Enhancing the error diagnosis capability for constraint-based tutoring systems

  • Authors:
  • Nguyen-Thinh Le;Niels Pinkwart

  • Affiliations:
  • Clausthal University of Technology, Germany;Clausthal University of Technology, Germany

  • Venue:
  • AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
  • Year:
  • 2011

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Abstract

Constraint-based modelling techniques have been demonstrated a useful means to develop intelligent tutoring systems in several domains. However, when applying CBM to tasks which require students to explore a large solution space, this approach encounters its limitation: it is not well suited to hypothesize the solution variant intended by the student, and thus corrective feedback might be not in accordance with the student's intention. To solve this problem, we propose to adopt a probabilistic approach for solving constraint satisfaction problems.