply with the social distance regulation, educational institutions were
required to transition from a physical to a virtual learning environment. According to the
population of learning institutions in various locations, maintaining a social distance of at least 1.5

meters may be problematic. However, if students may use e-learning systems to study at home,
the rate of Covid-19 spread will be lowered since there would be fewer possibilities for students
to gather in large groups. The review will focus on advanced education establishments (HEIs) that
have carried out e-learning frameworks. In any event, for the individuals who had recently would
not permit such a learning interaction to happen, the pandemic constrained an exceptional and
abrupt change. While understudies might have the option to proceed with their learning processes,
signing up for e-learning programs has various downsides. During Covid-19, the impact of e-
learning on society and the existences of understudies at HEIs in Oman was blended, which will
be addressed and inspected in the examination to reveal what the realizing program has meant for
society and the existences of understudies at HEIs in Oman. While e-learning has a number of
issues and consequences, the impact of attention will be confined to students. There will be
ramifications for educational institutions as well as professors and lecturers, but the focus will be
on students. Students are part of an educational system that prepares them for future careers and
vocations, which might be jeopardized if they fail to complete practical responsibilities like
attending laboratory classes.
1.2 Research Background:
E-learning has been around since 1999, when it was coined by the CBT systems seminar.
Following that, further terms were looked up, including "online learning" and "virtual learning,"
among others. The first test on a computer-based training program was released, despite the many
tests and upgrades carried out to bring e-learning to completion. The number of students enrolling
in HEI courses has increased dramatically in Oman, causing traffic congestion. This must be
addressed through the implementation of online systems capable of handling huge numbers of
students without congestion. In spite of the way that there are various measures to think about
while surveying e-learning programs, it was essential to inspect what is happening during Covid-
19, when practically all HEIs had to create and work utilizing e-learning stages. Whenever Covid-
19 was announced an overall pandemic liable for the passings of millions of individuals all through
the world, instructive organizations had to close. Understudies are supposed to be shown utilizing
web empowered advancements like Zoom, Skype, Google Meetings, and different sorts of
innovation based schooling as opposed to ordinary homeroom guidance. To allow for the exchange

of information and interaction between students and their instructors, learning stations set up in
homes need a computer or laptop as well as a decent internet connection.
1.3 Research Aim and Objectives:
1.3.1 Aim:
Because educational institutions had a high number of students, staff, and other visitors, the Covid-
19 outbreak caused a significant adjustment in how operations were conducted, with learning
activities being the most affected. When all learning activities were relocated from the classroom
to simulated platforms where anybody may attend online courses from their backgrounds or dorm
rooms, students who were not prepared for online learning were taken aback. The study's purpose
is to evaluate how the e-learning program impacts pupils in Covid-19, when resources like money
are short due to lower economic activity.
1.3.2 Objectives:
1. Determine the efficiency of e-learning from the perception of students at higher education
institutions.
2. To find a relationship among important criteria, such as student happiness, and various e-
learning technologies.
3. To gain insight into the challenges and opportunities facing the e-learning ecosystem.
1.4 Value of the Research:
The exploration will help understudies since they will be the significant focal point of the
assessment of the effect of e-learning on them during Covid-19, when pretty much every human
action has been upset here and there. There are consistently advantages and difficulties in the lead
of the e-learning process among understudies. It will aid in identifying how to continue the learning
process successfully in order to have a great experience while decreasing the issues. Students may
be taught about how technology has created new chances for them to participate in activities while
remaining in the comfort of their own homes. The research will assist in the creation of low-cost
alternatives to e-learning so that students may afford the essential equipment and continue their
studies, even if they were previously hostile to online learning. Because the outcome of the Covid-
19 pandemic is uncertain, the research will aid children in finishing their education so that they do
not waste time while waiting for normal school programs to resume. Rather of spending time on

registered courses, students will benefit from e-learning since it will help them grasp the need of
continuing to study and completing educational programs and calendars as required.
1.5 Practical Importance:
Professionals and other service providers may now work on projects in various regions of the globe
while still meeting their obligations thanks to the internet. It will show how lecturers and professors
may operate remotely and earn a living without ever having to meet with students by taking lessons
online. Similarly, students will get an understanding of how they may put their skills and talents
to good use by locating opportunities that allow them to work remotely when their educational
courses are done.
“The current study is crucial to understanding how the shift from face-to-face education to remote
online education impacts student’s motivation and commitment to their studies, initiated by
COVID-19. In Oman, there has never been a time like when almost all HEIs shifted completely to
online education through electronic platforms such as Zoom, Skype, Google Meetings, and other
forms of technology teaching. Therefore, research in this area benefits all stakeholders, including
students, academics, and policymakers. This study helps shed light on student’s attitudes towards
online learning and what aspects of online learning encourage autonomous learning. The findings
can be generalised to other contexts because students worldwide share many experiences after the
shutdown of HEIs due to the pandemic.
Unlike most studies on COVID-19 and their effect on education that have used quantitative tools,
this study provides authentic thoughts from the experiences of students who shared their feelings
openly about their experiences during their first in-home-studying semester.”
1.6 Academic Importance:
Students will be able to complete the courses without needing to wait for Covid-19 to end or be
monitored and managed before continuing their studies. Due to the persistence of the learning
process even throughout the pandemic era, students will profit from a good outcome if they are
able to graduate on time. E-Learning will assist students since it will allow everything to proceed
according to plan and timetables to work out well for them.

2. Literature Review:
2.1 e-Learning:
E-learning, as per Azlan et al. (2020), is an approach to getting information through the utilization
of innovation. The significant entertainer in innovation is the web, which can pass data on through
an assortment of apparatuses. Among the apparatuses displayed all through the examination were
Adobe Presenter, the Xerte Project, Quick Lessons, Composica, and Udutu. The best web based
learning framework is one in which the web association is steady and the power supply is reliable,
forestalling unsettling influences that could lead a few members to miss important conversations
or presentations (Azlan et al., 2020). The technology employed is greatly influenced by the
resources available and the user experience that users enjoy inside a particular educational
institution.
“The past studies show that the term e-learning is defined by (K.H. Fee, 2005) as any learning that
involves using internet or intranet. A year later (K. Cheng, 2006) made the definition more
generalized by indicating that it is anything delivered, enabled, or mediated by electronic
technology for explicit purpose of learning. According to (H Li, 2009) e in e-learning should not
stand for electronic; it should be an abbreviation for evolving, enhanced, everywhere, every time
and everybody. Although the e-learning term and tools do exist for over a decade, the educational
research field has not given enough attention to the study of student motivation under the effect of
e-learning.”
“According to a research, e-Learning is a promising instructional medium as well as a ripe area in
which to conduct investigation on its impact and effectiveness on student knowledge acquisition
and teaching methodology. Many organizations adapt E-Learning to train employees while
educational institutions use technology and internet to improve the quality of education (Simmons,
2002; Sahin & Thompson, 2007; Selim, 2007).”
2.2 Pandemic – Covid-19:
A perilous infection was found in late 2019 that has made different passings and is incredibly
irresistible due viral parts inhaled from a contaminated patient. While learning establishments were
closing down, youngsters and different understudies were creating and requesting to join the
learning educational program, prompting the reception of e-realizing, which allows the interaction

to be continuous, as indicated by Krishnapatria (2020). Understudies were expected to have
PCs/workstations and web associations, while educators were provided systems to permit them to
lead gaining programs from their homes of learning foundations, since the school personnel is
small and can satisfy social distance prerequisites (Krishnapatria, 2020). Since most of
understudies were supported by their folks, guardians were expected to give the learning assets
utilized in the e-learning process, for example, making web associations in their homes and buying
PCs for the learning system.
2.3 Methods of e-Learning:
“E-learning has grown in significance as an educational tool just like technology has developed
and progressed over the years. Interestingly, there have been more efforts at advancing technology
than on attempting to understand the needs and learning styles of individual learners and
instructional design. The 21st century has seen rapid progress with such things as the Internet and
online learning. The technology enhancement learning techniques give flexibility and freedom to
the faculty to select the proper assistance applications in course enhancement and motivated
students to more understanding. The selection of the right application gives beneficial results of
using E-Learning techniques with teaching experience in assessment to improve both academic
performance and developing teaching assessment methods with updated requirements for higher
education institutions in Oman.”
Numerous advanced education foundations in Oman have presented e-learning frameworks for
their understudies, with Computer Managed Learning (CML), Computer Assisted Instruction
(CAI), Adaptive E-Learning, and Asynchronous Online Learning being the most frequently
utilized systems. In his exploration, Pustika (2020) used ways to deal with uncover that various
organizations utilize various ways in view of how well the work force (educators) can apply the
strategies in accomplishing instructive models without experiencing impediments. One more
component considered by Oman HEIs is the expected endeavors of direction among understudies
in understanding how to utilize the predefined techniques for e-learning.
2.4 Challenges of e-Learning:
Before Covid-19, numerous HEIs had not executed e-learning programs, which were generally
utilized by parttime understudies who worked during the week and went to classes on ends of the

week and evenings. Following the pandemic's disclosure, which upheld limitations and regulation
ordering movements of every kind to be completed at home, e-learning bloomed, convincing all
understudies to study from home using innovation. Almaiah et al. (2020) investigated what the
world's most serious issues with e-learning were, and thought of a rundown that incorporates an
obsolete UI, in a hurry course access, unfortunate understudy commitment, and an absence of
homeroom like educator presence. Most of stages just let understudies to see the educator, not the
stage, so they can notice the teacher's feelings and exercises. At the point when understudies know
that they are not being checked, they are bound to mingle and take an interest in exercises other
than enrolling their presence dynamic while giving practically no consideration. Numerous
understudies, for instance, may sign up for a Zoom meeting lead by an instructor, liking to put
down their gadgets and participate in different exercises while they can simply pop in to answer
when their anxiety is required.
“Zhang et al., (2004) stated that E-learning is still not in a place to replace traditional learning due
to several issues, although E-learning is an effective method in certain situations. As learning is
more of a social cognitive task, E-learning cannot cover such an element between students
themselves and even with the instructor. The lack of face-to-face interaction would be easily
revealed within such teaching. Getting bored can be also observed with students: staying in front
of a computer for a long time will add to that. Other aspects which need some considerations are
issues related to the responsibilities of instructors, students, and other interested parties.”
“Another challenge of e-learning according to research is the accessibility to educational
technology has been identified as vital for acquisition of knowledge and information dissemination
to students, as well as interaction between lecturers and students. If e-learning is to benefit students
by offering students greater access to higher education, it is necessary to consider not only access
to education but also the access to technology where computers become an indispensable element
of effective e-learning courses (Ribiero, 2002). Students who have access to networked computers
may have the opportunity to experience a more flexible learning process, but students and indeed
higher educational institutions could fail to benefit from this opportunity, due to students not being
able to afford or gain access to a computer (Shaba, 2002). Therefore, students with no computer
at home are disadvantaged in e-learning environments. In addition, as a major consequence of an
increased participation in higher education, a large number of students originate from low-income

backgrounds and will have little disposable income to purchase computers (Holley, 2002), and
therefore increased reliance on technology to deliver higher education may potentially lead to
further divisions in society (Shaba, 2002). In such cases, deprived home backgrounds militant
against the acquisition of technological skills which further impedes on acquisition of knowledge
through e-learning.”
2.5 Opportunities of e-Learning:
Radha et al. (2020) directed an examination that featured a portion of the e-learning instructive
potential that might be revealed and used to help understudies and different partners. Utilizing on
the web films, video-conferencing applications, and contacting people of interest, associations and
organizations have constructed ways for interfacing with individuals from everywhere the globe.
Tasks and other learning materials are progressively being submitted or conveyed in delicate
duplicate structures, which need the utilization of innovation to get to and use (Radha et al., 2020).
While e-learning was 'strongly' forced and requested of all HEIs in Oman and the remainder of the
globe, it gave the innovation area a lift as far as creating understudies who are market prepared
subsequent to finishing their tasks at the learning organizations.
“A study from Oman (Al Musawi, 2010) highlighted that program can be offered through E-
learning as well as the traditional approach. The study summarised those students and teacher are
aware of the importance of E-learning and a need to reconsider the standards before having a high
level of E-learning, especially when it comes through the implementation stage. In addition, Wu
et al. (2019) stressed that with E-learning, students can study anytime and anywhere. The use of
learning and teaching platforms can be developed in a way to suit both instructors and students.
Good communication skills and a clear study plan would result in an effective learning.”
“Another study shows that e-learning is a tool student in HEIs adopt to learn rationally regardless
of time and space (Daukilas and Vaisnoriene, 2009; Nuryyev et al., 2020). E-learning helps create
and develop human capabilities. For instance, if teachers and students in the private HEIs are better
trained using e-learning tools for delivering lectures, they become more innovative (Loogma et al.,
2012; Agostini, and Nosella, 2020). Also, the shift from conventional classroom learning to e-
learning is an important transformation for both the learning model and HEIs (Saheed et al., 2019).
This leads to innovative behaviour and attitude. Besides, some major innovation capabilities are
required for effective exploitation of e-learning (Hong et al., 2018). Learning may affect

innovation positively and subsequently lead to higher education excellence (Jimenez-Jimenez and
Sanz-Valle, 2011). E-learning systems can develop private HEIs that are open to learning.
Therefore, in the implementation of an e-learning program within private HEIs, efforts should be
made to create a transfer opportunity, since preceding studies (see Pineda-Herrero et al., 2011;
Asongu and Le Roux, 2017) have shown that few HEIs offer the resources, time and opportunity
to apply what the employees learned after attending e-learning courses. E-learning adoption and
use by students in private HEIs is vital because it provides an opportunity to consider e-learning
adoption and use by universities in the promotion of teaching. It offers students significant benefits
such as increased access to learning opportunities, the convenience of time, and place, provide a
greater assortment of learning resources, improves opportunities for learning by individuals and
the emergence of more powerful intellectual tools.”
2.6 Resources:
e-Learning necessitates the availability of professional resources that institutions may use to offer
information and skills to students from the comfort of their homes or dormitories. In their research,
Gohiya and Gohiya (2020) distinguished a portion of the free e-learning assets that can be applied
or utilized by any foundation or individual, including Free e-Learning Storyboards, Free e-
Learning and Instructional Design eBooks, and Free e-Learning ROI Calculators, among different
assets that might be helpful to understudies. Because of the debilitated economy because of Covid-
19 and the failure of most of understudies to purchase such assets, understudies request financially
savvy assets. Beside fundamental assets like a strong web association and PCs (workstations), the
assets used to make the concentrated on information open and connect with the gatherings
(understudy and teacher) are basic (Gohiya and Gohiya, 2020). Because they are expensive to
make freely accessible, the bulk of the resources are obtained by buying them. Open-source
software designed for educational purposes and societal benefit is the only one that may be
accessed for free.
“According to Zaid (2009) E-Learning is a term for all types of technology-enhanced learning
(TEL), where technology is used to support the learning process. Many educational institutions
implement E-Learning and utilize technologies experience tremendous impact and carve a niche
in the field (Sahin & Thompson 2007; Selim 2007). Some students who use E-Learning have better
learning performance and positive attitude (Kirby et al., 2007); others have been less positive about

E-Learning due to difficulty of use, workload, lack of technological skills, and lack of face-to-face
interactions (Picciano, 2002).”
2.7 Physical Learning Vs e-Learning:
Despite the fact that the Covid-19 epidemic has increased the usage of e-learning applications in
practically all nations for higher education, physical and e-learning are both necessary for use in
educational institutions. There are certain activities, such as laboratory practical sessions, that can't
be done online since they need actual presence in the classroom. Physical learning and e-learning
were both determined to be necessary to the various degrees of usage by Tawafak et al. (2021).
Regardless of this, e-learning is more widely accepted when the necessary materials and
applications are easily accessible and user-friendly. Because students study from home, they avoid
paying travel fees as well as expenditures for snacks and meals while at college, e-learning saves
on numerous costs associated with commuting and meals. Students prefer to study at home rather
than in the classroom. When the weather makes it difficult to go from one location to another, the
school instruction becomes tedious (Tawafak et al., 2021). For example, when it is raining,
students may find it difficult to schedule meetings; however, e-learning sessions may be attended
from the comfort of one's own home, overcoming this difficulty.
“Experts in the fields of education and technology have studied this topic from various
perspectives, such as the differences between e-learning and physical learning, the advantages, and
disadvantages of one over the other, student’s attitudes towards one form and/or the other, their
emotions, whether positive or negative, and their sense of belonging, to mention just a few. For
example, Oye et al. point out that e-learning is more student-cantered, compared to physical
learning, which is more teacher-centred, as it does not focus exclusively on instructions and
guidelines coming from teachers, but it is individually adjustable to the student. The difference
between e-learning and physical learning has also been pointed out in relation to the main sources
of information, as well as the evaluation and quality of learning. Whereas in physical learning,
students are evaluated exclusively by teachers, who represent their main source of information,
and the quality of learning is strongly dependent on them, in e-learning, student’s evaluations can
be carried out using tools, they can access information from various documents uploaded onto the
platforms, and the quality of learning is strongly dependent on both the teacher’s level of digital
training and their teaching style.”

“Most of the studies carried out in the field focus on the advantages and disadvantages of e-learning
vs. physical learning. Naved et al. argue that, unlike physical learning, e-learning has its
advantages, such as flexibility, no need to travel to school, and a low cost, requiring only an
Internet connection. However, this does not mean that e-learning does not have its shortcomings,
such as inequities in accessing technology or learning computer skills, or even a lack of physical
space for this teaching/learning process. E-learning is dependent on technology, the Internet, and
various devices that not all potential beneficiaries can access. Student’s experience of quality
learning is not only related to the teacher’s skills and abilities to capture attention during the e-
learning process but also to their own training, characteristics, and digital skills. In e-learning,
physical space should foster involvement in interpersonal relationships, thus encouraging didactic
communication.”
2.8 Other Research:
In other study, Soni (2020) discovered that, as a result of technological advancements, e-learning
would be in great demand, much as it was during Covid-19. Every other activity is moving online,
which means students will need to become acclimated to managing operations and studies online
so that after they finish their studies, they can work with technology without difficulty. Some of
the platforms used to host meetings and lectures are comparable to those used by businesses to
hold corporate meetings (Soni, 2020). According to the findings, e-learning programs provide
advantages even after Covid-19, which will recognize and support the world's adoption of
technological improvements. Other studies focused on how instructors and institutions might
manage and support learning activities. They all collaborate as a team, however the bulk of the
material evaluated focuses on how e-learning affects students' learning experiences.
“Studies that investigated the impact of online learning on student’s motivation are not recent. For
example, a study was conducted by Kim and Frick (2011) to investigate the factors that stimulate
student’s motivation in direct self-learning and to investigate the level of learner motivation.
Additionally, the researchers determined how levels change during a course’s progression to
identify the factors associated with changing motivation. The study concluded that four primary
factors affect the learner’s motivation: interest, awareness of the learning’s importance, self-
confidence, and satisfaction. The correlation of these factors with direct self-learning enables the
learner to achieve the learning goals successfully. The study concluded that student’s motivation

and satisfaction increase in direct self-education when the content is relevant to the learner’s life
and how easily they interact with technology. Other factors include student’s desire for continuous
self-learning, the belief that it is their right to learn, and the reinforcement and support students
received at the beginning and during the lessons.”
2.9 Psychological Impact:
At the point when Covid-19 made learning organizations and organizations close, Khan et al
explored understudy brain science and presumed that permitting understudies to take part in e-
learning programs freed them from the pressure of missing a year or long periods of school.
Students who were unclear when they would be able to complete their courses due to the sudden
closure of learning institutions found e-learning to be a source of motivation and inspiration rather
than staying at home and not completing their studies. Students' wounded mental conditions were
not only mended by the development and promotion of e-learning, but their tremendous hopes of
completing their studies according to the previously defined timetables set by HEI programs were
also revived. Students have a certain amount of time to finish the education program, which should
not cause them any frustration or interfere with their own goals. Students who are sponsored and
asked to attend other programs by their sponsors may suffer considerably, but the system's
continuance via e-learning offers a method of encouraging and strengthening their morale in taking
educational activities seriously. Despite the fact that educational resources are costly, they provide
relief to students by ensuring expected years of completion of enrolled programs.
“Some studies show that e-learning does not have the same impact as physical learning. It seems
that online students may lose them focus and miss deadlines for different tasks. Over time, both
teachers and students may experience various negative effects from e-leaning, such as sight
problems (due to long periods in front of the screen) or back pain, and, at the same time, they may
feel the lack of activities in open spaces.”

3. Research Methodology:
3.1 Introduction:
“As we know that one of the important research tools is questionnaire. In order to develop a
survey/questionnaire, first the researcher should decide how the data is measured to collect.
Scaling is the branch of measurement that involves the construction of an instrument. There are a
number of factors that should be considered to choose an appropriate scaling method in a
questionnaire and which ones to use while analysing data.” Various tasks, the most essential of
which are data collecting and sample size determination, will be carried out in this chapter of the
study. There are several HEIs in Oman, but the best technique to choose the optimum sample size
and kind of data will be determined by the variables chosen (Abutabenjeh and Jaradat, 2018).
Because the results will be based on the analyzed data, which includes participant replies, the
chapter establishes the foundation for the conclusions to be drawn.
3.2 Sources of Data:
In Oman, there are several HEIs whose students will be randomly recruited using prepared
questionnaires that include information about the research's selected variables. Students will be
the major data providers, receiving surveys through Google Forms. Because the e-learning
program is offered online, the survey will be completed online (Torp-Pedersen, et al. 2020). It will
be another another method of demonstrating the value of utilizing the internet to study.
3.3 Sample Size:
Oman has a large number of higher education institutions, and many students will be chosen to
participate in the survey. Due to the enormous number of students from diverse institutions in
Oman, a random selection of institutions from which students will be sampled will be conducted
and selected using a random process that ensures that all HEIs have a comparable and equal
probability of being chosen (Sim et al., 2018). Due to the restricted time available for conducting
research, a random sample of 150 participants from the specified HEIs will be chosen. The
questionnaires given to the few chosen colleges will be handed to students at random, who will fill
out the forms and submit them online once they are completed.

3.4 Questionnaire:
When doing research, there are several instruments that may be used in the data gathering process.
Questionnaires and interviews are the most often utilized data collecting devices. Because the
survey will be conducted using online Google forms to gather data, arranging interviews with
students may be difficult, making the research exercise to utilize questionnaires unnecessary (Rahi
et al., 2019). “A questionnaire has been divided into two main categories, open questions and
closed question. An open question is one in which the respondent does not have to indicate a
specific response. Open questions tend to generate lengthy answers. Often, respondents see open
questions as an opportunity to respond to a question in detail. The advantage of open questions is
that they allow the respondent to provide an answer that is not restricted to a select view. In
addition, open questions can provide some very interesting qualitative findings that may lead to
new insights, or possibly help to develop future research ideas (Wilson, 2010). There are two
disadvantages associated with open questions. First, too many open questions can make the
analysis and interpretation of the findings extremely time-consuming. Second, it can make a
comparative analysis of qualitative answers difficult while a closed question is one in which a
respondent must choose from a limited number of potential answers. Usually this is a
straightforward yes or no. Other closed questions may require the respondent to choose from
multiple response options such as multiple-choice questions, Likert scale and Semantic differential
scale. From another angel, scale methods could be classified as a rating scales and attitude scales.”
3.5 Key Variables:
“All research projects are based around variables. A variable is the characteristic or attribute of an
individual, group, educational system, or the environment that is of interest in a research study.
Variables can be straightforward and easy to measure, such as gender, age, or course of study.
Other variables are more complex, such as socioeconomic status, academic achievement, or
attitude toward school. Variables may also include an aspect of the educational system, such as a
specific teaching method or counselling program. Characteristics of the environment may also be
variables, such as the amount of school funding or availability of computers. Therefore, once the
general research topic has been identified, the researcher should identify the key variables of
interest. For example, a researcher is interested in low levels of literacy. Literacy itself is still a
broad topic. In most instances, the broad topic and general variables need to be specifically

identified. For example, the researcher needs to identify specific variables that define literacy:
reading fluency (the ability to read a text out loud), reading comprehension (understanding what
is read), vocabulary, interest in reading, etc. If a researcher is interested in motivation, what
specific motivation variables are of interest: external motivation, goals, need for achievement, etc?
Reading other research studies about your chosen topic will help you better identify the specific
variables of interest.”
The learning efficiency, e-learning tools, practical problems & possibilities, and the advantages &
flexibility of e-learning to students would be the major factors of concern while collecting
information (statistics) on the influence of e-learning on students (Henseler and Schuberth, 2020).
The variables will be measured to identify and help in the understanding of the effect of e-learning
on pupils.
3.6 Qualitative Analysis:
Qualitative analysis is the division of gathered data into sections or groups that may be analyzed
together by looking for correlations or discrepancies. A qualitative analysis will be conducted
based on the data obtained through questionnaires in order to categorize the data for conclusive
conclusions and outcomes (Queirós et al., 2017). “The study was also designed as cross-sectional
research because it was implemented at one time as the aim was not to investigate the changes in
the variables over a period. This qualitative study aimed to explore the impact of online education
on students’ motivation using semi-structured interviews to understand students’ perceptions
deeper and a creative writing task in which students discuss their motivation in virtual classrooms.
After performing a qualitative analysis by grouping of the collected data into groups or sets, tests
of regression and correlation will be performed to understand the relationship existing between the
identified and tested variables. The obtained results from the performed tests will be interpreted
and explained to help users to the research report to understand the findings on how e-learning
impacts students.”
3.7 Quantitative Analysis:
“Quantitative research methods emphasize objective measurements and the statistical,
mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys,
or by manipulating pre-existing statistical data using computational techniques. Quantitative

research focuses on gathering numerical data and generalizing it across groups of people or to
explain a particular phenomenon.”. To understand the link between the identified and tested
variables, tests of regression and correlation will be done after a qualitative analysis by classifying
the obtained data into groups or sets (Queirós et al., 2017). The test results will be evaluated and
described to assist consumers of the study report in comprehending the findings on how e-learning
affects pupils.
3.8 Approach to Data Analysis:
The study will employ qualitative and quantitative data analysis methods, both of which are
intimately linked to the usage of a research questionnaire. The data will be analyzed using a Likert
scale that has been calibrated with numerical values. Statistical tests will be performed on the
numeric data using the SPSS program (Xu and Hua, 2017). The tools will be used because of their
capacity to gather large amounts of data and provide summary findings that are simple to integrate
and publish. Despite the fact that the SPSS program is typically used to conduct statistical tests, it
will be utilized to assist in the management of the massive data response gathered from the sampled
participants (students).
3.9 Research Limitations:
The biggest constraint of the research will be students' ignorance, who will see the survey as a
waste of time, despite the fact that it will aid in improving the weak areas of the e-learning process
(Chepurenko, 2017). Apart from the students' inexperience, HEIs may refuse to be utilized as case
studies because they are afraid of being exposed for how poorly their e-learning systems are
implemented.

4. Data Collection and Analysis:
4.1. Response Rate
“In total, 150 questionnaires were distributed, however, 100 questionnaires received, and
questionnaires were found to be useful, and they were retained for further analysis. The usefulness
of questionnaire was judged based on the missing data. Tabachnick and Fidell (2007) explained
that questionnaire who has more than 5 percent of a systematic missing data, should be excluded
from the analysis. This is because missing data in a systematic manner provides wrong
interpretation of the findings, and it may lead to type I or type II errors, rejecting an alternative
hypothesis when it is true or accepting an alternative hypothesis when it is false. Therefore, missing
data can lead to biased results. In our case, as you can see in the table given below that the response
rate of participants is 100% as no missing data is found”
“Table 4.1: Statistics of the respondents”
Statistics
Gender Age Education Institution
N
Valid 100 100 100 100
Missing 0 0 0 0
4.2. Demographic Profile:
4.2.1. Gender:
“There were a number of 100 questionnaire distributed to the students ofthe selected
HEIs using a random approach and found out that in total, there were 37 males and
63 females who responded to the survey. The male represents 37 percent from the
total sample and on the other hand 63 percent of the sample were females.”
“Table 4.2: Gender Representations of the respondents”

Gender
Frequency Percent Valid Percent Cumulative
Percent
Valid
Female 63 63.0 63.0 63.0
male 37 37.0 37.0 100.0
Total 100 100.0 100.0
“Pie-Chart showing the Gender representation of Males in Green and Females in Blue”
4.2.2. Age:
HEIs using a random approachand found out that in total, there were 33 respondents
who responded to the survey falling the age-period of 17-21, 40 respondents who
responded to the survey falling the age-period of 22-25, 11 respondents who
responded to the survey falling the age-period of 26-30, and 16 respondents who
responded to the survey were those having age above 30.”

“Table 4.3: Age Representations of the respondents”
Age
Percent
Valid
17 - 21 33 33.0 33.0 33.0
22 - 25 40 40.0 40.0 73.0
26 - 30 11 11.0 11.0 84.0
Above 30 16 16.0 16.0 100.0
Total 100 100.0 100.0
“Pie-Chart showing the Age representation of the respondents, i-e: Blue colour shows
respondents having age between 17-21, Green colour shows respondents having age
between 22-25, etc.”
4.2.3. Levelof Study:

who responded to thesurvey were ofbachelors-level, 24 respondents who responded
to the survey were of diploma-level, 15 respondents who responded to the survey
were at foundation-level, and 13 respondents who responded to the survey were of
masters-level.”
“Table 4.4: Level of Study Representations of the respondents”
Level of Study
Percent
Valid
Bachelors 48 48.0 48.0 48.0
Diploma 24 24.0 24.0 72.0
Foundation 15 15.0 15.0 87.0
Masters 13 13.0 13.0 100.0
T
o
t
a
l
100 100.0 100.0

“Pie-Chart showing the Level of Study representation of the respondents, i-e: blue colour
shows respondents who were in bachelor’s level, Green colour shows respondents who are
in diploma level, etc.”
4.2.4. Institution:
who responded to thesurvey belonged to the government sector, 47respondents who
responded to the survey belonged to the private sector.”
“Table 4.5: Institution Representations of the respondents”
Institution
Percent
Valid
Government 53 53.0 53.0 53.0
Private 47 47.0 47.0 100.0
Total 100 10.0 100.0

“Pie-Chart showing the Institution representation of the respondents, i-e: blue colour
shows respondents were belonged to the Government sector, Green colour shows
respondents were belonged to the Private sector.”
4.3. Reliability Test:
“The reliability test is used as an indication of the internal consistency of the items. A Cronbach
alpha technique is used to measure the reliability of the variables. The Cronbach alpha technique
implies how well do the respondents understand and comprehend it the items of questionnaire. For
this, the test was carried out for each variable. Namely, e-Tools, e-Ecosystem, and effectiveness.”
4.3.1. e-Tools:
“The e-Tool variable was measured using 6 items. The Cronbach’s alpha of 0.706 sounds adequate
and reasonable. Since it is above 0.6, then it can be concluded that the reliability of this variable
is very good. However, many researchers in preference of the use of more stringent threshold of
the minimum accepting level of 0.7. Hair et al. (1998) showed through simulation studies that

reliability of 0.6 is acceptable and robust. For this reason, the reliability can take any value of 0.6
and above, whereby 0.7 deemed to be a very good reliability.”
“Table 4.6: Reliability Statistics of e-Tools”
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized Items
N of Items
.706 .696 6
4.3.2. e-Ecosystem:
“e-Ecosystem was measured through 4 items. However, it demonstrated a reliability of 0.795. The
Cronbach’s alpha of 0.795 sounds adequate and reasonable. Since it is above 0.6, then it can be
concluded that the reliability of this variable is very good. However, many researchers in
preference of the use of more stringent threshold of the minimum accepting level of 0.7. Hair et
al. (1998) showed through simulation studies that reliability of 0.6 is acceptable and robust. For
this reason, the reliability can take any value of 0.6 and above, whereby 0.7 deemed to be a very
good reliability.”
“Table 4.7: Reliability Statistics of e-Ecosystem”
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized Items
N of Items
.795 .799 4
4.3.3. Effectiveness:
“The effectiveness variable was measured through 15 items. However, it demonstrated a reliability
of 0.739. The Cronbach’s alpha of 0.739 sounds adequate and reasonable. Since it is above 0.6,
then it can be concluded that the reliability of this variable is very good. However, many

researchers in preference of the use of more stringent threshold of the minimum accepting level of
0.7. Hair et al. (1998) showed through simulation studies that reliability of 0.6 is acceptable and
robust. For this reason, the reliability can take any value of 0.6 and above, whereby 0.7 deemed to
be a very good reliability.”
“Table 4.8: Reliability Statistics of Effectiveness”
Cronbach's Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.739 .751 15
4.4. Descriptive Statistics:
“A descriptive statistic was carried out for all the variables under investigation in this study. In
total, there were three variables two of which are independent variables of e-tools and e-ecosystem
and the dependent variable of effectiveness. A breadth of statistic summary was used, such as
minimum, maximum, mean, standard deviation, skewness, and kurtosis. While the mean score is
a measure of central location, standard deviation is a measure of the disparity. Furthermore,
skewness and kurtosis are indicators of univariate normality. All the variables were computed
using the transformation function in SPSS. The table below provides the statics summary of the
variables. With reference to e-tools, there was an overall agreement that e-tools are to some extent
well maintained (mean = 3.67). The respondents have close answers to each other as indicated by
a standard deviation below 1. To less extent, students perceived that the score mean of the
effectiveness variable was the lowest with mean equals to 3.3700. Furthermore, the students’
commitment demonstrated a good level with a mean score of 3.59. This indicates that overall, the
students’ exhibit a positive impact of e-learning commitment towards an e-ecosystem, as it is
above 2.5.
Hair et al. (2016) provided a stringent criterion of the acceptable value for both skewness and
kurtosis. They argued that the optimal range of both should lie between +1 to -1. This is an
important criterion, otherwise if it is violated, the variable is said to have deviation from univariate

normality assumption. By inspecting Table V, it is shown that all the variables have adequate
amount of skewness and kurtosis that fall within the recommended range. Some of the variables
are positively skewed others are negatively skewed.”
“Table 4.9: Descriptive Statistics for all variables”
Descriptive Statistics
N Range Minimu
m
Maximu
m
Mean Std.
Deviation
Variance Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std.
Error
e-tools 100 3.3333 1.6667 5.0000 3.671667 .6018373 .362 -.358 .241 .307 .478
e-ecosystem 100 4.00 1.00 5.00 3.5975 .83098 .691 -.729 .241 1.173 .478
effectiveness 100 2.8462 1.9231 4.7692 3.370000 .4932992 .243 -.083 .241 1.114 .478
Valid N
(listwise)
100
4.5. Linear Regression Assumptions:
“A series of a simple linear regression was undertaken, in order to test the proposed hypothesizes.
In general, there were 2 proposed hypothesizes (H1 – H2). Each one of them was separately tested
using a ANOVA regression test. ANOVA regression test is like the t-test, ANOVA helps in finding
out whether the differences between groups of data are statistically significant. It works by
analysing the levels of variance within the groups through samples taken from each of them. If
there is a lot of variances (spread of data away from the mean) within the data groups, then there
is more chance that the mean of a sample selected from the data will be different due to chance.
As well as looking at variance within the data groups, ANOVA considers sample size (the larger
the sample, the less chance there will be of picking outliers for the sample by chance) and the
differences between sample means (if the means of the samples are far apart, it’s more likely that
the means of the whole group will be too).”

4.5.1 e-tools andeffectiveness:
“The e-tools variable was able to explain around 7.1 percent of the variation of the effectiveness.
The beta coefficient is positive, and the relationship indicates a significant and positive relationship
between e-tools with the effectiveness. The beta coefficient equals to 0.219 and the relationship is
significant at 99% confidence of interval (p-vale is less than 1%).”
Model Summary
Equation 1
Multiple R .267
R Square .071
Adjusted R Square .062
Std. Error of the Estimate .478
ANOVA
Sum of Squares df Mean Square F Sig.
Equation 1
Regression 1.720 1 1.720 7.535 .007
Residual 22.371 98 .228
Total 24.091 99
Coefficients
Unstandardized Coefficients Beta t Sig.
B Std. Error
Equation 1
(Constant) 2.566 .297 8.644 .000
etools .219 .080 .267 2.745 .007
4.5.2. e-ecosystemand effectiveness:
“The e-ecosystem and effectiveness were able to explain 20.1 percent of the variation for the
effectiveness. Beta coefficient was positive and strong, the hypothesis of the relationship can be

confirmed, and it is a positive relationship between both variables, since beta is positive, and p-
value is less than 1% (0.000).”
Model Summary
Equation 1
Multiple R .448
R Square .201
Adjusted R Square .193
Std. Error of the Estimate .443
ANOVA
Sum of Squares df Mean Square F Sig.
Equation 1
Regression 4.845 1 4.845 24.674 .000
Residual 19.246 98 .196
Total 24.091 99
Coefficients
Unstandardized Coefficients Beta t Sig.
B Std. Error
Equation 1
(Constant) 2.412 .198 12.193 .000
eecosystem .266 .054 .448 4.967 .000
4.6. Correlation Analysis:
“The correlation between the independent variables is shown in the table below. All the
independent variables showed that there is a positive correlation between them and the
effectiveness commitment. The strongest correlation exists between e-tools and e-ecosystem
(0.589). Equally, the correlation between e-tools and effectiveness is very high (1). Furthermore,
the independent variables should not have a very strong correlation between them, otherwise it
indicates a multi-collinearity. The independent variables do not have strong correlation (all the
correlations are less than 0.8) (Cortina et al., 1993).”
“Table 4.10: Summary of Correlation Analysis”

Correlations
effectiveness e-ecosystem e-tools
effectiveness
Pearson Correlation 1 .448**
.267**
Sig. (2-tailed) .000 .007
N 100 100 100
e-ecosystem
Pearson Correlation .448**
1 .589**
Sig. (2-tailed) .000 .000
N 100 100 100
e-tools
Pearson Correlation .267**
.589**
1
Sig. (2-tailed) .007 .000
N 100 100 100
**. Correlation is significantatthe 0.01 level (2-tailed).
4.7. Heteroscedasticity:
“The linear regression is sensitive towards the heteroscedasticity assumption. The latter concept
refers to unequal variance of the variable. One of the important assumptions for linear regression,
is that the residual should have an unequal variance. This unequal variance exhibits itself as a
systematic spreading of the residual value. As shown in the table below we can easily depict that
for the sample of 100, the maximum residual is 1.5479 and that of maximum Standard Residual is
3.493.”
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 2.678460 3.743392 3.370000 .2212338 100
Residual -1.0467148 1.5479403 0E-7 .4409078 100
Std. Predicted Value -3.126 1.688 .000 1.000 100
Std. Residual -2.362 3.493 .000 .995 100
a. DependentVariable: effectiveness
4.8. Histogram:
“The below histogram chart for the dependent variable of effectiveness and regression
standardized residual depicts that that the variable having the sample size has a mean value of -

1.37E-15 and the Standard Deviation value of 0.995 and the curve tells us that the assumption for
the linear regression is to ensure that the residual of the dependent variable (effectiveness) follows
a normal distribution. The latter can be described by having one peak, symmetric shape (identical
shape by dividing them into two halves), skewness and kurtosis should be zero or at least not very
extreme. The acceptable range of kurtosis and skewness for not indicating strong deviation from
the normal assumption is between +1 to -1. There is another statistical test, but they are less reliable
with small sample size. Instead, the shape of distribution is used to investigate the normality of
distribution. The below distribution though is somewhat skewed, nevertheless, it is not extremely
skewed. The shape looks more and less normal, indicating that the residual of dependent variable
satisfies the normal distribution. This more evident by looking into the skewness and kurtosis of
the residual, they have adequate value that fall within the range of acceptability.”

5. Conclusion and Recommendations
5.1. Conclusion:
This study proposes that involving internet learning in an assortment of instructive establishments
gives various advantages. Internet learning supports understudy focused learning and is easy to
work during the lockdown. The overall expansion of COVID-19 has brought about the conclusion
of instructive establishments. The COVID-19 pandemic lockdown affected most members'
scholarly accomplishment. It's actually significant that web based learning is as yet in its outset in
numerous countries all through the world. It started as 'crisis remote learning,' and with additional
financing, we will actually want to conquer any impediments.
5.2. Recommendations:
There are, obviously, other instructing modalities that should be executed as required parts of an
ideal undergrad teaching training model. Therefore, the web-based module's principally
synchronized learning offers an important and energizing opportunities for the fate of clinical
instruction, and it very well might be coordinated into the educational program to further develop
long lasting learning adequacy. This put schools under a magnifying glass as far as their
preparation to adapt to an emergency that requires the utilization of present day innovation, like
equipment and programming, to work with fruitful web based learning. Because of this conclusion,
the advancement of web based learning conditions has sped up, it isn't obstructed to guarantee that
learning.
There should be more updated and advance soft wares that helps in tacking the various educational
unethical behaviors in online learning like plagiarism and cheating etc. with online Case Based
Learning. Notwithstanding, others accept that once the COVID-19 plague is taken care of, survey
meetings and psychomotor active preparation ought to be advertised.
They suggested Technology use should be optimized by following different ways. Personnel ought
to be prepared in utilizing on the web modalities and concocting illustration plans with less mental
burden and greater intuitiveness.

With the expanded use of internet getting the hang of during COVID-19, dissecting their progress
as far as educating and gaining from an assortment of perspectives' significant.
There is an expansion in torment during the e-learning process, and the term and seriousness of
this distress develops as the length of work area/PC time increments..
College understudies might have encountered mental enduring because of the serious lockdown
necessities. That ought to be managed considering the understudies' status.
Understudies can keep focused with online training since it permits them to learn at their own
speed. The most concerning issue that internet based training faces in clinical and applied sciences,
where understudies' requests are pragmatic courses, is the manner by which to get them.
Since the vast majority of the courses are functional, learning them online is troublesome.
Understudies accept that finishing viable abilities just through internet based schooling is testing.
Making on the web training more intelligent, introducing operations, in actuality, conditions,
conveying clear data, and giving 3D virtual apparatuses to reproduce what is going on are
everything that might be done to further develop it.
Specialized concerns, individual conduct highlights, institutional method restrictions, and the
absence of non-verbal signs were all difficulties for our exploration members.

Timeline
15.03 to
30.03.22
01.04 to
15.04.22
16.04 to
30.04.22
01.15 to
05.15.22
week
1
week
2
week
3
week
4
week
5
week
6
week
7
week
8
Introduction
Literature review
Methodologyreview
Data collectionandsampling
Data Analysis
Findings
Discussion
Conclusionandrecommendation
Improve andFinalize report
SubmitReport

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