Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

79

Research Article

Facilitating positive attitude in students:  
A study of critical e-learning factors

Iti Verma1 & Shalini Nigam2

1Research Scholar, Management, Dayalbagh Educational Institute, Agra  

Email- itiverma140069@dei.ac.in                                                                                                                                           
2Professor, Dept. of Dayalbagh Educational Institute, Agra

Abstract

Planning the implementation of e-learning requires study of various factors that play a 
key role in its success. Although many studies on e-learning factors have been conducted 
from time to time, the majority of them aimed at identifying critical success factors based 
on literature review or through surveys, while only a few studied the impact of critical 
success factors on other variables. (Farid et al., 2018; Qammach and Al-Sharifi, 2021). 
The present study aims to analyze the impact of critical success factors on students’ 
attitudes towards e-learning. Through the questionnaire, a total of 300 respondents 
were reached, out of which 221 responded giving a response rate of 74 per cent. Analysis 
of data was done using IBM SPSS and AMOS graphics. Findings reveal that University 
Support has a positive impact on students’ attitudes towards online learning, whereas, 
technology issues have a negative impact on students’ attitudes towards e-learning. 
Instructor support is seen to have an insignificant impact on students’ attitudes towards 
e-learning. Only three critical factors have been tested in the present study to study their 
impact on students’ attitudes, while future studies can involve even more factors. The 
study holds importance for all stakeholders in the education industry.

Keywords: University Support, Technology, Instructor Support, Students’ Attitude, 
Critical Success Factors.

Introduction

In recent years, online learning is gaining 
momentum in schools and colleges 
around the world due to its feature of 
flexibility and student-centric approach. 
However, it is very important to pre-plan 
the implementation process of online 
learning as an unplanned effort can be 
a waste of time, effort, and knowledge. 
The adoption and implementation 
of e-learning need careful analysis of 
critical success factors of e-learning. 
A lot of previous research has tried 
to draw attention to some critical 
success factors that can improve the 
performance and success chances of 
online learning. 

According to the Center for Management 
and Organization Effectiveness, 2022, 
“Critical Success Factors refer to those 
specific elements or action areas 
that require focus and should be 
implemented for achieving strategic 
goals”. In the context of e-learning, 
Critical success factors refer to those 
factors that help to accelerate the 
success of online learning by achieving 
planned learning outcomes. These 
factors can include a wide variety 
of elements but frequently include, 
student-related factors, instructor-
related factors, technology-related 
factors, and university-related factors. 

For the purpose of study, students’ 
perception of e-learning will be 



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

80

analysed. Students are the end users of 
e-learning, and satisfying them should 
be one goal of effective e-learning. If 
students’ attitudes are positive, they will 
accept e-learning, and it will be easier to 
engage them leading to better learning 
outcomes. A study of critical success 
factors of e-learning is important as 
e-learning requires a strong base to 
function effectively, which is possible 
only if certain elements are actively 
engaged in the learning environment 
like competency of students and 
instructors, reliable technology, quality 
content, supportive institutional 
policies, etc. 

The present study will aim at 
recognizing the frequently prioritized 
critical success factors of e-learning 
and analyzing their role in influencing 
students’ attitudes towards e-learning.  
The study is important for higher 

educational institutes in planning the 
successful implementation of e-learning 
through focused investment in the 
critical success factors of e-learning 
as they result in positive attitude of 
students which result in increased 
student acceptance of online learning 
and thereby better learning outcomes.

Literature Review

The study has collected literature 
reviews from the period 2007 to 
2020 which dealt with the study of 
key factors pertaining to e-learning 
implementation, key factors related to 
e-learning adoption, and key factors 
impacting the success and effectiveness 
of e-learning especially in higher 
education. The following table highlights 
various studies that investigated the 
Critical Success Factors of e-learning:

Table-1: Showing Review of Literature related to Critical Success Factors of e-Learning

S. No. Author (yr.) Title Purpose Methodology Findings

1. (Qammach and Al-
Sharifi, 2021)

The Impact of 
Critical Success 
Factors for 
E-Learning 
on Strategic 
Performance: 
An applied study 
in a sample of 
the faculties for 
the University of 
Baghdad

To test the 
impact of critical 
success factors 
for e-learning 
on the strategic 
performance 
of a sample 
of Baghdad 
University 
faculties.

Survey There is a correlation 
and a statistically 
significant effect 
between the critical 
success factors 
for e-learning with 
its dimensions 
(information 
technology, the 
teaching staff) and the 
strategic performance 
with its dimensions

2. (Priatna et al., 2020) Key Success 
Factors of 
e-Learning 
Implementation 
in Higher 
Education

This study aims 
to analyze the 
Key Success 
Factors (KSFs) 
of e-learning 
implementation

Multi Attribute 
Utility Theory 
Approach

The dominant factor 
that needs attention is 
organizational aspect, 
while other factors are 
technology and human 
resource.

3. (Alqahtani and 
Rajkhan, 2020)

E-learning 
critical success 
factors during 
the covid-19 
pandemic: A 
comprehensive 
analysis of 
e-learning 
managerial 
perspectives

To identify the 
critical success 
factors for 
E-learning during 
COVID-19

Analytical 
Hierarchy 
Process

Technology 
management, support 
from management, 
increased student 
awareness to use

E-learning systems, 
and demanding a high 
level of information 
technology from 
instructors, students, 
and universities were 
the most influential 
factors for E-learning 
during COVID-19.



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

81

4. (Raman et al., 2019) Investigating 
Key Factors 
for successful 
e-learning 
implementation

To identify the 
critical success 
factors of 
e-learning

Extensive 
Literature 
Review

The CSFs are teacher’s 
characteristics 
(teacher’s attitude, 
teacher’s computing 
or technical skills, 
interaction among 
teacher-students, 
teaching style, 
knowledge in 
e-learning content 
development and 
self-efficacy), student’s 
characteristics 
(attitude, computer 
competency, 
interaction, self-
efficacy, motivation 
and cultural and 
social norms), 
information technology 
infrastructure (internet 
accessibility, reliability 
and availability), design 
and content (perceived 
ease of use and 
perceived usefulness) 
and organization 
characteristics (training 
and support).

5. (Kasani and 
Mourkani, 2019)

A research 
synthesis of 
critical success 
factors of 
e-learning: 
A model 
development

To identify 
critical success 
factors of 
e-learning to 
develop a model 
for e-learning 
success

Review E-learning success 
factors include three 
dimensions: Structural 
dimension (including: 
organizational, 
educational, content, 
support, and system 
quality); Content or 
behavioral dimension 
(including factors: 
learner and teacher); 
and the contextual 
or environmental 
dimension (including 
factor: technology)

6. (Cheriyan, 2018) Critical Success 
Factors for 
E-learning: An 
Indian Perspective

This paper 
attempts to 
identify the 
critical factors 
attributing to 
the success of 
e-learning in 
higher education 
sector through 
a student 
perspective.

Survey

Principal 
Component 
Analysis

The study identifies five 
factors as critical in the 
success of e-learning 
viz. technological 
support, e-learning 
resources, e-learning 
support and training, 
characteristics 
of student, and 
characteristics of 
instructor in their order 
of relative importance 
with technological 
support being the most 
critical factor

7. (Farid et al., 2018) Critical Success 
Factors of 
E-Learning 
Systems: A Quality 
Perspective.

To identify CSFs 
through review 
and identify 
their impact 
on e-learning 
quality

Review and 
Survey 

Perceived usefulness, 
lack of learning objects 
in local languages, 
quality of educational 
system, Lack of 
instructional designer, 
lack of instructional 
design process and 
information quality have 
emerged as top critical 
factors hindering the 
quality of e-learning.



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

82

8. (Anggrainingsih et 
al., 2016)

Determining 
eLearning critical 
success factor 
at Sebelas 
Maret University 
using Analytical 
Hierarchy Process 
(AHP)

To determine the 
Critical Success

Factors of the 
UNS e-learning 
implementation 
using Analytic 
Hierarchy 
Process 

Citations 
(AHP).

- The most important 
factor is Technology, 
followed by 
the E-learning 
Development,

Students’ 
characteristics, 
Lecturer’s 
characteristics, and 
Management Support.

9. (Basak, Wotto and 
Bélanger, 2016)

A Framework 
on the Critical 
Success Factors 
of E-Learning 
Implementation 
in Higher 
Education: A 
Review of the 
Literature

This paper 
presents a 
conceptual 
framework 
on the critical 
success factors 
of e-learning 
implementation 
in higher 
education, 
derived from an 
in-depth survey 
of literature 
review. 

Review The proposed 
conceptual framework 
on critical success 
factors of e-learning 
include Technological 
Factors, Institutional 
factors, Pedagogical 
factors, Ethical factors, 
Resource factors, 
Evaluation Factors, 
Management factors, 
Social Interaction 
Factors

10. (Gamage, Fernando 
and Perera, 2014)

Factors affecting 
to effective 
eLearning: 
Learners

Perspective

To explore the 
dimensions of 
effectiveness 
from learners’ 
perspective 
catering to the 
current demand.

Interview and 
observation

(Qualitative 
methodology)

Identified 10 factors 
that affect e-learning 
effectiveness, out of 
which the top 5 are as 
follows: Interactivity, 
Collaboration, 
Motivation, Network 
of Opportunities, 
Pedagogy. The 
remaining 5 factors 
are Content/Material, 
Assessment, Usability, 
Technology, Support 
for Learners

11. (Cheawjindakarn, 
Suwannatthachote 
and 
Theeraroungchaisri, 
2012)

Critical Success 
Factors for 
Online Distance 
Learning in 
Higher Education: 
A Review of the 
Literature

The aim of 
this paper is 
to specify the 
Critical Success 
Factors (CSFs) for 
Online Distance 
Learning

(ODL) in Higher 
Education (HE).

Review of 
Literature

The critical success 
factors of ODL 
include institutional 
management, 
learning environment, 
instructional design, 
services support, and 
course evaluation. 

12. (Fitzpatrick, 2012) Key Success 
Factors of 
eLearning in 
Education: A 
Professional

Development 
Model to Evaluate 
and Support 
eLearning

The purpose of 
this paper is to 
introduce the 
KSF (Key Success 
Factors) model 
of eLearning 
to support 
and evaluate 
eLearning in 
secondary 
schools.

In-depth 
Interview

Dominant factors 
of e-learning are 
technology, human, 
design, support, and 
evaluation.

13. (Musa and Othman, 
2012)

Critical Success 
Factor in 
E-Learning: An 
Examination of 
Technology and 
Student Factors

To examine 
the e-learning 
critical success 
factors (CSFs) as 
perceived

by students.

Survey Internet browsing 
speed and instructor 
participation in 
discussion groups are 
most critical factors for 
e-learning.



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

83

14. (Rijal & Wardani, 
2012)

Critical success 
factors for 
e-learning in 
developing 
countries: A 
comparative 
analysis between 
ICT experts and 
faculty

It aims at 
identifying the 
Critical Success 
Factors that 
aim to influence 
the acceptance 
of e-learning 
in developing 
nations.

Interview

Delphi and AHP 
method

Technology awareness, 
motivation, and 
changing learners’ 
behavior are 
prerequisites for 
successful e-learning 
implementations.

15. (Bhuasiri et al., 
2012)

Critical success 
factors for 
e-learning in 
developing 
countries: A 
comparative 
analysis between 
ICT experts and 
faculty

To identify 
multiple factors 
that influence 
the success 
of e-learning 
systems.

Delphi and AHP Technology awareness, 
motivation, and 
changing learners’ 
behavior are 
prerequisites for 
successful e-learning 
implementations.

16. (Selim, 2007) E-learning critical 
success factors: 
an exploratory

investigation 
of student 
perceptions

To identify and 
measure its 
Critical Success

Factors (CSFs) 
from student 
perceptions.

Survey The surveyed 
students indicated 
that instructor 
characteristics factor is 
the most critical factor 
followed by support 
and technology. The

Student characteristics 
factor was perceived 
as the least critical 
factor to the success of 
e-learning.

Research Gap

Although there are a lot of studies on 
critical success factors of e-learning, 
no study has tried to investigate the 
relationship between critical success 
factors of e-learning and students’ 
attitudes towards e-learning. Moreover, 
most studies are review papers and 
lack empirical investigation. As such,, 
there is a need to explore the role of 
critical success factors of e-learning 
in developing positive attitudes of 
students towards e-learning.

Research Objectives

The study aims at fulfilling the following 
objectives:

1. To analyse the impact of 
university support on students’ 
attitudes towards online  
learning

2. To analyse the impact of 
instructor support on students’ 
attitudes towards online learning

3. To analyse the impact of 
technology issues on students’ 
attitudes towards online  
learning.

Conceptual Framework and Research 
Hypotheses

The most frequently identified critical 
success factor in past literature has 
been technology (indicating technology 
issues or technology support), followed 
by university support, and instructor 
support. Thus, based on a detailed 
analysis of the literature review, three 
factors, technology, university support 
and instructor support, have been 
chosen as the critical success factors 
for further analysis of their impact 
on students’ attitudes towards online 
learning. 



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

84

Figure-1: Shows Conceptual Framework proposed for the Study

University  
Su•University 

•University

Technology

University  
Su•University 

•University

University  
Su•University 

•University

University  
Su•University 

•University

University  
Su•University 

•University

Instructor  
Support

Students’ attitude 
towards e-learning

H1

H2

H3

Source: Self Constructed The study will 
involve the perception of students as 
well as analysis of students’ attitudes 
towards online learning. Students are 
the end users of e-learning system. 
Students’ acceptance of online learning 
is important to fully realize the benefits 
of online learning, which can only be 
possible if they have a positive attitude. 
If students’ attitude towards e-learning is 
positive, it makes them more interested 
and motivated to learn, whereas, if the 
students’ attitude towards e-learning 
is negative, it can create hurdle in 
achieving learning outcomes. According 
to Maheshwari Greeni, 2020 Students 
who enjoy their courses have stronger 
intentions to use e-learning in future 
also.

H1: University support positively influence 
students’ attitude towards e-learning

University Support is also an essential 
component of e-learning system. 
Without university support, it might 
not be possible for e-learning to be 
successfully implemented at ground 
levels. According to Maheshwari 
Greeni, 2020 Students intentions to 
use e-learning system in future are 
influenced by the level of institutional 
support provided to them. The present 
study will aim to understand if university 
support influence students’ attitude 
towards e-learning. 

H2: Technology issues negatively 
influences students’ attitude towards 
e-learning

The term ‘technology’ can include 
variables indicating technology 
management or lack of technology 
management in the form of 
technological barriers and issues. 
According to Zalat et al., 2021, the 
highest barrier in accepting e-learning 
included insufficient or unstable internet 
connectivity, inadequate computer 
labs, lack of computers/laptops, 
and technical problems. Technology 
Support implies managing technology 
in a way that the technological barriers 
in e-learning system are minimized 
and the benefits of e-learning 
technology can be fully realized. Proper 
management of technology is important 
as it ensures uninterrupted internet 
access, reliability on technology, better 
browsing speed, etc. Technology has 
been identified as an important factor 
in majority of studies (Raman et al., 
2019); (Anggrainingsih et al., 2016); 
(Gamage, Fernando and Perera, 2014); 
(Fitzpatrick, 2012); (Priatna et al., 2020); 
(Selim, 2007); (Musa and Othman, 
2012); (Qammach and Al-Sharifi, 2021); 
(Basak, Wotto and Bélanger, 2016); 
(Kasani and Mourkani, 2019); (Alqahtani 
and Rajkhan, 2020). According to Taat 
& Francis, 2019, Technology support 
plays a vital role in e-learning adoption 
and implementation. It is the lack 
of technology support that leads to 
technical issues and challenges that 
hinder the success of e-learning process. 
The present study will aim to analyze the 
impact of technology issues on students’ 

H3



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

85

attitude towards online learning.

H3: Instructor Support positively influence 
students’ attitude towards e-learning

For e-learning to be effective, support 
of instructors to students in online 
learning environment is essential. 
Instructor characteristics include their 
Attitude, technical skills, interaction, 
participation, teaching style, knowledge 
of content development on online 
learning platforms and self-efficacy. 
(Raman et al., 2019); (Anggrainingsih et 
al., 2016); (Kasani and Mourkani, 2019) 
and such characteristics should be 
utilized to support students’ learning in 
virtual environment. Instructors should 
guide and encourage students to boost 
their motivation to use e-learning (Taat 
& Francis, 2019). The present study 
will aim to analyze whether instructor 
support influences students’ attitude 
towards e-learning. 

Research Methodology

Data and sample: Primary data have 
been collected through an online 
questionnaire distributed to graduate 
students of different colleges in 
Western U.P. using purposive sampling. 
Purposive sampling is used as the study 
aimed at collecting the responses of 
only those graduate students who have 
taken online courses in their colleges. 
Self-constructed questionnaire is made 
to measure the constructs of proposed 
conceptual framework using detailed 

review of past literatures. A total of 300 
respondents were reached out of which 
210 responded resulting in response rate 
of 74 per cent. The data were coded and 
checked for outliers and missing values 
before proceeding for further analysis. 

Variables of the study: The study aimed 
at studying variables four variables which 
includes university support, instructor 
support, technology issues, and students’ 
attitude towards e-learning. 

Scales of measurement: All variables 
were measured using 5-point Likert 
scale, where 1 meant “strongly 
disagree” and 5 meant “strongly agree”. 
The questions were self-constructed 
through variables identified from past 
literature. 

Statistical techniques: Analysis of 
demographic and study habits was 
done using SPSS 20. Structural equation 
modelling was used to study structural 
relationships between the variables. For 
Structural equation modelling, AMOS 
Graphics was used.

Results and analysis

57.5 per cent males and 42.5 per cent 
females participated in the survey, 
out of which majority of students took 
online classes in regular mode. 

Table-2: showing Factor items reliability 
and validity through Average variance 

extracted (AVE) and construct reliability 
(CR)

Cronbach 
alpha

Factor loadings AVE CR

University 
Support

US2

US3

US4

US5

US6

US7

0.841 .505

.520

.759

.837

.773

.810 0.491 0.857



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

86

Instructor Support IS1

IS2

IS3

IS4

IS5

IS6

IS7

0.781 .503

.562

.800

.524

.629

.552

.780 0.601 0.818

Technology issues T1 
T2

T3

T4

T6

T7

0.808 .737

.711

.738

.648

.747

.664 0.498 0.858

Students’ 
Attitude towards 
e-learning 

SA1

SA2

SA3

SA4

SA5

0.802 .734

.767

.791

.518

.738 0.487 0.838

Overall reliability 0.804
Source: IBM SPSS Statistics

The reliability of constructs is checked 
using Cronbach alpha which is within 
acceptable limits of 0.6 to 0.8 for all 
items indicating internal consistency of 
the scale. Factor loadings are at least 
0.5. The value of AVE should be at least 
0.5 and the value of CR should be at 

least 0.7. Approximately all factors fit in 
the criteria.

Structural equation modeling

The study uses AMOS graphics for 
studying the hypothesised relationships 
which gives the following results:

Table-3: showing the hypothesised relationships tested using AMOS

Hypothesis Path Path 
coefficient

Critical 
Ratio

p 
value

Direction Decision

H1 US 🡪 SA .242 4.492 *** Positive Supported

H2 T 🡪 SA -.236 -3.767 *** Negative Supported

H3 IS 🡪 SA 0.051 0.913 0.361 Positive Not 
Supported

*** Significant at 0.001 level

Source: AMOS Graphics



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

87

It can be observed that University 
Support (US) influence students’ attitude 
towards e-learning (SA) in a significant 
positive way. (r= 0.242; CR= 4.492), thus, 
H1 is supported. T represents technology 
issues due to lack of technology 
support which negatively impacts 
students’ attitude towards e-learning 
(SA), thus supporting H2 (r= -0.236; 
CR= -3.767). Instructor Support (IS) 
does not significantly impact students’ 
attitude towards e-learning (SA) and  
hence, H3 is not supported (r= 0.051; 
CR= 0.913).

Discussion

The impact of critical success factors of 
e-learning on students’ attitudes has 
not been studied beforehand. Findings 
indicate that critical success factors play 
an important role in shaping students’ 
positive attitudes towards e-learning. 
Active support from universities in 
the field of e-learning helps to develop 
positive attitude towards e-learning in 
the mind of students, whereas, the role 
of instructor support is insignificant in 
influencing students’ attitude towards 
e-learning. Lack of technology support 
results in technology related issues and 
challenges which negatively influence 
students’ attitude towards e-learning 
usage. There should be an active effort to 
mitigate technological issues in e-learning, 
as well as proactive university support in 
planning e-learning in universities.

Research Implications

The research can be beneficial as it 

pinpoints the basic requirements for 
successful implementation of e-learning 
in Higher education, through active 
university support and technology 
support. Many studies have identified 
critical success factors of online 
learning from time to time, but rarely 
have they tried to analyse their 
impact on students’ attitude towards 
e-learning. The research is valuable to 
all stakeholders, but most importantly 
to the universities in planning the 
implementation of e-learning. 
E-learning can only be effective if it 
is wholeheartedly accepted by the 
students. Positive attitude of students 
towards online learning is possible 
only if university provides enough 
support in e-learning implementation, 
and by mitigating the technical barriers 
in e-learning.

Limitations and Scope of future study

Due to time constraint, the present 
study has considered only three critical 
success factors including instructors 
support, technology support and 
university support, while future studies 
can involve analysis of other key factors 
also in understanding their role in 
students’ acceptance of online learning 
by developing their positive mindset 
towards e-learning. Moreover, the 
study has taken place in western Uttar 
Pradesh and can involve analysis in 
other geographical areas to check the 
replicability of results. Future studies 
can extend to analysis of more critical 
success factors and even involve model 
proposition. 

References

Alqahtani, A. Y. and Rajkhan, A. A. (2020) ‘E-learning critical success factors during the 
covid-19 pandemic: A comprehensive analysis of e-learning managerial perspectives’, 
Education Sciences, 10(9), pp. 1–16. doi: 10.3390/educsci10090216.

Anggrainingsih, R. et al. (2016) ‘Determining elearning critical success factor at Sebelas 
Maret University using analytical hierarchy process (AHP)’, in Proceedings - 2016 International 
Seminar on Application of Technology for Information and Communication, ISEMANTIC 2016. 
Semarang, Indonesia: IEEE, pp. 191–196. doi: 10.1109/ISEMANTIC.2016.7873836.



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

88

Basak, S. K., Wotto, M. and Bélanger, P. (2016) ‘A Framework on the Critical Success Factors 
of E-Learning Implementation in Higher Education: A Review of the Literature’, International 
Journal of Educational and Pedagogical Sciences, 10(7), pp. 2409–2414. doi: https://doi.
org/10.5281/zenodo.1125677.

Bhuasiri, W. et al. (2012) ‘Critical success factors for e-learning in developing countries: A 
comparative analysis between ICT experts and faculty’, Computers and Education, 58(2), pp. 
843–855. doi: 10.1016/j.compedu.2011.10.010.

Center for Management and Organization Effectiveness. (2022, July 7). Critical Success Factors. 
CMOE. Retrieved September 21, 2022, from https://cmoe.com/glossary/critical-success-factors/

Cheriyan, N. K. (2018) ‘Critical Success Factors for E-Learning: An Indian Perspective’, in 
International Conference on Culture Technology (ICCT 2018). Shaoxing, China, pp. 1–15. 
Available at: http://iacst.org/iacst/Conferences/ICCT2018/sessions/Session ST4/603.htm.

Cheawjindakarn, B., Suwannatthachote, P. and Theeraroungchaisri, A. (2012) ‘Critical Success 
Factors for Online Distance Learning in Higher Education: A Review of the Literature’, Creative 
Education, 03(08), pp. 61–66. doi: 10.4236/ce.2012.38b014.

Farid, S. et al. (2018) ‘Critical Success Factors of E-Learning Systems: A Quality Perspective.’, 
Pakistan Journal of Distance and Online Learning, 4(1), pp. 1–20.

Fitzpatrick, T. (2012) ‘Key success factors of eLearning in education: A professional 
development model to evaluate and support eLearning’, US-China Education Review A9, 9, 
pp. 789–795.

Gamage, D., Fernando, S. and Perera, I. (2014) ‘Factors affecting to effective eLearning : 
Learners Perspective’, Scientific Research Journal (SCIRJ), II(V), pp. 42–48. Available at: http://
www.scirj.org/papers-0514/scirj-P0514139.pdf.

Kasani, H. A. and Mourkani, G. S. (2019) ‘A research synthesis of critical success factors of 
e-learning: A model development’, Technology of Education Journal (TEJ), 13(1), pp. 25–39. 
Available at: https://jte.sru.ac.ir/article_805_en.html.

Maheshwari, G. Factors affecting students’ intentions to undertake online learning: an 
empirical study in Vietnam. Educ Inf Technol 26, 6629–6649 (2021). https://doi.org/10.1007/
s10639-021-10465-8

Musa, M. A. and Othman, M. S. (2012) ‘Critical Success Factor in E-Learning: an Examination 
of Technology and Student Factors’, International Journal of Advances in Engineering & 
Technology, 3(2), pp. 2231–1963.

Priatna, T. et al. (2020) ‘Key success factors of e-learning implementation in higher education’, 
International Journal of Emerging Technologies in Learning, 15(17), pp. 101–114. doi: 10.3991/
ijet.v15i17.14293.

Qammach, N. I. J. and Al-Sharifi, M. A. R. A. (2021) ‘The Impact of Critical Success Factors for 
E-Learning on Strategic Performance An applied study in a sample of the faculties for the 
University of Baghdad’, Turkish Journal of Computer and Mathematics Education, 12(13), pp. 
5212–5222.

Raman, K., Othman, N. and Danaraj, G. (2019) ‘Investigating Key Factors for Successful 
E-Learning Implementation’, Asia Proceedings of Social Sciences, 4(2), pp. 49–52. doi: 10.31580/
apss.v4i2.725.

Rijal, B. S. and Wardani, R. (2012) ‘Critical success factors for e-learning in vocational training: 
A comparative analysis between ICT experts, trainer and faculty’, Computers & Education, 
58(2), pp. 843–855.

Selim, H. M. (2007) ‘E-learning critical success factors: An exploratory investigation of student 
perceptions’, International Journal of Technology Marketing, 2(2), pp. 157–182. doi: 10.1504/
IJTMKT.2007.014791.



Indian Journal of Educational Technology
Volume 6, Issue 1, January 2024

89

Taat, M. S., & Francis, A. (2019, December 23). Factors Influencing the Students’ Acceptance 
of E-Learning at Teacher Education Institute: An Exploratory Study in Malaysia. International 
Journal of Higher Education, 9(1), 133–141. https://doi.org/10.5430/ijhe.v9n1p133

Zalat MM, Hamed MS, Bolbol SA. The experiences, challenges, and acceptance of e-learning 
as a tool for teaching during the COVID-19 pandemic among university medical staff. PLoS 
One. 2021 Mar 26;16(3):e0248758. doi: 10.1371/journal.pone.0248758. PMID: 33770079; 
PMCID: PMC7997029. 

Table Legends

Table 1 shows the review of the literature collected relating to critical success factors 
of e-learning. The researcher has reviewed sixteen past studies relating to key factors 
for e-learning success, key factors for e-learning quality, key factors for e-learning 
implementation, key factors for e-learning acceptance etc. Most studies have explored 
critical factors, while the impact of these factors on other variables has been rarely studied.

Table 2 shows the calculation of important values like construct reliability and average 
variance extracted which is important to validate the constructs. It also depicts Cronbach 
alpha and factor loading values calculated using IBM SPSS. AVE shows convergent validity 
and ideally, all calculated values of AVE are 0.5 or more. Cronbach alpha shows internal 
consistency of scale and ideally, all values are between 0.6 to 0.8.  Construct reliability is also 
an indicator of internal consistency of scale and all calculated values are ideally above 0.7 
assuring internal consistency.

Table 3 shows the hypothesis testing conducted using AMOS graphics. Initially, AMOS has 
been used just to test the presence and direction of the relationship between the variables 
although, it can also be used for creating an SEM model.

Figures Legend

Fig. 1  shows the conceptual framework for the study. The variables have been chosen based 
on a systematic review of past literature. The framework reflects the potential hypothesis 
that will be tested in the study. All variables have already been explored in previous studies 
as critical to the success of online learning and hence are taken for analysis.