Volume 10, Issue 1, Janyary-March-2023

p ISSN : 2349-8811
e ISSN : 2349-9133

The International Quarterly Journal

Horizons of
Holistic Education
Peer Reviewed and Referred Journal

:: Published By ::
Children’s University
Sector-20, Gandhinagar-382021 (Gujarat) India
Email : editorhhecu@gmail.com
Website : hhe.cugujarat.ac.in
p ISSN : 2349-8811 e ISSN : 2349-9133

Horizons of Holistic Education

Peer Reviewed and Referred Journal

January-March-2023, 10(1)

INDEX

Sr. No. Title & Authors Page No.

Weight Loss and Pre-Diabetic Stage Reverse Prediabetic Stage to

1 Non-Diabetic with Weight Loss 1-12
- Monika R. Mer

Development and Tryout of Computer Assisted Instruction on

Dayanand Saraswati
2 13-17
- Narendrasinh Pratapsinh Gohil

A Study of the Impact of Faculty on the Opinion of Beneficiary

Candidates of the Scheme of Developing High Quality Research
3 Regarding the Scheme 18-32
- Parmar Bhavini Laxmanbhai, Dr. Harshad A. Patel

Influence of Demographic Variables on E-learning Readiness of

4 Students 33-43
- Ishfaq Majid, Y. Vijaya Lakshmi

Poisonous Pedagogy- a present treatment leading to future

5 mistreatment 44-55
- Ruchi Dwivedi

Enhancing Early Childhood Development with Knowledge of

Panchamahabhutas
6 56-66
- Hitesh M. Patel, Samir Bhupendrakumar Vaghrodia, Jyoti Rupin
Kumar Raval
 ICSSR Sponsored Journal
Horizons of Holistic Education p ISSN : 2349-8811
January-March,-2023, 10(1), 33-43 e ISSN : 2349-9133

Influence of Demographic Variables on E-learning Readiness of Students

Ishfaq Majid
Research Scholar
Center for Studies & Research in Education, School of Education
Central University of Gujarat

Dr. Y. Vijaya Lakshmi

Assistant Professor
Center for Studies & Research in Education, School of Education
Central University of Gujarat

Received: 25-02-2023 Accepted: 18-03-2023

ABSTRACT

E-learning is being considered as a solution for the rising demand for higher education. It is
an innovative open learning multimedia modality to deliver education. E-learning makes use
of multimedia technologies to enhance teaching and learning. However, the readiness to E-
learning is influenced by many factors and hence, the current study aimed at exploring the
influence of Gender, Location of Institution and Type of Institution on the E-learning
Readiness (ELR) of Students. The sample of the study consisted of 57 students of higher
education institutions of the Jammu region of Jammu and Kashmir. The students were asked
to rate their readiness to E-learning on a five-point symmetric likert scale consisting of 43
items related to various dimensions of ELR. The collected data was analysed with the help of
SPSS V26. The statistical techniques like Independent Samples t-test was used to test the
hypotheses. The results of the study reveal that Gender, Location of Institution and Type of
Institution have no significant influence on the ELR of Students. The study concludes by
giving further suggestions for research in this area.

Keywords: Information and Communication Technology, E-learning, E-learning Readiness,

Gender, Location of Institution, Type of Institution, Higher Education

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Introduction
E-learning is considered as a vital technology of modern era where it aims to create an
interactive learning environment which is based on computers and internet. It empowers
learners by provindg them access to information from anywhere in the world (Mosa et al.,
2016). It is an innovative open learning multimedia modality to deliver education in which
acquisition of knowledge is primarily facilitated and distributed by electronic means. It can
be defined as the use of electronic media (Paiva, et al., 2016; Agarwal & Pandey, 2013),
Information and Communication Technology (ICT) and Educational Technology (ET) in
education (Contreras & Hilles, 2015; Al-araibi, et al., 2019). E-learning uses a variety of
digital communication devices and softwares to carry out teaching learning activities
remotely (Hadining et al., 2019). The E-learning system possesses the ability to support
interactive communication which gives the students full control of their learning (Liaw &
Huang, 2011). E-learning makes use of multimedia technologies to enhance teaching and
learning. It is helpful in the delivery of just-in-time information and guidance from experts
belonging to various walks of life and also efficient in eliminating the distance barriers
between teaching and learning. It is being introduced for enhancing the learning opportunities
and facilitating students' access and success in education (Coopasami, et al., 2017). However,
the potential benefits of E-learning can be accured only when the stakeholders of it are ready
to embrace it i,e. E-learning Ready. The adoption of E-learning in higher education can only
be achieved by measuring the readiness towards it (Rohayani et al., 2015).
E-learning Readiness (ELR) can be defined as the “state of mental, physical and material
preparedness of stakeholders for fruitful e-learning experience and action” (Nwagwu, 2019;
Navani & Ansari, 2020). It can also be defined as the level of readiness and the ability to use
new technological tools (Watkins & Triner, 2004; Hashim & Tasir, 2014). The ELR
assessment helps organizations to design the E-learning strategies comprehensively (Kaur &
Abas, 2004). It is one of the most critical factor for the successful implementation of E-
learning in higher education (Rohayani et al., 2015). E-learning is being considered as a new
phenomenon and the instructors and students are trying to adopt to it for its successful
implementation (Mahajan & Kalpana, 2018). Hence, for successful implementation of E-
learning, it becomes necessary to assess the readiness towards it.
Method
The population of the study consisted of students of higher education institutions belonging
to Jammu region of Jammu and Kashmir state. The data for the study was collected online
during the year 2021 when India was facing the 2nd wave of COVID19. On the basis of

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review of literature (Lindasari et al., 2021; Alam, 2020; Ullah et al., 2021 etc.), the researcher
used simple random sampling technique for selecting the sample of the study. The research
tool was emailed to 121 students in the form of an online survey prepared in the google form.
Out of 121 students, 57 students responded to the survey and hence the response rate of the
study is 47.1 %.
To study the influence of demographic variables on the ELR of the students, the respondents
were asked to provide their personal information and also to rate about their ELR on a
continuum of five-point likert type scale of “Strongly Agree, Agree, Neutral, Disagree,
Strongly Disagree”. The scale consisted of 43 items categorized under 03 dimensions namely
“Technological Readiness, Psychological Readiness and Infrastructure Readiness”. To ensure
the face validity of the tool, the tool before implementation was sent to around 05 subject
experts for their suggestions. The suggestions/corrections given by the subject experts were
incorporated and the reliability of the full scale and dimension wise reliability tested using
Cronbach Alpha (vide table 1.1) reveals that the tool was reliable (Heale & Twycross, 2015).
The collected data was further analysed using SPSS V26.
Table 1.1: Reliability Statistics of the tool
Dimension Cronbach’s Alpha
Technological Readiness 0.8
Psychological Readiness 0.73
Infrastructure Readiness 0.8
Overall 0.89

Results

The current study aimed to explore the influence of Gender, Location of Institution and Type
of Institution on ELR of Students. The data was collected from students of higher education
institutions of Jammu region. The collected data on E-learning readiness of students was
without outliers and was normally distributed as shown in figure 1.1

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Figure 1.1: Box Plot, Normal Probability Curve and Test of Normality of ELR of Students
The students were asked to express their level of ELR by responding to the items given on a
continuum 5 point scale of ELR tool. The mean score on ELR of students was 162.89 (table
1.2) and around 52% of students are above the mean score and around 47% of them are
below the mean score. The standard deviation value indicates that the E-learning readiness
score of students is not highly deviated. The value of Std. Error of Mean indicates that the
sample mean is more accurate reflection of the actual population mean (table 1.2)
Table 1.2: Descriptive Statistics of ELR of Students
Mean
162.89
Std. Error of Mean
2.34
Std. Deviation
17.67
Minimum
130.00
Maximum
203.00

To study the influence of Gender on ELR of students, the collected data was tested for
normality (table 1.3) and was found normally distributed (Male: KS=0.081, df=30, p > 0.05;
Female: KS=0.097, df=27, p > 0.05) and use of “Independent Samples t-test” (t-test = 0.842,
p > 0.05) (table 1.3) revealed that gender does not have any significant influence on ELR of
students and hence both male and female students are equal in terms of their ELR.

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Table 1.3: Influence of gender on ELR of students

Kolmogorov-Smirnov Levene's Test for Equality of Variances
Gender of Statistics df Sig.
Students 0.069 0.793**
Male 0.081 30 0.200*
Female 0.097 27 0.200*
*Normal Equal variances assumed**
H01 “There is no significant difference in the
mean scores of E-learning Readiness of
students on the basis of their gender”
Sig 0.842
Decision Fail to reject H01

To study the influence of Location of Institution on ELR of students, the collected was tested
for normality (table 1.4) and was found normally distributed (Urban: KS=0.081, df=46, p >
0.05; Rural: KS=0.165, df=11, p > 0.05) and use of “Independent Samples t-test” (t-test =
0.655, p > 0.05) (table 1.4) revealed that location of institution does not have any significant
influence on ELR of students and hence students studying in institutions located in urban and
rural areas area are equal in terms of their ELR
Table 1.4: Influence of location of institution on ELR of students
Kolmogorov-Smirnov Levene's Test for Equality of Variances
Area Statistics df Sig.
Urban 0.081 46 0.200* 0.330 0.568**
Rural 0.165 11 0.200*
*Normal Equal variances assumed**
H02 “There is no significant difference in the
mean score of E-learning Readiness of
students on the basis of Location of
Institution”
Sig 0.655
Decision Fail to reject H02

To study the influence of Type of Institution on ELR of students, the collected data was

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tested for normality (table 1.5) and was found normally distributed (Central level: KS=0.089,
df=42, p > 0.05; State level: KS=0.116, df=15, p > 0.05) and use of “Independent Samples t-
test” (t-test = 0.822, p > 0.05) (table1.5) revealed that type of institution does not have any
significant influence on ELR of students and hence students from Central and State level
institutions do not differ significantly in their ELR.
Table 1.5: Influence of type of institution on ELR of students
Kolmogorov-Smirnov Levene's Test for Equality of
Variances
Type of Statistics df Sig.
Institution 0.277 0.601**
Central Level 0.089 42 0.200*
State Level 0.116 15 0.200*
*Normal Equal variances assumed**
H03 “There is no significant difference in
the mean scores of E-learning
Readiness of students on the basis of
type of Institution”
Sig 0.822
Decision Fail to reject H03

Discussion & Conclusion

E-learning is going to play a crucial role in Education 4.0. It has the potential to address
various challenges of higher education and hence, it becomes highly essential to study the
readiness of stakeholders towards it. ELR is a multi-dimensional construct and demographic
variables may play an important direct or indirect influence in it (Aydin and Tasci, 2005;
Xhaferi et al., 2022; Aldowah et al., 2013). The demographic characteristics of students can
contribute more when they are used in predicting the outcomes of learning (Rizvi et al.,
2019). The influence of demographic variables on ELR of students was explored earlier as
well by various researchers but as clear conclusions about them is still not established, the
present research also tried to explore whether the demographic variables like Gender,
Location of Institution and Type of Institution influence the ELR of Students or not. The
influence of these variables on ELR was tested using “Independent Samples t-test” in SPSS
V26. Gender gaps in ELR were one of the most explored questions in ELR. The influence of
Gender on ELR was measured and it was found that Gender has no significant influence on

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the mean score of ELR of students. The result relate to other precedent studies by
Mohammad (2019); Gay, (2018), Hashim & Tasir, (2014); Tweed, (2013), Aslam et al.,
(2021), Adams et al., (2022) & Changiz et al., (2013) whereas the study by Naresh et al.,
(2016) reveal that Gender has influence on ELR of students. Similarly, the researchers tested
the influence of location of institution and type of institution on ELR of students. It was
found that both location of institution and type of institution have no influence on the mean
score of ELR of students. The result relate to other earlier studies by Sharavjamts et al.,
(2022); Kaushik & Agrawal (2020); Yoo et al., (2015); Rasouli et al., (2016); Malkawi et. al.,
(2021). Contrary to this, the study by Sulistio (2021) reveals that location of the institution
has influence on ELR of students. Also Adams et al., (2018) in his study revealed that there
was influence of demographic variables on ELR of students. Similarly, Islam et al., (2021) in
his study revealed that demographic variables have significant affect on effectiveness of E-
learning.
The current study contributes to the existing literature by highlighting the influence of
demographic variables of students on ELR. The data for the current study was collected by
fully online mode due to COVID19. Regarding the delimitation of the study, the current
study was delimited to Students of Higher Education Institutions (HEI‟s) of Jammu and
Kashmir, India. The current study was conducted on the basis of data collected during
COVID pandemic and there may be a probability for this scenario to change and hence, there
is a need to conduct ex-post facto studies in this area. Further, similar study can be conducted
on both students and teachers of HEI‟s to explore about their comparative ELR.

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