The Impacts of Demographic Variables of students on attitudes towards e-learning in higher education

The Impacts of Demographic Variables of students
on attitudes towards e-learning in higher
education
Gazmend Xhaferi
University of Tetovo
Tetovo, Macedonia
gazmend.xhaferi@unite.edu.mk
Rovena Bahiti
University of Tirana
Tirana, Albania
rbahiti@hotmail.com
Arta Farizi XH.
SEE University
Tetovo, Macedonia
arta_farizi@yahoo.com
Abstract— The fast development of information, communication
and technologies (ICT) has initiated an unparalleled
transformation in universities all over the world. This
development of technology and learning is offering new
techniques to represent knowledge, new practices, and new global
communities of students. E -learning is now increasing as the
advance model for teaching and learning process in higher
education. However, the integration of e-learning system in
higher education is not an easy task because of some challenges.
The aim of this paper is to analyses the impacts of demographic
factors of students on their attitudes towards e-learning. Student
attitudes and beliefs towards e-learning are regarded as success
determinants of future e-learning initiatives. An analysis of
relationships between student attitudes towards e-learning and
their demographic characteristics: gender, study year, study
program and e-learning knowledge is also included. The study
was conducted for measuring the attitude of university students
towards e -learning in University of Tetovo by taking 223
students from different study program and different study year.
In this paper was used questionnaire to collect data from a
sample of undergraduate students. Statistical techniques are used
for the analyses of data. The result revealed that students’ have
high attitude towards e-learning and their attitude scores did not
differ significantly according to gender, but on the other hand
results indicate there was difference according to study year,
study program and e-learning knowledge of students . The
reported findings might be of interest to academics,
administrators, and decision-makers involved in planning,
developing and implementation of future e-learning strategies in
Macedonia and similar developing countries. The obtained data,
from such study, can provide information about what academic
institutions can do before implementing e-learning to reduce and
overcome the challenges in implementing e-learning in
universities.
Keywords - student' attitudes, gender, study program, study
year, e-learning knowledge.
I. INTRODUCTION
Information and Communication Technologies (ICT) have
made a big change in the lifestyle of the people, their work
and education in the 21st century. Over the past decade there
has been a huge revolution in learning and educational
computer applications and the use of computers in education,
that increases day by day. With rapid development and
widespread use of e-mail, social networks, electronic books,
chat rooms, web conferences, interactive multimedia
applications and internet technologies, internet came into use
as educational environment (Yamamato, Demiray, & Kesim,
2011; Yapici & Akbayin, 2012). This new learning
environment has been accompanied by such concepts as online
learning, distance learning and e-learning. In the last years, the
use of e-learning has been increasing rapidly and has become
an important system offered by most colleges and universities
all over the world. This comes as the consequence of the
innovative transfer of knowledge and learning which has been
influenced by the advent of the Internet and other ICT [1, 2].
This change has had a significant impact on the curricula, the
methodology of teaching and learning processes. E-learning
presents an opportunity to enhance learning as to create
environments where students and teachers can share
knowledge. Similarly, e-leaning system enable students to
access diverse contents any time and from any location. This
gives students more control over their learning experience,
enabling them to gather the materials they need and study
when they have time to do so [3]. So, it is very important to
design an efficient e-learning platform for teaching, learning,
resources, and administration for higher education [4, 5, 6]
However, the major important question is here: Does the
students are willing to adopt e-learning in their learning
process and which demographic characteristics impacts in
their attitudes toward e-learning? In order to find the answer
was investigated the attitude of the students of University of
Tetovo (UT) towards e-learning and impacts of the
demographic characteristic of students on the attitudes toward
e-learning. [7] Asserted that when people have favorable
attitudes towards a particular technology, those people are
more likely to use that technology. Research revealed that
there are significant links between attitudes and beliefs and
links between attitudes and behaviors, and that attitudes form
the foundations of one‘s beliefs which influence one‘s
behaviors [8].
Research has found that based on certain characteristics
such as age, background, computing ability, computing
attitude and motivation all have an impact on the likeness of
students using a computer to support their studies [9].
Understanding student characteristics is especially crucial
when need to implement e-learning system. The demographic
International Journal of Computer Science and Information Security (IJCSIS),
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93 https://sites.google.com/site/ijcsis/
ISSN 1947-5500

characteristics and technological skills are considered as
global problem to the students. Therefore, understanding
students' personal characteristics and e-learning system
integration is necessary to introduce an effective e-learning.
As for student’s factors, the researchers focused on
investigating students’ characteristics regarding to their
gender, and technology experience and skills also. Previous
studies show that there is a rareness of researches about
student’s individual differences such as Gender, Technology
Usage and Skills. A long list of research studies are available
wherein demographic impacts have been measured on the
attitudes of users towards e -learning in different countries 10,
11, 12, 13]
This research want to investigate the impact of the students
demographic variables like age, gender, ICT experience, e-
learning knowledge in their attitudes toward integration of e-
learning on the teaching and learning process in University of
Tetovo (UT). According to [14], e-learning and attitude were
not examined in terms of different personal characteristics in
any of these studies. In the present study, the attitude towards
e-learning was examined by different personal characteristics
of the students such as gender, department, class level,
experience in using computer, frequency of using internet,
learning method, way of studying and motivation type.
II. THEORETICAL BACKGROUND
In this part of the study, we will present some related
previous studies on the variables under consideration for our
paper proposal. Many researches investigate the influence of
demographic profiles such as computer ownership, age,
gender, education, personal skills and computer and internet
on university students’ attitude towards e-learning [15]. From
the literature review shows that gender plays a important role
in perception towards technology and attitudes on e-learning.
Various studies have been undertaken to investigate the effect
of gender, age, and year of study on student attitudes [15,16,
17, 18]. Also, [17] identified characteristics like age, gender,
computer experience, technology acceptance, and individual
learning styles as principal factors when investigating the
students attitudes concerning e-learning processes. [19]
examined the attitude towards e-learning of secondary
students of Delhi and found that demographic variables play a
significant role for e-learning.
Many studies confirmed that student’s male have more
positively attitudes towards e learning than female students
[20]. According to [21], they concluded that female would
accept information and communication technologies (ICTs)
use more than males. [20] their findings confirmed that male
owns a positive attitude toward e-Learning than female. [22]
found no gender differences in relation to the attitudes towards
e-learning. These results are in line with some recent research
studies which revealed that the gap between men and women
(gender divide) is narrowing [23, 24, 25, 26, 27].
[28] examined the familiarity of university students’ in e-
learning, discussion of analysis were carried out on the
students’ perceptions regarding to gender, technology usage
and the knowledge about e-learning implementation. Results
shows that gender have a significant effect on attitudes
towards e-learning [29], 46% of males from first-year students
prefer replacing “traditional learning” by using computer in
learning, while only 22% of women support this result.
The attitude toward e-learning can be viewed as a an
umbrella for the methods of education supported by ICT, and
specified with the consent or lack of consent of the students or
lack of consent on the importance of technology and their
special skills. Besides that, students’ attitude towards e-
learning affected through what they see as the advantages and
disadvantages for this type of education. [16] talking about e
learning, a favorable attitude shows a greater probability that
learners will accept the new learning system.
III. RESEARCH OBJECTIVE AND RESEARCH HYPOTHESIS
The objective of this study is to investigate and to assess if
there are significant differences of demographic factors of UT
students on attitudes towards integration of e-leaning. So, the
study was conducted with the following objectives:
• To conduct whether attitudes of UT students towards e-
learning varies according to gender;
• To reveal whether attitudes of UT students towards e-
learning varies according to study year;
learning varies according to study program;
learning varies according to e-learning knowledge;
From those objectives, were formulated some question
as below:
1. What are the distributions of students of UT in
terms of gender, study year, study field, e-learning
knowledge?
2. What are the attitudes towards integration of e-
learning among the students of UT?
3. Do the attitudes towards e-learning vary
significantly among the students of UT by: (a) gender; (b)
study year (c) study program; (d) e-learning knowledge.
The hypotheses for this study are as follows:
1. The first hypothesis (H1): There are no statistically
significant differences in students' attitudes towards e-learning
integration according to gender.
2. The second hypothesis (H2): There are statistically
significant differences in students' attitudes towards e-learning
integration according to study year.
3. The third hypothesis (H3): There are significant
differences in attitudes towards e-learning integration
according to study program.
4. The fourth hypothesis (H4): There are significant
differences in attitudes towards e-learning integration
according to e-leaning knowledge.
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IV. RESERCH METHODOLOGY
The purpose of this paper is to analyses effects and
differences of students demographic factors on their attitude
towards e-learning integration in higher education.
Determining students’ attitude towards e- learning represents
an important stage in predicting the adoption of a certain
behaviour. This research was conducted through a
questionnaire developed through exploratory research. Survey
was conducted to collect data and to prove the hypotheses.
The population for this study was students of University of
Tetovo. A total of 200 questionnaires were distributed to
students, comprising the following departments, such as
Mathematics, Informatics and Economy and Business. Out of
the 200 students who received the questionnaire, 185
completed and returned the questionnaire given an ninety two
percent (92%) rate of return. The actual sample size used in
the study was sufficient to meet this target sample size.
In this study, singular and relational survey methods were
used. Singular survey method was used to determine the
students’ attitudes towards e-learning. Singular survey method
focuses the research on a single variable and examines its
change in a moment or in a period. The other was used to
indicate the relationship between some variables and attitudes
towards e-learning. Relational survey method is generally used
to determine interactions between several variables. [30]. The
data was analysed using SPSS software. Descriptive statistics
were used to summarize and describe the data collected from
the students.
The research instrument’s reliability was assessed using
Cronbach's alpha (α). In this paper, the significant differences
between the students' attitudes toward integration of e-learning
with the demographic variables were analyzed by using
Analysis of variance (ANOVA) and T-test. The one-way
ANOVA and T-test were employed to identify the effects of
demographic variables on the students' attitudes towards e-
learning. One-way ANOVA measures the mean of one or
more groups based upon independent demographic variables.
On the other hand, t-test is usually employed to evaluate the
difference in the means between two groups.
The survey instrument consisted of two section. While the
first section include 5 items of demographic characteristics of
students, such are: gender, study year, department and e-
learning knowledge. The second part, which is the Scale of
students' Attitude towards integration of E- learning, consists
of 11 items, each rates a 5-point Likert scale running from
(1=Strongly disagree, 2=Disagree, 3=Undecided, 4= Agree,
and 5= Strongly Agree).
Survey was distributed during the class under supervision
of the lecturers. the objective of the survey was clear and
understand for all participants. The survey was anonym that
participants should not write their names or putting any
personal information.
V. DATA ANALYSIS AND RESULTS
A. Descriptive statistics
Data was analyzed using Statistical Package for Social
Science (SPSS) software. Descriptive statistics was done for
each factor and also for the variable students' attitude toward
integration of e-learning. Study collected data from 238
students. The frequency and percentage distributions were used
to represents the demographic characteristics of the students
(gender, study year, department, e-learning knowledge) which
are presented in the table 1. The result for demographic profile
by the respondent comprises that 114 (51.1 %) are female,
whereas 109 (48.9%) were males. Students academic year of
study was normally distributed with four years, first year, (53,
23.8%); second year (60, 26.9%); third year (60, 26.9%); and
fourth year (50, 22.4 %). In terms of study program, results
demonstrates that 72 (32.3%) students belongs to the
Informatics, 69 (30.9%) Mathematics and, 82 (36.8%)
Economy and Business. Finally, students who have knowledge
about e-learning exceeded those who have used, with
percentages of 150 (67.3%), compared to 73 (32.7%). In the
table below was presented the descriptive statistics related to
the scale of students' attitudes towards integration of e-learning.
The analyses of the students' attitude towards e-
learning overall scores on the attitude scale indicated that
students’ responses to this scale were positive. Table 2 shows
that all the participating students had positive attitudes towards
integration technology and e-learning, they felt confident in
using computers, enjoyed using ICTs in their studies, believed
in the benefits of e-learning, and would be interested in
studying courses that used e-learning. In particular, students
believed strongly that e-learning would give them the
opportunity to acquire new knowledge and enhance their
learning experiences. Results show that the mean values
scored was 42.15 that is more near the maximum, which
represent positive students' attitude.
B. Reliability test for construct attitudes
Reliability was evaluated by considering the inter-item
consistency assessed by Cronbach’s Alpha value. The
reliability analysis measured the internal validity and
consistency of items used for each construct. In this study for
the construct students' attitude towards e-learning was used to
measure the reliability. Calculating Cronbach’s alpha
coefficient tested the factor reliability. This measures the
internal consistency by indicating how a set of items are
closely related as a group [31]. A Cronbach alpha value of 0.7
is acceptable, with a slightly lower value might sometimes be
acceptable [32]. Cronbach’s alpha values for factors is attitude
above is 0.70 (see Table 3) indicating that all measures
employed in this study demonstrate a satisfactory internal
consistency. Therefore, the survey is considered a reliable
measurement instrument.
TABLE 1. STUDENTS DEMOGRAPHIC CHARACTERISTICS
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TABLE 2. DESCRIPTIVE STATISTICS OF STUDENTS' ATTITUDES
TOWARD E-LEARNING
Units Value
Minimum 12.00
Maximum 59.00
Mean statistic and Standard error 42.1513 .45483
Standard deviation 7.01672
Variance 49.234
Coeficient Skewness (CS) and CS Standard error .690 .158
Coeficient Kurtosis (CK) and CK Standard error 1.530 .314
TABLE 3: CRONBACH ALPHA COEFFICIENTS FOR CONSTRUCT
ATTITUDE
Construct Cronbach Alpha Number of Items
Attitude toward e-learning 0.830 12
C. Hypothesis Testing
The significant differences between the students' attitudes
toward integration of e-learning with the demographic
variables were analyzed by using Analysis of variance
(ANOVA) and T-test. The one-way ANOVA and T-test were
employed to identify the effects of demographic variables on
the students' attitudes towards e-learning. The Statistical
Package for Social Sciences (SPSS) software tests the
hypotheses.
1) Testing of First hypothesis (H1):
From the results in the table 4, shows the mean of attitude
scores for male and female is found to be 42.49 (SD =5.79) for
male and 43.12 (SD = 6.94) for female. This indicate that both
male and female students of UT have high attitude towards e-
learning although results indicate slightly differences between
male and female students. The same results this finding
corroborates the work of [33,34] who found that Indian
postgraduate students have high positive attitude towards e-
learning. T-Value is found to be (t = 45.044) at significance
level of (0.000) which is statistically significant . Female
students have very slightly higher attitude towards e-learning
than male, but we can conclude there are not differences
between male and female students towards e-learning. This
result supported by [35], who found that between male and
female university no differences of attitude towards e-learning.
In view of the above, the first hypothesis (H1) is accepted.
Thus, There are no statistically significant differences in
attitude towards e-learning integration, between UT students
based on gender.
TABLE 4: RESULTS FROM TESTING HYPOTHESIS 1 (H1)
Variable
difference
in
attitude
towards
e-learning
based in
students
gender
G
e
n
d
e
r
N Mean Std. Df
(t)
value
(Sig.)
Level
Mean
Differ.
F 114 43.12 6.94
222 45.044 .000 1.511
M 108 42.49 5.79
2) Testing of second (H2) hypothesis
In the table below, the mean of attitude scores for students
of study program Informatics is found to be 44.14 (SD =
6.52), of the Mathematics 41.33 (SD = 5.95) and for students
of Economy and Business 42.85 (SD=6.46) respectively. T-
Value is found to be (t = 36.717) at significance level of
(0.000) which is statistically significant. The results indicates
that UT students from different study program have
differences in a attitudes towards integration of e-learning.
Thus, students of Informatics have higher Mean value than
students of Economy and Business and also than Mathematics
Students. Therefore, there are differences towards attitudes of
e-learning between students of UT according to study
program. So, the second hypothesis is accepted.
The results provided in Table 6 show that there were
significant differences in the levels of attitudes towards e-
learning between students of different year of study students.
Thus, results form table below shows that the mean of attitude
scores for students of first year are 40.79 (SD = 6.09), for
second year 42.48 (SD = 7.33), for third year 43.07 (SD=6.05)
and for fourth year 45.04 (SD=5.25).
T-Value is found to be (t = 34.110) at significance level of
(0.000) which is statistically significant. The results indicates
that UT students from different year of study have differences
in a attitudes towards integration of e-learning.
Charachteristics Category
Frequency &
Percentage in the Study
N %
Gender
Study program
Year of study
E-learning
knowledge
Male
Female
109
114
48.9%
51.1%
Informatics
Mathematics
Economy and Business
72
69
82
32.3%
30.9%
36.8%
First (I)
Second (II)
Third (III)
Forth (IV)
53
60
60
50
23.8%
26.9%
29.9%
22.4%
Yes
No
150
73
67.3%
32.7%
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Variable
Difference in attitude
towards e-learning based
in students year of study
Year of study N Mean Std. Df (t) value (Sig.) Level Mean differ.
first 53 40.79 6.09
222 34.110 .000 2.480
second 60 42.48 7.33
third 60 43.07 6.05
fourth 50 45.04 5.25
Thus, students of fourth year have higher Mean value than
students of, third, second and first. The results show that
student level of attitudes towards e-learning according to year
of study are listed descending from fourth year to first year.
Therefore, there are differences towards attitudes of e-learning
between students of UT according to year of study. So, the
third hypothesis is accepted.
Mean score of the students having knowledge about e-
leaning in relation to their attitudes towards e-learning is 43.26
(SD=6.61) while that of the students with no or very little
knowledge about e-learning is 41.85 (SD=5.86). This finding
imply that there are significant differences between students’
attitudes towards e-learning and their knowledge about e-
learning (Table 7). T-Value is found to be (t = 42.146) at
significance level of (0.000) which is statistically significant.
The results indicates that UT students according to knowledge
about e-leaning have differences in their attitudes towards
integration of e-learning. Thus, students of with knowledge
have Mean value than students with no knowledge about e-
leaning. So, the fourth hypothesis is accepted.
VI. DISCUSSION AND CONCLUSION
In this study has examined the impacts of gender, year of
study, study program and e-learning knowledge on students’
attitude towards the integration of e- learning. The results of
the analysis made with the students of the University of
Tetovo, students’ attitudes towards e-learning correspond to
Mean score of 42.1513, with minimum 12 and maximum 59.
This shows that attitudes of the UT students towards e-
learning are positively at a good level. This result shows
parallelism with some of the studies in the literature. In
addition, this study has found that the influence of gender,
year of study, study program and e-learning knowledge are
statistically significant. therefore, outcomes from analyses
provide strong support the four hypotheses. This study shows
that e-learning is providing significant opportunities for higher
education institutions (HEIs) and also provides an analysis of
the influences of students' demographic factors on e-learning
integration into higher education. The results obtained in this
study indicate that there were no significant differences
between the variable of gender and attitudes of the students
toward integration of e-learning. This result shows similarity
to the study in the literature [32]. In addition, results indicate
difference towards attitudes of e-learning between students of
UT according to year of study. Also, based on study program
of the students of UT, there are differences between
Informatics, Mathematics and Economy and Business
students toward e-learning. Finally, finding imply that there
are significant differences between students’ attitudes towards
e-learning and their knowledge about e-learning.
Since the E-Learning attitude has found to be very high for
all groups, it is expected that the undergraduate student will
accept to integrate the E-Learning strategy for learning during
their university studies. In generally, attitude towards
technology indicates in a certain degree the possibility of
adopting certain behaviors. Talking about an e-learning
system, a favorable and positive attitude of students towards it
suggests a greater probability that they will accept it to
integrate in the teaching and learning process in higher
education.
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Variable
Difference in attitude
towards e-learning based
in students study program
Study program N Mean Std. Df (t) value (Sig.) Level Mean differ.
Informatics 72 44.14 6.52
222 36.717 .000 2.045Mathematics 69 41.33 5.95
Economy and Business 82 42.85 6.46
Variable
Difference in attitude towards
e-learning based in students
study program
e-learning
knowledge
N Mean Std. Df (t) value (Sig.) Level Mean differ.
Yes 150 43.26 6.61
222 42.146 .000 1.33
No 73 41.85 5.86
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ISSN 1947-5500

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AUTHORS PROFILE
Mr Gazmend Xhaferi is a PhD candidate in the department of Statistical and
Applied Informatics at University of Tirana in Tirana, Albania, where he
is currently undertaking a research project entitled “Integration and
impact of a system for organizing e-learning in the higher education.
Case study: University of Tetovo”. He is Assistant at Faculty of Natyral
Sciences and Mathematics at University of Tetovo, in Tetovo, Republic
of Macedonia. He has published a series of articles on conferences and
journals on the field of of e-larning.
Prof. Asoc. Dr. Rovena Bahiti is Associate Professor in the departament of
Statistical and Applied Informatics at University of Tirana in Tirana,
Albania. She has more than 20 papers. She has been involved in
numerous research and evaluation projects in the field of education,
economy and Financial Accounting. She has been for several years
consultative at World Bank and other donor projects in the role of expert
in financial management of projects. In December 2013 he was
appointed Director of the National Computer Security Agency
(ALCIRT), holding it until April 2017
Mrs. Arta Farizi is a Mrsc. candidate in the department of Computer Sciences
- Software and Applications at South East European University in
Vol. 16, No. 6, June 2018
ISSN 1947-5500

Tetovo, Macedonia. She is teacher primary schole “Perparimi” in
Tetovo, Republic of Macedonia.
Vol. 16, No. 6, June 2018
ISSN 1947-5500

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