An application of social network analysis to knowledge building

Paper presented at the structured poster symposium of AERA Annual Meeting 2003 Theme: Probing individual, social, and cultural aspects of knowledge building This paper is a design study that explores the use of server log data to guide knowledge building. We use the Analytic Toolkit for Knowledge Fo...

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Bibliographic Details
Main Authors: Sha, L, van Aalst, Jan
Format: Conference Object
Language:English
Published: American Educational Research Association. The Journal's web site is located at http://www.aera.net/Default.aspx?id=26 2003
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Online Access:http://hdl.handle.net/10722/57623
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Summary:Paper presented at the structured poster symposium of AERA Annual Meeting 2003 Theme: Probing individual, social, and cultural aspects of knowledge building This paper is a design study that explores the use of server log data to guide knowledge building. We use the Analytic Toolkit for Knowledge Forum™ (KF) and techniques from social network analysis to analyze participation and interactivity in two KF databases. In doing so, we connect individual measures on the use of KF features with measures that probe collaboration at a more systemic level. In this, we are attempting to move from a view of assessment that in our view is overly individual (Chan & van Aalst, in press). The first case study is drawn from a grade 4 class studying electricity and First Nations issues; the second study is drawn from a grade 9 class preparing for the International Baccalaureate Program. In each case, the results uncover useful information about participation and interactivity. In the first study, there were correlations between the use of KF features and the social network variables that deteriorated over time; there also was a lack of reciprocity in the interactions. The students in the second study used the features of KF more extensively, which was accompanied by more reciprocity. In that study there were no significant relationships between the use of KF features and the social network variables. We emphasize not the findings of the studies themselves, but argue that analyses like these be used to inform a class’s ongoing efforts to improve its knowledge building discourse. postprint