WEB USAGE MINING APPROACH TO DETECT STUDENT’S COLLABORATIVE SKILLS

Authors

  • ELENA B. DURÁN National University of Santiago del Estero, Argentina
  • ANALÍA AMANDI UNICEN University, CONICET, Argentina

Keywords:

Web Usage Mining, association rules, collaborative learning, student model, collaborative profile

Abstract

An effective collaboration in learning environments involves a set of skills that students must learn and cultivate. Detecting the contexts in which students apply these skills facilitates personalized assistance in learning environments during the learning process. This work introduces a method to detect collaborative behavior patterns automatically. It is based on Web Usage Mining techniques and allows us to identify contexts in which collaborative skills are applied. The patterns are discovered using association rules and then are used to update a Collaborative Profile in a Collaborative and Dynamic Student Model. The method was validated with simulation techniques and the results obtained suggest that Web Usage Mining is an effective method for detecting collaborative profiles in distance learning environments.

 

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Published

2009-10-28

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