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Team learning and knowledge management has been viewed as a form of intellectual capital that can be leveraged to create organizational value and a competitive advantage (Sense, 2003, 2007). Consequently, it essential to develop a deeper understanding of the processes teams undergo to learn, create and share knowledge. Team configurations employed by organizations depend on opportunities and constraints of the organizational context which can lead to team formation decisions such as temporarily structured teams (Staples & Zhao, 2006; Bechky, 2003), traditional intact collocated teams (Desivilya & Eizen, 2005), or geographically dispersed and technology-mediated teams (Gibson & Gibbs, 2006; Nunamaker, Reinig, & Briggs, 2009). These teams provide leverage derived from their collective knowledge and skill bases that afford execution of and completion of tasks that would otherwise exhibit greater difficulty when attempted by individuals alone (Kanawattanachal &Yoo, 2007; Littlepage et al., 2008).
In a review of research on team learning, Wilson, Goodman and Cronin (2007) argued that inconsistent definitions of “team learning” was a significant factor in the inability to effectively test it and derive a coherent and consistent research stream on the topic (cf. Edmondson, Bohmer, & Pisano, 2001; Ellis, Hollenbeck, Ilgen, & Porter, 2003; van der Vegt & Bunderson, 2005; Wong, 2004). Specific problems attributed to inconsistent findings in research on team learning include 1) inconsistency between level of theory and level of measurement (e.g., individual level measures used with team level theory), 2) omission of critical observable learning behaviors due to inaccurate construct definition, and 3) failure to look at learning as a dynamic evolving process. Wilson, Goodman, and Cronin (2007) called for a process analysis approach (i.e., assessment of discourse and behavior) in investigating team learning. By directly observing team learning behaviors, the current study seeks to identify exactly how the team learning process is either enhanced or constrained in real time. In addition, this study argues that prior research on assessing acquired knowledge have relied on post-task measures which are essentially limited to measuring explicit knowledge. In their discussion on knowledge creation theory, Nonaka and von Krogh (2009) noted that explicit knowledge is knowledge that can be uttered, formulated in sentences, and captured in drawings and writing. In contrast, tacit knowledge is rooted in action, procedures, and routines. In other words, tacit knowledge is not spelled out; instead, it is revealed through its use to perform an action. The direct observation approach used in this study addresses a gap in prior research in that it offers the opportunity to account for variation attributed to tacit knowledge (via behavioral observation) that would otherwise be overlooked. As such, the current study also addresses the need to confirm the organizational knowledge creation theory’s view that tacit and explicit knowledge are not separate but “mutually complementary” in that they dynamically interact with each other in creative activities by individuals and groups (Nonaka & von Krogh, 2009).
The purpose of this study is to extend current research on technology-mediated team performance by examining the effects of collaboration mode (collocated or technology-mediated non-collocated) on team interactions during team learning. In addition, meta-cognition (i.e., monitoring, assessment and regulation of a learning situation) in the form of task reflexivity and social reflexivity is presented to show how these behaviors mediate the effect of team learning on productivity and perceived interaction quality. The following research questions are addressed in this study: