A Preliminary Examination of the Factors for Knowledge Sharing in Technology Mediated Learning

By Hwang, Yujong | Journal of Information Systems Education, Winter 2008 | Go to article overview

A Preliminary Examination of the Factors for Knowledge Sharing in Technology Mediated Learning


Hwang, Yujong, Journal of Information Systems Education


1. INTRODUCTION

Technology-mediated learning (TML) has been defined as "an environment in which the learner's interactions with learning materials (e.g., readings, assignments, exercises), peers, and/or instructors are mediated through advanced information technologies" (Alavi and Leidner, 2001b, p.2). Since mandatory involvement requirements may not intrinsically motivate learners to achieve high quality learning (Bullen, 1998), affective commitment, psychological attachment mechanism such as identification and internalization, is an especially important determinant of TML success. Thus, affective commitment and intrinsic motivation to share knowledge are critical issues in developing successful TML and knowledge management (KM) systems. In addition, social intervention for interaction and communication in e-learning positively influence outcomes in varied dimensions of TML (Rourke and Anderson, 2002; Garrison et al., 2003; Baugher et al., 2003; Gallardo et al., 2007; Ellis, 2007). Given that effective learning requires engagement with others in the learning community (Laurillard, 2000; Rungtusanatham et al., 2004; Janicki & Steinberg, 2003; Antony and Santhanam, 2007; Bullen, 1998), these social factors should be investigated further in the TML context. Bohlken (1998) suggested that incorporating the social aspects of e-learning can enhance classroom effectiveness within a TML environment. For example, several studies suggest that in-depth learning effects are accomplished when students realize the need to learn by collaboratively sharing knowledge (Cooney, 2000; Arbaugh, 2000; Poole, 2000; Siau et al., 2006; Hopgood and Hirst, 2007).

Knowledge sharing has been an important variable in the TML and KM literature incorporating social factors (e.g., Alavi et al., 2006; Alavi and Leidner, 2001a; Bock et al., 2005; Ko et al., 2005; Wasko & Faraj, 2005; Chiu et al., 2007; Powell et al., 2007). Despite the availability of the best technologies and rich information in the knowledge organization, KM system users' motivation and commitment to sharing knowledge in the organization often determine the success or failure of KM systems (Dyer and McDonough, 2001; Malhotra and Galletta, 2003). For example, a simple system for "knowledge sharing" that was sent out with questions and email invitations to potential participants failed, without even a single user posting any message after six months (Charles, 2002). In the TML systems context, peer participation can influence the student's attitude and action toward knowledge sharing (Piccoli et al., 2001). Janz and Prasarnphanich (2003) explained the relationships among organizational climate, the level of cooperative learning that takes place between knowledge workers, and the resulting level of knowledge created by team performance and individual satisfaction levels.

Based on insights into the social factors of knowledge sharing behavior, the role of affective commitment, such as identification (relationships established and maintained among group members), for the proactive adoption of KM or TML systems is recently gaining significant interest from IS and KM researchers (e.g., Venkatesh and Speier, 2000; Malhotra and Galletta, 2005; Alavi and Leidner, 2001a). Malhotra and Galletta (2005) argued that a system user's affective commitment development was omitted in the previous research model which investigated IS adoption in the IS and KM literature. Malhotra and Galletta (2003, 2005) argued that previous KM literature focused on commitment by compliance (to gain extrinsic reward), which makes our understanding of social influence, such as social identity and self identity, and knowledge sharing behavior incomplete. Thus, this paper investigates several psychological variables that have been recently introduced into the IS and KM literature, which enables us to more fully understand the important factors and dynamic relationships involved in knowledge sharing in the TML environment.

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