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Impact of Social Networking Sites on Students' Academic Performance

Autor:   •  December 29, 2017  •  3,667 Words (15 Pages)  •  278 Views

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Theoretical framework of the impact of social networking sites on students’ academic performance;

Academic performance is an important factor in individual education carrier, for admitting in any institution academic performance is consider prerequisite. Many students are searching for perfect college and universities to attend and their eligibility is measured by their previous academic performance. It’s also an important factor for finding job, so it is an important part in every individual carrier and its evident that (CGPA ,Grading etc.) can affect the performance of students.


Cumulative grade point (CGPA) a massive factor in affecting student’s academic performance. Many institutions prefer student’s with higher GPA.

Time spent on social networking in a day

According to Ahmed and qazi (2011) that student spent time on social networking site with respect to their study have a positive impact on student’s academic performance.

Time spent on study per day

- According to Weng, Chen (2011) that students are often seen busy in social networking during study hours, so social networking affect student’s performance negatively.

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The model of the impact of social networking sites on students’ academic performance;

Academic performance = β + β1(NHS) + β2(NHSNS) + β3(NOAC) + µ

In this study, β is the intercept and µ is the error term, the dependent variable is students’ academic performance measure in term of CGPA. The independents variables are no of hours spent on study per day, no of hours spent on social networking in a day and total number of account on social networking sites.

Research methodology

In this paper both primary and secondary sources of data is included the primary data was collected through a questionnaire for the literature review of the study secondary data was collected from already published research paper article etc.

Sampling design

One hundred 100 respondents were randomly selected from Baluchistan univerty of information technology And management science Quetta (BUIEMS) and the respondents were only students out of 100 Questionnaire only 93 were accumulated and response rate was 93%. Out of which 66% male and 34% Female contributed is the questionnaire, the data generated from collected questionnaire were access through excel. The questionnaire was divide in to two part 1st part contained respondents personal data such as Name gender etc and second part on the proper question related to the study.

Empirical Result and Interpretation

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Equal to 0.05 which is a poor fit to the model. 5% variation in CGDP is explained by the explanatory variable such as No of account, hours spent on social networking sites and hours spent on study.

Multiple R

Is 0.24, this indicate that correlation between the independent and dependent variable is positive.

Adjusted R

the adjusted R in this model is 0.02 which show that there are only 0.02 of the data explained in the model.

Significance F and P-value

In the regression output F stat equal to 0.14 which is higher than 0.05 Its shows that only one variable have an explanatory power in the model.

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A P-value of 5% or less are generally accepted, point at which to reject the null hypothesis. In my study, this is the case (3.29, 0.83, 0.97 and 0.02)

. T statistics

These are the t-statistics and their associated 2-tailed p-values used in testing whether a given coefficient is significantly different from zero. Using an alpha of 0.05: The coefficient for hours spent on study (2.32) is significantly different from 0 because its p-value is 0.02 which is smaller than 0.05.The coefficient for hours spent on social networking sites (-0.025) is not significantly different from 0 because its p-value is 0.97, which is larger than 0.05. The coefficient for number of accounts (-0.01) is not statistically significantly different from 0 because because its P-value is larger than 0.05 which is not significant at this level of confidence interval 0.05.


The regression line Y= CGDP = 2.39 – 0.01*NOA - 0.0034*HSSNS + 0.23*HSS +µi

Constant variable is 2.39 students earn CGPA given other variable equal to zero. For sign up to one more account on social networking, sites decrease the CGPA on the average by 0.01 point. Spending one additional hour on social networking, sites decrease CGPA on the average by 0.0034 point. Study for an extra hour increase by CGPA on the average by 0.23 point.


Thirtyone (31) or 31% of the students have successfully reached satisfactory academic performance and reaming 69% perform below the satisfactory level. Based on the outcomes of the study, it’s stated that no of account and hours spent on social networking sites seems both insignificant variable in the study because it has a negative relationship and its impact to the students CGPA negatively, since most of the respondents (CGPA) range from 1.75 to 2.25, and social networking sites in relation to study have a significance effect in their (CGPA), since only 31% of the respondend CGPA range from 2.5 to 3.0 base on average (CGPA).it can only explained that social networking sites in relation to study has a positive effect.


- M, Rithika., Selvaraj, S., (2010). Impact of social media on students’ academic performance. A journal of logistics and supply chain management. Perspective.

- Boyd, N., Ellision., (2007). Social networking sites, history and definition. Journal of computer mediated sciences volume (13). P.P. 220-230.

- Camilia,. Ibrahim, SD & Dalahuatu, L. (2013). The effects of social


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