Learning to identify students' relevant and irrelevant questions in a micro-blogging supported classroom

Authors:
Suleyman Cetintas;Luo Si;Sugato Chakravarty;Hans Aagard;Kyle Bowen
Affiliations:
Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Consumer Sciences and Retailing, Purdue University, West Lafayette, IN;Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN;Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN
Venue:
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Year:
2010

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Abstract

This paper proposes a novel application of text categorization for two types questions asked in a micro-blogging supported classroom, namely relevant and irrelevant questions Empirical results and analysis show that utilizing the correlation between questions and available lecture materials in a lecture along with personalization and question text leads to significantly higher categorization accuracy than i) using personalization along with question text and ii) using question text alone.