Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/3042
Title: Automating the analysis of collaborative discourse: Identifying idea clusters
Authors: Fujita, Nobuko
Teplovs, Christopher
Issue Date: Jun-2009
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Fujita, N. & Teplovs, C. (2009). Automating the analysis of collaborative discourse: Identifying idea clusters. In Dimitracopoulou, A., O'Malley, C., Suthers, D., & Reimann, P. (Eds.), Computer Supported Collaborative Learning Practices: CSCL2009 Community Events Proceedings (pp. 162-164). Rhodes, Greece: International Society of the Learning Sciences.
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.
URI: https://doi.dx.org/10.22318/cscl2009.2.162
https://repository.isls.org//handle/1/3042
Appears in Collections:CSCL 2009

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