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Journal of Social Sciences & Humanities Research

JSSHR 22|Volume 1|Issue 2|2015

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Research Article

INFLUENCE OF SOCIAL NETWORKING ON THE STUDY HABITS

AND PERFORMANCE OF STUDENTS IN A STATE UNIVERSITY

Ariel R. Judilla1, Raymund B. Gemora

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1West Visayas State University – Janiuay Campus, Iloilo Philippines

Correspondence should be addressed to Ariel R. Judilla

Received October 31, 2015; Accepted November 10, 2015; Published December 04, 2015;

Copyright: © 2015 Ariel R. Judilla et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the

original work is properly cited.

Cite This Article: Judilla, A., Gemora, R.(2015). Influence of Social Networking on the Study Habits and Performance of Students in a State University. Journal of Social Sciences & Humanities Research, 1(2).1-12

ABSTRACT

This study aimed to ascertain the influence of social networking on the study habits and academic performance of tertiary

students of the West Visayas State University (WVSU) System. It likewise aimed to determine the significant differences

on the extent of influence of social networking on the study habits and academic performance of the students when they

were grouped as to age, sex, socio economic status and educational attainment of parents; as well as to ascertain the

significant relationships among the extent of influence of social networking and students’ study habits and their academic

performance. This study utilized the descriptive-correlational method in describing how social networking influenced the

study habits and academic performance of the students. Two hundred thirty five (235) graduating students taking Bachelor

of Science in Information Technology (BS InfoTech) at WVSU were utilized as respondents of the study.Researcher-made

and duly-validated instruments such as questionnaire checklists that described the influence of social networking and the

status of students’ study habits and the WVSU terminal competencies assessment to measure their academic performance

were used to gather data. Means and standard deviations were used to describe the influence of social networking on the

study habits and academic performance of the students. The t-test and ANOVA were used to assess the significant

differences on the influence of social networking on the respondents’ study habits and academic performance and Pearson’s-

r correlation was used to test the significant relationships among the extent of influence of social networking, students’

study habits and their academic performance. Results revealed a high extent of influence of social networking on the

respondents regardless of age, sex, socio economic status, and educational attainment of their parents. The status of the

students’ study habits was also high while their level of academic performance was basic. There were significant differences

in the level of academic performance of students when classified as to age, socio economic status and educational

attainment of parent while significant relationship existed between the extent of influence of social networking and the

status of the study habits of the respondents and between the respondents’ extent of influence of social networking and the

level of their academic performance.

KEYWORDS: Social Networking, Influence, Performance, Study Habits

INTRODUCTION

Internet technologies have, for the past few decades,

significantly altered the way individuals both in and out of

colleges work, play, and interact and even now, Internet

communication is emergent; as the speed of the Internet

increases, so too does the number of tools that utilize this

still-growing technology [1] .

Horrigan [2] noted that the Internet has become a primary

vehicle for many individuals’ day-to-day activities, with the

advent and historic growth of technologies such as

electronic mail (e-mail), instant messaging, online

newspapers, eBooks, research databases, Weblogs,

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eCommerce, and social networking sites and it is an

increasing rarity for an individual in the US to go even a

day without some sort of interaction using an Internet

technology.

Madden [3] explained that internet-based technology that

holds promise for screening in this important population is

social networking and more than 80% of adults aged 18 to

29 visit social networking sites such as Facebook. The

utilization of Facebook has been found to increase users’

sense of personal belonging among college students and

also, this sense of belonging has in and of itself been

positively correlated with academic performance [4].

Social Networking Site (SNS) covers all about engagement

creating relationships, communicating with one’s readers,

building his following and connecting with his online

audience. It has been observed as the practice of expanding

the number of one's business and/or social contacts by

making connections through individuals.

Livingstone [5] stated that affinity for self-presentation is

often a mark of adolescence, and SNS use has made it

possible for one’s own display of personality to reach a

larger audience than previous generations.

However, there are some overlap and integration with

social media and social networking. Social media experts

say that Facebook, Twitter and Pinterest are whole package

platforms -- and are considered both social media (tools)

and social networking (a way to engage). You Tube, on the

other hand, is a tool for video, so it's social media. Chatting

with other colleagues on LinkedIn? That's social

networking. Both work together for one’s overall social

media strategy.

Hughes [6] defines social media as a collection of Internet

websites, services, and practices that support collaboration,

community building, participation, and sharing, these

technologies have attracted the interest of higher education

faculty members looking for ways to engage and motivate

their students to be more active learners.

Similarly, there has been interest in integrating various

social media tools (such as blogs, microblogs, video-

sharing sites, and social networking) into the learning

process [7], especially by faculty members with a

disposition towards the use of newer technology in

education [8].

Junco, Merson and Salter [9] discusses the excessive use of

social media tools by college students has led to debate

over whether or not it has changed the very shape and

structure of students’ social behavior and academic

practices, and has thus caused leading educators to redefine

their understanding of interpersonal communication and

study dynamics.

According to Wang, Chen and Liang [10] students use

social media tools for many purposes such as access to

information, group discussion, resource sharing and

entertainment. On the contrary, Gross and Acquisti [11]

argue that users may be putting themselves at risk both

offline (e.g., stalking) and online (e.g., identify theft).

In this study, social networking and social media are used

interchangeably.

Social networking has only one goal. It is to encourage

new ways to communicate and share information.

Observations showed, however, that many students have

been blaming various social networking for it affects

adversely their study habits and the steady decrease in their

grade point averages. This emergent phenomenon has

aroused the researcher to look into social networking and

why it affects the study habits of students.

The System’s theory input-output model developed by

Ludwig Von Bertalanffy, according to Koontz and

Weihrich [12], postulates that an organized enterprise does

not exist in a vacuum; it is dependent on its environment in

which it is established. They add that the inputs from the

environment are received by the organization, which

then transforms them into outputs. As adapted in this

study, the students (Inputs) from different social

economic backgrounds and are from various school

backgrounds, and how the social networking affects the

output which is the study habits and can be seen through

their academic performance.

Study habits, are learning tendencies that enable students

to work privately. Azikiwe [13] describes that good study

habits are good asset to learners because they assist

students to attain mastery on areas of specialization for a

consequent academic performance.However, Devine [14]

asserted that researchers have not found any one study

strategy or skill that is best for all students in all learning

tasks. There are many useful strategies or skill, and the

ones that a particular individual uses will depend on the

individual and the learning situations.

According to Hay [15], the more time spent on social

networking sites, the less they may be good for students’

social lives, in the way that it may cause them to be more

illiterate; short forms, and even the limited amount of

characters one is allowed to type on certain statuses, don’t

help expand the writing portion of a student’s mind

resulting in lower grade averages and less time spent on

studies.However, the positive is also that an ‚interactive

world‛ full of ideas and insight and opinions can act as an

aid for school work in the sense that students have a wide

range of people’s information, knowledge, and experience

to learn from and to report on. In this study, study habits is

one of the variables upon which the researchers believed

may have been affected by social networking, either good

or bad.

Academic performance, on the other hand, is not a concept

that is new, many social scientists and researchers alike

have defined academic performance in various ways.

Tuckman [16] rightly put it that performance is the

apparent demonstration of understanding, concepts, ideas

and knowledge of a person and proposed that grades

clearly depict the performance of a student. Thus, their

academic performance must be managed efficiently

keeping in mind all the factors that can positively or

negatively affect their educational performance. Banquil

[17] states that a student is generally judged on

examination performance. Performance, therefore, is the

application of a learning product that at the end of the



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process provides mastery. It is the acquisition of particular

grades on examinations that indicates candidates’ ability,

mastery of the content, skills in applying learned

knowledge to particular situations. A student’s success is

generally judged on examination performance. Success on

examinations is a crucial indicator that a student has

benefited from a course of study [18].

According to Vaughn [19], student users are affected by

the internet and this impact is determined by the type of

internet usage. They are positively or negatively affected

by the informative use of internet while having drastic

impact of recreational use of internet on them. Also, Flad

[20] asserted that internet is advantageous to both students

and teachers if used as a tool of knowledge creation and

dissemination. As another variable for this study, the

researchers also believed that there may be impact of social

networking that can be put at forefront especially when

respondents were classified as to age, sex, socio-economic

status and educational attainment of parents.

Social networking evidently has a lot of positive effects,

but there are also some negative impacts. Interesting

relevant information on the impact of social networking or

social media on the study habits and academic performance

of tertiary students at the West Visayas State University

System would be put to fore. Credible evidences that

would solidify the support on controlling the activities of

social networking and reducing the risk of assimilating

such addicting activities and damaging impacts would also

be highlighted; hence, this study.

This study aimed to describe how social networking

influenced the study habits and academic performance of

the Bachelor of Science in Information Technology

graduating students of the West Visayas State University

System. Specifically, it also sought answers to: Extent of

utilization of social networking by the students as an entire

group and as to their age, sex, socio economic status, and

educational attainment of their parents; status of study

habits of the students as an entire group and as to their age,

sex, socio economic status, and educational attainment of

their parents; level of academic performance of the

students as an entire group and as to their age, sex, socio

economic status, and educational attainment of their

parents; if significant differences exist in the extent of

utilization of social networking of students as an entire

group and when classified as to age, sex, socio economic

status, and educational attainment of their parents; if

significant differences exist in the status of study habit of

the students as to their age, sex, socio economic status, and

educational attainment of their parents; if significant

differences exist in the level of academic performance of

the students as to their age, sex, socio economic status, and

educational attainment of their parents; if significant

relationship exists between the extent of influence of social

networking and the status of study habit of students; if

significant relationship exists between the extent of

influence of social networking and the level of academic

performance of students; and if significant relationship

exists between the status of study habit and the level of

academic performance of students.

MATERIALS AND METHODS

Conducted among the 235 (100%) graduating students

enrolled in the Bachelor of Science in Information

Technology (BS InfoTech) program of West Visayas State

University System for school year 2012 – 2013, this study

aimed to ascertain the extent of influence of social

networking on the respondents’ status of study habits and

level of academic performance.

This study utilized the descriptive-correlational type of

research. According to Gay [21], the descriptive method of

research involves collecting data to answer questions

concerning the current status of the subject under study.

Correlation studies, on the other hand, determine whether

or not two variables are correlated. This means to study

whether an increase or decrease in one variable

corresponds to an increase or decrease in the other

variable. This study involved collecting data to be used in

determining whether, and to what degree relationship

exists among the given variables.

The independent variables were the respondents’ age, sex,

socio economic status, and educational attainment of their

parents. The moderator variable was the influence of social

networking and the dependent variables were the status of

study habits and the level of academic performance of the

respondents.

Employed statistics were means and standard deviations, t-

test, ANOVA, and Pearson’s r Correlation. Statistical level

for all inferential tests was set at .05 alpha. All statistical

computations were processed through the Statistical

Package for the Social Sciences (SPSS) software.

The respondents were classified as to age, sex, socio


parents. As to age, the respondents were classified as to

young (20 years old below) and old (above 20 years old).

As to sex, they were classified as to male and female. As to

socio economic status, they were classified as to low,

average, and high. As to educational attainment of their

parents, they were classified as to elementary, high school,

and college.

To gather data from the respondents such as age, sex, socio

economic status and educational attainment of their

parents, a personal data sheet was attached to the

questionnaire checklists. To determine the academic

performance of the respondents, the Terminal

Competencies Assessment (TCA) results were used. TCA

is divided in to two parts: general competencies and the

specialized knowledge. The general competencies include:

Critical Thinking, Historical Perspective, Civic

Responsibility, Technological Facility, Research

Competence, Scientific Literacy, Information Literacy, and

Effective Communications. The specialized knowledge

covers disciplinary knowledge and skills in line with the

respondents’ area of specialization.

Study habit component skills included were homework and

assignment, time allocation, reading and note-taking, study

period procedure, concentration, written work,

examination, teacher consultation.



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The researcher-made and duly validated questionnaire

checklists were used to obtain the data on the influence of

social networking and study habits of students. A five-point

scale was used with the following weights and descriptions

to the responses: 1—never, 2- seldom, 3- sometimes, 4-

often, and 5- always. The instrument was validated by

experts in research of the University. The instruments were

pilot tested by the proponents. Split-half method was used

to determine the reliability of the data gathering

instruments.

The data obtained from the study were subjected to

descriptive and inferential statistical tools. Means and

standard deviations were used to determine the influence of

social networking, the status of study habits, and the level

of students’ academic performance.

To determine the extent of influence of social networking

and the status of study habits, this scale and its descriptions

were used: 4.21-5.00 - Very Highly Influenced; 3.41- 4.20

– Highly Influenced; 2.61-3.40 – Moderately Influenced;

1.81-2.60 – Fairly Influenced; 1.00-1.80 – Not Influenced.

To determine the level of academic performance, this scale

and its descriptions were used: 65-75 – Advanced; 54-64 -

Very proficient; 43-53 – Proficient; 32-42 – Basic; 21-31 –

Novice. To determine the socio-economic status, this scale

and its descriptions were used: Php 8, 801.00–above –

High; Php 4, 701.00-Php 18,000.00 – Average; Php 4,

700.00-below – Low.

Table I shows the distribution of respondents when

grouped as to age, sex, socio-economic status and

educational attainment of parents.

The total number of respondents was 235 or 100% of the

total population. Out of 235 respondents, as to age, 140

(60%) were young and 95 (40%) were old; as to sex, 85

(36%) were males and 150 (64%) were females; as to

socio-economic status, 130 (55%) were low, 68 (29%)

were average and 37 (16%) were high; as to mother’s

educational attainment, 46 (19%) finished elementary; 89

(38%), finished high school; and 100 (43%) finished

college; and as to father’s educational attainment, 17 (7%)

finished elementary; 108 (46%) finished high school; and

110 (47%) finished college

Table 1: Distribution of Respondents

Category

N

%

Entire group

235

100

Age

Young (20 years old and below)

140

60

Old (above 21 years old) 95

40

Sex

Male

85

36

Female

150 64

Socio Economic Status

Low 130 55

Average 68 29

High 37 16

Educational Attainment

Mother

Elementary 46 19

High School 89 38

College 100 43

Father

Elementary 17 7

High School 108 46

College 110 47



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RESULTS AND DISCUSSIONS

As to the descriptive and inferential findings of this study, Table 2 shows that as an entire group, social networking highly

influenced the respondents (M=3.43, SD=.64). The extent of influence of social networking among the students covered the

use of social networks for their social life, entertainment and educational reasons.

Table 2: Extent of Influence of Social Networking among the Respondents

Category

N

Mean

SD

Description

Entire group

235

3.43

64

Highly Influenced

Age


140

3.43

64

Highly Influenced

Old (above 21 years old) 95 3.43 60 Highly Influenced

Sex

Male

85

3.54

. 66

Highly Influenced

Female 150 3.37 65 Highly Influenced


Low 130 3.33 .57 Highly Influenced

Average 68 3.47 .67 Highly Influenced

High 37 3.71 .43 Highly Influenced


Mother

Elementary 46 3.44 62 Highly Influenced

High School 89 3.28 67 Highly Influenced

College 100 3.57 .73 Highly Influenced

Father

Elementary 17 3.32 62 Highly Influenced

High School 108 3.35 .60 Highly Influenced

College 110 3.56 .60 Highly Influenced

Legend: 4.21-5.00 - Very Highly Influenced; 3.41- 4.20 – Highly Influenced; 2.61-3.40 – Moderately Influenced; 1.81-2.60

– Fairly Influenced; 1.00-1.80 – Not Influenced

.

When they were classified as to age, social networking

highly influenced the young (M=3.43, SD=.64) and the

old (M=3.43, SD=.65). Likewise, as to sex, social

networking highly influenced the male (M=3.54, SD=.60)

and the female (M=3.37, SD=.66). When the respondents

were grouped as to socio-economic status, social

networking highly influenced those with low income

(M=3.35, SD=.65), those with average income (M=3.47,

SD=.57) and those with high income (M=3.71, SD=.67).

When they were classified as to educational attainment of

parents, social networking highly influenced those whose

mothers finished elementary (M=3.44, SD=.43), high

school (M=3.28, SD=.62) and college (M=3.57,

SD=.67). Similarly, those whose fathers finished

elementary (M=3.32, SD=.72), high school (M=3.35,

SD=.62) and college (M=3.56, SD=.60). The SDs

obtained showed the narrow dispersion of the means for

each group, revealing the homogeneity of the respondents

concerned in relation to the general influence of social

networking on their study habits and academic

performance. These results proved that the respondents’

study habits and academic performance were to a high

extent influenced by social networking. Most likely that

this high influence may have been result of easy access to

and brought about by the availability of gadgets at hand

like cell phones, desktops, laptops with mobile data and

Wi-Fi connection. The affordability of these gadgets in the

market may have been another reason.

Table 3 reveals that as entire group, the respondents had

highstatus of study habits (M=3.82, SD=.63). The study

habit component skills upon which the researchers based

the respondents’ status of study habits included homework

and assignment, time allocation, reading and note-taking,



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study period procedure, concentration, written work, examination, and teacher consultation.

Table 3: Status of Study Habit of the Respondents

Category

N

Mean

SD

Description

Entire group

235

3.82

.63

High

Age

Y oung (20 years old and below)

140

3.73

.63

High

Old (above 21 years old) 95 3.96 .62 High

Sex

Male

85

3.81

.65

High

Female 150 3.83 .62 High


Low 130 3.87 .60 High

Average 68 3.84 .56 High

High 37 3.61 .80 High


Mother

Elementary 46 3.43 .43 High

High School 89 3.28 62 High

College 100 3.57 67 High

Father

Elementary 17 3.32 .73 High

High School 108 3.35 .62 High

College 110 3.56 .60 High

Legend:4.21-5.00 - Very High; 3.41- 4.20 – High; 2.61-3.40 – Moderate; 1.81-2.60 – Fair; 1.00-1.80 – Poor.

When they were classified as to age, the respondents

yielded high status for both the young (M=3.73, SD=.63)

and the old (M=3.96, SD=.62). Likewise, as to sex, they

showed high status for both male (M=3.81, SD=.65) and

female (M=3.83, SD=.62). When the respondents were

grouped as to socio-economic status, they showed high

status for all those with low income (M=3.87, SD=.60),

those with average income (M=3.84, SD=.56) and those

with high income (M=3.61, SD=.80). When they were

classified as to educational attainment of parents, the

respondents yielded high status for all those whose

mothers finished elementary (M=3.44, SD=.43), high

school (M=3.28, SD=.62) and college (M=3.57,

SD=.67). Also, those whose fathers who finished

elementary (M=3.32, SD=.72), high school (M=3.35,

SD=.62) and college (M=3.56, SD=.60). The SDs

obtained showed the narrow dispersion of the means for

each group, revealing the homogeneity of the respondents

concerned in relation to the status of their study habits. The

overall results disclosed a high status among respondents’

study habits. The revealed high status may have been

brought about by their academic struggles, perseverance to

pass their subjects with high grades, ability to adapt to

academic demands and pressures, systematic study

schedules, and the like. Most likely that they have relevant

study practices as well as influences of peer groups and

others as regards how to balance and focus on their studies.

Table 4 shows that as entire group, the respondents had

basic level of academic performance (M=35.17,

SD=6.09).

When they were classified as to age, the respondents

yielded basiclevel of academic performance for both the

young (M=36.55, SD=6.55) and the old (M=33.04,

SD=4.60). Likewise, as to sex, they showed basiclevel of

academic performance for both male (M=36.15,

SD=6.55) and female (M=34.59, SD=5.75). When the

respondents were grouped as to socio-economic status,

they showed basic level of academic performance for all

those with low income (M=34.36, SD=5.73), those with

average income (M=35.04, SD=.5.30) and those with

high income (M=38.13, SD=7.67). When they were

classified as to educational attainment of parents, the

respondents yielded basic level of academic

performancefor all those whose mothers finished

elementary (M=34.00, SD=5.22), high school (M=33.69,

SD=5.15) and college (M=36.74, SD=6.66). Also, those

whose fathers who finished elementary (M=34.64,



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SD=7.30), high school (M=33.89, SD=5.33) and college

(M=36.54, SD=5.89). The SDs obtained showed the

narrow dispersion of the means for each group, revealing

the homogeneity of the respondents concerned in relation

to the level of their academic performance. The general

competencies covered in the terminal assessment test

administered to the respondents like critical thinking,

historical perspective, civic responsibility, technological

facility, research competence, scientific literacy,

information literacy, and effective communications yielded

overall results of a basic level of academic performance

among the respondents, showing a very modest

accomplishment.These turn out may have been brought

about by personal factors, lack of review or to the extent,

weak teaching-learning procedures. Most likely, though

it’s a specialized learning that covered disciplinary

knowledge and skills in line with the respondents’ area of

specialization, there may be lack of experiential learning,

practice and more practice.

Table 4:level of academic performance of the respondents

Category

N

Mean

SD

Description

A

Entire group

235

35.17

6.09

Basic

B

Age

Young (20 years old and below) 140 36.55 6.55 Basic

Old (above 21 years old) 95 33.04 4.60 Basic

C

Sex

Male

85 36.15 6.55 Basic

Female 150 34.59 5.75 Basic

D


Low 130 34.36 5.73 Basic

Average 68 35.04 5.30 Basic

High 37 38.13 7.67 Basic

E


Mother

Elementary 46 34.00 5.22 Basic

High School 89 33.69 5.15 Basic

College 100 36.74 6.66 Basic

Father

Elementary 17 34.64 7.30 Basic

High School 108 33.89 5.33 Basic

College 110 36.54 5.89 Basic

Legend: 65-75 – Advanced; 54-64 - Very proficient; 43-53 – Proficient; 32-42 – Basic; 21-31 – Novice

t-test and ANOVA results on Table 5 revealed that there

were no significant differences on the extent of influence of

social networking on the respondents as to their age (t =

.02, p = .98), sex (t = 1.94; p = .05) and educational

attainment of father (F=.40, p = .26). Social networking

has been and will be a worldwide trend, and the clientele

regardless of age, young or old, are captive users. Sex,

represented by male and female, may be an interesting and

important variable, yet in this study may not be significant

at all. This may be due to the mental and emotional

interests of both sexes on using social networking. Both

have been observed to be sociable people living in a

sociable society. As to their everyday activities and

decisions, they may resort to such occupational hobby or

serious business of social networking and no sex is an

exception. Most likely that they’re both strongly exposed

to social media as their springboard for social networking.

Regardless of their father’s educational attainment, the

respondents took personally their interests and perhaps

developed attachment on social networking through the

use of available gadgets at hand.

On the other hand, ANOVA results showed significant

differences existed when the respondents were classified as

to socio economic status (F=.40, p=.01) and educational

attainment of mother (F=.40, p=.003). It is well noted

that the higher the socio economic status, the better

opportunity for anyone to avail gadgets like cell phones,



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laptops and the like and can change them with more high-

tech ones at one’s disposal. Social networking may have a

better impact to those who can afford the technology.

Likewise, the respondents, when classified as to

educational attainment of mother, also showed a significant

difference as to social networking’s influence. This may be

due to the closeness and the impact of mothers to their

kids. The higher the education of the mother, the higher

the possibility that she has influenced how her kids would

prefer to be socially active and be adept with social

networking.

Table 5:Differences in the Extent of Influence of Social Networking on the Respondents

Category Mean df t-value 2-tailed Probability

Statistical Decision

Age


36.55

233

.02

.98

Not Significant

Old (above 21 years old)

33.04

Sex

Male 36.15 232

1.94

.05 Not Significant

Female 34.59

Category

Mean

df

mean-Square

2-tailed

Probability



Low 34.36

232

.40

.01

Significant

Average 35.04

High 38.13 Educational Attainment

Mother Elementary 34.00 232 .40

.003

Significant High School 33.69

College 36.74 Father Elementary 34.64 232 .40

.26

Not Significant High School 33.89

College 36.54 P, <.05


was a significant difference on the status of study habits of

the respondents when classified as to their age (t =-2.66,

p = .01). It may be posited that age is a factor on how one

prioritizes his studies. Getting aged perhaps creates a

better perspective and system on how one can manage his

time schedule and activities, be it in the classroom or in

personal life; most likely, with the respondents of this

study.

When they were classified as to sex (t=-.16, p = .87),

socio economic status (F=.39, p = .08) and educational

attainment of parents: mother (F=.40; p= .18), father

(F=.40, p=.07), there were no significant differences on

the status of study habits of the respondents. Irrespective

of these variables, the students’ study habits may have

been a result of the stringent instructional activities

afforded by their teachers and their institution; that their

academic demand and pressure may have drove them to

study, set time schedules and religiously follow these

schedules.



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Table 6:Differences in the Status of Study Habits of the Respondents



Age


36.55

233

-2.66

.01

Significant


33.04

Sex

Male 36.15 232

-.16

.87

Not Significant

Female 34.59

Category

Mean

df

mean-Square

2-tailed

Probability



Low 34.36

232

39

.08

Not Significant

Average 35.04

High 38.13


Mother

Elementary

34.00

232

.40

.18

Not Significant

High School 33.69

College 36.74

Father

Elementary

34.64

232

.40

.07

Not Significant

High School 33.89

College 36.54

P, <.05


were significant differences on the level of academic

performance of the respondents when classified as to their

age (t=-4.50, p=.00), socio economic status (F=-35.65,

p=.003), and educational attainment of parents: mother

(F=-35.12, p=.001) and father (F=-35.93, p=.009). It has

been observed that as one aged, supported with better

family income and strong educational background of

parents yielded better academic performance on the

students. Hence, these variables may have been generally

true when gauged with academic performance.

When they were classified as to sex (t=1.84, p=.07), no

significant difference was noted. Regardless of sex, the

respondents may have been generally to either be

academically high or less performing as brought about by

equal opportunity given them in academic activities and

instructional endeavours. They may have been similarly to

be academically prepared, ready or otherwise; hence, no

significant difference was found.



10

Table 7: Differences in the Level of Academic Performance of the Respondents



Age


36.55

233

4.50

.00

Significant


33.04

Sex

Male 36.15 232

1.84

.07

Not Significant

Female 34.59

Category

Mean

df

mean-Square

2-tailed

Probability



Low 34.36

232

35.61

.003

Significant

Average 35.04

High 38.13 Educational Attainment

Mother Elementary 34.00 232 35.12

.001

Significant High School 33.69

College 36.74 Father Elementary 34.64

232

35.93

.009

Significant

High School 33.89 College 36.54

P, <.05

As shown on Table 8, a significant correlation existed

between the extent of influence of social networking and

the status of the study habits of the respondents as shown

by Pearson’s r of .36 and two-tailed probability of .00

which was less than the set of 0.05 level of significance It

may been well underscored the importance of one with the

other. This significant relationship may have been

contributed by the degree program of the respondents, to

whom this study was administered, knowing the

respondents as computer education and information

technology learners. Social networking would have been

fastened in their daily activities and school requirements;

hence, to their study habits.

Also, a significant relationship existed between the extent

of influence of social networking and the level of academic

performance of the respondents as revealed by Pearson’s r

of .13 and two-tailed probability of .04 which was less than

the set of 0.05 level of significance. As information

technology students, social networking would have been

embedded in their instructional activities in school or more

likely, at home. This significant relationship would have

been a result of the respondents’ imbibing both as part of

their system, where one exists so with the other.

While it was found out that no significant relationship

existed between the status of the study habits and level of

academic performance of the respondents as revealed by

Pearson’s r of -117 and two-tailed probability of .07 which

was greater than the set of 0.05 level of significance. No

significant correlation was noted because both variables

may not have much of impact to the respondents’ daily

instructional activities. They may have become vital

components in their studies of information technology but

not much relationship significance has been identified.



11

Table 8:Relationship between the Extent of Influence of Social Networking and Status of

CONCLUSIONS

The extent of influence of social networking on students as

an entire group and regardless of age, sex, socio economic

status, and educational attainment of their parents was

high. It also proved that the respondents’ study habits and

academic performance were to a high extent influenced by

social networking. Most likely that this high influence may

have been result of easy access to and brought about by the

accessibility of gadgets like cell phones with mobile data

and Wi-Fi connection. The affordability and availability of

these gadgets in the market may have been another reason.

Likewise, this implies that students may have not realized

that spending more time in social networking could be a

hindrance to a good academic performance. In fact they

have more important things to do like school works and

studying their lessons. The status of study habits of

students as an entire group and regardless of age, sex, socio


parents was high. This means that students may have

established certain habits in accordance to their needs and

have their aspirations and purpose of utilizing social

networking in improving their academic performance.

The level of academic performance of students as an entire

group and regardless of age, sex, socio economic status,

and educational attainment of their parents was basic. The

findings mean that being active in social networking could

affect students socially, emotionally and academically. This

may mean that social networking could highly influence

study habits and academic performance of students

negatively. Being involved in social networking can

influence the students not to give importance to their

academic subjects.

Students should utilize certain time for researching or

advance study aside from social networking. Students

would have certain restrictions on how will they use and

view the pages of social networking sites. For example, if

they have spare time or they are on the time of net

researching they could visit their educational social

networking sites. Students should evaluate themselves;

assess their aspirations in looking for friends. They should

not always seek attention, instead try to confide themselves

with those people who appreciate them.

It is suggested that parents should get appropriate guidance

and counselling about dealing on how to develop good

study habits for the educational development of their

children. Healthy and sympathetic teacher-student

relationship should be initiated to upgrade the level of

academic self-esteem of students. Self-study should be

encouraged and emphasized. The teachers should ask the

Category

Pearson’s r

2-tailed Probability


Social Networking

Study Habit

.36

.00

Significant

Social Networking

Academic Performance

.13

.04

Significant

Study Habit

Academic Performance

-117

.07

Not Significant



12

students to keep the record of their progress towards their

set goals. Academic heads must enforce academic advising

among their teachers. Provisions on compulsory academic

counselling for underachievers must be imposed and may

consider giving more remedial actions to improve student’s

learning.

In closure, the present study may be replicated to further

investigate how this learning environment that

integrates the proposed framework for confluent academic

interventions affects students’ study habits and learning

behavior and enhances students’ educational development.

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