SlideShare a Scribd company logo
USAGE OF SMART MOBILE PHONES BY
COLLEGE STUDENTS
by
Siddharth Bhatnagar
i
ACKNOWLEDGMENT
I am highly indebted to Prof. A.H. Sequeira for his guidance and for giving me the
opportunity to work on this captivating project ‘Usage of Smartphones by college students.’
His constant supervision and help played a key role in the successful completion of this
project.
I would also like to express my sincere gratitude to all participants of the survey for their
support and guidance during the conduct of this exercise.
I would like to express my special gratitude and thanks to my team members: Vijay, Veena,
Swarnava, Suraj, Vargob and Piyush for providing valuable and timely inputs in developing
the project.
My thanks and appreciations also go to my colleagues and people who have willingly helped
me out with their abilities.
Siddharth Bhatnagar
ii
ABSTRACT
Smartphones are an inventions that keep individuals connected to society, especially college
students. This report discusses the relationships between Smartphone usage and the effects
Smartphone have on college student’s social lives, education lives, and physical activity. In
this research the major usages of smartphones for socializing, information collection,
entertainment and as an aid to learning are analyzed in synchronization with the different
demographic factors such as gender, age, educational qualifications and monthly income of
parents. The objective of the research is that to check whether there is a significant
relationship between the different demographic factors and the usages or not.
iii
CONTENTS
Particulars Page No.
Acknowledgement i
Abstract ii
List of Tables & Figures iv
Chapter-1: Introduction 1
1.1 Research Question 1
1.2 Investigative Questions 1
1.3 Research Objective 2
1.4 Hypothesis 2
1.5 Limitations 3
Chapter-2: Literature Review 4
Chapter-3: Research Methodology 6
3.1 Method 6
3.1.1 Data 6
3.1.2 Reasoning 6
3.1.3 Research Tools 7
3.2 Sampling Design 7
3.3 Sample Size Calculations 7
3.3 Questionnaire Design 8
Chapter-4: Data Analysis & Interpretation 9
4.1 Demographic Presentation 9
4.2 Hypothesis Testing 33
4.3 Findings 36
Chapter-5: Conclusion 38
References 39
Appendix A 40
Appendix B 41
iv
LIST OF TABLES & FIGURES
Table/Figure Number and Name Page Number
Table 2.1: Important findings of Literature Review 5
Table 4.1.1: Gender 9
Table 4.1.2: Student Age Group 10
Table 4.1.3: Marital Status 11
Table 4.1.4: Education 12
Table 4.1.5: Income 13
Table 4.1.6: College/University 14
Table 4.1.7: Smart Phone for Social Media. 15
Table 4.1.8: Smart Phone for text message. 16
Table 4.1.9: Smart Phones for Calls and Conversations. 17
Table 4.1.10: Smart phones are used to check electronic mails. 18
Table 4.1.11: Smart phones for using search engine. 19
Table 4.1.12: Smart phones to get college announcements and 20
information.
Table 4.1.13: Smart phones to check news and weather conditions. 21
Table 4.1.14: Smart phones to get sports updates. 22
Table 4.1.15: Smart phones to listen to music. 23
Table 4.1.16: Smart phones to watch video and games. 24
Table 4.1.17: Smart phones for taking photos. 25
Table 4.1.18: Smart phones to book movie tickets. 26
Table 4.1.19: Smart phones to do online shopping. 27
Table 4.1.20: Smart phones used as calculator. 28
Table 4.1.21: Smart phones to take down notes. 29
Table 4.1.22: Smart phones to read documents in PDF and Word. 30
v
Table 4.1.23: Smart phones to Search Online on Urgent Topics 31
about Subjects.
Table 4.2.1: Null Hypothesis Test for the usage of smartphones to Gender. 33
Table 4.2.2: Null Hypothesis Test for the usage of smartphones to Age. 34
Table 4.2.3: Null Hypothesis Test for the usage of smartphones to 35
Educational Qualification.
Table 4.2.4: Null Hypothesis Test for the usage of smartphones to 36
Monthly Income of Parents.
Fig. 4.1.1: Gender 10
Fig. 4.1.2: Student Age Group 11
Fig. 4.1.3: Marital Status 12
Fig. 4.1.4: Education 13
Fig. 4.1.5: Income 14
Fig. 4.1.6: College/University 15
Fig. 4.1.7: Smart Phone for Social Media. 16
Fig. 4.1.8: Smart Phone for text message. 17
Fig. 4.1.9: Smart Phones for Calls and Conversations. 18
Fig. 4.1.10: Smart phones are used to check electronic mails. 19
Fig. 4.1.11: Smart phones for using search engine. 20
Fig. 4.1.12: Smart phones to get college announcements and 21
information.
Fig. 4.1.13: Smart phones to check news and weather conditions. 22
Fig. 4.1.14: Smart phones to get sports updates. 23
Fig. 4.1.15: Smart phones to listen to music. 24
Fig. 4.1.16: Smart phones to watch video and games. 25
Fig. 4.1.17: Smart phones for taking photos. 26
vi
Fig. 4.1.18: Smart phones to book movie tickets. 27
Fig. 4.1.19: Smart phones to do online shopping. 28
Fig. 4.1.20: Smart phones used as calculator. 29
Fig. 4.1.21: Smart phones to take down notes. 30
Fig. 4.1.22: Smart phones to read documents in PDF and Word. 31
Fig. 4.1.23: Smart phones to Search Online on Urgent Topics 32
about Subjects.
1
Chapter-1
INTRODUCTION
Smartphones, one of the recent inventions are already the most popular product used by i-
Generation. Its sophisticated features make it very versatile product as the user can click
pictures, surf the internet and can get connected to the world around. Studies suggest that
university students are the major contributions to the smartphones sales ad 99.8% of the
college students have a cellphone and 68% students use smartphones for educational
purposes. With thousands of apps, online courses and videos, it is the major contributor to the
e-learning concept. Smartphones are an integral part of college life and culture as they are
used, both overtly and covertly, in every possible campus setting, including the classroom,
the device is capable of contributing to student learning and improved academic
performance. Smartphones provide students with immediate, portable access to many of the
same education-enhancing capabilities as an Internet-connected computer, such as online
information retrieval, file sharing, and interacting with professors and fellow students. Cell
phone apps have added new features to entice the mobile users as well, like location tagging
and status updates.
1.1 Research Question
How the students use smartphone in colleges?
1.2 Investigative Questions
1. What is the relationship between gender and usage of smartphones?
2. How age is related with usage of smartphones?
3. What is the relationship between Educational Qualifications and the usage of
smartphones?
2
4. How monthly income is related with usage of smartphones?
1.3 Research Objectives
1. To study the usage of smart phones by college students.
2. To determine the relationship between gender and usage of smartphones.
3. To understand the relationship between age and usage of smartphones.
4. To analyze the relationship between education qualification and usage of
smartphones.
5. To examine the relationship between monthly income and usage of smart
phones.
1.4 Hypothesis
HO1: There is no significant relationship between Gender and the usage of smartphones.
HA1: There is significant relationships between Gender and the usage of smartphones.
HO2: There is no significant relationship between Age and the usage of smartphones.
HA2: There is significant relationships between Age and the usage of smartphones.
HO3: There is no significant relationship between Educational Qualifications and the usage
of smartphones.
HA3: There is significant relationships between Educational Qualifications and the usage of
smartphones.
HO4: There is no significant relationship between Monthly Income and the usage of
smartphones.
HA4: There is significant relationships between Monthly Income and the usage of
smartphones.
3
1.5 Limitations
1. Some recent technologies such as the m-banking and other digitally advanced
payment options are not considered.
2. The timeframe to carry out the research was very less therefore the population
engagement for survey is small in count.
4
Chapter-2
LITERATURE REVIEW
The aim of the research was to study about the usage of smartphones by the college students
throughout the country. This research utilized a more holistic measure of cell phone use than
previous studies. The measure accounts for the cell phone’s expanded capabilities in the
realm of social networking, gaming, and Internet use. Presently, cell phone use is a dominant
and defining characteristic of this generation of college students and often occurs during
class time, while completing homework, and while studying,
In this study, we developed four hypotheses to examine the relationship between formed
variables and actual usage of smartphones by the college students. Dr. Mohammad Jafar
Esmaeili states that students find that using the smartphone is useful and could benefit them
in process of learning, they are more willing to utilize it in the classroom.
Laird found that 55% of the college students use smartphones for gaming purposes while
Jesse found that atleast 80% of the students have used smartphones once in a running class.
According to S. Saraswathi. 68% of students uses smartphone for academic purposes or to
take pictures of class notes or for social networking.
5
Table 2.1: Important findings of Literature Review
S.No. Author/Publication Title Year Findings
1. Dr. Gayle,R. Jesse Smartphone and App
Usage Among College
Students.
2015 University students
are the major
contributors to
smartphones sales.
2. S Saraswathi Smartphone usage
among students
2017 68% of the students
use
3. Andrew lepp, Jacob E
Barkley
The Relationship
Between Cell Phone
Use and Academic
Performance.
2015 Smartphone have a
negative impact on
student during
lectures.
4. Dr. Mohammad Jafar
Esmaeili
Perceptions of
Students toward
Utilizing Smartphone
2011 Using smartphone has
an impact on
students’ career.
6
Chapter-3
RESEARCH METHODOLOGY
3.1 Method
To determine the Usage of Smart Mobile Phones by College Students, mixed approach was
used which included both exploratory and inductive reasoning in order to accumulate
background information on the given topic to filter the research questions. The identification
of the information which is to be used along the sample to derive the response and their
analysis, investigative questions were formulated.
3.1.1 Data
Primary Data:
Survey data gathered from questionnaire is used as the primary source of data.
Secondary Data:
The various scholarly journals & research articles were used as the secondary source of data.
3.1.2 Reasoning
We employed inductive and exploratory reasoning because it satisfies the exploratory nature
of our research.
7
3.1.3 Research Tools
A study is conducted on the sample population using a self-framed questionnaire which is
forwarded to the respondents through the web-link.
The steps used to conduct the survey include:
 Defining the objective of the survey
 Determining the sampling group
 Preparing the questionnaire
 Registering the responses
 Data analysis
3.2 Sampling Design
Sampling is selecting some elements in a population and drawing conclusion about the entire
population. Population is the total collection of elements about which we wish to make some
references. Convenience sampling is used in the study of the population as it is a non-
probability sampling technique where respondents are selected as per the accessibility and
proximity. The population involved is very large in number it’s clear that individual
interaction in impossible to carry out. Convenience sampling being very fast, inexpensive is
the most relevant choice for sampling design.
3.3 Sample Size Calculation
The Population (Number of professional college students in India) is N = 2,000,000
Confidence Interval (e) = 6%
Sample proportion (p) = 0.5
q = 1 – p = 0.5
Confidence Level = 95%
Z-Score = 1.96
Formula to calculate Sample Size:
For larger or infinite population;
8
S = (Z2* p * q) / e2
And Sample Size (n) = S / [1 + (S - 1)/N]
Therefore, Sample size (n) = 266.67 ~ 267
3.4 Questionnaire Design
The questionnaire has been thoughtfully designed keeping the research objectives in mind. It
consists of 24 questions in total; out of which 7 are demographic and the remaining 17 are
intended to capture data at all the levels (Nominal, Ordinal, Interval & Ratio).
We have kept the questionnaire as concise as possible to get the maximum reliable responses.
The questionnaire consists of the following kinds of questions:
 Simple Category scale
 Multiple Choice, Single Response scale
 Likert Scale
 Open Ended Question
9
Chapter-4
DATA ANALYSIS & INTERPRETATION
This chapter consists of the analysis and interpretation of 267 responses collected on an
unbiased basis from students of different parts of the country. Analysis was done with the
help of Google Forms and then generating useful graphs in Microsoft excel. Hypothesis
testing was done by chi-square method using the SPSS software and various graphs were
obtained from MS Excel and Google sheets.
4.1 Demographic Presentation
Table 4.1.1: Gender
Frequency Percentage
Female 103 38.6
Male 164 61.4
Total 267 100
10
Fig. 4.1.1: Gender
The total samples collected from students are 267, out of which 38.6% are female and 61.4%
are male students. This is given in Table 4.1.1
Table 4.1.2: Student Age Group
Frequency Percentage
Under 20 33 12.4
21-25 181 67.8
26-30 46 17.2
Above 31 7 2.6
Total 267 100
38.6%
61.4%
Female
Male
11
Fig. 4.1.2: Student Age Group
As seen in Fig. 4.1.2 & Table 4.1.2, 65.6% of the students are in the age group 21-25, 17.9%
in 26-30 age group, 14% in the age group under 20 and 2.6% in the age group above 31.
From this we can conclude that most of the respondents are in the age group of 21-25.
Table 4.1.3: Marital Status
Frequency Percentage
Married 50 18.7
Single 217 81.3
Total 267 100
67.8%
17.2%
2.6%
12.4%
21-25
26-30
Above 31
under20
12
Fig. 4.1.3: Marital Status
Of all the respondents, when it comes to their Marital Status 82% (217 respondents) are
unmarried and 18% (50 respondents) are married. This is given in Fig. 4.1.3 and Table 4.1.3
Table 4.1.4: Education
Frequency Percentage
Secondary School 12 4.5
Bachelor Degree 168 62.9
Master Degree 76 28.5
Others 11 4.1
Total 267 100
18.7%
81.3%
Married
Single
13
Fig. 4.1.4: Education
As seen in Fig. 4.1.4 and Table 4.1.4, 62.9 % of the respondents were enrolled in Bachelor’s
Degree, 28.5 % in Master’s Degree, and 4.1 % in other programs such as PhD. From this it
clear that most of the respondents are perusing Bachelor’s degree.
Table 4.1.5: Income
Frequency Percentage
Less than 20,000 71 26.6
20,001-40,000 72 27.0
40,001-60,000 63 23.6
Above 60,001 61 22.8
Total 267 100
62.9%
28.5%
4.1%
4.5%
Bachelor’s Degree
Master Degree
Others
Secondary School
14
Fig. 4.1.5: Income
When it comes to the monthly income of the respondent’s parents, 26.6 % comes in the
category Less than 20,000, 27 % comes in the range of 20,001-40,000: 23.6 % in 40,001-
60,000 and 22.8 % are having an income of 60,001 or more.
Table 4.1.6: College/University
Frequency Percentage
Autonomous 54 20.2
Pre-university 18 6.7
University 178 66.7
Other 17 6.4
Total 267 100
27%
23.6%22.8%
26.6%
20,001 -40,000
40,001 -60,000
Above 60,001
Less than 20,000
15
Fig. 4.1.6: College/University
From the Table 4.1.6 and Fig.4.1.6 it is evident that majority of the respondents are perusing
their courses in University (66.7%) followed by Autonomous (20.2%). Following the trail is
those who are in Pre-university (6.7%) and others (6.4%).
Table 4.1.7: Smart Phone for Social Media.
Frequency Percentage
Strongly disagree 13 4.9
Disagree 18 6.7
Neither Agree nor Disagree 61 22.8
Agree 64 24.0
Strongly agree 111 41.6
Total 267 100
20.2%
6.7%
66.7%
6.4%
Autonomous
Pre-university
University
Other
16
Fig. 4.1.7: Smart Phone for Social Media.
From the Table 4.1.7 and Fig. 4.1.7 it clear that a majority of the respondents (41.6%) said
that they Strongly Agree with the fact that the use Smart phones for social media and only
4.1% of the respondents agreed the other way around.
Table 4.1.8: Smart Phone for text message.
Frequency Percentage
Strongly disagree 36 13.5
Disagree 45 16.9
Neither agree or disagree 44 16.4
Agree 71 26.6
Strongly agree 71 26.6
Total 267 100
13
18
61 64
111
0
20
40
60
80
100
120
Strongly disagree Disagree Neither Agree or
Disagree
Agree Strongly agree
17
Fig. 4.1.8: Smart Phone for Text Message.
From the Table 4.1.8 and Fig. 4.1.8 we can see that more than 50% of the respondents are
agree or strongly agree with the fact that they use smart mobile phones for texting. Only
30.1% of the whole respondents is going for strongly disagree or disagree. As a result we can
conclude that most of the respondents are using Smart phones for text messaging.
Table 4.1.9: Smart Phones for Calls and Conversations.
Frequency Percentage
Strongly disagree 8 3.0
Disagree 18 6.7
Neither agree or disagree 48 18.0
Agree 73 27.3
Strongly agree 120 45.0
Total 267 100
36
45 44
71 71
0
10
20
30
40
50
60
70
80
Strongly disagree disagree Neither agree or
disagree
agree Strongly agree
18
Fig. 4.1.9: Smart Phones for Calls and Conversations.
In a question related to usage of smart phones for calls and conversations, most respondents
(45%) felt that they strongly agree with the fact that they use smart phones for calling and
conversation purpose.
Table 4.1.10: Smart phones are used to check electronic mails.
Frequency Percentage
Strongly disagree 6 2.2
Disagree 30 11.2
Neither agree or disagree 43 16.1
Agree 82 30.7
Strongly agree 106 39.7
Total 267 100
8
18
48
73
120
0 20 40 60 80 100 120 140
STRONGLY DISAGREE
DISAGREE
NEITHER AGREE OR DISAGREE
AGREE
STRONGLY AGREE
19
Fig. 4.1.10: Smart phones are used to check electronic mails.
A majority of the respondents strongly agree (39.7%) or agree (30.97%) with the fact that
they use smart phones for checking e-mails and only 13.4 % disagreed with the above fact.
Table 4.1.11: Smart phones for using search engine.
Frequency Percentage
Strongly disagree 9 3.4
Disagree 18 6.7
Neither agree or disagree 41 15.4
Agree 75 28.1
Strongly agree 124 46.4
Total 267 100
6
30
43
82
106
0
20
40
60
80
100
120
Strongly disagree Disagree Neither agree or
disagree
Agree Strongly Agree
20
Fig. 4.1.11: Smart phones for using search engine.
From the Table 4.1.11 and Fig. 4.1.11 it is evident that majority of the respondents (74.5%)
either agree or strongly agree that they use smart phones for accessing search engines such as
Google and Bing.
Table 4.1.12: Smart phones to get college announcements and information.
Frequency Percentage
Strongly disagree 10 3.7
Disagree 36 13.5
Neither agree or disagree 43 16.1
Agree 71 26.6
Strongly Agree 107 40.1
Total 267 100
9
18
41
75
124
0 20 40 60 80 100 120 140
STRONGLY DISAGREE
DISAGREE
NEITHER AGREE OR DISAGREE
AGREE
STRONGLY AGREE
21
Fig. 4.1.12: Smart phones to get college announcements and information.
From the Table 4.1.12 and Fig. 4.1.12 it is evident that majority of the respondents (66.7%)
either agree or strongly agree that they use smart phones for accessing college announcement
and information.
Table 4.1.13: Smart phones to check news and weather conditions.
Frequency Percentage
Strongly disagree 12 4.5
Disagree 37 13.9
Neither agree or disagree 70 26.2
Agree 60 22.5
Strongly Agree 87 32.6
Total 267 100
10
36
43
71
107
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
22
Fig. 4.1.13: Smart phones to check news and weather conditions.
From the Table 4.1.13 and Fig. 4.1.13 it is evident that majority of the respondents (55.1%)
either agree or strongly agree that they use smart phones to check news and weather
conditions.
Table 4.1.14: Smart phones to get sports updates.
Frequency Percentage
Strongly disagree 21 7.9
Disagree 38 14.2
Neither agree or disagree 52 19.5
Agree 72 27.0
Strongly Agree 84 31.5
Total 267 100
12
37
70
60
87
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
23
Fig. 4.1.14: Smart phones to get sports updates.
From the Table 4.1.14 and Fig. 4.1.14 it is evident that majority of the respondents (58.5%)
either agree or strongly agree that they use smart phones to get sports updates.
Table 4.1.15: Smart phones to listen to music.
Frequency Percentage
Strongly disagree 4 1.5
Disagree 9 3.4
Neither agree or disagree 43 16.1
Agree 62 23.2
Strongly Agree 149 55.8
Total 267 100
21
38
52
72
84
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
24
Fig. 4.1.15: Smart phones to listen to music.
From the Table 4.1.15 and Fig. 4.1.15 it is evident that majority of the respondents (79%)
either agree or strongly agree that they use smart phones to listen to music.
Table 4.1.16: Smart phones to watch video and games.
Frequency Percentage
Strongly disagree 6 1.9
Disagree 17 6.4
Neither agree or disagree 30 11.2
Agree 68 25.5
Strongly Agree 147 55.1
Total 267 100
4 9
43
62
149
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
25
Fig. 4.1.16: Smart phones to watch video and games.
From the Table 4.1.16 and Fig. 4.1.16 it is evident that majority of the respondents (80.6%)
either agree or strongly agree that they use smart phones to watch video and games.
Table 4.1.17: Smart phones for taking photos.
Frequency Percentage
Strongly disagree 11 3.8
Disagree 23 8.6
Neither agree or disagree 39 14.7
Agree 72 27.1
Strongly Agree 122 45.9
Total 267 100
6
17
30
68
147
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
26
Fig. 4.1.17: Smart phones for taking photos.
From the Table 4.1.17 and Fig. 4.1.17 it is evident that majority of the respondents (73%)
either agree or strongly agree that they use smart phones for taking photos.
Table 4.1.18: Smart phones to book movie tickets.
Frequency Percentage
Strongly disagree 28 10.5
Disagree 29 10.9
Neither agree or disagree 49 18.4
Agree 66 24.7
Strongly Agree 95 35.6
Total 267 100
11
23
39
72
122
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
27
Fig. 4.1.18: Smart phones to book movie tickets.
From the Table 4.1.18 and Fig. 4.1.18 it is evident that majority of the respondents (60.3%)
either agree or strongly agree that they use smart phones to book movie tickets.
Table 4.1.19: Smart phones to do online shopping.
Frequency Percentage
Strongly disagree 13 4.9
Disagree 22 8.2
Neither agree or disagree 53 19.9
Agree 84 31.5
Strongly Agree 95 35.6
Total 267 100
28 29
49
66
95
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
28
Fig. 4.1.19: Smart phones to do online shopping.
From the Table 4.1.19 and Fig. 4.1.19 it is evident that majority of the respondents (67.1%)
either agree or strongly agree that they use smart phones to do online shopping.
Table 4.1.20: Smart phones used as calculator.
Frequency Percentage
Strongly disagree 18 6.7
Disagree 33 12.4
Neither agree or disagree 77 28.8
Agree 59 22.1
Strongly agree 80 30.0
Total 267 100
13
22
53
84
95
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
29
Fig. 4.1.20: Smart phones used as calculator.
From the Table 4.1.20 and Fig. 4.1.20 it is evident that majority of the respondents (52.1%)
either agree or strongly agree that they use smart phones as calculator.
Table 4.1.21: Smart phones to take down notes.
Frequency Percentage
Strongly disagree 21 7.9
Disagree 33 12.4
Neither agree or disagree 77 28.8
Agree 68 25.5
Strongly Agree 68 25.5
Total 267 100
18
33
77
59
80
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
30
Fig. 4.1.21: Smart phones to take down notes.
From the Table 4.1.21 and Fig. 4.1.21 it is evident that majority of the respondents (51%)
either agree or strongly agree that they use smart phones to take down notes.
Table 4.1.22: Smart phones to read documents in PDF and Word.
Frequency Percentage
Strongly disagree 8 3
Disagree 15 5.6
Neither agree or disagree 41 15.4
Agree 80 30
Strongly Agree 123 46.1
Total 267 100
21
33
77
68
68
STRONGLY DISAGREE
DISAGREE
NEITHER AGREE OR DISAGREE
AGREE
STRONGLY AGREE
31
Fig. 4.1.22: Smart phones to read documents in PDF and Word.
From the Table 4.1.22 and Fig. 4.1.22 it is evident that majority of the respondents (76.1 %)
either agree or strongly agree that they use smart phones to read documents in PDF and
Word.
Table 4.1.23: Smart phones to Search Online on Urgent Topics about Subjects.
Frequency Percentage
Strongly disagree 8 3.0
Disagree 13 4.9
Neither agree or disagree 35 13.1
Agree 82 30.7
Strongly Agree 129 48.3
Total 267 100
8
15
41
80
123
0 20 40 60 80 100 120 140
STRONGLY DISAGREE
DISAGREE
NEITHER AGREE OR DISAGREE
AGREE
STRONGLY AGREE
32
Fig. 4.1.23: Smart phones to Search Online on Urgent Topics about Subjects.
From the Table 4.1.23 and Fig. 4.1.23 it is evident that majority of the respondents (79%)
either agree or strongly agree that they use smart phones to search online for urgent topics
about Subjects.
8 13
35
82
129
STRONGLY
DISAGREE
DISAGREE NEITHER AGREE
OR DISAGREE
AGREE STRONGLY AGREE
33
4.2 Hypothesis Testing
The four hypotheses developed in the earlier stages were put to test with the help of a chi-
square analysis. For this purpose, we have used SPSS for analysis. To complete the analysis,
the four hypotheses were put to test with the different attributes i.e. usage for different tasks
and their outputs are presented in the tables below:
Table 4.2.1: Null Hypothesis Test for the usage of smartphones to Gender.
S. No. Usage Chi-Square
value
df Table
Value
Null
Hypothesis
1. Social Networking 16.559 8 15.51 Rejected
2. Text Messages 6.534 8 15.51 Accepted
3. Calls 3.324 8 15.51 Accepted
4. e-mails 18.164 8 15.51 Rejected
5. Internet Surfing 1.881 8 15.51 Accepted
6. College Announcement 6.113 8 15.51 Accepted
7. News & Weather Update 6.113 8 15.51 Accepted
8. Sports Update 6.113 8 15.51 Accepted
9. Music 3.468 8 15.51 Accepted
10. Pictures 3.468 8 15.51 Accepted
11. Videos/Gaming 5.279 8 15.51 Accepted
12. Booking Movie Ticket 15.728 8 15.51 Rejected
13. Online Shopping 34.026 8 15.51 Rejected
14. Calculation 4.171 8 15.51 Accepted
15. Taking Notes 5.353 8 15.51 Accepted
16. Reading Documents 41.505 8 15.51 Rejected
17. e-Learning 4.677 8 15.51 Accepted
*Significance Level=95% (α=0.05)
34
Table 4.2.2: Null Hypothesis Test for the usage of smartphones to Age.
S. No. Usage Chi-Square
value
df Table
Value
Null
Hypothesis
1. Social Networking 31.2 16 26.3 Rejected
2. Text Messages 14.27 16 26.3 Accepted
3. Calls 30.82 16 26.3 Rejected
4. e-mails 27.063 16 26.3 Rejected
5. Internet Surfing 12.472 16 26.3 Accepted
6. College Announcement 14.63 16 26.3 Accepted
7. News & Weather Update 30.085 16 26.3 Rejected
8. Sports Update 25.26 16 26.3 Accepted
9. Music 30.479 16 26.3 Rejected
10. Picture 21.492 16 26.3 Accepted
11. Videos/Gaming 9.797 16 26.3 Accepted
12. Booking Movie Ticket 50.129 16 26.3 Rejected
13. Online Shopping 33.817 16 26.3 Rejected
14. Calculation 22.054 16 26.3 Accepted
15. Taking Notes 20.14 16 26.3 Accepted
16. Reading Documents 14.747 16 26.3 Accepted
17. e-Learning 16.992 16 26.3 Accepted
*Significance Level=95% (α=0.05)
35
Table 4.2.3: Null Hypothesis Test for the usage of smartphones to Educational Qualification.
S. No. Usage Chi-Square
value
df Table
Value
Null
Hypothesis
1. Social Networking 13.969 16 26.3 Accepted
2. Text Messages 18.935 16 26.3 Accepted
3. Calls 22.729 16 26.3 Accepted
4. e-mails 31.016 16 26.3 Rejected
5. Internet Surfing 20.947 16 26.3 Accepted
6. College Announcement 37.468 16 26.3 Rejected
7. News & Weather Update 13.711 16 26.3 Accepted
8. Sports Update 7.523 16 26.3 Accepted
9. Music 11.417 16 26.3 Accepted
10. Picture 12.667 16 26.3 Accepted
11. Videos/Gaming 20.241 16 26.3 Accepted
12. Booking Movie Ticket 15.069 16 26.3 Accepted
13. Online Shopping 15.017 16 26.3 Accepted
14. Calculation 16.324 16 26.3 Accepted
15. Taking Notes 11.815 16 26.3 Accepted
16. Reading Documents 11.773 16 26.3 Accepted
17. e-Learning 27.736 16 26.3 Rejected
*Significance Level=95% (α=0.05)
36
Table 4.2.4: Null Hypothesis Test for the usage of smartphones to Monthly Income of Parents.
S. No. Usage Chi-Square
value
df Table
Value
Null
Hypothesis
1. Social Networking 27.93 16 26.3 Rejected
2. Text Messages 16.221 16 26.3 Accepted
3. Calls 24.101 16 26.3 Accepted
4. e-mails 21.566 16 26.3 Accepted
5. Internet Surfing 12.371 16 26.3 Accepted
6. College Announcement 26.276 16 26.3 Accepted
7. News & Weather Update 16.768 16 26.3 Accepted
8. Sports Update 17.792 16 26.3 Accepted
9. Music 15.194 16 26.3 Accepted
10. Pictures 3.468 16 26.3 Accepted
11. Videos/Gaming 11.522 16 26.3 Accepted
12. Booking Movie Ticket 18.887 16 26.3 Accepted
13. Online Shopping 27.62 16 26.3 Rejected
14. Calculation 13.66 16 26.3 Accepted
15. Taking Notes 23.374 16 26.3 Accepted
16. Reading Documents 16.083 16 26.3 Rejected
17. e-Learning 28.601 16 26.3 Accepted
*Significance Level=95% (α=0.05)
4.3 Findings
Questions 1 to 4 are related to socializing aspect of usage of smart phones by college
students.
Questions 5 to 8 are related to information aspect of usage of smart phones by college
students.
37
Questions 9 to 13 are related to entertainment aspect of usage of smart phones by college
students.
Questions14 to 17 are related to aid to learning aspect of usage of smart phones by college
students
Table 4.2.1: Gender
The relationship between the usage of smartphones and gender is evident from the fact that
social networking, emails, booking movie tickets, online shopping, reading documents have a
significant relationship with the gender of college students.
Table 4.2.2: Age
The relationship between the usage of smartphones and age is evident from the data that
social networking, calls, emails, news and weather update, music, booking movie tickets,
online shopping have a significant relationship with the age of college students.
Table 4.2.3: Educational Qualification
The relationship between the usage of smartphones and educational qualification is evident
from the data that emails, college announcement and e-learning have a significant
relationship with the educational qualification of college students.
Table 4.2.4: Monthly Income of Parents
The relationship between the usage of smartphones and monthly income of parents is evident
from the data that social networking, online shopping and e-learning have a significant
relationship with the monthly income of parents of college students.
38
Chapter-5
CONCLUSION
The results of this project are based on the analysis of data collected from a sample of 267
students across the country. Students participated in the survey are from various educational
background having different age groups.
The main objective of this research was to understand the usage of smartphones among
college students the analysis of the data showed that gender, age, educational qualification
and monthly income of parents of students have significant relationship with the usage of
smartphones for some of the attributes.
 Social networking, emails, booking movie tickets, online shopping, reading
documents are the attributes which have a significant relationship with the gender of
college students.
 Social networking, Calls, emails, News and weather update, music, booking movie
tickets, online shopping are the attributes which have a significant relationship with
the age of college students.
 E-mails, college announcement and e-learning are the attributes which have a
significant relationship with the educational qualification of college students.
 Social networking, online shopping and e-learning are the attributes which have a
significant relationship with the monthly income of parents of college students.
39
REFERENCES
 Anastasios A. Economides, Nick Nikolaou (2005). Evaluation of hand held devices
for mobile learning. International Journal of Engineering Education. Retrieved from
http://www.conta.uom.gr/
 Karlson AK, Bederson BB, Contreras-Vidal JL. (2006). Understanding single-handed
mobile device interaction. HCIL Tech Report, Human-Computer Interaction Lab,
University of Maryland, College Park.
 Saraswathi S., 2017, “Smartphone usage among students,” IERJ, 3 (6), pp. 195
 Kibona L.and Mgaya G., “Smartphones’ Effects on Academic Performance of Higher
Learning Students”, 2015, JMEST 2(4), pp. 779.
 Jesse GR.., Smartphone and app usage among College Students: Using Smartphones
Effectively for Social and Educational Needs, ISCAP, 2015.
40
APPENDIX A
Distribution of Chi-Square
DF 0.99 0.975 0.95 0.90 0.10 0.05 0.025 0.01
1 __ 0.001 0.004 0.016 2.706 3.841 5.024 6.635
2 0.020 0.051 0.103 0.211 4.605 5.991 7.378 9.210
3 0.115 0.216 0.352 0.584 6.251 7.815 9.348 11.345
4 0.297 0.484 0.711 1.064 7.779 9.488 11.143 13.277
5 0.554 0.831 1.145 1.610 9.236 11.041 12.833 15.086
6 0.872 1.237 1.635 2.204 10.645 12.592 14.449 16.812
7 1.239 1.690 2.167 2.833 12.017 14.067 16.013 18.475
8 1.646 2.180 2.733 3.490 13.362 15.507 17.535 20.090
9 2.088 2.700 3.325 4.168 14.684 16.919 19.023 21.666
10 2.558 3.247 3.940 4.865 15.987 18.307 20.483 23.209
11 3.053 3.816 4.575 5.578 17.275 19.675 21.920 24.725
12 3.571 4.404 5.226 6.304 18.549 21.026 23.337 26.217
13 4.107 5.009 5.892 7.042 19.812 22.362 24.736 27.688
14 4.660 5.629 6.571 7.790 21.064 23.685 26.119 29.141
15 5.229 6.262 7.261 8.547 22.307 24.996 27.48 30.578
16 5.812 6.908 7.962 9.312 23.542 26.296 28.845 32.000
17 6.408 7.564 8.672 10.085 24.769 27.587 30.191 33.409
18 7.015 8.231 9.390 10.865 25.989 28.869 31.526 34.805
19 7.633 8.907 10.117 11.651 27.204 30.144 32.852 36.191
20 8.260 9.591 10.851 12.443 28.412 31.410 34.170 37.566
21 8.897 10.283 11.591 13.240 29.615 32.671 35.479 38.932
22 9.542 10.982 12.338 14.042 30.813 33.924 36.781 40.289
23 10.196 11.689 13.091 14.848 32.007 35.172 38.076 41.638
24 10.856 12.401 1.848 15.659 33.196 36.415 39.364 42.980
25 11.524 13.120 14.611 16.473 34.382 37.652 40.646 44.314
26 12.198 13.844 15.379 17.292 35.563 38.885 41.923 45.642
27 12.879 14.573 16.151 18.114 36.741 40.113 43.194 46.963
28 13.565 15.308 16.928 18.939 37.916 41.337 44.461 48.278
29 14.257 16.047 17.708 19.768 39.087 42.557 45.722 49.588
30 14.954 16.791 18.493 20.599 40.256 43.77 46.979 50.892
41
APPENDIX B
Questionnaire
Good day! This brief survey requires about 5 minutes for completion. Through this, we are
trying to determine the usage of smartphones by college students. Your response will only be
used for survey purposes and is strictly confidential and unanimous.
Thank you very much for your time and suggestions.
PART - A
1. Gender * (Mark only one oval.)
Male Female Others
2. Age * (Mark only one oval.)
Under 20 21 -25 years
26 -30 years above 30 years
3. Marital Status (Mark only one oval.)
Unmarried Married Other
42
4. Education
Secondary School Master Degree
Bachelor’s Degree Other
5. Monthly Income of Parents: (In rupees)
Less than 20,000 20,001 -40,000
40,001 -60,000 Above 60,001
6. College/ University
Pre-university University
Autonomous Other
7. Monthly Income of Parents: (In rupees)
Less than 20,000 20,001 – 40,000
40,001-60,000 Above 60,000
8. Do you use Smart Mobile Phone?
Yes No
43
PART –B
1. I use smart phone for networking sites such as Whatsapp, Facebook, Twitter and
Instagram.
2. I use smart phones for sending text.
3. Smart phone is used to make calls and conversation.
4. Smart phones are used to check electronic mails.
5. Check information in Google, Bing and yahoo with smart phone.
6. To get college announcement and information I use smart phones.
44
7. To check news and weather conditions I use smart phones.
8. I use smart phone to get sports updates.
9. I use smart phone to listen to music.
10. I use smart phone for taking pictures.
11. I use smart phones to watch videos and games.
12. I book movie tickets with the help of smart phones.
45
13. I do online shopping with smart phone.
14. Smart phones are best favored to use as calculator.
15. I use smart phones to take down note.
16. With the help of smart phones I read documents in PDF and words.
17. I use smart phones to search online on urgent topics about subject.

More Related Content

What's hot

Pictorial Data Presentation
Pictorial Data PresentationPictorial Data Presentation
Pictorial Data PresentationAmita Bhardwaj
 
Positive & negative effects of mobile phones on kids
Positive & negative effects of mobile phones on kidsPositive & negative effects of mobile phones on kids
Positive & negative effects of mobile phones on kidsVivien Vivien
 
Sampling Design
Sampling DesignSampling Design
Sampling DesignJale Nonan
 
Contents of research report
Contents of research reportContents of research report
Contents of research reportAbhinav Kp
 
Physical and psycological impact of child labour on children
Physical and psycological impact of child labour on childrenPhysical and psycological impact of child labour on children
Physical and psycological impact of child labour on childrenTanjin Tamanna urmi
 
Boys are more intelligent than girls
Boys are more intelligent than girlsBoys are more intelligent than girls
Boys are more intelligent than girlsJawad Nasar Shah
 
Impact of Smartphones on Society
Impact of Smartphones on SocietyImpact of Smartphones on Society
Impact of Smartphones on Societypuru_bhattarai
 
Method of data collection
Method of data collectionMethod of data collection
Method of data collectionBalaji P
 
Research Design, Process of research with examples
Research Design, Process of research with examplesResearch Design, Process of research with examples
Research Design, Process of research with examplesDr. Anita Rathod
 
Research design
Research designResearch design
Research designBalaji P
 
Data, Classifications and Sources.
Data, Classifications and Sources.Data, Classifications and Sources.
Data, Classifications and Sources.RajaKrishnan M
 
Questionnaire as a tool for data collection
Questionnaire as a tool for data collectionQuestionnaire as a tool for data collection
Questionnaire as a tool for data collectionNeha Deo
 
Statistics collection of data
Statistics collection of dataStatistics collection of data
Statistics collection of dataShourav Mahmud
 
Limitations of social research
Limitations of social researchLimitations of social research
Limitations of social researchRajaKrishnan M
 

What's hot (20)

Research design
Research designResearch design
Research design
 
Questionnaire design
Questionnaire designQuestionnaire design
Questionnaire design
 
Pictorial Data Presentation
Pictorial Data PresentationPictorial Data Presentation
Pictorial Data Presentation
 
Positive & negative effects of mobile phones on kids
Positive & negative effects of mobile phones on kidsPositive & negative effects of mobile phones on kids
Positive & negative effects of mobile phones on kids
 
Sampling Design
Sampling DesignSampling Design
Sampling Design
 
Contents of research report
Contents of research reportContents of research report
Contents of research report
 
Physical and psycological impact of child labour on children
Physical and psycological impact of child labour on childrenPhysical and psycological impact of child labour on children
Physical and psycological impact of child labour on children
 
MEASUREMENT AND SAMPLING TECHNIQUES
MEASUREMENT AND SAMPLING TECHNIQUESMEASUREMENT AND SAMPLING TECHNIQUES
MEASUREMENT AND SAMPLING TECHNIQUES
 
Boys are more intelligent than girls
Boys are more intelligent than girlsBoys are more intelligent than girls
Boys are more intelligent than girls
 
Impact of Smartphones on Society
Impact of Smartphones on SocietyImpact of Smartphones on Society
Impact of Smartphones on Society
 
Method of data collection
Method of data collectionMethod of data collection
Method of data collection
 
Research Design, Process of research with examples
Research Design, Process of research with examplesResearch Design, Process of research with examples
Research Design, Process of research with examples
 
Research design
Research designResearch design
Research design
 
Consent form for participants
Consent form for participantsConsent form for participants
Consent form for participants
 
Data, Classifications and Sources.
Data, Classifications and Sources.Data, Classifications and Sources.
Data, Classifications and Sources.
 
Questionnaire as a tool for data collection
Questionnaire as a tool for data collectionQuestionnaire as a tool for data collection
Questionnaire as a tool for data collection
 
Statistics collection of data
Statistics collection of dataStatistics collection of data
Statistics collection of data
 
Limitations of social research
Limitations of social researchLimitations of social research
Limitations of social research
 
Ch04 sampling
Ch04 samplingCh04 sampling
Ch04 sampling
 
Survey
SurveySurvey
Survey
 

Similar to A study on Usage of Smartphone by College Students

Useofmobilephone 170103205620
Useofmobilephone 170103205620Useofmobilephone 170103205620
Useofmobilephone 170103205620Nirali Nayi
 
Use of electronic mobile devices in teaching and learning in higher education...
Use of electronic mobile devices in teaching and learning in higher education...Use of electronic mobile devices in teaching and learning in higher education...
Use of electronic mobile devices in teaching and learning in higher education...African Virtual University
 
Caribbean studies IA Dejon Harris
Caribbean studies IA Dejon HarrisCaribbean studies IA Dejon Harris
Caribbean studies IA Dejon HarrisDejon Harris
 
Study on How College Students Update their knowledge on Current Affairs
Study on How College Students Update their knowledge on Current AffairsStudy on How College Students Update their knowledge on Current Affairs
Study on How College Students Update their knowledge on Current AffairsMuhammed Anaz PK
 
Sjskkskskskkss
SjskkskskskkssSjskkskskskkss
SjskkskskskkssVerizeyh
 
Impact of smartphone review on negative effect on students
Impact of smartphone review on negative effect on studentsImpact of smartphone review on negative effect on students
Impact of smartphone review on negative effect on studentsBIDDY RATHI
 
160316_Asif.pptx
160316_Asif.pptx160316_Asif.pptx
160316_Asif.pptxRiadHasan25
 
IRJET- Social Media Effect on Youth
IRJET-  	  Social Media Effect on YouthIRJET-  	  Social Media Effect on Youth
IRJET- Social Media Effect on YouthIRJET Journal
 
Perceived Effects of Facebook on Academic Activities of Agricultural Students...
Perceived Effects of Facebook on Academic Activities of Agricultural Students...Perceived Effects of Facebook on Academic Activities of Agricultural Students...
Perceived Effects of Facebook on Academic Activities of Agricultural Students...IOSR Journals
 
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...African Virtual University
 
Comparative study of social media (networking) usage by undergraduates in two...
Comparative study of social media (networking) usage by undergraduates in two...Comparative study of social media (networking) usage by undergraduates in two...
Comparative study of social media (networking) usage by undergraduates in two...Alexander Decker
 
Is Social Media Use Bad for Students’ Academic Performance?
Is Social Media Use Bad for Students’ Academic Performance?Is Social Media Use Bad for Students’ Academic Performance?
Is Social Media Use Bad for Students’ Academic Performance?daffygraveyard868
 
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19IRJET Journal
 
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...limedy534
 
Study on Effects of Social Networks Usage on PG Students
Study on Effects of Social Networks Usage on PG StudentsStudy on Effects of Social Networks Usage on PG Students
Study on Effects of Social Networks Usage on PG Studentsijtsrd
 
Covid-19 and Mauritian University Education
Covid-19 and Mauritian University Education Covid-19 and Mauritian University Education
Covid-19 and Mauritian University Education MuhammadSaadWaheed1
 
customer satisfaction towards whatsapp bba project
customer satisfaction towards whatsapp bba projectcustomer satisfaction towards whatsapp bba project
customer satisfaction towards whatsapp bba projectsjsuriya
 
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptx
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptxFINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptx
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptxjekkdelubio
 

Similar to A study on Usage of Smartphone by College Students (20)

Useofmobilephone 170103205620
Useofmobilephone 170103205620Useofmobilephone 170103205620
Useofmobilephone 170103205620
 
Use of electronic mobile devices in teaching and learning in higher education...
Use of electronic mobile devices in teaching and learning in higher education...Use of electronic mobile devices in teaching and learning in higher education...
Use of electronic mobile devices in teaching and learning in higher education...
 
Caribbean studies IA Dejon Harris
Caribbean studies IA Dejon HarrisCaribbean studies IA Dejon Harris
Caribbean studies IA Dejon Harris
 
Study on How College Students Update their knowledge on Current Affairs
Study on How College Students Update their knowledge on Current AffairsStudy on How College Students Update their knowledge on Current Affairs
Study on How College Students Update their knowledge on Current Affairs
 
Sjskkskskskkss
SjskkskskskkssSjskkskskskkss
Sjskkskskskkss
 
Impact of smartphone review on negative effect on students
Impact of smartphone review on negative effect on studentsImpact of smartphone review on negative effect on students
Impact of smartphone review on negative effect on students
 
160316_Asif.pptx
160316_Asif.pptx160316_Asif.pptx
160316_Asif.pptx
 
IRJET- Social Media Effect on Youth
IRJET-  	  Social Media Effect on YouthIRJET-  	  Social Media Effect on Youth
IRJET- Social Media Effect on Youth
 
Perceived Effects of Facebook on Academic Activities of Agricultural Students...
Perceived Effects of Facebook on Academic Activities of Agricultural Students...Perceived Effects of Facebook on Academic Activities of Agricultural Students...
Perceived Effects of Facebook on Academic Activities of Agricultural Students...
 
C0121216
C0121216C0121216
C0121216
 
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...
EXPLORING THE PERCEPTIONS AND USAGE OF SOCIAL NETWORKING SITES AMONG DISTANCE...
 
Comparative study of social media (networking) usage by undergraduates in two...
Comparative study of social media (networking) usage by undergraduates in two...Comparative study of social media (networking) usage by undergraduates in two...
Comparative study of social media (networking) usage by undergraduates in two...
 
Is Social Media Use Bad for Students’ Academic Performance?
Is Social Media Use Bad for Students’ Academic Performance?Is Social Media Use Bad for Students’ Academic Performance?
Is Social Media Use Bad for Students’ Academic Performance?
 
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19
AN INVESTIGATION ON THE CHANGES OF SOCIAL MEDIA USE CAUSED BY COVID-19
 
53ca0-404-413.21389.pdf
53ca0-404-413.21389.pdf53ca0-404-413.21389.pdf
53ca0-404-413.21389.pdf
 
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...
Effects of Smartphone Addiction on the Academic Performances of Grades 9 to 1...
 
Study on Effects of Social Networks Usage on PG Students
Study on Effects of Social Networks Usage on PG StudentsStudy on Effects of Social Networks Usage on PG Students
Study on Effects of Social Networks Usage on PG Students
 
Covid-19 and Mauritian University Education
Covid-19 and Mauritian University Education Covid-19 and Mauritian University Education
Covid-19 and Mauritian University Education
 
customer satisfaction towards whatsapp bba project
customer satisfaction towards whatsapp bba projectcustomer satisfaction towards whatsapp bba project
customer satisfaction towards whatsapp bba project
 
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptx
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptxFINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptx
FINAL RESEARCH - JEYA&LEZIEL [Autosaved].pptx
 

More from Siddharth Bhatnagar

Summer Internship Project Report at Arokee Bangalore
Summer Internship Project Report at Arokee BangaloreSummer Internship Project Report at Arokee Bangalore
Summer Internship Project Report at Arokee BangaloreSiddharth Bhatnagar
 
Summer Internship Project at Arokee Bangalore.
Summer Internship Project at Arokee Bangalore.Summer Internship Project at Arokee Bangalore.
Summer Internship Project at Arokee Bangalore.Siddharth Bhatnagar
 
A Report on Online Community Management.
A Report on Online Community Management. A Report on Online Community Management.
A Report on Online Community Management. Siddharth Bhatnagar
 
Strategies of Attitude Change for a Pizza Restaurant.
Strategies of Attitude Change for a Pizza Restaurant.Strategies of Attitude Change for a Pizza Restaurant.
Strategies of Attitude Change for a Pizza Restaurant.Siddharth Bhatnagar
 
CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.Siddharth Bhatnagar
 
Report on Impact of Brand Image on Customer Loyalty.
Report on Impact of Brand Image on Customer Loyalty.Report on Impact of Brand Image on Customer Loyalty.
Report on Impact of Brand Image on Customer Loyalty.Siddharth Bhatnagar
 
Presentation on Impact of Brand Image on Customer Loyalty.
Presentation on Impact of Brand Image on Customer Loyalty.Presentation on Impact of Brand Image on Customer Loyalty.
Presentation on Impact of Brand Image on Customer Loyalty.Siddharth Bhatnagar
 
ABC Tri component model of Attitude.
ABC Tri component model of Attitude.ABC Tri component model of Attitude.
ABC Tri component model of Attitude.Siddharth Bhatnagar
 
Advertisement: Closure Perception
Advertisement: Closure PerceptionAdvertisement: Closure Perception
Advertisement: Closure PerceptionSiddharth Bhatnagar
 
Customer Loyalty Programs: AMEX & Starbucks.
Customer Loyalty Programs: AMEX & Starbucks.Customer Loyalty Programs: AMEX & Starbucks.
Customer Loyalty Programs: AMEX & Starbucks.Siddharth Bhatnagar
 
Consumer Materialism: Perception & Reality.
Consumer Materialism: Perception & Reality.Consumer Materialism: Perception & Reality.
Consumer Materialism: Perception & Reality.Siddharth Bhatnagar
 
Seminar Report on Online Branding
Seminar Report on Online BrandingSeminar Report on Online Branding
Seminar Report on Online BrandingSiddharth Bhatnagar
 
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.Siddharth Bhatnagar
 

More from Siddharth Bhatnagar (20)

Summer Internship Project Report at Arokee Bangalore
Summer Internship Project Report at Arokee BangaloreSummer Internship Project Report at Arokee Bangalore
Summer Internship Project Report at Arokee Bangalore
 
Summer Internship Project at Arokee Bangalore.
Summer Internship Project at Arokee Bangalore.Summer Internship Project at Arokee Bangalore.
Summer Internship Project at Arokee Bangalore.
 
A Report on Online Community Management.
A Report on Online Community Management. A Report on Online Community Management.
A Report on Online Community Management.
 
Online Community Management.
Online Community Management.Online Community Management.
Online Community Management.
 
Strategies of Attitude Change for a Pizza Restaurant.
Strategies of Attitude Change for a Pizza Restaurant.Strategies of Attitude Change for a Pizza Restaurant.
Strategies of Attitude Change for a Pizza Restaurant.
 
Strategies of attitude change.
Strategies of attitude change.Strategies of attitude change.
Strategies of attitude change.
 
CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.
 
Report on Impact of Brand Image on Customer Loyalty.
Report on Impact of Brand Image on Customer Loyalty.Report on Impact of Brand Image on Customer Loyalty.
Report on Impact of Brand Image on Customer Loyalty.
 
Presentation on Impact of Brand Image on Customer Loyalty.
Presentation on Impact of Brand Image on Customer Loyalty.Presentation on Impact of Brand Image on Customer Loyalty.
Presentation on Impact of Brand Image on Customer Loyalty.
 
Health Club Logo.
Health Club Logo.Health Club Logo.
Health Club Logo.
 
ABC Tri component model of Attitude.
ABC Tri component model of Attitude.ABC Tri component model of Attitude.
ABC Tri component model of Attitude.
 
The Long Tail
The Long TailThe Long Tail
The Long Tail
 
Advertisement: Closure Perception
Advertisement: Closure PerceptionAdvertisement: Closure Perception
Advertisement: Closure Perception
 
Brand Personality: Colors
Brand Personality: ColorsBrand Personality: Colors
Brand Personality: Colors
 
Customer Loyalty Programs: AMEX & Starbucks.
Customer Loyalty Programs: AMEX & Starbucks.Customer Loyalty Programs: AMEX & Starbucks.
Customer Loyalty Programs: AMEX & Starbucks.
 
Consumer Materialism: Perception & Reality.
Consumer Materialism: Perception & Reality.Consumer Materialism: Perception & Reality.
Consumer Materialism: Perception & Reality.
 
Types of Advertisements
Types of AdvertisementsTypes of Advertisements
Types of Advertisements
 
Presentation on Online Branding
Presentation on Online BrandingPresentation on Online Branding
Presentation on Online Branding
 
Seminar Report on Online Branding
Seminar Report on Online BrandingSeminar Report on Online Branding
Seminar Report on Online Branding
 
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.
Financial Analysis of Indian Fast Moving Consumer Goods (FMCG) Industry.
 

Recently uploaded

Exploratory Data Analysis - Dilip S.pptx
Exploratory Data Analysis - Dilip S.pptxExploratory Data Analysis - Dilip S.pptx
Exploratory Data Analysis - Dilip S.pptxDilipVasan
 
Pre-ProductionImproveddsfjgndflghtgg.pptx
Pre-ProductionImproveddsfjgndflghtgg.pptxPre-ProductionImproveddsfjgndflghtgg.pptx
Pre-ProductionImproveddsfjgndflghtgg.pptxStephen266013
 
Artificial_General_Intelligence__storm_gen_article.pdf
Artificial_General_Intelligence__storm_gen_article.pdfArtificial_General_Intelligence__storm_gen_article.pdf
Artificial_General_Intelligence__storm_gen_article.pdfscitechtalktv
 
Business update Q1 2024 Lar España Real Estate SOCIMI
Business update Q1 2024 Lar España Real Estate SOCIMIBusiness update Q1 2024 Lar España Real Estate SOCIMI
Business update Q1 2024 Lar España Real Estate SOCIMIAlejandraGmez176757
 
2024 Q1 Tableau User Group Leader Quarterly Call
2024 Q1 Tableau User Group Leader Quarterly Call2024 Q1 Tableau User Group Leader Quarterly Call
2024 Q1 Tableau User Group Leader Quarterly Calllward7
 
basics of data science with application areas.pdf
basics of data science with application areas.pdfbasics of data science with application areas.pdf
basics of data science with application areas.pdfvyankatesh1
 
How I opened a fake bank account and didn't go to prison
How I opened a fake bank account and didn't go to prisonHow I opened a fake bank account and didn't go to prison
How I opened a fake bank account and didn't go to prisonPayment Village
 
一比一原版纽卡斯尔大学毕业证成绩单如何办理
一比一原版纽卡斯尔大学毕业证成绩单如何办理一比一原版纽卡斯尔大学毕业证成绩单如何办理
一比一原版纽卡斯尔大学毕业证成绩单如何办理cyebo
 
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsWebinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsCEPTES Software Inc
 
一比一原版西悉尼大学毕业证成绩单如何办理
一比一原版西悉尼大学毕业证成绩单如何办理一比一原版西悉尼大学毕业证成绩单如何办理
一比一原版西悉尼大学毕业证成绩单如何办理pyhepag
 
Fuzzy Sets decision making under information of uncertainty
Fuzzy Sets decision making under information of uncertaintyFuzzy Sets decision making under information of uncertainty
Fuzzy Sets decision making under information of uncertaintyRafigAliyev2
 
Tabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsTabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsalex933524
 
一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理cyebo
 
Jpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJames Polillo
 
Supply chain analytics to combat the effects of Ukraine-Russia-conflict
Supply chain analytics to combat the effects of Ukraine-Russia-conflictSupply chain analytics to combat the effects of Ukraine-Russia-conflict
Supply chain analytics to combat the effects of Ukraine-Russia-conflictJack Cole
 
how can i exchange pi coins for others currency like Bitcoin
how can i exchange pi coins for others currency like Bitcoinhow can i exchange pi coins for others currency like Bitcoin
how can i exchange pi coins for others currency like BitcoinDOT TECH
 
一比一原版阿德莱德大学毕业证成绩单如何办理
一比一原版阿德莱德大学毕业证成绩单如何办理一比一原版阿德莱德大学毕业证成绩单如何办理
一比一原版阿德莱德大学毕业证成绩单如何办理pyhepag
 
How can I successfully sell my pi coins in Philippines?
How can I successfully sell my pi coins in Philippines?How can I successfully sell my pi coins in Philippines?
How can I successfully sell my pi coins in Philippines?DOT TECH
 

Recently uploaded (20)

Exploratory Data Analysis - Dilip S.pptx
Exploratory Data Analysis - Dilip S.pptxExploratory Data Analysis - Dilip S.pptx
Exploratory Data Analysis - Dilip S.pptx
 
Pre-ProductionImproveddsfjgndflghtgg.pptx
Pre-ProductionImproveddsfjgndflghtgg.pptxPre-ProductionImproveddsfjgndflghtgg.pptx
Pre-ProductionImproveddsfjgndflghtgg.pptx
 
Artificial_General_Intelligence__storm_gen_article.pdf
Artificial_General_Intelligence__storm_gen_article.pdfArtificial_General_Intelligence__storm_gen_article.pdf
Artificial_General_Intelligence__storm_gen_article.pdf
 
Business update Q1 2024 Lar España Real Estate SOCIMI
Business update Q1 2024 Lar España Real Estate SOCIMIBusiness update Q1 2024 Lar España Real Estate SOCIMI
Business update Q1 2024 Lar España Real Estate SOCIMI
 
2024 Q1 Tableau User Group Leader Quarterly Call
2024 Q1 Tableau User Group Leader Quarterly Call2024 Q1 Tableau User Group Leader Quarterly Call
2024 Q1 Tableau User Group Leader Quarterly Call
 
Abortion pills in Dammam Saudi Arabia// +966572737505 // buy cytotec
Abortion pills in Dammam Saudi Arabia// +966572737505 // buy cytotecAbortion pills in Dammam Saudi Arabia// +966572737505 // buy cytotec
Abortion pills in Dammam Saudi Arabia// +966572737505 // buy cytotec
 
basics of data science with application areas.pdf
basics of data science with application areas.pdfbasics of data science with application areas.pdf
basics of data science with application areas.pdf
 
How I opened a fake bank account and didn't go to prison
How I opened a fake bank account and didn't go to prisonHow I opened a fake bank account and didn't go to prison
How I opened a fake bank account and didn't go to prison
 
一比一原版纽卡斯尔大学毕业证成绩单如何办理
一比一原版纽卡斯尔大学毕业证成绩单如何办理一比一原版纽卡斯尔大学毕业证成绩单如何办理
一比一原版纽卡斯尔大学毕业证成绩单如何办理
 
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsWebinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
 
Machine Learning for Accident Severity Prediction
Machine Learning for Accident Severity PredictionMachine Learning for Accident Severity Prediction
Machine Learning for Accident Severity Prediction
 
一比一原版西悉尼大学毕业证成绩单如何办理
一比一原版西悉尼大学毕业证成绩单如何办理一比一原版西悉尼大学毕业证成绩单如何办理
一比一原版西悉尼大学毕业证成绩单如何办理
 
Fuzzy Sets decision making under information of uncertainty
Fuzzy Sets decision making under information of uncertaintyFuzzy Sets decision making under information of uncertainty
Fuzzy Sets decision making under information of uncertainty
 
Tabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsTabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflows
 
一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理
 
Jpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization Sample
 
Supply chain analytics to combat the effects of Ukraine-Russia-conflict
Supply chain analytics to combat the effects of Ukraine-Russia-conflictSupply chain analytics to combat the effects of Ukraine-Russia-conflict
Supply chain analytics to combat the effects of Ukraine-Russia-conflict
 
how can i exchange pi coins for others currency like Bitcoin
how can i exchange pi coins for others currency like Bitcoinhow can i exchange pi coins for others currency like Bitcoin
how can i exchange pi coins for others currency like Bitcoin
 
一比一原版阿德莱德大学毕业证成绩单如何办理
一比一原版阿德莱德大学毕业证成绩单如何办理一比一原版阿德莱德大学毕业证成绩单如何办理
一比一原版阿德莱德大学毕业证成绩单如何办理
 
How can I successfully sell my pi coins in Philippines?
How can I successfully sell my pi coins in Philippines?How can I successfully sell my pi coins in Philippines?
How can I successfully sell my pi coins in Philippines?
 

A study on Usage of Smartphone by College Students

  • 1. USAGE OF SMART MOBILE PHONES BY COLLEGE STUDENTS by Siddharth Bhatnagar
  • 2. i ACKNOWLEDGMENT I am highly indebted to Prof. A.H. Sequeira for his guidance and for giving me the opportunity to work on this captivating project ‘Usage of Smartphones by college students.’ His constant supervision and help played a key role in the successful completion of this project. I would also like to express my sincere gratitude to all participants of the survey for their support and guidance during the conduct of this exercise. I would like to express my special gratitude and thanks to my team members: Vijay, Veena, Swarnava, Suraj, Vargob and Piyush for providing valuable and timely inputs in developing the project. My thanks and appreciations also go to my colleagues and people who have willingly helped me out with their abilities. Siddharth Bhatnagar
  • 3. ii ABSTRACT Smartphones are an inventions that keep individuals connected to society, especially college students. This report discusses the relationships between Smartphone usage and the effects Smartphone have on college student’s social lives, education lives, and physical activity. In this research the major usages of smartphones for socializing, information collection, entertainment and as an aid to learning are analyzed in synchronization with the different demographic factors such as gender, age, educational qualifications and monthly income of parents. The objective of the research is that to check whether there is a significant relationship between the different demographic factors and the usages or not.
  • 4. iii CONTENTS Particulars Page No. Acknowledgement i Abstract ii List of Tables & Figures iv Chapter-1: Introduction 1 1.1 Research Question 1 1.2 Investigative Questions 1 1.3 Research Objective 2 1.4 Hypothesis 2 1.5 Limitations 3 Chapter-2: Literature Review 4 Chapter-3: Research Methodology 6 3.1 Method 6 3.1.1 Data 6 3.1.2 Reasoning 6 3.1.3 Research Tools 7 3.2 Sampling Design 7 3.3 Sample Size Calculations 7 3.3 Questionnaire Design 8 Chapter-4: Data Analysis & Interpretation 9 4.1 Demographic Presentation 9 4.2 Hypothesis Testing 33 4.3 Findings 36 Chapter-5: Conclusion 38 References 39 Appendix A 40 Appendix B 41
  • 5. iv LIST OF TABLES & FIGURES Table/Figure Number and Name Page Number Table 2.1: Important findings of Literature Review 5 Table 4.1.1: Gender 9 Table 4.1.2: Student Age Group 10 Table 4.1.3: Marital Status 11 Table 4.1.4: Education 12 Table 4.1.5: Income 13 Table 4.1.6: College/University 14 Table 4.1.7: Smart Phone for Social Media. 15 Table 4.1.8: Smart Phone for text message. 16 Table 4.1.9: Smart Phones for Calls and Conversations. 17 Table 4.1.10: Smart phones are used to check electronic mails. 18 Table 4.1.11: Smart phones for using search engine. 19 Table 4.1.12: Smart phones to get college announcements and 20 information. Table 4.1.13: Smart phones to check news and weather conditions. 21 Table 4.1.14: Smart phones to get sports updates. 22 Table 4.1.15: Smart phones to listen to music. 23 Table 4.1.16: Smart phones to watch video and games. 24 Table 4.1.17: Smart phones for taking photos. 25 Table 4.1.18: Smart phones to book movie tickets. 26 Table 4.1.19: Smart phones to do online shopping. 27 Table 4.1.20: Smart phones used as calculator. 28 Table 4.1.21: Smart phones to take down notes. 29 Table 4.1.22: Smart phones to read documents in PDF and Word. 30
  • 6. v Table 4.1.23: Smart phones to Search Online on Urgent Topics 31 about Subjects. Table 4.2.1: Null Hypothesis Test for the usage of smartphones to Gender. 33 Table 4.2.2: Null Hypothesis Test for the usage of smartphones to Age. 34 Table 4.2.3: Null Hypothesis Test for the usage of smartphones to 35 Educational Qualification. Table 4.2.4: Null Hypothesis Test for the usage of smartphones to 36 Monthly Income of Parents. Fig. 4.1.1: Gender 10 Fig. 4.1.2: Student Age Group 11 Fig. 4.1.3: Marital Status 12 Fig. 4.1.4: Education 13 Fig. 4.1.5: Income 14 Fig. 4.1.6: College/University 15 Fig. 4.1.7: Smart Phone for Social Media. 16 Fig. 4.1.8: Smart Phone for text message. 17 Fig. 4.1.9: Smart Phones for Calls and Conversations. 18 Fig. 4.1.10: Smart phones are used to check electronic mails. 19 Fig. 4.1.11: Smart phones for using search engine. 20 Fig. 4.1.12: Smart phones to get college announcements and 21 information. Fig. 4.1.13: Smart phones to check news and weather conditions. 22 Fig. 4.1.14: Smart phones to get sports updates. 23 Fig. 4.1.15: Smart phones to listen to music. 24 Fig. 4.1.16: Smart phones to watch video and games. 25 Fig. 4.1.17: Smart phones for taking photos. 26
  • 7. vi Fig. 4.1.18: Smart phones to book movie tickets. 27 Fig. 4.1.19: Smart phones to do online shopping. 28 Fig. 4.1.20: Smart phones used as calculator. 29 Fig. 4.1.21: Smart phones to take down notes. 30 Fig. 4.1.22: Smart phones to read documents in PDF and Word. 31 Fig. 4.1.23: Smart phones to Search Online on Urgent Topics 32 about Subjects.
  • 8. 1 Chapter-1 INTRODUCTION Smartphones, one of the recent inventions are already the most popular product used by i- Generation. Its sophisticated features make it very versatile product as the user can click pictures, surf the internet and can get connected to the world around. Studies suggest that university students are the major contributions to the smartphones sales ad 99.8% of the college students have a cellphone and 68% students use smartphones for educational purposes. With thousands of apps, online courses and videos, it is the major contributor to the e-learning concept. Smartphones are an integral part of college life and culture as they are used, both overtly and covertly, in every possible campus setting, including the classroom, the device is capable of contributing to student learning and improved academic performance. Smartphones provide students with immediate, portable access to many of the same education-enhancing capabilities as an Internet-connected computer, such as online information retrieval, file sharing, and interacting with professors and fellow students. Cell phone apps have added new features to entice the mobile users as well, like location tagging and status updates. 1.1 Research Question How the students use smartphone in colleges? 1.2 Investigative Questions 1. What is the relationship between gender and usage of smartphones? 2. How age is related with usage of smartphones? 3. What is the relationship between Educational Qualifications and the usage of smartphones?
  • 9. 2 4. How monthly income is related with usage of smartphones? 1.3 Research Objectives 1. To study the usage of smart phones by college students. 2. To determine the relationship between gender and usage of smartphones. 3. To understand the relationship between age and usage of smartphones. 4. To analyze the relationship between education qualification and usage of smartphones. 5. To examine the relationship between monthly income and usage of smart phones. 1.4 Hypothesis HO1: There is no significant relationship between Gender and the usage of smartphones. HA1: There is significant relationships between Gender and the usage of smartphones. HO2: There is no significant relationship between Age and the usage of smartphones. HA2: There is significant relationships between Age and the usage of smartphones. HO3: There is no significant relationship between Educational Qualifications and the usage of smartphones. HA3: There is significant relationships between Educational Qualifications and the usage of smartphones. HO4: There is no significant relationship between Monthly Income and the usage of smartphones. HA4: There is significant relationships between Monthly Income and the usage of smartphones.
  • 10. 3 1.5 Limitations 1. Some recent technologies such as the m-banking and other digitally advanced payment options are not considered. 2. The timeframe to carry out the research was very less therefore the population engagement for survey is small in count.
  • 11. 4 Chapter-2 LITERATURE REVIEW The aim of the research was to study about the usage of smartphones by the college students throughout the country. This research utilized a more holistic measure of cell phone use than previous studies. The measure accounts for the cell phone’s expanded capabilities in the realm of social networking, gaming, and Internet use. Presently, cell phone use is a dominant and defining characteristic of this generation of college students and often occurs during class time, while completing homework, and while studying, In this study, we developed four hypotheses to examine the relationship between formed variables and actual usage of smartphones by the college students. Dr. Mohammad Jafar Esmaeili states that students find that using the smartphone is useful and could benefit them in process of learning, they are more willing to utilize it in the classroom. Laird found that 55% of the college students use smartphones for gaming purposes while Jesse found that atleast 80% of the students have used smartphones once in a running class. According to S. Saraswathi. 68% of students uses smartphone for academic purposes or to take pictures of class notes or for social networking.
  • 12. 5 Table 2.1: Important findings of Literature Review S.No. Author/Publication Title Year Findings 1. Dr. Gayle,R. Jesse Smartphone and App Usage Among College Students. 2015 University students are the major contributors to smartphones sales. 2. S Saraswathi Smartphone usage among students 2017 68% of the students use 3. Andrew lepp, Jacob E Barkley The Relationship Between Cell Phone Use and Academic Performance. 2015 Smartphone have a negative impact on student during lectures. 4. Dr. Mohammad Jafar Esmaeili Perceptions of Students toward Utilizing Smartphone 2011 Using smartphone has an impact on students’ career.
  • 13. 6 Chapter-3 RESEARCH METHODOLOGY 3.1 Method To determine the Usage of Smart Mobile Phones by College Students, mixed approach was used which included both exploratory and inductive reasoning in order to accumulate background information on the given topic to filter the research questions. The identification of the information which is to be used along the sample to derive the response and their analysis, investigative questions were formulated. 3.1.1 Data Primary Data: Survey data gathered from questionnaire is used as the primary source of data. Secondary Data: The various scholarly journals & research articles were used as the secondary source of data. 3.1.2 Reasoning We employed inductive and exploratory reasoning because it satisfies the exploratory nature of our research.
  • 14. 7 3.1.3 Research Tools A study is conducted on the sample population using a self-framed questionnaire which is forwarded to the respondents through the web-link. The steps used to conduct the survey include:  Defining the objective of the survey  Determining the sampling group  Preparing the questionnaire  Registering the responses  Data analysis 3.2 Sampling Design Sampling is selecting some elements in a population and drawing conclusion about the entire population. Population is the total collection of elements about which we wish to make some references. Convenience sampling is used in the study of the population as it is a non- probability sampling technique where respondents are selected as per the accessibility and proximity. The population involved is very large in number it’s clear that individual interaction in impossible to carry out. Convenience sampling being very fast, inexpensive is the most relevant choice for sampling design. 3.3 Sample Size Calculation The Population (Number of professional college students in India) is N = 2,000,000 Confidence Interval (e) = 6% Sample proportion (p) = 0.5 q = 1 – p = 0.5 Confidence Level = 95% Z-Score = 1.96 Formula to calculate Sample Size: For larger or infinite population;
  • 15. 8 S = (Z2* p * q) / e2 And Sample Size (n) = S / [1 + (S - 1)/N] Therefore, Sample size (n) = 266.67 ~ 267 3.4 Questionnaire Design The questionnaire has been thoughtfully designed keeping the research objectives in mind. It consists of 24 questions in total; out of which 7 are demographic and the remaining 17 are intended to capture data at all the levels (Nominal, Ordinal, Interval & Ratio). We have kept the questionnaire as concise as possible to get the maximum reliable responses. The questionnaire consists of the following kinds of questions:  Simple Category scale  Multiple Choice, Single Response scale  Likert Scale  Open Ended Question
  • 16. 9 Chapter-4 DATA ANALYSIS & INTERPRETATION This chapter consists of the analysis and interpretation of 267 responses collected on an unbiased basis from students of different parts of the country. Analysis was done with the help of Google Forms and then generating useful graphs in Microsoft excel. Hypothesis testing was done by chi-square method using the SPSS software and various graphs were obtained from MS Excel and Google sheets. 4.1 Demographic Presentation Table 4.1.1: Gender Frequency Percentage Female 103 38.6 Male 164 61.4 Total 267 100
  • 17. 10 Fig. 4.1.1: Gender The total samples collected from students are 267, out of which 38.6% are female and 61.4% are male students. This is given in Table 4.1.1 Table 4.1.2: Student Age Group Frequency Percentage Under 20 33 12.4 21-25 181 67.8 26-30 46 17.2 Above 31 7 2.6 Total 267 100 38.6% 61.4% Female Male
  • 18. 11 Fig. 4.1.2: Student Age Group As seen in Fig. 4.1.2 & Table 4.1.2, 65.6% of the students are in the age group 21-25, 17.9% in 26-30 age group, 14% in the age group under 20 and 2.6% in the age group above 31. From this we can conclude that most of the respondents are in the age group of 21-25. Table 4.1.3: Marital Status Frequency Percentage Married 50 18.7 Single 217 81.3 Total 267 100 67.8% 17.2% 2.6% 12.4% 21-25 26-30 Above 31 under20
  • 19. 12 Fig. 4.1.3: Marital Status Of all the respondents, when it comes to their Marital Status 82% (217 respondents) are unmarried and 18% (50 respondents) are married. This is given in Fig. 4.1.3 and Table 4.1.3 Table 4.1.4: Education Frequency Percentage Secondary School 12 4.5 Bachelor Degree 168 62.9 Master Degree 76 28.5 Others 11 4.1 Total 267 100 18.7% 81.3% Married Single
  • 20. 13 Fig. 4.1.4: Education As seen in Fig. 4.1.4 and Table 4.1.4, 62.9 % of the respondents were enrolled in Bachelor’s Degree, 28.5 % in Master’s Degree, and 4.1 % in other programs such as PhD. From this it clear that most of the respondents are perusing Bachelor’s degree. Table 4.1.5: Income Frequency Percentage Less than 20,000 71 26.6 20,001-40,000 72 27.0 40,001-60,000 63 23.6 Above 60,001 61 22.8 Total 267 100 62.9% 28.5% 4.1% 4.5% Bachelor’s Degree Master Degree Others Secondary School
  • 21. 14 Fig. 4.1.5: Income When it comes to the monthly income of the respondent’s parents, 26.6 % comes in the category Less than 20,000, 27 % comes in the range of 20,001-40,000: 23.6 % in 40,001- 60,000 and 22.8 % are having an income of 60,001 or more. Table 4.1.6: College/University Frequency Percentage Autonomous 54 20.2 Pre-university 18 6.7 University 178 66.7 Other 17 6.4 Total 267 100 27% 23.6%22.8% 26.6% 20,001 -40,000 40,001 -60,000 Above 60,001 Less than 20,000
  • 22. 15 Fig. 4.1.6: College/University From the Table 4.1.6 and Fig.4.1.6 it is evident that majority of the respondents are perusing their courses in University (66.7%) followed by Autonomous (20.2%). Following the trail is those who are in Pre-university (6.7%) and others (6.4%). Table 4.1.7: Smart Phone for Social Media. Frequency Percentage Strongly disagree 13 4.9 Disagree 18 6.7 Neither Agree nor Disagree 61 22.8 Agree 64 24.0 Strongly agree 111 41.6 Total 267 100 20.2% 6.7% 66.7% 6.4% Autonomous Pre-university University Other
  • 23. 16 Fig. 4.1.7: Smart Phone for Social Media. From the Table 4.1.7 and Fig. 4.1.7 it clear that a majority of the respondents (41.6%) said that they Strongly Agree with the fact that the use Smart phones for social media and only 4.1% of the respondents agreed the other way around. Table 4.1.8: Smart Phone for text message. Frequency Percentage Strongly disagree 36 13.5 Disagree 45 16.9 Neither agree or disagree 44 16.4 Agree 71 26.6 Strongly agree 71 26.6 Total 267 100 13 18 61 64 111 0 20 40 60 80 100 120 Strongly disagree Disagree Neither Agree or Disagree Agree Strongly agree
  • 24. 17 Fig. 4.1.8: Smart Phone for Text Message. From the Table 4.1.8 and Fig. 4.1.8 we can see that more than 50% of the respondents are agree or strongly agree with the fact that they use smart mobile phones for texting. Only 30.1% of the whole respondents is going for strongly disagree or disagree. As a result we can conclude that most of the respondents are using Smart phones for text messaging. Table 4.1.9: Smart Phones for Calls and Conversations. Frequency Percentage Strongly disagree 8 3.0 Disagree 18 6.7 Neither agree or disagree 48 18.0 Agree 73 27.3 Strongly agree 120 45.0 Total 267 100 36 45 44 71 71 0 10 20 30 40 50 60 70 80 Strongly disagree disagree Neither agree or disagree agree Strongly agree
  • 25. 18 Fig. 4.1.9: Smart Phones for Calls and Conversations. In a question related to usage of smart phones for calls and conversations, most respondents (45%) felt that they strongly agree with the fact that they use smart phones for calling and conversation purpose. Table 4.1.10: Smart phones are used to check electronic mails. Frequency Percentage Strongly disagree 6 2.2 Disagree 30 11.2 Neither agree or disagree 43 16.1 Agree 82 30.7 Strongly agree 106 39.7 Total 267 100 8 18 48 73 120 0 20 40 60 80 100 120 140 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 26. 19 Fig. 4.1.10: Smart phones are used to check electronic mails. A majority of the respondents strongly agree (39.7%) or agree (30.97%) with the fact that they use smart phones for checking e-mails and only 13.4 % disagreed with the above fact. Table 4.1.11: Smart phones for using search engine. Frequency Percentage Strongly disagree 9 3.4 Disagree 18 6.7 Neither agree or disagree 41 15.4 Agree 75 28.1 Strongly agree 124 46.4 Total 267 100 6 30 43 82 106 0 20 40 60 80 100 120 Strongly disagree Disagree Neither agree or disagree Agree Strongly Agree
  • 27. 20 Fig. 4.1.11: Smart phones for using search engine. From the Table 4.1.11 and Fig. 4.1.11 it is evident that majority of the respondents (74.5%) either agree or strongly agree that they use smart phones for accessing search engines such as Google and Bing. Table 4.1.12: Smart phones to get college announcements and information. Frequency Percentage Strongly disagree 10 3.7 Disagree 36 13.5 Neither agree or disagree 43 16.1 Agree 71 26.6 Strongly Agree 107 40.1 Total 267 100 9 18 41 75 124 0 20 40 60 80 100 120 140 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 28. 21 Fig. 4.1.12: Smart phones to get college announcements and information. From the Table 4.1.12 and Fig. 4.1.12 it is evident that majority of the respondents (66.7%) either agree or strongly agree that they use smart phones for accessing college announcement and information. Table 4.1.13: Smart phones to check news and weather conditions. Frequency Percentage Strongly disagree 12 4.5 Disagree 37 13.9 Neither agree or disagree 70 26.2 Agree 60 22.5 Strongly Agree 87 32.6 Total 267 100 10 36 43 71 107 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 29. 22 Fig. 4.1.13: Smart phones to check news and weather conditions. From the Table 4.1.13 and Fig. 4.1.13 it is evident that majority of the respondents (55.1%) either agree or strongly agree that they use smart phones to check news and weather conditions. Table 4.1.14: Smart phones to get sports updates. Frequency Percentage Strongly disagree 21 7.9 Disagree 38 14.2 Neither agree or disagree 52 19.5 Agree 72 27.0 Strongly Agree 84 31.5 Total 267 100 12 37 70 60 87 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 30. 23 Fig. 4.1.14: Smart phones to get sports updates. From the Table 4.1.14 and Fig. 4.1.14 it is evident that majority of the respondents (58.5%) either agree or strongly agree that they use smart phones to get sports updates. Table 4.1.15: Smart phones to listen to music. Frequency Percentage Strongly disagree 4 1.5 Disagree 9 3.4 Neither agree or disagree 43 16.1 Agree 62 23.2 Strongly Agree 149 55.8 Total 267 100 21 38 52 72 84 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 31. 24 Fig. 4.1.15: Smart phones to listen to music. From the Table 4.1.15 and Fig. 4.1.15 it is evident that majority of the respondents (79%) either agree or strongly agree that they use smart phones to listen to music. Table 4.1.16: Smart phones to watch video and games. Frequency Percentage Strongly disagree 6 1.9 Disagree 17 6.4 Neither agree or disagree 30 11.2 Agree 68 25.5 Strongly Agree 147 55.1 Total 267 100 4 9 43 62 149 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 32. 25 Fig. 4.1.16: Smart phones to watch video and games. From the Table 4.1.16 and Fig. 4.1.16 it is evident that majority of the respondents (80.6%) either agree or strongly agree that they use smart phones to watch video and games. Table 4.1.17: Smart phones for taking photos. Frequency Percentage Strongly disagree 11 3.8 Disagree 23 8.6 Neither agree or disagree 39 14.7 Agree 72 27.1 Strongly Agree 122 45.9 Total 267 100 6 17 30 68 147 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 33. 26 Fig. 4.1.17: Smart phones for taking photos. From the Table 4.1.17 and Fig. 4.1.17 it is evident that majority of the respondents (73%) either agree or strongly agree that they use smart phones for taking photos. Table 4.1.18: Smart phones to book movie tickets. Frequency Percentage Strongly disagree 28 10.5 Disagree 29 10.9 Neither agree or disagree 49 18.4 Agree 66 24.7 Strongly Agree 95 35.6 Total 267 100 11 23 39 72 122 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 34. 27 Fig. 4.1.18: Smart phones to book movie tickets. From the Table 4.1.18 and Fig. 4.1.18 it is evident that majority of the respondents (60.3%) either agree or strongly agree that they use smart phones to book movie tickets. Table 4.1.19: Smart phones to do online shopping. Frequency Percentage Strongly disagree 13 4.9 Disagree 22 8.2 Neither agree or disagree 53 19.9 Agree 84 31.5 Strongly Agree 95 35.6 Total 267 100 28 29 49 66 95 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 35. 28 Fig. 4.1.19: Smart phones to do online shopping. From the Table 4.1.19 and Fig. 4.1.19 it is evident that majority of the respondents (67.1%) either agree or strongly agree that they use smart phones to do online shopping. Table 4.1.20: Smart phones used as calculator. Frequency Percentage Strongly disagree 18 6.7 Disagree 33 12.4 Neither agree or disagree 77 28.8 Agree 59 22.1 Strongly agree 80 30.0 Total 267 100 13 22 53 84 95 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 36. 29 Fig. 4.1.20: Smart phones used as calculator. From the Table 4.1.20 and Fig. 4.1.20 it is evident that majority of the respondents (52.1%) either agree or strongly agree that they use smart phones as calculator. Table 4.1.21: Smart phones to take down notes. Frequency Percentage Strongly disagree 21 7.9 Disagree 33 12.4 Neither agree or disagree 77 28.8 Agree 68 25.5 Strongly Agree 68 25.5 Total 267 100 18 33 77 59 80 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 37. 30 Fig. 4.1.21: Smart phones to take down notes. From the Table 4.1.21 and Fig. 4.1.21 it is evident that majority of the respondents (51%) either agree or strongly agree that they use smart phones to take down notes. Table 4.1.22: Smart phones to read documents in PDF and Word. Frequency Percentage Strongly disagree 8 3 Disagree 15 5.6 Neither agree or disagree 41 15.4 Agree 80 30 Strongly Agree 123 46.1 Total 267 100 21 33 77 68 68 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 38. 31 Fig. 4.1.22: Smart phones to read documents in PDF and Word. From the Table 4.1.22 and Fig. 4.1.22 it is evident that majority of the respondents (76.1 %) either agree or strongly agree that they use smart phones to read documents in PDF and Word. Table 4.1.23: Smart phones to Search Online on Urgent Topics about Subjects. Frequency Percentage Strongly disagree 8 3.0 Disagree 13 4.9 Neither agree or disagree 35 13.1 Agree 82 30.7 Strongly Agree 129 48.3 Total 267 100 8 15 41 80 123 0 20 40 60 80 100 120 140 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 39. 32 Fig. 4.1.23: Smart phones to Search Online on Urgent Topics about Subjects. From the Table 4.1.23 and Fig. 4.1.23 it is evident that majority of the respondents (79%) either agree or strongly agree that they use smart phones to search online for urgent topics about Subjects. 8 13 35 82 129 STRONGLY DISAGREE DISAGREE NEITHER AGREE OR DISAGREE AGREE STRONGLY AGREE
  • 40. 33 4.2 Hypothesis Testing The four hypotheses developed in the earlier stages were put to test with the help of a chi- square analysis. For this purpose, we have used SPSS for analysis. To complete the analysis, the four hypotheses were put to test with the different attributes i.e. usage for different tasks and their outputs are presented in the tables below: Table 4.2.1: Null Hypothesis Test for the usage of smartphones to Gender. S. No. Usage Chi-Square value df Table Value Null Hypothesis 1. Social Networking 16.559 8 15.51 Rejected 2. Text Messages 6.534 8 15.51 Accepted 3. Calls 3.324 8 15.51 Accepted 4. e-mails 18.164 8 15.51 Rejected 5. Internet Surfing 1.881 8 15.51 Accepted 6. College Announcement 6.113 8 15.51 Accepted 7. News & Weather Update 6.113 8 15.51 Accepted 8. Sports Update 6.113 8 15.51 Accepted 9. Music 3.468 8 15.51 Accepted 10. Pictures 3.468 8 15.51 Accepted 11. Videos/Gaming 5.279 8 15.51 Accepted 12. Booking Movie Ticket 15.728 8 15.51 Rejected 13. Online Shopping 34.026 8 15.51 Rejected 14. Calculation 4.171 8 15.51 Accepted 15. Taking Notes 5.353 8 15.51 Accepted 16. Reading Documents 41.505 8 15.51 Rejected 17. e-Learning 4.677 8 15.51 Accepted *Significance Level=95% (α=0.05)
  • 41. 34 Table 4.2.2: Null Hypothesis Test for the usage of smartphones to Age. S. No. Usage Chi-Square value df Table Value Null Hypothesis 1. Social Networking 31.2 16 26.3 Rejected 2. Text Messages 14.27 16 26.3 Accepted 3. Calls 30.82 16 26.3 Rejected 4. e-mails 27.063 16 26.3 Rejected 5. Internet Surfing 12.472 16 26.3 Accepted 6. College Announcement 14.63 16 26.3 Accepted 7. News & Weather Update 30.085 16 26.3 Rejected 8. Sports Update 25.26 16 26.3 Accepted 9. Music 30.479 16 26.3 Rejected 10. Picture 21.492 16 26.3 Accepted 11. Videos/Gaming 9.797 16 26.3 Accepted 12. Booking Movie Ticket 50.129 16 26.3 Rejected 13. Online Shopping 33.817 16 26.3 Rejected 14. Calculation 22.054 16 26.3 Accepted 15. Taking Notes 20.14 16 26.3 Accepted 16. Reading Documents 14.747 16 26.3 Accepted 17. e-Learning 16.992 16 26.3 Accepted *Significance Level=95% (α=0.05)
  • 42. 35 Table 4.2.3: Null Hypothesis Test for the usage of smartphones to Educational Qualification. S. No. Usage Chi-Square value df Table Value Null Hypothesis 1. Social Networking 13.969 16 26.3 Accepted 2. Text Messages 18.935 16 26.3 Accepted 3. Calls 22.729 16 26.3 Accepted 4. e-mails 31.016 16 26.3 Rejected 5. Internet Surfing 20.947 16 26.3 Accepted 6. College Announcement 37.468 16 26.3 Rejected 7. News & Weather Update 13.711 16 26.3 Accepted 8. Sports Update 7.523 16 26.3 Accepted 9. Music 11.417 16 26.3 Accepted 10. Picture 12.667 16 26.3 Accepted 11. Videos/Gaming 20.241 16 26.3 Accepted 12. Booking Movie Ticket 15.069 16 26.3 Accepted 13. Online Shopping 15.017 16 26.3 Accepted 14. Calculation 16.324 16 26.3 Accepted 15. Taking Notes 11.815 16 26.3 Accepted 16. Reading Documents 11.773 16 26.3 Accepted 17. e-Learning 27.736 16 26.3 Rejected *Significance Level=95% (α=0.05)
  • 43. 36 Table 4.2.4: Null Hypothesis Test for the usage of smartphones to Monthly Income of Parents. S. No. Usage Chi-Square value df Table Value Null Hypothesis 1. Social Networking 27.93 16 26.3 Rejected 2. Text Messages 16.221 16 26.3 Accepted 3. Calls 24.101 16 26.3 Accepted 4. e-mails 21.566 16 26.3 Accepted 5. Internet Surfing 12.371 16 26.3 Accepted 6. College Announcement 26.276 16 26.3 Accepted 7. News & Weather Update 16.768 16 26.3 Accepted 8. Sports Update 17.792 16 26.3 Accepted 9. Music 15.194 16 26.3 Accepted 10. Pictures 3.468 16 26.3 Accepted 11. Videos/Gaming 11.522 16 26.3 Accepted 12. Booking Movie Ticket 18.887 16 26.3 Accepted 13. Online Shopping 27.62 16 26.3 Rejected 14. Calculation 13.66 16 26.3 Accepted 15. Taking Notes 23.374 16 26.3 Accepted 16. Reading Documents 16.083 16 26.3 Rejected 17. e-Learning 28.601 16 26.3 Accepted *Significance Level=95% (α=0.05) 4.3 Findings Questions 1 to 4 are related to socializing aspect of usage of smart phones by college students. Questions 5 to 8 are related to information aspect of usage of smart phones by college students.
  • 44. 37 Questions 9 to 13 are related to entertainment aspect of usage of smart phones by college students. Questions14 to 17 are related to aid to learning aspect of usage of smart phones by college students Table 4.2.1: Gender The relationship between the usage of smartphones and gender is evident from the fact that social networking, emails, booking movie tickets, online shopping, reading documents have a significant relationship with the gender of college students. Table 4.2.2: Age The relationship between the usage of smartphones and age is evident from the data that social networking, calls, emails, news and weather update, music, booking movie tickets, online shopping have a significant relationship with the age of college students. Table 4.2.3: Educational Qualification The relationship between the usage of smartphones and educational qualification is evident from the data that emails, college announcement and e-learning have a significant relationship with the educational qualification of college students. Table 4.2.4: Monthly Income of Parents The relationship between the usage of smartphones and monthly income of parents is evident from the data that social networking, online shopping and e-learning have a significant relationship with the monthly income of parents of college students.
  • 45. 38 Chapter-5 CONCLUSION The results of this project are based on the analysis of data collected from a sample of 267 students across the country. Students participated in the survey are from various educational background having different age groups. The main objective of this research was to understand the usage of smartphones among college students the analysis of the data showed that gender, age, educational qualification and monthly income of parents of students have significant relationship with the usage of smartphones for some of the attributes.  Social networking, emails, booking movie tickets, online shopping, reading documents are the attributes which have a significant relationship with the gender of college students.  Social networking, Calls, emails, News and weather update, music, booking movie tickets, online shopping are the attributes which have a significant relationship with the age of college students.  E-mails, college announcement and e-learning are the attributes which have a significant relationship with the educational qualification of college students.  Social networking, online shopping and e-learning are the attributes which have a significant relationship with the monthly income of parents of college students.
  • 46. 39 REFERENCES  Anastasios A. Economides, Nick Nikolaou (2005). Evaluation of hand held devices for mobile learning. International Journal of Engineering Education. Retrieved from http://www.conta.uom.gr/  Karlson AK, Bederson BB, Contreras-Vidal JL. (2006). Understanding single-handed mobile device interaction. HCIL Tech Report, Human-Computer Interaction Lab, University of Maryland, College Park.  Saraswathi S., 2017, “Smartphone usage among students,” IERJ, 3 (6), pp. 195  Kibona L.and Mgaya G., “Smartphones’ Effects on Academic Performance of Higher Learning Students”, 2015, JMEST 2(4), pp. 779.  Jesse GR.., Smartphone and app usage among College Students: Using Smartphones Effectively for Social and Educational Needs, ISCAP, 2015.
  • 47. 40 APPENDIX A Distribution of Chi-Square DF 0.99 0.975 0.95 0.90 0.10 0.05 0.025 0.01 1 __ 0.001 0.004 0.016 2.706 3.841 5.024 6.635 2 0.020 0.051 0.103 0.211 4.605 5.991 7.378 9.210 3 0.115 0.216 0.352 0.584 6.251 7.815 9.348 11.345 4 0.297 0.484 0.711 1.064 7.779 9.488 11.143 13.277 5 0.554 0.831 1.145 1.610 9.236 11.041 12.833 15.086 6 0.872 1.237 1.635 2.204 10.645 12.592 14.449 16.812 7 1.239 1.690 2.167 2.833 12.017 14.067 16.013 18.475 8 1.646 2.180 2.733 3.490 13.362 15.507 17.535 20.090 9 2.088 2.700 3.325 4.168 14.684 16.919 19.023 21.666 10 2.558 3.247 3.940 4.865 15.987 18.307 20.483 23.209 11 3.053 3.816 4.575 5.578 17.275 19.675 21.920 24.725 12 3.571 4.404 5.226 6.304 18.549 21.026 23.337 26.217 13 4.107 5.009 5.892 7.042 19.812 22.362 24.736 27.688 14 4.660 5.629 6.571 7.790 21.064 23.685 26.119 29.141 15 5.229 6.262 7.261 8.547 22.307 24.996 27.48 30.578 16 5.812 6.908 7.962 9.312 23.542 26.296 28.845 32.000 17 6.408 7.564 8.672 10.085 24.769 27.587 30.191 33.409 18 7.015 8.231 9.390 10.865 25.989 28.869 31.526 34.805 19 7.633 8.907 10.117 11.651 27.204 30.144 32.852 36.191 20 8.260 9.591 10.851 12.443 28.412 31.410 34.170 37.566 21 8.897 10.283 11.591 13.240 29.615 32.671 35.479 38.932 22 9.542 10.982 12.338 14.042 30.813 33.924 36.781 40.289 23 10.196 11.689 13.091 14.848 32.007 35.172 38.076 41.638 24 10.856 12.401 1.848 15.659 33.196 36.415 39.364 42.980 25 11.524 13.120 14.611 16.473 34.382 37.652 40.646 44.314 26 12.198 13.844 15.379 17.292 35.563 38.885 41.923 45.642 27 12.879 14.573 16.151 18.114 36.741 40.113 43.194 46.963 28 13.565 15.308 16.928 18.939 37.916 41.337 44.461 48.278 29 14.257 16.047 17.708 19.768 39.087 42.557 45.722 49.588 30 14.954 16.791 18.493 20.599 40.256 43.77 46.979 50.892
  • 48. 41 APPENDIX B Questionnaire Good day! This brief survey requires about 5 minutes for completion. Through this, we are trying to determine the usage of smartphones by college students. Your response will only be used for survey purposes and is strictly confidential and unanimous. Thank you very much for your time and suggestions. PART - A 1. Gender * (Mark only one oval.) Male Female Others 2. Age * (Mark only one oval.) Under 20 21 -25 years 26 -30 years above 30 years 3. Marital Status (Mark only one oval.) Unmarried Married Other
  • 49. 42 4. Education Secondary School Master Degree Bachelor’s Degree Other 5. Monthly Income of Parents: (In rupees) Less than 20,000 20,001 -40,000 40,001 -60,000 Above 60,001 6. College/ University Pre-university University Autonomous Other 7. Monthly Income of Parents: (In rupees) Less than 20,000 20,001 – 40,000 40,001-60,000 Above 60,000 8. Do you use Smart Mobile Phone? Yes No
  • 50. 43 PART –B 1. I use smart phone for networking sites such as Whatsapp, Facebook, Twitter and Instagram. 2. I use smart phones for sending text. 3. Smart phone is used to make calls and conversation. 4. Smart phones are used to check electronic mails. 5. Check information in Google, Bing and yahoo with smart phone. 6. To get college announcement and information I use smart phones.
  • 51. 44 7. To check news and weather conditions I use smart phones. 8. I use smart phone to get sports updates. 9. I use smart phone to listen to music. 10. I use smart phone for taking pictures. 11. I use smart phones to watch videos and games. 12. I book movie tickets with the help of smart phones.
  • 52. 45 13. I do online shopping with smart phone. 14. Smart phones are best favored to use as calculator. 15. I use smart phones to take down note. 16. With the help of smart phones I read documents in PDF and words. 17. I use smart phones to search online on urgent topics about subject.