This chapter investigates the relationships between communication styles, social networks, and learning in a Computer-Supported Collaborative Learning (CSCL) community. Using Social Network Analysis (SNA) and longitudinal survey data, the authors analyzed how 31 distributed learners developed collaborative learning social networks, when they had work together on the design of aerospace systems using online collaboration tools. The results showed that both learner’s personality characteristics (communication styles) and structural factors (a pre-existing friendship network) significantly affected the way the learners developed collaborative learning social networks. More specifically, learners who possessed high Willingness to Communicate (WTC) or occupied initially peripheral network positions were more likely to explore new network linkages in a distributed learning environment. The authors propose that the addition of personality theory (operationalized here as communication styles) to structural analysis (SNA) contributes to an enhanced picture of how distributed learners build their social and intellectual capital in the context of CSCL.
TopIntroduction
A growing body of research has demonstrated that communication and conversation are central elements in collaborative learning environments (Harasim, Hiltz, Teles, & Turoff, 1995; Haythorthwaite, 2002). From the social network perspective, learning is a social and collective outcome achieved through seamless conversations, shared practices, and networks of social connections (Brown & Duguid, 1991). Knowledge, in this sense, is not a static object acquired by an atomic individual but is actively co-constructed through ongoing social exchanges and collaborations among multiple learners embedded in social networks (Cohen & Prusak, 1998; Lave & Wenger, 1991; Nonaka & Konno, 1998). Social networks also play instrumental roles in learning environments as a major conduit of resource and knowledge exchanges (Cho, Stefanone, & Gay, 2002) and as a source of social support and socialization for distributed learners (Haythorthwaite, 2002). Hence, the way individuals create social capital—or the way they are situated in social networks from the structuralist point of view—should significantly influence the acquisition, construction, and exchange of knowledge.
Theoretically, there are abundant discussions emphasizing the value and the impact of social networks in the studies of organizational learning (Nahaphiet & Goshal, 1998), knowledge management (Cohen & Prusak, 1998), and distance learning (Haythorthwaite, 2002). Empirically, however, very few studies have actually examined the “origins” of social networks in actual Computer-Supported Collaborative Learning (CSCL) or Cooperative Work (CSCW) settings (Millen, Fontaine, & Muller, 2002; Woodruff, 2002). In other words, relatively little research has been conducted to explicitly examine what factors influence the creation of different social networks in the context of CSCL, or why some learners occupy structurally advantageous positions than others. This is surprising, as “individual differences” have long been a central variable in educational research (Ellis, 2003; Scalia & Asckmary, 1996; Webb & Palincsar, 1996).
The aim of this study is to identify individual and structural factors that influence the way people develop emergent collaborative social and collaborative structures. In particular, we focus on how learners’ personality characteristics (operationalized here as communication styles) interact with social-structural elements of collaborative learning (a pre-existing social network) to influence learning activities in a distributed learning environment. By adding personality theory to structural analysis (SNA), we attempt to contribute to an enhanced picture of how distributed learners build their social and intellectual capital in the context of CSCL.