Mining Data and Modelling Social Capital in Virtual Learning Communities

Authors:
Ben K. Daniel;Gordon I. McCalla;Richard A. Schwier
Affiliations:
ARIES Research Laboratory, Department of Computer Science, University of Saskatchewan;ARIES Research Laboratory, Department of Computer Science, University of Saskatchewan;Educational Communication and Technology, University of Saskatchewan, 3 Campus Drive, S7N 5A4, Saskatoon, Canada
Venue:
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Year:
2005

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Abstract

This paper describes the use of content analysis and Bayesian Belief Network (BBN) techniques aimed at modelling social capital (SC) in virtual learning communities (VLCs). An initial BBN model of online SC based on previous work is presented. Transcripts drawn from two VLCs were analysed and inferences were drawn to build scenarios to train and update the model. The paper presents three main contributions. First, it extends the understanding of SC to VLCs. Second; it offers a methodology for studying SC in VLCs. Third the paper presents a computational model of SC that can be used in the future to understand various social issues critical to effective interactions in VLCs.