Internet Addiction and Academic Performance of University Students

Abstract

This study has an aim to investigate the relationship between internet addiction and academic performance of university students. For this purpose, 267 undergraduate students were selected from different colleges affiliated with Sambalpur University. Internet addiction scale developed by Young (1998) was used to collect the data from the sample. The results of this study revealed that on an average 47.65 university students are internet addicted irrespective of their gender, streams of education and habitat. This study also revealed that academic performance of university students can be significantly predicted by internet addiction as the R 2 =.034 (3.4%). Gender and habitat were not significant predictors of internet addiction, but streams of education were significant predictors of internet addiction. With reference to gender and streams of education there is significant difference but with reference to habitat or residence there is no significant difference. There is also no significant difference in internet addiction due to the interaction between gender and streams of education, gender and habitat, streams of education and habitat, and among gender, streams of education and habitat.

Full text

International Journal of Academic Multidisciplinary Research (IJAMR)
ISSN: 2643-9670
Vol. 7 Issue 5, May - 2023, Pages: 118-128
www.ijeais.org/ijamr
118
Internet Addiction and Academic Performance of University
Students
Ranjit Kumar Behera, Anindita Nanda, Subhankita Rath, Manisha Pradhan, Madhusmita Dalai
Ranjit Kumar Behera (Former MA Education Scholar of G M University, Sambalpur)
Anindita Nanda (Assistant professor in Education, Panchayat College, Bargarh)
Subhankita Rath (Former MA Education Scholar, Govt. Auto. College, Rourkela)
Manisha Pradhan (Former MA Education Scholar, Govt. Auto. College, Rourkela)
Madhusmita Dalai (Former MA Education Scholar, Kurukshetra University)
Abstract: This study has an aim to investigate the relationship between internet addiction and academic performance of university
students. For this purpose, 267 undergraduate students were selected from different colleges affiliated with Sambalpur University.
Internet addiction scale developed by Young (1998) was used to collect the data from the sample. The results of this study revealed
that on an average 47.65 university students are internet addicted irrespective of their gender, streams of education and habitat.
This study also revealed that academic performance of university students can be significantly predicted by internet addiction as the
R2=.034 (3.4%). Gender and habitat were not significant predictors of internet addiction, but streams of education were significant
predictors of internet addiction. With reference to gender and streams of education there is significant difference but with reference
to habitat or residence there is no significant difference. There is also no significant difference in internet addiction due to the
interaction between gender and streams of education, gender and habitat, streams of education and habitat, and among gender,
streams of education and habitat.
Keywords: Internet addiction, Academic performance, and University students
Introduction:
With the emergence of technology and high-speed internet, more students are using the internet to fulfil their individual needs. Every
student can be able to access the knowledge and information at anytime and anywhere via the internet. On the other hand, Covid-19
pandemic has changed the structure and function of the educational system. It increases the demand of online learning as well as
shifts the process of delivering instruction from the traditional way to digital forms of learning. In this regard, students have spent
more time on the internet for various purposes (Ito et al., 2008). This excessive use of the internet especially among university
students can create an interest among the researchers to know whether the overuse of the internet leads to addictive behaviour or
does spending more time in the internet affect the academic career of the students?
The use of the internet has been significantly increased throughout the world, especially among young people. It has been found that
18.3% from Great Britain (Niemz et al, 2005); 16.2% from Poland (Licwinko et al, 2011); 15.1% from Taiwan (Lin et al., 2011);
9.8% from USA (Anderson, 2001); 5.6% from China (Dong et al., 2012); and 2.8% from Iran (Ghamari et al., 2011) university
students are internet addicted. In India, the number of internet users has increased from 5 million in 2000 to 560 million in 2019
(Internet World Stats as cited by Kumari et al., 2022). The reason for the growing demand of using the internet among the users
especially in young generations is complicated. Some students use it to facilitate their research, academic works, interpersonal
relationships, and business transactions (Goel et al., 2013). On the other hand, others may use it to indulge in social media platforms
(Kuss & Griffiths, 2011; Leung & Lee, 2012) like Facebook (Kittinger et al., 2012), Instagram, YouTube, WhatsApp (And one et al.,
2016; Chen et al., 2017) and online chatting (Huang, 2006; Leung, 2004).
Though the use of the internet has brought significant contribution to our life, but its excessive use may lead to addiction. Internet
addiction is defined as an uncontrolled use of the internet that can impair social and functional behaviour of an individual (Solomon,
2009). Additionally, the lack of control over the use of the internet may lead to various psychological, social, academical, and
occupational problems for individuals (Davis et al., 2002; Goldsmith et al., 2000). The term ‘Internet Addiction’ was first used by
Dr. Ivan Goldberg in 1995. According to him, when the individuals excessively or compulsively use the internet, they can become
internet addicted. Several terms are also associated with it like ‘Internet addiction disorder’, ‘pathological internet use’, ‘problematic
internet use’, ‘excessive internet use’, and ‘compulsive internet use’.
Related literatures:
It has been found that the use of internet has both positive and negative implications. Constant touch with friends, planning for
summer vacation, economic management, improving in communication skills as well as using successful strategies for academic
benefits are some of the advantages of internet (Mishra, 2014). Similarly, some other studies have also shown that the use of internet
has increased academic performance of the students as it provides necessary information for completing the homework (Borzekowski

International Journal of Academic Multidisciplinary Research (IJAMR)
ISSN: 2643-9670
Vol. 7 Issue 5, May - 2023, Pages: 118-128
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& Robinson,2005; Jackson et al., 2006). On the other hand, disruption in daily habits, conflict in family relationships, and low
academic performance are some of the negative effects of internet (Akhter, 2013; Frangos, 2009; Moisan, 2012). Apart from these,
it also negatively affects the physical such as Disturbed in sleep pattern, headache, and fatigue (Jeon, 2005; You, 2007; Yang & Tung,
2004) and psychological Unable to control emotions, restlessness, irritability, anxiety, and lack of proper way of thinking aspects of
the students (Ferraro et al., 2007).
With reference to the use of internet there is a variation in gender. Though a significant number of studies state that boys are more
prone to internet addicted (Akhter, 2013; Chou et al., 2005; Morhan-Martin & Schumacher, 2000; Yang & Tung, 2007; Simos et al.,
2008; Widyanto & Griffiths, 2006) but others have supported to girls (Igarashi et al., 2005; Shahrestanaki et al., 2020) and some said
that there is no difference in gender (Preza et al., 2004; Chung, 2011). Instead of these inconsistencies in gender, most of the
researchers of India have documented that boys are more internet addicted (Kumari et al., 2021; Bhat & Kawa, 2015; Goel et al.,
2013; Jain et al., 2020; Sinha et al., 2018). But this variation in using internet among the students is mostly culture specific. For
instance, in eastern culture female students are strictly regulated by their family members to use internet whereas male or boys are
getting more freedom from their family to use the internet which may be the reason of internet addicted. On the other hand, in
western culture there is less emphasis on regulating the use of internet in terms of gender which may be the reason for no difference
of gender in using of internet.
Previous empirical evidence indicates that excessive use of internet has an adverse effect on the academic performance of the students
(Nemati & Matlabi, 2017). The students who spend more time in internet have less interest in studying, lack of concentration on the
classroom, as well as less involvement in academic activities (Beyens et al., 2015). Along with the above, it can also lead to
absenteeism in the classroom and increase the dropout rates. In this regard, a study has been conducted on 9949 Chinese students
and found that excessive use of internet can negatively affect academic performance, increase dropout rates and absenteeism in the
classroom (Anthony et al., 2021).
Though a significant number of research studies have been conducted around the world to study the impact of internet addiction on
academic performance (Fitzpatrick, 2008; Thatcher & Goolam, 2005; Ko et al., 2006; Ferraro et al., 2007) but it is very less explicit
in Odisha state especially in Bargarh district. Despite its various effect, there are very few numbers of studies available in Bargarh
district.
RQ1: Does academic performance of university students predict by internet addiction?
RQ2: Does internet addiction predict by gender, streams of education, and habitat?
RQ2: Does internet addiction vary in terms of gender, streams of education, and habitat?
Research objectives:
1. To find out the level of internet addiction of university students.
2. To study whether academic performance of university students can be predicted by internet addiction.
3. To study whether internet addiction of university students is predicted by gender, habitat, and streams of education.
4. To study whether internet addiction can be differed by gender, habitat, streams of education, and their interaction.
Research hypothesises:
H01: Academic performance cannot be predicted by internet addiction.
H02: Internet addiction cannot be predicted by gender, habitat, and streams of education.
H03: Internet addiction cannot be differed by gender, habitat, and stream of education.
Methodology:
Method: The present study is quantitative in nature and the aim is to study the association between internet addiction and academic
performance of university students. For this purpose, descriptive survey cum correlational research design was used.
Participants: A total group of 267 undergraduate internet users were selected from 4 different colleges of Bargarh district affiliated
by Sambalpur University. For this, convenience sampling technique was used.
Instruments: Internet addiction test (IAT) was used for assessing the level of internet addiction. This scale was developed by
Kimberley Young, 1998. This scale consists of 20 items and each item is scored in five-point rating ranged from 0-5. The range of
internet addiction 0-29 indicates normal level of addiction, 30-49 indicates mild level of addiction, 50-79 indicated moderate levels

International Journal of Academic Multidisciplinary Research (IJAMR)
ISSN: 2643-9670
Vol. 7 Issue 5, May - 2023, Pages: 118-128
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of addiction and 80-above indicates severe levels of addiction. The reliability of this scale is 0.899 (Cronbach Alpha). Previous
semester marks were considered as academic performance of the university students.
Statistical techniques: The collected data were analysed by using percentage, graph, average, SD, ANOVA, and regression.
Table.1. Distribution of sample (N=267)
Category
Group
N
Percentage
Gender
Girls
155
58.05%
Boys
112
41.95%
Habitat
Rural
161
60.29%
Urban
101
39.71%
Stream of education
Arts
152
56.92%
Science
46
17.22%
Commerce
69
25.84%
Results:
The collected data was analysed via SPSS.27. The following tables represent the results of the present study.
1. Descriptive analysis of the internet addiction:
Table.2. Range of internet addiction (N=267)
Range
Frequency
Percentage
Results
0-29
28
10.48%
Normal
30-49
105
39.32%
Mild
50-79
97
36.32%
Moderate
80-100
34
12.73%
Severe
From the above table it can be said that out of 267 students 10.48% (28) students are normal level of internet addicted, 39.32% (105)
students are mild level of internet addicted, 36.32% (97) students are moderate level of internet addicted, and 12.73% (34) students
are severe level internet addicted. The results of the above table are represented with the help of graph.
Figure-1
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
Normal Mild Moderate Severe
10.48%
39.32%
36.32%
12.73%

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Table.3. Mean and SD of internet addiction in terms of gender, habitat, and stream of education.
Category
Group
Mean
SD
Sex
Girls
48.21
17.630
Boys
53.94
17.195
Habitat
Rural
48.35
17.598
Urban
48.76
17.225
Streams of education
Arts
53.61
17.305
Commerce
48.26
15.727
Science
37.46
13.285
Total
47.65
16.56
The above table displays the descriptive statistics i.e., mean, and standard deviation of internet addiction among university students
in relation to their gender, habitat, and streams of education. In this table, it was found that the Mean and SD of internet addiction
for girls is 48.21 & 17.630 respectively, and for boys is 53.94 & 17.195 respectively. The Mean and SD for rural students is 48.35
& 17.598 respectively and for urban students is 48.76 & 17.225 respectively. Similarly, the mean and SD for arts students is 53.61
& 17.305, for commerce students is 37.46 & 13.285 respectively, and for science students is 47.65 & 16.56 respectively. It has been
also found that on an average 47.65 university students are internet addicted irrespective of their sex, habitat, and streams of education
which means they have moderate level of internet addicted.
2. To study whether academic performance of university students is Predicted by internet addiction or not:
One of the objectives of present study was to investigate whether the academic performance of university students is predicted by
internet addiction or not. In this study, both academic performance and internet addiction are scaled variables. Academic performance
is an outcome variable whereas internet addiction is an independent variable. For this, Simple linear regression was used. The results
of simple linear regression were given below.
Table.4. Regression coefficient of internet addiction and academic performance of university students
Variables
B
β
R2
SE
F-value
P-value
t-value
P-value
Constant
464.822
-.184
.034
12.383
9.263**
.003
37.538**
.001
Internet
addiction
-.731
-.731
** Significant at 0.01 level
* Significant at 0.05 level
The above table shows the results of simple linear regression where the outcome variable (academic performance) was regressed or
predicted by internet addiction. It is found that internet addiction is a significant predictor of the academic performance of university
students. The result of R2 is .034 which means 3.4% difference or variation in academic performance of students is due to internet
addiction. The f statistic of this model is 9.263 for the df (1, 265) which is significant at 0.01 level. Similarly, the t-value of this study
is 37.538 which is also significant at 0.001 level. So, the null hypothesis i.e., academic performance cannot be predicted by internet
addiction is rejected at 0.01 level.
3. To study whether Gender, Habitat, and Streams of education as predictors of Internet addiction or not.
One of the objectives of this study is to find-out whether gender, habitat, and stream of education are significant predictors of internet
addiction or not. In this objective, gender has two categories i.e., boys and girls, habitat has two categories rural and urban, and
streams of education have three categories i.e., arts, commerce, and science. To fulfil the above objectives, simple linear regression
was run by converting the above cited independent variables into dummy variables with the help of SPSS.27
Table. 5. Results of simple linear regression
Model
Regression
weight
β
R2
F
P-value
t-value
P-value
1. Gender
Girls (Ref.)
.731
.000
.114
.736
.338
.736
Boys
2. Habitat
Rural (Ref.)
.416
-.004
.036
.849
.191
.849

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Urban
3. Stream of
education
Arts (Ref.)
.153
23.887**
.001
Commerce
-5.344
1.974*
.049
Science
-16.141
6.911**
.001
**Significant at 0.01
*Significant at 0.05
From the above table it is found that only stream of education is a significant predictor of internet addiction (R2-.153, F-23.887,
P<.001) whereas gender (R2-.000, F-.114, P>.005) and habitat (R2-.004, F-.036, P>.05) is not significant. It has been found that
only 15.3 % variation in internet addiction is predicted by stream of education. So, the null hypothesis i.e., internet addiction cannot
be predicted by gender and habitat is accepted whereas the null hypothesis i.e., internet addiction cannot be predicted by the streams
of education is rejected.
4. To study whether internet addiction of university students is differed by gender, habitat, streams of education, and
their interaction or not.
In this objective there are three independent variables i.e., gender, habitat, and streams of education and one dependent variable i.e.,
internet addiction. Gender has two levels i.e., boys and girls, streams of education have three levels i.e., arts, commerce, and science
and habitat has two levels i.e., rural, and urban. In this regard, 3-way ANOVA (2*3*2) was run with the help of SPSS.27.
Table. 6. Results of three-way ANOVA
Source
Sum of
Squares
df
Mean
Squares
F
Sig.
Results
Gender
1012.054
1
1012.054
3.879*
.050
Significant
Streams of education
12600.493
2
6300.247
24.147**
.001
Significant
Habitat
783.733
1
783.733
2.831
.094
Not significant
Gender*streams of
education (2*3)
61.378
1
30.689
.118
.889
Not significant
Gender*habitat (2*2)
2.327
1
2.327
.009
.925
Not significant
Streams of
education*Habitat (3*2)
467.093
2
233.547
.895
.410
Not significant
Gender*Streams of
education*Habitat (2*3*2)
199.908
2
99.954
.383
.682
Not significant
Error
66531.678
255
260.909
Total
709107.000
267
Corrected total
80716.704
266
a. R Squared= .176 (Adjusted R Squared= .140)
*Significant at .05
**Significant at .01
4.1. Variation in internet addiction due to the gender:
From the above table no 6 it can be said that the F value is 3.879 for gender which is significant at 0.05 level of significance. It
means there is a significant difference in internet addiction between boys and girls. So, the null hypothesis i.e., internet addiction
can not be differed by gender is rejected.
4.2. Variation in internet addiction due to the streams of education.

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The above table 6 shows the F-value for streams of education is 24.147 which is significant at 0.01 level. It means, there is a
significant difference in internet addiction among arts, commerce, and science students. So, the null hypothesis i.e., internet addiction
cannot be differed by streams of education is rejected.
As there is a variation in internet addiction due to streams of education and significant differences exist among arts, commerce, and
science students, so, it can be better for conducting post-hoc test to know whether each stream is significantly differed from each
other or not. For this purpose, Turkey method was employed with the help of SPSS.27.
Table.7. Multiple comparison.
(I)Stream of
education
(J) Stream of
education
Mean
difference
(I-J)
Std.
Error
Sig.
95% confidence interval
Lower bound
Upper bound
Arts
Commerce
5.34
2.718
.123
-1.06
11.75
Science
16.14**
2.345
.001
10.61
21.67
Commerce
Arts
-5.34
2.718
.123
-11.75
1.06
Science
10.80**
3.075
.002
3.55
18.05
Science
Arts
-16.14**
2.345
.001
-21.67
-10.61
Commerce
-10.80**
3.075
.002
-18.05
-3.55
**Significant at .01
*Significant at .05
The above table7 shows the mean difference in internet addiction among arts, commerce, and science students. From these multiple
comparisons it is found that Arts vs Science students and Commerce vs Science students are significantly different in internet
addiction at 0.01 level whereas Arts vs Commerce students is not significantly different in internet addiction.
4.3. Variation in internet addiction due to the habitat:
From the above table 6 it can be said that the F value for habitat is 2.831 which is not significant at 0.05 level of significance. It
means there is no significant mean difference in internet addiction between rural and urban students. So, the null hypothesis i.e.,
internet addiction can not be differed by habitat is accepted.
4.4. Variation in internet addiction due to the interaction of gender and streams of education:
The above table 6 shows the F value of interaction between gender and streams of education is .118 which is not significant at 0.05
level of significance. It means the mean score of internet addiction of boys and girls belonging from arts, commerce, and science
streams of education did not differ significantly. So, the null hypothesis i.e., internet addiction cannot be differed due to the interaction
between gender and streams of education is accepted.
4.5. Variation in internet addiction due to interaction between gender and habitat:
From the above table 6 it can be said that the F value for the interaction between gender and habitat is .009 which is not significant
at .05 level of significance. It means the mean score of internet addiction of boys and girls belonging to rural and urban areas did not
differ significantly. So, the null hypothesis that internet addiction of university students can not be differed by the interaction between
gender and habitat is accepted.
4.6. Variation in internet addiction due to the interaction between streams of education and habitat:
The above table 6 shows the result of F-value for the interaction between streams of education and habitat is .895 which is not
significant at 0.05 level of significance. It means the mean score of arts, commerce, and science students belonging from rural and
urban areas did not differ significantly. So, the null hypothesis that internet addiction of university students can not be differed due
to the interaction between streams of education and habitat is accepted.
4.7. Variation in internet addiction due to the interaction between gender, streams of education, and habitat:
The F-value for the interaction among gender, streams of education, and habitat is .383 which is not significant at 0.05 level of
significance. It means the mean score of university boys and girls having arts, commerce, and science stream of education and
belonging to rural and urban areas in internet addiction did not differ significantly. So, the null hypothesis that internet addiction
cannot be differed due to the interaction among gender, streams of education, and habitat is accepted.
Summary:

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Table. 8. Summary of the outcomes in objective wise
Objectives
Hypothesis
Accepted/
Rejected
Results
To study the level of
internet addiction of
university students
10.48%-Normal level of addicted,
39.32%- Mild level of addicted,
36.32% moderate level of addicted,
and 12.73% severe level of internet
addicted.
To study whether academic
performance of university
students can be predicted
by internet addiction.
Academic
performance cannot be
predicted by internet
addiction.
Rejected
3.4 % of academic performance can be
predicted by internet addiction.
To study whether internet
addiction can be predicted
by gender, streams of
education and habitat.
Internet addiction
cannot be predicted by
gender, streams of
education, and habitat.
Hypothesis
partially
rejected
Internet addiction was predicted by
streams of education but not be gender
and habitat.
To study whether internet
addiction of university
students can be differed by
gender, streams of
education, habitat, and
their interaction.
Internet addiction of
university students
cannot be differed by
gender, streams of
education, habitat, and
their interaction.
Hypothesis
partially
rejected
Significant difference in internet
addiction between boys and girls, arts,
commerce, and science students but
not in between rural and urban
students.
Not significant difference between the
interaction of gender and streams of
education, gender and habitat, streams
of education and habitat.
Not significant difference among the
interaction of gender, streams of
education, and habitat.
Discussion:
The main aim of present study was to investigate the relationship between internet addiction and academic performance of university
students. The results of this study revealed that on an average 47.65 university students are internet addicted irrespective of their
gender, streams of education, and habitat. The results of this study revealed that internet addiction of university students is more than
the USA, Great Britain, Poland, China, and Taiwan (Anderson, 2001; Niemz et al, 2005; Licwinko et al, 2011; Dong et al., 2012;
Lin et al., 2011).
The result of this study shows that academic performance can be significantly predicted by internet addiction. Excessive use of
internet may lead to distraction and procrastination among the university students. University students have spent more time on
social media, online gaming, and other online activities which may impair their academic performance. The result of this study is
consistent with several previous studies (Nemati & Matlabi, 2017; Beyens et al., 2015).
Gender and residential locality were not significant predictors of internet addiction of university students, but streams of education
were a significant predictor of internet addiction. But with reference to gender, streams of education, and habitat, it is found that
there is a significant difference in internet addiction between boys and girls university students. As the mean score of boys is higher
than girls, so, it can be said that boys are more internet addicted than girls. This result is consistent with previous studies (Akhter,
2013; Chou et al., 2005; Morhan-Martin & Schumacher, 2000; Yang & Tung, 2007; Simos et al., 2008; Widyanto & Griffiths, 2006).
With reference to the streams of education, it is found that there is a significant difference in internet addiction among arts, commerce,
and science university students. After the post-hoc test it has been found that there is a significant difference between arts and science,
science and commerce but not arts and commerce. The result of this study also revealed that there is no significant difference in
internet addiction between rural and urban university students. It is also found from this study that internet addiction cannot be
differed due to the interaction between gender and streams of education, gender and habitat, streams of education and habitat, and
interaction among gender, streams of education, and habitat.
Conclusion:

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In present day internet has become an essential part of every individual especially for university students. Though internet provides
number of benefits to the students, but its excessive use can have negative impact on various aspects of university students including
their academic performance. Overuse of internet may create distraction from the study, lead to procrastination, as well as affect the
psycho-social aspects of the students.
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