Abstract
Knowledge building as defined in this study is emergent collaborative learning on ill-structured tasks. Although discourses in collaborative learning have been analyzed with traditional qualitative approaches in the learning sciences field, it is difficult to capture the group dynamics. Hence, we are trying to establish a methodology for discourse analysis in collaborative learning from the perspective of complex network science. In order to conduct this study effectively, we are currently developing an application platform, called Knowledge Building Discourse Explorer (KBDeX). The goal of this project is not only to facilitate productive communication between researchers who are concerned with research on knowledge building or emergent collaborative learning, but also to encourage students to explore their own group dynamics by themselves. KBDeX is an analysis platform to visualize network structures of discourse based on the bipartite graph of words × discourse units. KBDeX can visualize them into three different network structures of: (1) students, (2) discourse units, and (3) selected words. The users can explore these three networks with its coefficients and analyze the discourse across phases or in a and stepwise way. Using discourse which has been already analyzed with a traditional qualitative approach, we will demonstrate the beneficial attributes of the KBDeX platform.
Keywords: Collaborative Learning, Discourse Analysis, Network Anasysis ;Bipartited Network, Application Platform
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