How can we model the impact of group interactions on group outcomes? Consider a classroom context. Students interact with each other and with the teacher. What model of conversation sequencing is more likely to lead to learning? How can turns of speech be manipulated on the basis of an ideal model of interaction to maximize desirable outcomes, such as inquiry based education? Professor Ming Ming Chiu proposes in this presentation a complex methodology combining several statistical approaches to solve these dilemmas. The methdology is also presented in the paper attached below the presentation.
The presentation was given on November 2, 2015 at Purdue University as part of the Computational Social Science Talk Series at Purdue University organized by the CyberCenter under the direction of Professors Sorin Adam Matei (Brian Lamb School of Communication) and Elisa Bertino (Computer Science).
Professor Chiu is Charles R. Hicks Professor of Educational Psychology, Dept of Educational Studies, Purdue University
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Chiu, M. M. (2015). Statistical Discourse Analysis. In L. Resnick, C. Asterhan & S. Clarke’s (Eds.) Socializing Intelligence through Academic Talk and Dialogue (pp. 301-314). Washington, DC: American Educational Research Association [AERA].