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Quest International Multidisciplinary Research Journal Available at www.mahidachintan.com

Volume – II , Issue – I June – 2013 Journal Impact Factor : 1.732 (ISRA)

ISSN : 2278 – 4497 Article ID # 2105

Copyright © 2013. Eshaghali Azizi and Dr. K. Yeshodhara. This is an open access refereed article

distributed under the Creative Common Attribution License which permits unrestricted use, distribution

and reproduction in any medium, provided the original work is properly cited.

RESEARCH PAPER

LEVEL OF INTERNET COMPETENCY AMONG

BACHELOR DEGREE SCIENCE STUDENTS OF

DIFFERENT TYPES OF COLLEGES

– A COMPARATIVE STUDY

Eshaghali Azizi1 and Dr. K. Yeshodhara

2

INTRODUCTION

One of the main components of quality in higher education is the quality of teaching -

learning process. The quality of this component depends on the quality of teaching and learning performance. The approaches vicissitude of learning psychology from behaviorism to cognitivism and

constructivism have provided theoretical foundation for the teacher towards the selection of

appropriate strategies of teaching and achieve the desired level of learning. But in practice, it is necessary for teachers and students to be familiar with teaching-learning strategies and learning

principles and. On the other hand vast improvements in the learning science and application of

information and communication technologies in higher education, and use of active learning methods

have facilitated both teachers and learners to result in effective learning (http://cuqa-learning.ut.ac.ir/).

1Ph.D. Student, Department of Studies in Education ,University of Mysore, Mysore( Karnataka)

2 Professor and BOS, Department of Studies in Education, University of Mysore, Mysore (Karnataka)

ABSTRACT

Today, Internet competency (IC) and knowledge is part of needs of necessary each student and student can't

access easily and quickly to needed information and resources. The present study is an attempt to compare

the level of IC among bachelor degree science students of different types of colleges under university of Mysore. This paper tries to answer whether the students of University of Mysore constituent college,

Government, Private aided and Private unaided degree colleges differ in their IC (in total and component

wise). A total of 254 bachelor degree science students were drawn randomly from the 4 selected colleges

giving representation to 3 different combination-PMCs, PCM and CBZ. One college under each type -

University of Mysore constituent college, Government, Private aided and Private unaided colleges - (total 4

colleges) was selected using convenience sampling technique. The IC Scale prepared by the researcher was

employed to assess the level of competency in total and component wise. It consisted of components on

Computer general knowledge, Computer General ability, Communication and Collaboration, General

Webpage Using, Information Management, Information Search. The data was analyzed using One Way

ANOVA and Duncan's multiple range test. Results revealed that there were significant differences among

bachelor degree science students of different types of colleges in the level of total IC and in the components

of Communication and Collaboration, General Webpage Using, Computer general knowledge, Computer General ability, Information Management and Information Search.

KEY WORDS : IC, Computer General Knowledge, Computer General Ability, General Webpage Using,

Communication and Collaboration, Information Management and Information Search.

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Level of Internet Competency among Bachelor Degree Science Students Article ID # 2105

Quest International Multidisciplinary Research Journal ● Vol - II , Issue - I ● June - 2013

The internet has broken down barriers of communication access from anywhere in the world.

It is fast, reliable and does not have restrictions on content or format (except in certain countries). It

also has a limitless range of facilities which assist users to access the almost infinite information on the net. The internet offers the opportunity to access up-to-date research reports and knowledge

globally on topics as diverse as science and technology, business and finance, music and the arts.

Thus, it has become an important component of electronic services in academic institutions and thereby an invaluable tool for learning and research. For internet resources to be used effectively,

students and scholars are required to develop a set of new skills that include strategies for searching

relevant materials, skills in evaluating the quality of documents found, knowledge of web design,

skills in using discussion forums and chat rooms, as well as basic understanding of how to send e-mail attachments. (newezeh, 2010).

Internet Competency (IC) is the ability of an individual to use the internet properly. It is a combination of knowledge and skills to use the internet for better academic performance. In addition

to general Computer knowledge it includes the abilities like: Communication and Collaboration,

General Webpage Using, Information Search and Management etc.

Educators, trainers, and researchers have long been interested in exploring variables

contributing effectively for quality of performance of learners. These variables maybe internal or

external to school that affect students’ quality of academic achievement. These factors may be termed as student factors, family factors, school factors and peer factors (Crosnoe, Johnson and Elder, 2004).

The formal investigation about the role of the demographic factors rooted back in 17th century

(Farooq, Chaudhry, Shafiq and Berhanu, 2011). Generally these factors include age, gender, geographical belongingness, ethnicity, marital status, socioeconomic status (SES), parents’ education

level, parental profession, language, income and religious affiliations. Life is very fast in this age of

technology and computer. There is a great need for knowledge update, which is very much dependent

a the use of internet. As such IC in today's world is required for people, especially for students community.

NEED, CONTEXT AND IMPORTANCE OF THE STUDY

Some authors suggested that the Internet has positive effects on academic achievement

through the use of educational software, and the provision of useful information (Borzekowski & Robinson, 2005; Jackson, von Eye, Biocca, Barbatsis, Zhao, & Fitzgerald, 2006); others suggest that

the Internet provides positive effects on socialization as it stimulates the closeness of existing

interpersonal relationships by reducing restrictions of time and location (Lenhart, Madden, & Hitlin,

2005; Lenhart, Rainie, & Lewis, 2001).

The importance of this study is follows: today the Internet is pervasive in the lives of

individuals, institutions, and societies all over the world, so in India. The last few decades have witnessed a dramatic increase in the use of the Internet and an unprecedented proliferation of

computer-based technology. Computer technologies and the Internet bring social changes in modern

society. Since computers have become a common instrument of daily living for a vast proportion of

our society, the Internet has a significant influence on quality of life (Israel, 2000). Statistical research tell us that Internet users in the world numbered 16 million in 1996, and increased to 500 million by

2001 (Castells, 2001). For example, almost nine out of 10 American teens use the Internet, up from

seven in 2000 (PEW Internet and American Life Project, 2007). However, as stated in above, India is one of the fastest growing countries in Internet use. Adolescents and youth are more involved in

Internet activities than adults (Kim, 2011).

Studies about the use of internet and academic achievement were examined using the motives

of internet use (Choi, Watt, Dekkers, & Park, 2004), attitude of the students‟ internet use (Ebersole,

2000), online time management (Terry, 2002), supporting tools for self-regulatory skills in Web-based

20



learning environment (Niemi, Nevgi, & Virtanen, 2003), the advantages for self-regulated learners on

the internet (Hargis, 2000), and Internet uses and technology (Young, 2001; Reisberg, 2000). The

results of these studies showed that improved computer skills, better time management, and more positive attitudes of internet use improved academic achievement, while internet use among students

positively influences academic learning (Zenon, 2006).

REVIEW OF RELATED LITERATURE

Kim (2011) indicated that Korean boys and girls differed in the ways that they used the internet. Girls were more likely to use the internet to watch online education classes and blog more

frequently and longer than boys, whereas boys were more likely to use the internet for playing internet

games than girls. Results indicated that internet use for educational purposes was associated with adolescent academic achievement. Social and recreational-internet use of the internet was associated

with lower academic achievement.

Lim (2005) showed that the statistics using Spearman’s correlations verified that Internet

information literacy correlated with Internet literacy (mechanical aspect) at a relatively high

coefficient of 0.707 and with computer literacy at 0.675. However, it must be emphasized that an

Internet savvy student with high computer literacy is not necessarily also competent in information literacy. This is because the results verify that information literacy is also dependent on the students’

academic ability and proficiency in the English language. Therefore the mechanical IC level is not the

only factor influencing the competency level of information literacy. However, it does indicate that students must possess a certain level of computer, Internet and information literacy in order to be able

to make more effective use of the Internet (as evidenced by the score in information literacy; that is,

higher the score, the more effective the use of the Internet) as a source of information and knowledge.

In addition to computer and Internet literacy, factors influencing Internet information literacy are the English language proficiency and the innate academic ability of the participants. Furthermore, there

was correlation between the frequency of use of the Internet for schoolwork and the literacy level of

the participants in computer, Internet and information literacy, and also their innate ability.

Nwezeh (2010) reveal that a majority of the surveyed academic staff and the students found

the internet to be very useful. Internet resources mostly used by both groups were e-mail and the world wide web (www). Search interfaces were used for looking for research information. It was

discovered that the users were not given adequate user education to enable them make use of the

internet resources available.

Norris (2010) indicate that bullying by itself does not have a significant association with

achievement outcomes, while the influence of internet use varies in significant direction of effect

based on type of use. Chatting was the only measure of internet use that consistently had a significant negative relationship across all achievement outcomes. The association between bullying behaviors

and academic achievement was moderated by some forms of internet use such that at low levels of

bullying, children with low levels of internet use had significantly higher test scores. As levels of

bullying increased, low/high internet users test scores converged to the point that at high levels of bullying behaviors, differences in test scores between low/high internet users were statistically

insignificant. Email use and surfing the web were found to have moderate association between

bullying behaviors and reading comprehension. Surfing moderated bullying and math scores. Chatting moderated the relationship between bullying and each of the three outcomes. Lastly, there were no

significant race or gender differences in vocabulary or math scores, after controlling for

SES, internet use, parent/child relationships and time measures. However, African American (compared to whites) did less well on reading comprehension scores.

21



McGhee (2010) indicated that there were statistically significant relationships between

asynchronous interaction and academic achievement and between online technologies self-efficacy

and academic achievement. However, there were low correlations between self-regulated learning and academic achievement. The results of this study reflect the constructivist tenets that the student is at

the center of the learning experience.

Yangkim (2009) indicated that there were low correlations between self-regulation and

academic grades and self-regulation and internet use. None of the correlations were statistically

significant. Also, there was no statistically significant correlation between internet use and academic

achievement. Self-regulation was highly correlated to self-efficacy. Total internet access was highly correlated to nonacademic related internet browsing. Although not statistically significant, the

consistent negative correlations between nonacademic internet use with both self-regulation and

achievement indicate that the internet may present an attractive distraction to achievement which may be due to lack of self-regulation.

Bakay (2001) revealed that There are significant differences between students IC scores and their individual characteristics, such as the type of high school they are enrolled in, where these high

schools are located (center or suburb), and their Internet access conditions such as, having computer at

home or not, being subscribed to an internet company or not, where they connect, how they have

learned and how much time they devote to internet weekly, the most preferred activities on the internet, their level of English and if they are visiting internet cafes or not. There are no significant

differences between students’ IC scores and their individual characteristics such as sex, age, and grade

and study area.

Alex (2011) finds that performance is significantly correlated not only with gender

and academic ability, but also with the length of time students spend productively in

the online classroom as reflected in their achievement in online assessments.

Knight Dardenne (2010) showed that there is a significant difference in the student

achievement levels in schools with greater school use of the Internet and email for school-to-home communication. The results showed that schools are providing information that is accessible to

parents through technology, however; the level of use by schools can be improved and parent use is

still limited.

All these studies indicated the relationship between internet use/competency with many other

factors. This necessitated the present study attempting to compare the level of IC among bachelor

science students of different types of colleges.

METHOD OF STUDY

PARTICIPANTS

The population of this study includes final year students of the Yuvaraja, Maharani Science

For Women, Government First Grade in Kuvempunagar, Government First Grade for Women in Vijayanagara, Saradavilas, Mahajana First Grade, Teresian, MMK and SDM college for Women, NIE

Science, Mallamma Marimallappa Science and BBM and ST. Josephs First Grade colleges that have

science subjects in different combinations as (PMCs, PCM and CBZ) in Mysore city (Karnataka state - India). Only two colleges (Mallamma Marimallappa Science and BBM and ST. Josephs First Grade

colleges) were excluded from the population, because they didn't have final year students. The

population size is 745 students as detailed below: University of Mysore constituent college (274 students), Government (243 students), Private aided (171 students) and Private unaided college (57

students).

22



Convenience sampling technique was used to select the colleges in Mysore city and stratified

random sampling technique was used to draw final year students from different types of colleges

giving representation to different combination–PMCs, PCM AND CBZ. Totally 254 students were selected according to the table of Krejcie and Morgan (Hassanzadeh, 2003). All the colleges

constituting the sample of the study are affiliated to university of Mysore. One college was selected

under each types of colleges: University of Mysore constituent college (110 students), Government (86 students), Private aided (39 students) and Private unaided college (19 students). The details of the

sample selected for the study are given in the following table 1.

Table 1. Detail of the sample selected for the study

No College

Name

Type of

College

s

Sample

and

Population

Combination of Subject

Total PMCs PCM CBZ

M F T M F T M F T M F T

1 Yuvaraja UOM Population 50 28 78 109 25 134 50 12 62 209 65 274

Sample 20 11 31 44 10 54 20 5 25 84 26 110

2 Maharani

Science For

Women

Govt. Population - 34 34 - 97 97 - 82 82 - 213 213

Sample - 14 14 - 39 39 - 33 33 - 86 86

3 Sarada

Vilas

Private

Aided

Population 13 0 13 44 10 54 20 9 29 77 19 96

Sample 5 0 5 18 4 22 8 4 12 31 8 39

4 MMK and

SDM for

Women

Private

Unaided

Population - 35 35 - 11 11 - - - - 46 46

Sample - 14 14 - 5 5 - - - - 19 19

Total

Population 63 97 160 153 143 296 70 103 173 286 343 629

Sample 25 39 64 62 58 120 28 42 70 115 139 254

RESEARCH TOOLS

The IC Scale be used in this study to assess the level of IC was constructed by the researcher. This scale consisted of 6 main components, each consisting of multiple items. Each item has 5 levels

of responses like Nil , Poor, Average, Good, Very Good which were given rating of zero to the nil,

one to the poor, two to the average, three to the good and four to the very good. It consisted of 6 components-Computer General Knowledge, Computer General Ability, Communication and

Collaboration, General Webpage Using, Information Management, Information Search. In total this

Scale included 72 Items. For validation, the scale was given to faculty members and research scholar of University of Mysore, Department of Education, Regional Institute of Education Mysore (RIE),

and Department of Computer Science. Based on their discussion and suggestion, certain items were

modified, certain items were added/deleted and finalized the tool. Reliability obtained was Cronbach's

alpha coefficient 0.97.

Table 2. The details of the items included in Internet Competency Scale (ICS)

Components of IC Number of

questions

Range of questions

Computer general knowledge 23 1-23

Computer General ability 23 1-23

Communication Collaboration 17 24-40

General Webpage Using 9 41-49

Information Management 12 50-61

Information Search 11 62-72

Total 72 1-72

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DESIGN AND PROCEDURE

This is a comparative study with descriptive an analytical research design. The data was collected using IC Scale prepared by the investigator. During administration of the scale, clarifications

were given for certain items on demand. The data was analyzed using one way ANOVA and Duncan's

multiple range test on SPSS (version 15.0).

RESULTS

Table 3. Mean scores and SD of IC in total and component wise

with reference to different types of colleges

Component

Type of College

Total UOM

Constituent

College

Government Private

Aided

Private

Unaided

Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D.

Computer

general

knowledge

47.11

22.26

39.23

19.85

49.10

18.97

48.37

17.03

44.84

20.91

Computer

General ability

46.13

22.39

38.91

20.06

49.23

20.69

48.53

17.31

44.34

21.29

Communication

and

Collaboration

46.40

16.75

38.96

18.76

47.95

12.25

40.74

15.99

43.69

17.15

General

Webpage Using

22.74

8.69

18.96

10.26

24.07

7.053

21.26

9.02

21.56

9.22

Information

Management

35.29

9.62

31.52

11.26

36.49

8.19

32.74

11.87

34.01

10.32

Information

Search

25.44

10.16

21.77

11.84

27.20

7.63

22.37

10.19

24.24

10.58

Total

223.12

82.64

189.36

82.12

234.05

64.52

214.00

74.15

212.68

80.79

Table 3 presents Mean and standard deviation of IC scores in total and on its various

components of among the students of different types of colleges.

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Table 4. Results of One Way ANOVA for mean scores of IC in total and component

wise with reference to different types of colleges

Source Dependent

Variable

Sum of

Squares Df

Mean

Square

F

value

P

value

Types

of

Colleges

Computer

general

knowledge

between

groups 4215.65 3 1405.22 3.30 .021

within

groups 106406.05 250 425.62

Total 110621.70 253

Computer

General ability

between

groups 4155.75 3 1385.25 3.13 .026

within

groups 110523.13 250 442.09

Total 114678.88 253

Communication

and

Collaboration

between

groups 3600.78 3 1200.26 4.24 .006

within

groups 70834.88 250 283.34

Total 74435.66 253

General

Webpage Using

between

groups 982.39 3 327.46 3.98 .008

within

groups 20526.22 250 82.10

Total 21508.61 253

Information

Management

between

groups 982.41 3 327.47 3.15 .025

within

groups 25951.57 250 103.81

Total 26933.98 253

Information

Search

between

groups 1095.05 3 365.02 3.35 .020

within

groups 27245.30 250 108.98

Total 28340.35 253

Total between

groups 76597.62 3 25532.54 4.05 .008

within

groups 1574803.19 250 6299.21

Total 1651400.80 253

Table 4 present the details of the result of one way ANOVA. Table 4 shows that all the F

values for IC in total and all its components were found to be significant at 0.05 level and thus it is

concluded that there is significant difference among bachelor degree science students of different types of colleges (university of Mysore constituent college, government, private aided and private

unaided college) in their level of IC in total and in all its components Computer General Knowledge,

Computer General Ability, Communication and Collaboration, General Webpage Using, Information Management and Information Search.

25



In order to compare the level of IC among the student of different type of colleges Duncan's

multiple range test (post hoc test) was employed.

Table 5. Results of Duncan's multiple range test (a=0.05) Type of college N Subset for alpha = .05

1 2

Government 86 189.36

private unaided 19 214.00 214.00

University of Mysore constituent college 110 223.12 223.12

private aided 39 234.05

Sig. .071 .288

Table 5 shows that in total there is significant difference between IC mean scores of private

aided college students and government college students, University of Mysore constituent college and

Government college, Private unaided and Government college. Thus it is concluded that government

college students are lower in IC when compared to the students of other 3 types of colleges.

DISCUSSION

In this study results showed: There is significant difference among bachelor degree science

students of different types of colleges (University of Mysore constituent college government, private

aided and private unaided colleges) in their level of IC in total and each components (Communication and Collaboration competency, General Webpage Using competency, Computer general knowledge,

Computer General ability, Information Management competency, and Information Search).

Also the result of Duncan's multiple range test shows that government college students are lower in IC when compared to the students of other 3 types of colleges. This explains that the students

of government college are less exposed to the use of internet/computer. The college may not take

more interest in equipping the computer lab and encouraging student to use more and more internet for knowledge improvement when compared to other colleges. Students may also do not afford to

make use of internet facility outside the college, because of many reasons.

Since few studies exist on the subject. only two findings obtained in the present study are

partially in accordance with studies done earlier. Bakay (2001) revealed that There are significant

differences between students IC scores and their individual characteristics, such as the type of high

school they are enrolled in, where these high schools are located (center or suburb), and their Internet access conditions such as, having computer at home or not, being subscribed to an internet company

or not, where they connect, how they have learned and how much time they devote to internet weekly,

the most preferred activities on the internet, their level of English and if they are visiting internet cafes or not.

Poh-Gek (2005) showed that Internet information literacy correlated with Internet literacy

(mechanical aspect) at a relatively high correlation coefficient of 0.71 and with computer literacy at 0.67. However, it must be emphasized that an Internet savvy student with high computer literacy is

not necessarily also competent in information literacy. This is because the results verify that

information literacy is also dependent on the students’ academic ability and proficiency in the English language. Therefore the mechanical IC level is not the only factor influencing the competency level of

information literacy. However, it does indicate that students must possess a certain level of computer,

Internet and information literacy in order to be able to make more effective use of the Internet (as evidenced by the score in information literacy; that is, the higher the score, the more effective the use

of the Internet) as a source of information and knowledge. In addition to computer and Internet

literacy, factors influencing Internet information literacy are the English language proficiency and the

innate academic ability of the participants. Furthermore, there was correlation between the frequency of use of the Internet for schoolwork and the literacy level of the participants in computer, Internet

and information literacy, and also their innate ability.

26



This paper points to the need for quite a wide range of possible research areas into Internet

information literacy before we can integrate the use of the Internet into the curriculum. Possible areas for future research include reading strategies and comprehension using the Internet; the relation

between social capital and habitus and the use of the Internet; network infrastructure and the use of

the Internet in the classroom; the safe use of the Internet; alternative assessment using the Internet; and the provision of resources for disadvantaged students and differentiated instruction using the

Internet.

To educate and prepare the younger generation to work in the 21st century and to be able to

face the challenges of the future, we need to undertake research into the designing of classroom

activities making use of Internet information skills to learn discipline specific knowledge. This issue

and self-directed, engaged learning using the Internet will be the focus for research in differentiated instruction and Internet information literacy.

The Colleges should have a separate and more funding and the other measurable support for an information literacy agenda.

Technological infrastructure needs to be implemented to enable better utilization of the online

resources being subscribed.

There is a need to develop tutorials related to database search skills such as navigating the

database, searching specific interfaces, etc., and Internet skills such as web browser navigation, communication on the Internet, web search tools, web search strategies, evaluation of web resources,

using subject-based portals, and gateways, etc.

It is further recommended that government colleges also must take initiative to provide facilities for students and encourage them to develop IC for the betterment of their academic

performance.

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Please Cite this Article as :

Azizi, Eshaghali and Dr. K. Yeshodhara. “Level of Internet Competency among Bachelor Degree Science Students

of Different Types of Colleges – A Comparative Study.” Quest International Multidisciplinary Research Journal 2.1

(2013): 19-28. <www.mahidachintan.com>.

28

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http://cuqa-learning.ut.ac.ir/

http://chronicle.com/free/v46/i41/41a04301

research paper level of internet competency among ... - ugc · this paper tries to answer whether...

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