May14

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.4 NO.5 MAY 2014

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IJITCE PUBLICATION

International Journal of Innovative Technology & Creative Engineering

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May 2014

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From Editor's Desk

Dear Researcher, Greetings! Research article in this issue discusses about motivational factor analysis. Let us review research around the world this month; Researchers in California have identified a plausible biomarker that can be used to predict long-term MS progression. Using proton magnetic resonance spectroscopy (MRS), researchers measured metabolite abnormalities known to be associated with neurodegeneration. N-acetylaspartate (NAA) is an amino acid generated by mitochondria that is confined almost exclusively to neurons and axons in the CNS. A reduction of NAA will occur when there is loss of neurons and axons—thus reflecting neurodegeneration—but may also decrease when there is potentially reversible neuroaxonal dysfunction. Myo-inositol (mI) is generated by glial cells, in particular astrocytes. An increase of mI in white matter lesions and normal-appearing white matter (NAWM) in MS may reflect astrocyte proliferation. International Energy Agency (IEA), published Monday, looks at the cost of converting to green electricity in order to keep global warming below 2 °C. The agency found that it will cost $44 trillion more than keeping the current mix, where most electricity comes from fossil fuels. The extra money will go on building wind and solar power stations, efficient grids, electric vehicles and infrastructure. Although going green costs more upfront, it brings long-term savings. That is primarily because a more efficient infrastructure uses less fuel. The IEA says that, at $115 trillion by 2050, those savings more than offset the initial investment. Google unveils design for its own self-driving car. Revealed at the inaugural Code Conference in California this week, Google's two-person driverless car is an all-electric design with a top speed of 25 miles an hour. It incorporates a range of pedestrian, road and environmental sensing technologies based on lasers, radar and cameras. The firm has perfected these during 1 million kilometres of autonomous driving tests on the streets of California.Driverless operation seems to be a natural evolution of current systems like lane-keeping technology, adaptive cruise control and self-parking, which can all be activated at the touch of a button. It has been an absolute pleasure to present you articles that you wish to read. We look forward to many more new technologies related research articles from you and your friends. We are anxiously awaiting the rich and thorough research papers that have been prepared by our authors for the next issue. Thanks, Editorial Team IJITCE


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Dr. Chee Kyun Ng Ph.D Department of Computer and Communication Systems, Faculty of Engineering, Universiti Putra Malaysia,UPM Serdang, 43400 Selangor,Malaysia. Dr. Simon SEE Ph.D Chief Technologist and Technical Director at Oracle Corporation, Associate Professor (Adjunct) at Nanyang Technological University Professor (Adjunct) at Shangai Jiaotong University, 27 West Coast Rise #08-12,Singapore 127470 Dr. sc.agr. Horst Juergen SCHWARTZ Ph.D, Humboldt-University of Berlin, Faculty of Agriculture and Horticulture, Asternplatz 2a, D-12203 Berlin, Germany Dr. Marco L. Bianchini Ph.D Italian National Research Council; IBAF-CNR, Via Salaria km 29.300, 00015 Monterotondo Scalo (RM), Italy Dr. Nijad Kabbara Ph.D Marine Research Centre / Remote Sensing Centre/ National Council for Scientific Research, P. O. Box: 189 Jounieh, Lebanon Dr. Aaron Solomon Ph.D Department of Computer Science, National Chi Nan University, No. 303, University Road, Puli Town, Nantou County 54561, Taiwan Dr. Arthanariee. A. M M.Sc.,M.Phil.,M.S.,Ph.D Director - Bharathidasan School of Computer Applications, Ellispettai, Erode, Tamil Nadu,India Dr. Takaharu KAMEOKA, Ph.D Professor, Laboratory of Food, Environmental & Cultural Informatics Division of Sustainable Resource Sciences, Graduate School of Bioresources, Mie University, 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507, Japan Mr. M. Sivakumar M.C.A.,ITIL.,PRINCE2.,ISTQB.,OCP.,ICP Project Manager - Software, Applied Materials, 1a park lane, cranford, UK Dr. Bulent Acma Ph.D Anadolu University, Department of Economics, Unit of Southeastern Anatolia Project(GAP), 26470 Eskisehir, TURKEY Dr. Selvanathan Arumugam Ph.D Research Scientist, Department of Chemistry, University of Georgia, GA-30602, USA.

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Contents

Does self-efficacy effect on knowledge sharing intention in e-learning system? A motivational factor analysis in Open University Malaysia (OUM) by Dr. seyed mohammad bathaei, Seyed Ali Hosseini……………………….[206]


206 www.ijitce.co.uk

Does self-efficacy effect on knowledge sharing intention in e-learning system? A motivational factor analysis in Open

University Malaysia (OUM) Dr. seyed mohammad bathaei

Ministry of education Islamic republic of Iran Deputy of minister of education in Islamic republic of Iran

[email protected]

Seyed Ali Hosseini International Business School University Technology Malaysia (UTM) Malaysia

Jalan Semarak 50400 Kuala Lumpur, MALAYSIA -019-4616464 [email protected]

Abstract— The purpose of this paper is to examine the

self-efficacy factor influence intention to share

knowledge in E-Learning system within Open University

Malaysia (OUM). Moreover, its objective is to identify

the relationship between self-efficacy and perceived

behaviour control (PBC) and intention to share in E-

learning system. The current research expands a

theoretical framework of online knowledge sharing

factors with the Theory of Planned Behaviour (TPB). An

online questionnaire survey was applied to collect data

and the analysis was completed according to 583

responses from students who act in EL system of Open

University Malaysia (OUM). A semi-structured interview

was constructed with 10 participants who were

facilitators and teachers in EL system of OUM as the

case study to achieve knowledge sharing

comprehensible and understandable intention. The

outcomes of the study survey and interview support the

fundamental statement that self-efficacy direct to

influence intention to share knowledge well.

Key words — knowledge sharing (KS), E-learning (EL),

knowledge sharing behavior, theory of planned behavior

(TPB), self-efficacy (SE), intention to share, perceived

behavior control (PBC).

I. INTRODUCTION

The new learning methods assist cooperative

experience and virtual students’ society improvement

(Bransford et al., 2000), and valuable knowledge via

knowledge sharing (Zhang et al., 2007). Nevertheless,

these profits cannot be apprehended lacking of the

energetic participation of people. Latest empirical

research disclose little points of participation and

unwillingness to share knowledge in EL systems and

environments (Carr and Chambers, 2006; Ng, 2001),

and research of crucial factors influencing participation

in some systems disclose that this problem rests

unsolved (Xie et al., 2006). E-learning system structure

confirmed through constructivist theories of learning and

behavior (Prawat, 1996), and assists learning process

via increasing knowledge sharing behavior in learning

environment (Honebein, 1996; Wilson, 1996). As Hiltz

and Turoff (2005) referred, ‘‘EL is a modern

communicative procedure which gives enjoyment to

distance learning students, compared to traditional

classrooms (face to face)”. In spite of the attractiveness

of the EL environments, there are still major challenges

in the willingness to use EL systems, one of which is

that the students do not want to share their knowledge

and experiences (Zhang and Faerman, 2007).



II. Operational definition

E-Learning system

EL systems are the principal learning surroundings in

Higher Education. EL is recognized as new applications

by Learning Management System (LMS) and also

Course Management System (CMS) in distance learning

universities and institutions (Artino, 2010). Kanuka and

Rourke (2008) discover the modifications that are

happening in higher education (HE) as an outcome of

the use of EL system. They find that some technical

system prepares chances for developed accessibility,

compatible with the objective in application of modern

technology in education environment. Nevertheless, it is

also related to negative influences, as teachers and

learners experience to gather a lock of a feel of

belonging and responsiveness of borders.

Self-efficacy

Self-efficacy indicates the degree of an individual’s

confidence to perform and to coordinate the knowledge

and activities in daily educational tasks as required to

obtain knowledge, experiences, and successful

performance in the EL system environment. As Ormrod

(2006) defined it, “Self-Efficacy is the measure of the

belief in one's own ability to complete tasks and reach

goals". Bandura (1995) also believed that "Self-Efficacy

is individual’s beliefs about their competencies to create

success that impact on procedures growing their lives’

performance". A suggestion is that PBC might be

divisible into two separate constituents. These would be

“SE beliefs”, which is defined as the level of enactment

of the behaviour which is easy or difficult for the

individual. The next constituent is “perceived control

over the behaviour”, which reveals the level at which the

individual perceives the enactment of his/her behaviour

is under his/her control (Tavousi et al., 2009).

Theory of planned Behaviour (TPB)

Theory of Planned Behaviour (Ajzen, 1985) is

recognized as an advanced version of the theory reason

action (TRA). Fishbein and Ajzen (1991) completed

obligatory by the second representation ‘incapability to

contract with Behaviours done which individuals have

imperfect optional control. TPB recognizes actual

performed Behaviour as a people's effort of a convinced

Behaviour is performed by his or her/his intention to fulfil

that Behaviour. Attitude towards the actual Behaviour,

Subjective Norm (SN) about involving in the Behaviour,

and perceived Behaviour control (PBC) are supposed to

impact intention and online learning by Behaviour in

TPB producer (Baker and White, 2010). Moreover, a

number of current researches have shown the

substantial connection between SE and Perceived

Behavioural Control (PBC) based on TPB (Taylor and

Todd, 1995; Sheng and Noe, 2010) then SE can help

turn the person's behaviour towards KS (Lin et al., 2009;

Wasko and Faraj, 2005; Lin, 2007).

Intention to Share Knowledge

According to Ajzen (1991), the Intention is the most

important cause of people’s Behaviour. The

sophisticated purpose will be achieving certain

Behaviour, the advanced chances of the authentic

enactment of that exact Behaviour.

Perceived behaviour control (PBC)

PBC includes some features that affect the KS intention

in producing the actual behaviour in terms of individual’s

abilities, accessibility, skills, and feelings; also it is

supposed that PBC is recognized by the whole complex

of accessible control beliefs (Ajzen, 1991). In this

research, PBC is associated with electronic materials,

accessibility to an EL system, a technical support

system as facility conditions, and self-efficacy in the use

of an EL system.



iii. Significant of the Study

Chiu et al. (2006) believed that the most important

problem in predicating the online learning communities

is the lock of contributions and willingness to share

knowledge in the online communities. It is necessary to

recognize the motivational factors in order to encourage

students in performing and sharing their knowledge and

experiences in learning environment (Ma, 2009; Ellis et

al., 2002; Liu, 2008). Self-efficacy is the one of important

factor that effects on knowledge sharing behavior (Lin et

al., 2009; Wasko and Faraj, 2005; Lin, 2007; Chen et

al., 2009). The current research creates empirical and

theoretical contributions about SE and KS in EL

environment. The conclusions have empirical

consequences for on-line KS in an EL system. The

examination of the practical research of EL shows that a

few studies have been funded to increase KS by

behavioral mechanisms like SE (Chen et al., 2009),

such as the requirement of students to use the

interactive connections between students in EL systems.

Previous research has concentrated on gaps in

interaction due to the lack of physicality or wave signals

compared with face-to-face communication.

Nevertheless, current, practical research indicates that

the web is an intermediate instrument that encourages

the quick construction of neighboring connections that

support the above period, and even promote

involvement in the global geography. Prior EL and KS

research has concentrated on the influence of technical

factors on the adoption and continue behavior of EL and

KS, and a have rarely explored the students’ self-

efficacy factor influencing the promotion and

encouragement offered to students regarding

participation in EL activities (Bibi Alajmi, 2008; Kamarul,

2012). This research is also significant as it utilizes both

deductive and inductive tactics. On the one hand, it

produces a theoretical structure and arranges the

constructs under the categories within that framework

while on the other hand, through an inductive approach,

it validates the constructs that could be combined in the

online KS model.

IV. Research Questions

According to the statement of the research problem

explained before, the research questions have

developed the following questions:

1. Does self-efficacy influence on knowledge sharing

intention in E-learning system?

V. Research Objectives

The purpose of the research is to discover the

relationship between the motivational knowledge sharing

factors and intention to share knowledge in an EL

system. In connection to this, the researcher’s other

purpose is to achieve the following objectives:

1. To identify the influence of self-efficacy on knowledge

sharing behaviour in E-learning system.

VI. Research Hypotheses

The questions and objectives of the current study can

be further studied through the following hypotheses:

H1. Self-Efficacy has a positive effect on Perceived

Behavioural Control in the EL system.

H2. Perceived Behavioural Control has a positive effect

on the intention to share knowledge in the EL system.

Figure 1.1 Research Model and Hypothesis

VII Open University Malaysia (OUM)

OUM was named as Open Distance Learning (ODL) in

2000. It is the seventh private university in Malaysia and

it is owned by Malaysia’s eleven public university

associations. Based on the philosophy that learning is



supposed to be democratized, OUM has concentrated

on generating a reasonable and easy corridor to Higher

Education system with significant position on flexible

entrance necessities like a student-friendly education

system, and a blended learning method with mixtures of

dissimilar forms of education. This system was planned

to perform different features based on the student’s

requirements, information and communication

technologies and internet tools.

VIII Research Method

Research methodology has many classifications, such

as, research methodology in terms of qualitative and

quantitative methods (Williams, 2007). These

approaches can be used as single and mixture method

by investigators linked in OUM. For this study, mixed

method is performed. Researcher has used both

qualitative and quantitative approaches and he also

examines and establishes the data gathered from

selected cases (Creswell, 2012). Studies show that

Quantitative and qualitative approaches are appropriate

to grow the fortes and the reducing of weaknesses of

the research methods (Johnson and Onwuegbuzie,

2004). Thus, in this method we can say that the findings

and outcomes are more valid. Furthermore,

Quantitative study shows the actuality of the cause and

effectiveness of relationships among variables. On the

other hand, qualitative study approaches to discover the

implications and outlines, consider to particularly the

activities and records carefully. There are many

researches in the Knowledge management area in

which utilized the qualitative and quantitative methods

as their key resources to collect data and to use the

features of individual behavior constantly, which are

frequently veiled (Nonaka and Takeuchi, 1995;

Chennamaneni, 2006; Jones, 2007; Bock et al., 2005;

Ma, 2009; Stewart, 2008; Vashisth et al., 2010; Jewels

and Ford, 2006).

IX Instrument Development

Researcher gathered the data in two steps. Firstly, the

online questionnaire as a survey instrument is

distributed. After the online questionnaire, the interview

questions followed to improve the survey, and to

evaluate more appropriate outcomes and to develop the

survey's validity and reliability. In addition, the

investigator applied online questionnaire as pre-test to

evaluate the 25 questions and to enhance its value. In

this research, a pre-test investigation was applied with

emphasizing on the validity of citing knowledge sharing

in the EL.

X. Interview

This research has shown the semi-structure interview

questions that are comprised with; the research was

created in 6 knowledgeable interviews selected online

and off line by the facilitators and teachers in different

faculties of OUM. The data have been gathered during

two semesters in 2012-2013 academic years. In semi-

structured interviews where some facilitators, technical

administrators, and some online teachers were in

charge of distance learning system or EL. As revealed,

the questions on the interview were open-ended; and

each interview was about 10 to 15 minutes created on

their arrangement, while some of the interviews were

voice-recoded. The knowledge sharing intention factors

and the effects of the knowledge sharing on the success

of the EL were discussed in the case study area. Table

1.1 shows the interview questions.

XI. Questionnaire

Instrument Plan

Questionnaire survey based on the research

conducted in DTPB is composed of two main sections.

In the first part of the questionnaire, respondents were

asked questions about personal characteristics, such as

sex, age, educational level, duration of study, study

courses. This section uses EL system as a moderating



variable in the study. The second section of the

questionnaire is extracted from the DTPB model.

Question components are measured as well as what the

students ask and a Likert scale was used to rank it from

very low to very high. The investigator as a viewer can

approve examination methods of collecting data and

assessments by viewing how the learners engaged in

learning activities in EL system. The five-point Likert

scale was applied to measure each paradigm which

comprised 1= strongly disagree to 5= strongly agree.

The Likert response allocated numeric values to help the

analysis of the answers.

Table 1.1 The interview questions

NO. QUESTIONS

1

Are the students learning in the EL system, frequently exchange and share

knowledge and experiences with others? If not, what factors and situations preventing

them? If you think yes, why? And what factors affect it?

2 In your opinion, are the students in E-Learning system interested in participating and

willing to share their knowledge and courses with other students?

3 In your opinion, do they (students) share knowledge and develop learning

experiences within EL system easily? Do they think that knowledge sharing is useful?

4 In your opinion, what are the individual factors that effect on the student’s attitude

toward knowledge sharing?

5 Do they (students) think that they are comfortable and can trust and share better by

EL system?

6 Is EL system compatible with students’ values, current requirements and previous

experiences?

Table 1.2 Statistics for Self-Efficacy (SE)

Table 1.3 Descriptive Statistics for Perceived Behavioral

Control

Table 1.4 Descriptive Statistics for Intention to KS (IS)



Table 1.5 the learning centers that collect questionnaire

NO. LEARNING

CENTER (BRANCH) STUDENTS

1 Bangi Learning centre 70

2 Ipoh Learning centre 85

3 Johor Learning centre 80

4 Kelantan Learning centre 68

5 OUM KL center 180

6 OUM Petaling Jaya (PJ) Learning centre

100

583

XII Construct Measures

The research theoretical model of this research is

comprised of following paradigms, the independent

variables which comprise two factors (self-efficacy,

perceived behavior control (OBC)). Additionally,

dependent variable which intention to share knowledge,

contributes in this study, There are also thirteen main

constructions of the hypothetical model that are used in

this study. Knowledge sharing intention plays a double

role: dependent and independent paradigms. The 43

questionnaire items measured the relationship between

variables; these statements were calculated according

to a 5-point Likert scale which include 1=strongly

disagree to 5= strongly agree.

XIII Descriptive statistic of the questions and variables

Descriptive statistic questioner includes quantity value,

value, mean, standard deviation drawing was taken for

each question that its results is visible in table 1.6.

Table 1.6 Descriptive statistics of the questions

Q? Min Max Mean Std. Deviation

Skewness

Kurtosis

IS1 1 5 3.94 0.77 0.778 0.819

IS2 1 5 3.73 0.88 0.882 0.121

IS3 1 5 4.14 0.68 0.681 0.722

IS4 1 5 3.61 0.85 0.853 0.48

IS5 1 5 3.44 0.83 0.837 0.646

IS6 1 5 3.71 0.82 0.822 0.525

IS7 1 5 3.46 0.86 0.868 0.436

PBC1

1 5 3.69 0.76 -0.644 1.157

PBC2

1 5 4.02 0.69 -0.524 0.755

PBC3

1 5 3.69 0.73 -0.601 1.251

PBC1

1 5 3.69 0.76 -0.644 1.157

SE1 1 5 3.72 0.76 -0.625 1.322

SE2 1 5 3.53 0.82 -0.689 0.998

SE3 1 5 3.64 0.83 -0.643 0.843

SE1 1 5 3.72 0.76 -0.625 1.322

IS: Intention to knowledge sharing Behavior, PBC:

perceived behavior control, SE: self-efficacy,

XIV Descriptive statistic of variables

Dimensions of each question are made then descriptive

statistic include standard deviation and mean is gotten

by compute device in SPSS software that it’s results are

presents in table 1.7 the results of above table defines

the people are studies have gotten advantages more

than supposed mean, once these aren’t limitation for

their learning as electronic and their condition is suitable

in terms of the dimensions, special in subjects like

attitude toward knowledge sharing (AI) with mean 4.02,

succession in electronic teaching system (ES) with

mean 3.94.

Table 1.7 Descriptive statistical of variables

Variables Mean Std.

Deviation

Intention to knowledge

sharing Behavior (IS) 3.56 0.70

Perceived Behavior

Control (PBC) 3.80 0.56

Self-Efficacy (SE) 3.63 0.70



XV Qualitative Analysis

Interviews were carried out on the system facilitators

and teachers in OUM learning system. As mentioned

earlier, the interview was done after the results from the

survey research. In order to verify the research results

from the survey method about the antecedents was

used qualitative method as a supplementary technique

with the answers from the case study that cooperate the

self-efficacy effects on the knowledge sharing intention

in the EL system. This part of the study will report the

responses of the participants in the interview and how

those responses give answers to research questions.

XVI Participant Information

According to the quantity of individual interviews that

was dependent on participants from the OUM as case

study. Since the research needs some explanations

about details of study dimensions, the interview

questions were requested that contribute by a few

participants in OUM as case study. Choosing

interviewees were beneficial and only integrated a small

from the case study (Saunders et al., 2007). The

interviewees who were conducting as individual

interviews are recommended around 10 to 15 (Hill et al.,

1997). Participants in this study consisted of 10 system

facilitators and teachers engaging in the learning

practice within the OUM e-learning system.

XVII Conclusions and recommendations

To answer the questions related to hypotheses, four

main questions were proposed and investigated. These

research questions are:

Does self-efficacy effect on knowledge

sharing intention in e-learning system?

Self-Efficacy (SE), the first effective factor of PBC, refers

to individuals’ belief that their own educational

competences, to a greater extent than others’, have a

critical function in motivating them to accomplish and

control their behaviour. Investigators have proceeded to

prove its information validity as well as its convergent

validity in predicting general motivational findings, in

terms of learners’ practice selections, effort, persistence,

and emotional reactions. SE attitude has been found to

be responsive to understated modifications in learners’

performance background, to become involved with self-

regulated education procedures, and to mediate

learners’ educational accomplishment (2000 Academic

Press). Supporting this, the eleventh hypothesis is

designed to examine the effect of Self-Efficacy on

Perceived Behavioural Control.

H1: Self-Efficacy has a positive effect on Perceived

Behavioural Control in the EL system.

Perceived Behavioural Control (PBC) is the third

effective factor which determines students’ desire for KS

in the EL system. It refers to people's perceptions of

their ability to perform a given behaviour. It also points

to the degree of individual control over transferral of

information through the EL system. The higher the

degree of control, the greater will be the desire for KS in

the EL system. In order to examine the effect of

Perceived Behavioural Control on KS among the users

of the EL system, the next and fourth hypotheses of the

research were designed.

H2. Perceived Behavioural Control has a positive

effect on the intention to share knowledge in the EL

system.

Table 1.8 Hypothesis Testing Results

NO. Relationship Hypotheses Results

1

Perceived behavioral control and intention to share knowledge

H2. The perceived behavioral control has a positive effect on the intention to share knowledge in EL system.

The findings of the research indicate that perceived behavioral control has a positive impact on intention to share knowledge.

2

Knowledge Self-Efficacy and perceived behavioral control

H1. Self-Efficacy has a positive effect on perceived behavioral control in EL system.

The findings of the research supported that Self-Efficacy has a positive impact on perceived behavioral control.



Figure 1.2 Results of Structural Modelling Analysis

XVIII Restrictions of the study

There were some limitations in the research method and

data collecting. This often happens in similar studies

done in behavioral field. There are also restrictions in

the examination of EL system in OUM as Open

University which educates through online system where

students are not required to attend classes in the

traditional classroom as in face to face education.

Secondly, the investigation of some variables in this

research like intention to share knowledge is sometimes

very difficult because the control on effective changes

on this structure is hard, for example, the application of

the whole factors of knowledge sharing Behavior in

research model. Another research limitation is the lack

of examination tools for all main factors on students’

knowledge sharing behavior in EL system. The third

limitation was to adjust factors in relation to the intention

to share knowledge in online environment that students

can use many tools and technologies based on their

skills and abilities.

XIX Recommendations for Further Study

In the other aspect of this research it is also

recommended that the relation among research

structures must be investigated for successful results as

what this current study did, for example, the

investigation of the main factors on intention to share,

where it introduced two levels of intent to share. There

are three more effective structures in each level. Thus,

the effective examination of the factor of the variable

such as Self-Efficacy on this study will approve the

student’s intent to share knowledge in EL system if

these factors and variables will be applied. And because

of this, the need to work on more studies and examining

the related theories and models in the future can be

much easier.

REFERENCE

[1]. Ajzen, I. (1985). From intentions to actions: A theory of

planned Behaviour. In J. Kuhi and J. Beckmann

(Eds.):Action—control: From cognition to Behaviour (11-

39). Heidelberg:Springer.

[2]. Ajzen, I. (1991). The Theory of Planned Behaviour.

Organizational Behaviour and Human decision Processes,

50(1), 179-211.

[3]. Artino, A. R. (2010). On-line or face-to-face learning?

Exploring the personal factors that predict students

‘choice of instructional format. The Internet and Higher

Education, 1(3), 185.

[4]. Baker, R. K. and White, K. M. (2010). Predicting

adolescents’ use of social networking sites from an

extended theory of planned Behaviour perspective.

Computers in Human Behaviour, 26, 1591-1597.

[5]. Bock, G.-W., Zmud, R. W., Kim, Y. G. and Lee, J. N.

(2005). Behavioural intention formation in KS: Examining

the roles of extrinsic motivators, social-psychological

forces, and organizational climate. MIS Quarterly, 29(1),

87-111.

[6]. Bransford, J. D., A. L. Brown, and Cocking, R.R., eds.

(2000). How People Learn. Washington, D.C., National

Academy Press.

[7]. Carr, N., and Chambers, D. P. (2006). Teacher

professional learning in an online community: The

experiences of the National Quality Schooling Framework

Pilot Project. Technology, Pedagogy and Education,

15(2), 143 - 157.

[8]. Chen, I. Y. L., Chen, N.-S., and Kinshuk, (2009).

Examining the factors influencing participants' KS

behaviour in virtual learning communities. Educational

Technology & Society, 12(1), 134-148.

[9]. Chennamaneni, A. (2006). Determinants of KS Behaviours:

Developing and Testing an Integrated Theoretical Model.

The University Of Texas, Arlington.



[10]. Chiu, C.M., Hsu, M.H. and Wang, E.T.G. (2006).

Understanding KS in virtual communities: An integration of

social capital and social cognitive theories. Decision

Support Systems 42, 1872–1888.

[11]. Creswell, J. (2012). Educational research: Planning,

conducting, and evaluating quantitative and qualitative

research (4thed.). Upper Saddle River, NJ: Pearson

Education.

[12]. Ellis, A., Hollenbeck, J., Ilgen, D., Porter, C., West, B., and

Moon, H. (2003). Team learning: Collectively connecting

the dots. Journal of Applied Psychology, 88(5), 821–835.

[13]. Fadzil, M., Latifah, L.A. (2010). Enhancing Teaching and

Learning: Development of a New E-learning Model at

Open University Malaysia. Formal Education:

Technologies for Scaling up ODL Programmes. OUM

publication.

[14]. Fadzil, M., Latifah, L.A. (2012). Factors Influencing The

Development Of Lifelong Learning Skills: Oum Tracer

Study. The 40th Anniversary of KNOU Future of ODL for

‘Knowledge Network Society’ Korea National Open

University.

[15]. Hiltz, S. R. and Turoff, M., (2005). Education goes digital:

the evolution of on-line learning and the revolution in

higher education. Communications of the ACM, 48(10):

59-64.

[16]. Honebein, P. C. (1996). Seven goals for the design of

constructivist learning environments. In B. G. Wilson (Ed.),

Constructivist learning environments: Case studies in

instructional design (11-24). Englewood Cliffs, N.J.:

Educational Technology Publications. instructional

design. Englewood Cliffs, N.J.: Educational Technology

[17]. Jewels, T. and Ford, M. (2006). Factors Influencing KS in

Information Technology Projects. e-Service Journal, 5(1),

99-117.

[18]. Johnson, R. B. and Onwuegbuzie, A. J. (2004). Mixed

Methods Research: A Research Paradigm Whose Time

Has Come. Educational researcher, 33(7), 14-27.

[19]. Kanuka, H., and Rourke, L. (2008). Exploring the Non-

Neutrality of e-learning Technologies. Technology,

Pedagogy and Education, 17(1), 5-16.

[20]. Lin, H. -F. (2007). Knowledge sharing and firm innovation

capability: An empirical study. International Journal of

Manpower, 28(3/4), 315−332.

[21]. Lin, H. F. and Lee, G. G. (2006). Effects of Socio-

Technical Factors on Organizational Intention to

Encourage KS. Management Decision, 44(1), 74-88.

[22]. Lin, M.J., Hung S.W., Chen, C.J. (2009). Fostering the

determinants of knowledge sharing in professional virtual

communities. Computers in Human Behavior,25(4), 929–

939.

[23]. Liu, M.-C., and Wang, J.-Y. (2010). Investigating

,knowledge integration in web-based thematic learning

using concept mapping assessment. Educational

Technology & Society, 13 (2), 25-39.

[24]. Liu, S. (2008). Student Interaction Experiences in

Distance Learning Courses A Phenomenological Study.

On-line Journal of Distance Learning Administration,

X1(1).

[25]. Ma, W., W., (2009). Understanding on-line KS: An

interpersonal relationship perspective. Computers &

Education, 1–10.

[26]. Nonaka, I. and Takeuchi, H. (1995). The Knowledge

Creating Company, New York: Oxford University Press.

[27]. Prawat, R. S. (1996). Constructivism, modern and

postmodern. Educational Psychologist, 31(3/4),

215.Publications.

[28]. Saunders, M., Lewis, P. and Thornhill, A. (2007).

Research Methods for Business sharing in professional

virtual communities. Computers in Human Behavior,

Students (4th Ed.). Harlow, England: Pearson Education.

[29]. Stewart, G. (2008).Factors Affecting Contribution to

Knowledge Repositories in Environments without an

Explicit Supportive Reward System. The University of the

West Indies, Trinidad and Tobago.

[30]. Tavousi M., Hidarnia A.R., Montazeri A. and Taremain F.

(2009). Are Perceived Behavioural Control and SE

Distinct Constructs? European Journal of Scientific

Research, 31(1), 44-52.

[31]. Wasko, M.M. and Faraj, S. (2000). It is what one does:

Why people participate and help others in electronic

communities of practice. Journal of Strategic Information

Systems, 9, 2-3, 155-173.

[32]. Wilson, B. G. (1996). Constructivist learning

environments: Case studies in instructional design.

Englewood Cliffs, N.J.: Educational Technology

Publications.



[33]. Xie, K. U. I., Debacker, T. K., and Ferguson, C. (2006).

Extending the traditional classroom through on-line

discussion: The role of student motivation. Journal of

Educational Computing Research, 34(1), 67-89.

[34]. Zhang, J. and Faerman, S. R. (2007). Distributed

leadership in the development of a KS system, European

Journal of Information Systems, 16, 479-493.

[35]. Zhang, J., Scardamalia, M., Lamon, M., Messina, R., and

Reeve, R. (2007). Socio-cognitive dynamics of knowledge

building in the work of 9- and 10-years-olds. Educational

Technology Research and Development, 55(2), 117-145.

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