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
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
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Published in Lecture Notes in Computer Science, v.6095/2010
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Persistent link: /RePEc:csr:wpaper:1010
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