Academic journal article Educational Technology & Society

Factors Affecting Information Seeking and Evaluation in a Distributed Learning Environment

Academic journal article Educational Technology & Society

Factors Affecting Information Seeking and Evaluation in a Distributed Learning Environment

Article excerpt

Introduction

Computer-supported collaborative learning (CSCL) involves interpersonal processes by which students work together to complete a learning task designed to promote learning and intellectual discovery (Alavi, Wheeler, & Valacich, 1995). The distinguishing feature of CSCL is interaction among distributed learners. Peer-to-peer sharing of information, ideas, and knowledge is important for learners in increasing exposure to diverse problem-solving approaches, conflicting viewpoints, and different sets of knowledge. Each of these points enhances an individual's ability to recognize opportunities, to adapt, and to learn (Cohen & Levinthal, 1990). From this perspective, learning is an active, social process involving knowledge construction by community members rather than a cognitive process involving the acquisition of knowledge or skills by individuals.

Because of the fast development of communication technologies in recent decades, computer-mediated communication (CMC) has become an essential element in mediated learning environments such as distance learning (Lee, Cho, Gay, Davidson, & Ingraffea, 2003; Yeh, 2010). One of the underlying assumptions of using CMC tools in education is that learners with diverse pieces of information and multiple perspectives will interact with each other more efficiently with the help of CMC. That is, CMC participants are believed to be less bound by geographical and time barriers or other social contextual elements, and this greater freedom creates conditions for rapid information exchange among learners with diverse information and multiple perspectives.

In practice, however, previous research has consistently reported that using CMC tools in distributed learning does not always produce the expected results (Cho & Lee, 2008). For instance, distributed learning environments such as CSCL often fail to provide students with learning environments that have shared social contexts, which foster a seamless engagement in social interactions and learning (Cho, Lee, Stefanone, & Gay, 2005). This is largely because of the nature of the distributed learning environment, which prevents distributed learners from establishing a shared learning context (Huang, Jeng, & Huang, 2009).

Often, multiple-level social, psychical, and cultural boundaries divide distributed learners into discrete subgroups. These boundaries create substantial challenges for distributed learners who need to bridge the "discontinuities" (Watson-Manheim, Chudoba, & Crowston, 2002). With more of these boundaries, the "virtuality" of the team increases, creating "fault lines." "Fault lines" are hypothetical dividing lines that split a group into subgroups according to one or more social or cultural attributes such as demographic attributes, organizational affiliations, or nationalities (Lau & Murnighan, 1998).

A salient fault line causes people to categorize members of their own subgroup as an in-group and view other subgroups as out-groups. This can cause group members to communicate and share information within rather than across their subgroups (Katz & Allen, 1982). Such segregated communication and information sharing can degrade a group's ability to learn, performance, and satisfaction. As social network studies have demonstrated, strong social ties within groups can create a social circle/barrier that prevents group members from acquiring innovative and creative ideas from out-group members (Granovetter, 1973). When team members' interactions are confined to subgroups, they tend to exchange overlapping, redundant, or local information. Consequently, the existence of fault lines can significantly limit the effective exchange of information and reduce the opportunity for collaborative learning and knowledge construction.

In addition, individuals' characteristics play a significant role in the explanation and prediction of learning behavior (Jensen, 2003). …

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