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

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.