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Learning to Identify Students’ Relevant and IrrelevantQuestions in a Micro-blogging Supported Classroom

Suleyman Cetintas (), Luo Si (), Sugato Chakravarty (), Hans Aagard () and Kyle Bowen ()
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Suleyman Cetintas: Purdue University
Luo Si: Purdue University
Hans Aagard: Purdue University
Kyle Bowen: Purdue University

No 1010, Working Papers from Purdue University, Department of Consumer Sciences

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.

Keywords: student in-class interaction; micro-blogging; hotseat (search for similar items in EconPapers)
JEL-codes: G21 D82 O16 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mst and nep-sea
Date: 2011-02
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Published in Lecture Notes in Computer Science, v.6095/2010

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