Automating the analysis of collaborative discourse: identifying idea clusters

Authors:
Nobuko Fujita;Christopher Teplovs
Affiliations:
University of Toronto, Toronto, ON, Canada;University of Toronto, Toronto, ON, Canada
Venue:
CSCL'09 Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 2
Year:
2009

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Abstract

This poster explores CSCL practices relating to the use of a tool that employs information visualization techniques and large-scale text processing and analysis to complement qualitative analysis of collaborative discourse. Results from latent semantic analysis and qualitative analysis of online discussion transcripts are compared. Findings suggest that such tools that automate analyses of large text-based data sets can offer CSCL researchers a quantitative and unbiased way of identifying a subset of data to study in depth.