The impact of Facebook on students' academic performance

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THE IMPACT OF FACEBOOK ON STUDENTS’ ACADEMIC PERFORMANCE

  1. INTRODUCTION

Facebook is dominate potential –places among youth specially students. Most of students are spending more time in using Facebook which is lead to impact time spending in education. This research is going to study whether Facebook impact on students’ performance or not in SLIATE. The SLIATE (Sri Lanka Institute of Advanced Technological Education) is one of the leading educational institutions in Sri Lanka for higher education and is a statutory body coming under the purview of Higher Education Division, Ministry of Education. SLIATE has been established by the Parliament Act 29 of 1995 focusing on fostering Advanced Technical Education at a post-secondary level and its head is Director General appointed by the cabinet. It is mandated to establish Advanced Technical Institute (ATI) in every province for both Engineering and Business Studies. (http://www.sliate.net/about.htm)

  1. BACKGROUND OF THE STUDY

Nowadays most of peoples use Facebook to make social network among people all over the world. And students also spending most of their time on such social media called Facebook. Facebook.com (Facebook), the most popular and commonly used online social network Web site, has created passion among college students in modern years. College students are become very interest in online social networking.

“Online social network sites such as Facebook work as an important entertainment for undergraduates. Facebook, the most popular social network site, was specifically designed for undergraduates and is the most commonly used. Therefore, time spent on Facebook may affect academic performance. For example, time spent on Facebook may directly affect and/or reasonable the students’ academic performance.

  1. OBJECTIVE OF THE STUDY

The ultimate purpose of this study is going to examine the use of Facebook weather it is impact on students’ academic performance or not. The core research question of this survey is: what is the effect of online social networking site, Facebook, having on students’ academic performance (Examination Marks)? In other words does time spending (access) every day on Facebook have a significant impact on academic performance (Examination Marks)? In addition to that this survey going to test do Sex, age and status of the student impact on academic performance on them?

  1. SIGNIFICANCE OF THE STUDY

The college classroom is used to delivering the product (student education) of the college. The objective of education is to have students learn and succeed. Thus, it is important to know and understand how student use of online social network sites (i.e. Facebook) affects academic success. Therefore, a critical examination of the impact of Facebook on academic performance is very essential.

This useful presentation to help students, lecturer, teachers and academic leaders. Students, specially, can get better understand the consequences of Facebook site use on educational performance. Lecturer, teachers and academic leaders can get valued understanding and information about the relationship between the students time spend on Facebook and how it affects students’ academic performance. Also, academicians can be get well prepared to guide and mentor students regarding the negative impacts of Facebook sites on their academic performance.

  1. METHODOLOGY

This research is designed to test the impact of using Facebook on student academic success and performance in their exam. Research can explain through the collection of numerical data, which is then analyzed using computerized statistical package. With survey research, I can select a group of respondents, collect data, and analyze the data to answer the research question. I have collected quantitative as well as qualitative data from a sample using questionnaire technique. This research is an appropriate investigation tool for making generalized interpretations about a large group of people based on data collected from a smaller number of individuals from that group.

  1. POPULATION AND SAMPLE

The population for this study is Higher National Diploma 2009 Batch students of SLIATE, Kandy. The students’ academic performance is evaluated through final marks taken by students in Strategic Financial Management. The independent variable is use of Facebook every day. This data was taken from the respective student through small questioner during the class. Furthermore some demographic data also have been collected such as: gender, age, and student status weather full time or part time. They described the sample characteristics. The student (sample) selected the answers from the survey that best described them.

  1. DATA ANALYSIS

I used SPSS 16.0 to perform the statistical analysis. Basic frequency analyses were conducted using demographic information. The questions were analyzed using descriptive statistical analyzing techniques. Descriptive statistics was another statistical technique which is used in this study to define the mean, minimum value, maximum value, and standard deviation for all the demographic variables. SPSS is presented in tables and charts. Most importantly the core research question’s answer is tested by using Independent Samples Test and ANOVA test also is performed as statistical technique. I used this technique to find the impact of using (spending time every day) Facebook on student’s performance, by comparing means marks between student’s who are spending time on Facebook and who are not. So I used SPSS 16.0 to analyze statistic and interpret the result. This study is intended to bring attention to and awareness of the impact of using Facebook on students’ academic performance.

  1. FINDINGS

This section is presents the output generated by SPSS 16 from data collected for survey.

Table 1 :Facebook Time

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

45

42.5

42.5

42.5

No

61

57.5

57.5

100.0

Total

106

100.0

100.0

Table 1 represents the total number of respondents included in the sample of 106 students. Among them 45 students are spending time on Facebook every day which represent 42.5%. But 61 students (57.5%) are not spending time on Facebook every day.

Table 2 :Status

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Full Time

43

40.6

40.6

40.6

Part Time

63

59.4

59.4

100.0

Total

106

100.0

100.0

Table 2 represents the status of the students such as whether full time or Part time students. 43 students are engaging in Full Time and 63 students are engaged in part time course.

Table 3: Sex

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Female

64

60.4

60.4

60.4

Male

42

39.6

39.6

100.0

Total

106

100.0

100.0

Table 3 represents the total sample consist of 64 students are female (60.4%) and 42 students are male (39.6%).

Table 4: Age

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

24

10

9.4

9.4

9.4

25

68

64.2

64.2

73.6

26

16

15.1

15.1

88.7

27

12

11.3

11.3

100.0

Total

106

100.0

100.0

Table 4 represents the age group of the sample. 68% of the sample students represents the age group of 25 Years. 15.1 % of students in 26 years age group. Other age groups are approximately similar to 10%.

Table 5: Summary

Facebook Time

Yes

No

Status

Status

Full Time

Part Time

Full Time

Part Time

Sex

Sex

Sex

Sex

Female

Male

Female

Male

Female

Male

Female

Male

Count

11

10

16

8

11

11

26

13

Table 5 represents summary of respondents. 11 female and 10 male Fulltime students, and 16 female and 8 Male part-time students are spending time on Facebook every day. But 11 female and 11 male Fulltime students, and 26 female and 13 Male part-time students are not spending time on Facebook every day.

Table 6 :Descriptive

Facebook Time

Statistic

Std. Error

Marks

Yes

Mean

77.36

1.406

95% Confidence Interval for Mean

Lower Bound

74.52

Upper Bound

80.19

5% Trimmed Mean

77.60

Median

78.00

Variance

88.962

Std. Deviation

9.432

Minimum

57

Maximum

94

Range

37

Interquartile Range

14

Skewness

-.592

.354

Kurtosis

-.426

.695

No

Mean

77.93

.989

95% Confidence Interval for Mean

Lower Bound

75.96

Upper Bound

79.91

5% Trimmed Mean

78.02

Median

78.00

Variance

59.696

Std. Deviation

7.726

Minimum

60

Maximum

94

Range

34

Interquartile Range

10

Skewness

-.276

.306

Kurtosis

-.550

.604

Table: 6 represents the descriptive statistics of the sample with a variable of Facebook usage on student’s performance which is represented by Marks. The students mean marks those who are spending time on Facebook is 77.36. At 95% confidence level the mean marks of the student’s lies between 74.52 to 80.19 marks. But there is a 5% change to the mean marks not lies within the range. And the standard deviation of marks is 9.432, median is 78.00, normal distribution is negatively skewed to left at -.592.

The students mean marks those who are not spending time on Facebook is 77.93. At 95% confidence level the mean marks of the students lies Between 75.96 to 79.91. But there is a 5% change to the mean marks is not lies in the range. And the standard deviation of marks is 7.726. , median is 78.00, normal distribution is negatively skewed to left at -.276.

Tests of Normality

H0: Student’s marks are normally distributed

H1: Student’s marks are not normally distributed

Table 7:Tests of Normality

FacebookTime

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Sig.

Marks

Yes

.117

45

.142

.947

45

.040

No

.097

61

.200*

.977

61

.294

a. Lilliefors Significance Correction

*. This is a lower bound of the true significance.

The Tests of Normality are shown in the table 7. Here two tests for normality. For dataset small than 2000 elements, we use the Shapiro-Wilk test, otherwise, the Kolmogorov-Smirnov test is used. In our case, since we have only 106 elements, the Shapiro-Wilk test is used. From the table Group Yes p-value is .040 and Group No p value is .294. So in group yes, we can reject null hypothesis and we can conclude that the data comes is not normal distribution. But in case of Group No, We cannot reject the null hypothesis and conclude that the data comes from a normal distribution.

However when analyze the Normal Q-Q plot of marks in Figure: 1 Group yes is approximately normally distributed. So we can assume that data are normally distributed to use the independent sample test.

Figure: 1 Figure: 2

Figure: 3

Statistical Hypothesis

H0: Student’s marks of two groups are equal (µ=µ)

H1: Student’s marks of two groups are not equal (µ≠µ)

Research Hypothesis

H0: Use of Facebook is not significantly affect the students’ performance

H1: Use of Facebook is significantly affect the students’ performance

Table 8: Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

Marks

Equal variances assumed

1.844

.177

-.347

104

.729

-.579

1.668

-3.887

2.729

Equal variances not assumed

-.337

83.363

.737

-.579

1.719

-3.998

2.840

This table 8, represents the results of the independent-samples t-test. The Levene’s results had an F-statistic of 1.844 with a significance value (P) of 0.177. Because, P > α (0.177 > .05), the two variables has statistically equal variance distributions. Therefore, we can use the first row of t-test information to determine if the two group mean marks are statistically different from each other. The t-statistic value is -0.347. The degrees of freedom is 104. The 2-tailed significance value is 0.729. The difference between the means of two group is -0.579 and the standard error of this difference is 1.668. The 95% confidence interval of the difference ranged from -3.887 to 2.729.

Because P > α (0.729> 0.05), we cannot reject null hypothesis i.e. there is no significant evidence that two groups students’ average marks are different, so we can come to the conclusion that use of Facebook is not significantly impact on students’ performance.

Research Hypothesis

H0: Sex not significantly affect the students’ performance (µ=µ)

H1: Sex is significantly affect the students’ performance (µ≠µ)

Table 9: Group Statistics

Sex

N

Mean

Std. Deviation

Std. Error Mean

Marks

Female

64

78.03

7.607

.951

Male

42

77.17

9.678

1.493

Table 9:Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

Marks

Equal variances assumed

5.194

.025

.513

104

.609

.865

1.685

-2.476

4.206

Equal variances not assumed

.488

73.165

.627

.865

1.770

-2.664

4.393

The Levene’s results had an F-statistic of 5.194 with a significance value (P) of 0.025. Because, P < α (0.025 <.05), the two variables has statistically not equal variance distributions. Therefore, we can use the second row of t-test information to determine if the two group mean marks are statistically different from each other. The t-statistic value is 0.488. The degrees of freedom is 73.165. The 2-tailed significance value is 0.627. The difference between the means of two group is .865 and the standard error of this difference is 1.770. At 95% confidence interval difference ranged from -2.664 to 4.393. Because P > α (0.627> 0.05), we cannot reject null hypothesis, so we can come to the conclusion that the average marks is statistically not significantly different in sex of students. So sex of the students are not impact on students’ performance.

Research Hypothesis

H0: use of Facebook is not significantly affect the students’ performance (µ=µ)

H1: use of Facebook is significantly affect the students’ performance (µ≠µ)

Table 10: Group Statistics

Status

N

Mean

Std. Deviation

Std. Error Mean

Marks

Full Time

43

77.53

8.486

1.294

Part Time

63

77.79

8.499

1.071

Table 11: Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

Marks

Equal variances assumed

.023

.879

-.154

104

.878

-.259

1.680

-3.591

3.073

Equal variances not assumed

-.154

90.467

.878

-.259

1.680

-3.596

3.078

Table 11 represents the results of the independent-samples t-test. The Levene’s results had an F-statistic of 0.023 with a significance value (P) of 0.879. Because, P > α (0. 879 > .05), the two variables has statistically equal variance distributions. Therefore, we can use the first row of t-test information to determine if the two group mean marks are statistically different from each other. The t-statistic value is -0.154. The degrees of freedom is 104. The 2-tailed significance value is 0. 878. The difference between the means of two group is -0.259 and the standard error of this difference is 1.668. At 95% confidence interval difference ranged from -3.591to 3.073.because P > α (0 .878> 0.05), we cannot reject null hypothesis, so we can come to the conclusion that the average marks of the two group (Full time and Part Time) of students are statistically not significantly different. In other words student’s status is not impact on student’s performance.

Research Hypothesis

H0: Age is not significantly affect the students’ performance (µ=µ)

H1: Age is significantly affect the students’ performance (µ≠µ)

Table 12: ANOVA

Marks

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

162.710

3

54.237

.753

.523

Within Groups

7342.017

102

71.981

Total

7504.726

105

Table 12 is represent ANOVA output. Which is used to compare mean differnces between age groups of the sample. The F-statistic is 0.753, The Sig value is 0.523.P > α (0.523> 0.05), we cannot reject null hypothesis i.e there is no significant evidence to reject that age of students’ average marks are different, so we can come to the conclusion that the average marks of students’ age are statistically not significantly different. So student’s age is not impact on students’ performance.

  1. OVERALL CONCLUSION

The use of Facebook is statistically not impact of student’s performance. Even sex, Age, or Status also statistically not impact on students’ performance.

  1. LIMITATIONS

The selected variables are not significantly impact on students’ performance. To know what are the factors are affecting students’ performance, we have to include more variable in addition to this variable and include more samples into the survey. The potential limitation of this study is that the participants are sampled from only one institute. Therefore, the findings may cannot be represents to all academic institutes in Sri Lanka. I selected the institute because of convenient, size, familiarity, multiplicity of students, and cost-effectiveness. Also limitation of this study is I cannot say whether the students fill out the questionnaire exactly and appropriately. Students sometimes undervalue or overvalue the time they spend on the activities listed on the study. Students might also have trouble distinguishing between being logged on and actively using their Facebook site.

List of references

References

Moon, A. L., June 2011. The impact of Facebook on undergraduate academic performance: implications for educational leaders, Mount Pleasant, Michigan: Central Michigan University.

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