the effect of watching youtube on cgpa - completed

8/17/2019 The Effect of Watching YouTube on CGPA - Completed

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The Effect of Time Spent on Youtube to the Students’ CGPA

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CONTENTS

SECTION PAGE

ABSTRACT 3

INTRODUCTION 4

DATASET 5

METHOD-PRELIMINARY ANALYSIS 8

METHOD-FULL SCALE ANALYSIS 15

CONCLUSION AND RECOMMENDATION 17

REFERENCES 20

APPENDIX 21


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2.0 INTRODUCTION

In this project, we managed to conduct online survey by using Google Form. From the

result of the survey, there are 60 respondents from IIUM students successfully answered the

questionnaires. To be exact, the respondents are random by their gender but strictly from the KICT.

In IIUM, most of the students here have their own gadgets such as laptops, smartphones, tablet

etc. Therefore, watching Youtube videos can be done anywhere and anytime. Normally, students watch

video during their leisure time such as weekend, at night, or even during class interval.

We divide the data into four categories which are;

i) LOW hours of watching video (less than 2 hours per day)

ii) MEDIUM hours of watching video games (2 – 4 hours per day)

iii) HIGH hours of watching video games (4 – 6 hours per day)

We also break the CGPA range into four categories which are:

i) 2.0 – 2.4

ii) 2.5 – 2.9

iii) 3.0 – 3.4

iv) 3.5 – 3.9

We used the bar chart for each category so that it will be easier to conclude and see the

whole bigger picture later on. We also came up with a hypothesis that the higher hours of watching

Youtube videos, the lower the CGPA.


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3.0 DATASET

3.1 Low hours of playing video games (less than 2 hours)

Hours of watch Education / Entertainment CGPA

Less than 2 hours

Entertainment >2.5 and 2.0 and 3.0 and 3.0 and 3.5 and 2.5 and 3.0 and 3.0 and 2.5 and 3.0 and 2.5 and 3.5 and 2.5 and 3.0 and 2.5 and 3.5 and 3.0 and 2.5 and 2.5 and


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3.2 Medium hours of playing video games (2 - 4 hours)

Hours of play Time CGPA

2 - 4 hours

Education >2.5 and 3.0 and 3.5 and 3.0 and 2.5 and 3.0 and 2.0 and 3.0 and 3.0 and 2.5 and 3.0 and 2.5 and 3.5 and 3.0 and 3.0 and 3.0 and 2.5 and 2.5 and 3.0 and 3.5 and 2.5 and 2.5 and 3.5 and 2.5 and 2.5 and 3.0 and


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3.3 High hours of playing video games (4 - 6 hours)

Hours Purpose CGPA

4 - 6 hours

Education >3.0 and 2.0 and 2.5 and 3.0 and 2.0 and 2.5 and 3.0 and 3.0 and 3.0 and 2.5 and 3.0 and 2.5 and 2.5 and 3.0 and 2.0 and


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4.0 Method-Preliminary Analysis

4.1 Complete Data Presentation

CGPA CLASS CGPA HOURS OF FREQUENCY CUMULATIVE

BOUNDARIES PLAY FREQUENCY 2.0-2.4 1.95-2.45 Low 1

Medium 1 5High 3

2.5-2.9 2.45-2.95 Low 8Medium 10 28

High 5

3.0-3.4 2.95-3.45 Low 7Medium 12 54

High 73.5-3.9 3.45-3.95 Low 3

Medium 3 60High 0

Table 4


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4.2 Analysis for LOW spent hours of watching videos on Youtube

4.2.1 Graph of Frequency against CGPA for Low Category

Graph 1

4.2.2 Data Presentation

CGPA Frequency, f Midpoint, X m f.X m Midpoint, X m 2 f.X m 2

2.0 – 2.4 1 2.2 2.2 4.84 4.84

2.5 – 2.9 8 2.7 21.6 7.29 58.32

3.0 – 3.4 7 3.2 22.4 10.24 71.68

3.5 – 3.9 3 3.7 11.1 13.69 41.07

n = 19 ∑ . m = 57.3 ∑ . m 2 = 175.91

Table 5

0

12

3

4

5

6

7

8

9

2.0 - 2.4 2.5 - 2.9 3.0 - 3.4 3.5 - 3.9

f r e q u e c y

CGPA

Frequency vs CGPA : Low


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4.2.3 Data Description

Mean, ̅ = 1(2.2) + 8(2.7) + 7(3.2) + 3(3.7) / 19= 3.02

Modal Class = 2.5 – 2.9

Midrange = 2.0 + 3.9 / 2

= 2.95

Variance, s 2 =(∑ . ) − ∑ .

− =9 75.9 − 57.3

3

= 0.12

Standard deviation, s = √ 0.12 = 0.35


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4.3 Analysis for MEDIUM spent hours of watching videos on Youtube

4.3.1 Graph of Frequency against CGPA for Medium Category

Graph 2


CGPA Frequency, f Midpoint, X m f.X m Midpoint, X m 2 f.X m 2

2.0 – 2.4 1 2.2 2.2 4.84 4.84

2.5 – 2.9 10 2.7 27 7.29 72.9

3.0 – 3.4 12 3.2 38.4 10.24 122.88

3.5 – 3.9 3 3.7 11.1 13.69 41.07

n = 26 ∑ . m = 78.7 ∑ . m 2 = 241.69 Table 6

0

2

4

6

8

10

12

14

2.0 - 2.4 2.5 - 2.9 3.0 - 3.4 3.5 - 3.9

f r e q u e c y

CGPA

Frequency vs CGPA : Medium


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Mean, ̅ = 1(2.2) + 10(2.7) + 12(3.2) + 3(3.7) / 26= 3.03


Midrange = 2.0 + 3.9 / 2

= 2.95

Variance, s 2 = (∑ . ) – ∑ .

− =. 9 – 78.7

5

= 0.14



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4.4 Analysis for HIGH spent hours of watching videos on Youtube

4.4.1 Graph of Frequency against CGPA for High Category

Graph 3


CGPA Frequency, f Midpoint, X m f.X m Midpoint, X m 2

f.X m2

2.0 – 2.4 3 2.2 6.6 4.84 14.52

2.5 – 2.9 5 2.7 13.5 7.29 36.45

3.0 – 3.4 7 3.2 22.4 10.24 71.68

3.5 – 3.9 0 3.7 0 13.69 0

n = 15 ∑ . m = 42.5 ∑ . m 2 = 122.65 Table 7

0

1

2

3

4

5

6

7

8

2.0 - 2.4 2.5 - 2.9 3.0 - 3.4 3.5 - 3.9

f r e q u e c y

CGPA

Frequency vs CGPA : High


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Mean, ̅ = 3(2.2) + 5(2.7) + 7(3.2) + 0(3.7) / 15= 2.83


Midrange = 2.0 + 3.9 / 2

= 2.95

Variance, s 2 =(∑ . ) – ∑ .

− =5 . 5 – .5

= 0.16



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5.0 METHOD-FULL SCALE ANALYSIS

Based on the method preliminary analysis, we have collected data and translate it into a

bar graph for each category; LOW, MODERATE and HIGH. From our experiment, we made use

of the measurement of central tendency, that includes variance, standard deviation etc. We also

used the histogram to check the shape.

By referring on Graph 1 , we can see that LOW category which are for students who watch

less than 2 hours per day. Majority of them (8 students) watched less than 2 hours has a range of

CGPA 2.5 – 2.9. The second highest in the category are in the range of CGPA 3.0 – 3.4 with 7

students. Under the CGPA range of 2.0 – 2.4, there is only 1 student, which is very surprising since

we did not expect to someone to have such a low CGPA while he or she only watches less than 2

hours each day. In other discovery, only 3 students that obtain CGPA of 3.5 – 3.9 are included in

the LOW category. The average for LOW category is 3.02 . The graph for this category is right-

skewed.

Next is the MEDIUM category, refer Graph 2 . This group of students are watching

Youtube videos around 2 to 4 hours per day. There is 1 student who get CGPA under 2.0 – 2.4.

The modal class are in the CGPA range of 3.0 – 3.4 which accounted 12 students. They are

followed closely by the range of CGPA 2.5 – 2.9, with 10 students. There are 3 students who are

under the range of CGPA 3.5 – 3.9. Since the modal class is CGPA 3.0 – 3.4, the calculated mean

is 3.03 . The graph for this category is bell-shaped .


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Third category is the HIGH group of students who watched videos 4 to 6 hours each day

(Refer Graph 3). This group also has a modal class of CGPA 3.0 – 3.4, a total of 7 students.

There are no student who get a CGPA in the range of 3.5 – 3.9. In the CGPA range of 2.0 – 2.4,

there are 3 students and in CGPA range of 2.5 until 2.9, only 5 students involved. The mean for

the HIGH category is 3.57 . The graph for this category is J-shaped .

Based on our method-full scale analysis, we found out that our hypothesis, which the more

time spent on watching videos on YouTube, will give a low result of s tudent’s CGPA due to the

time they wasted on watching YouTube, can be accepted. This can be seen where there are none of the students who are in the CGPA range of 3.5 – 3.9, in the HIGH category. In addition, there

are 3 respondents from the students got CGPA range of 2.0 – 2.4 compared to LOW and MEDIUM

categories.


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6.0 CONCLUSION AND RECOMMENDATION

In conclusion, the results we obtained proved that our initial hypothesis that high amount

of times spent on video games will give the students lower CGPA is true and can be accepted .

Wasting time watching Youtube videos can affect your CGPA. Furthermore, the process of

learning can be distracted by watching videos on Youtube which not related to education.

Spending too much time in watching videos on Youtube does not necessarily increase your

CGPA, one must properly study, do their assignment and able to answer the exam questions in

order to get a good CGPA. Watching videos on Youtube can only indirectly affect the CGPA.

Our hypothesis was proven. Most of the surveys were spread to KICT students in

comparison to others course. In our survey, 33(55%) of them are Information Technology students

and 27(45%) are Computer Science (refer to Pie Chart 1 . In our survey, we also asked their opinion

whether the Internet limits their time on Youtube. From Pie Chart 2 , we can see that around 65

percent stated that they agree with the claim. Besides that, to make the survey more information,

we also include a question to know their main interest in watching videos on the Youtube. The Bar

Chart 1 explained, the respondents are most preferred to watch Music videos; 52(86.7%) compared

to only 7(11.7%) from the respondents used to watch about Human Sciences.


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We also ask a question about what kind of videos they would likely upload. Majority of

the respondents answered that they would like to upload any videos related to both entertainment

and education.

We also found out that some of the students who responded to our surveys, make money

from Youtube. Thus, Youtube can be another way or platform for students to generate their own

income passively by uploading variety of videos.

If we need to conduct another research, we will spread the surveys to students from other

course as well. As a recommendation, students should make their own timetable for study session

and leisure time. This is to ensure that students have a balanced lifestyle in order to achieve

academic excellence and in the Hereafter.


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Respondents Videos Preferences

Bar graph 3

7.0 REFERENCES

http://italeem.iium.edu.my/2015/course/view.php?id=13057


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8.0 APPENDIX

a. Survey Questions


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https://docs.google.com/forms/d/1CS0bcxLyEUGtfz_wVNRpqcuNMUaN5nRA-mrN_76q6L8/prefill


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b. Bad Sample


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c. Good Sample


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the effect of watching youtube on cgpa - completed

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