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Title: Quantified Measures of Online Discourse as Knowledge Building Indicators
Authors: Zhang, Jianwei
Sun, Yanqing
Issue Date: Jun-2011
Publisher: International Society of the Learning Sciences
Citation: Zhang, J. & Sun, Y. (2011). Quantified Measures of Online Discourse as Knowledge Building Indicators. In Spada, H., Stahl, G., Miyake, N., & Law, N. (Eds.), Connecting Computer-Supported Collaborative Learning to Policy and Practice: CSCL2011 Conference Proceedings. Volume I — Long Papers (pp. 72-79). Hong Kong, China: International Society of the Learning Sciences.
Abstract: This secondary data analysis examined a set of social interaction (e.g., social network patterns), content (e.g., questions, ideas), and lexical measures (e.g., academic words, domain terms) applied to a Knowledge Forum discourse database created by 22 fourth-graders as they investigated optics over a four-month period. Knowledge advancement was evaluated based on student portfolio notes focusing on the depth and breadth of their optical understanding. Correlations found between the measures of social interaction, content, and lexical usage in the discourse and the depth and breadth of student understanding help to empirically justify a set of online discourse measures that are sensitive to knowledge productivity. The results suggest a framework to inform the selection, creation, and integrated use of online discourse measures in research as well as design of automated assessment tools embedded in collaborative learning environments.
Appears in Collections:CSCL 2011

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