Probabilistic Student Modelling to Improve Exploratory Behaviour

  • Authors:

  • Andrea Bunt;Cristina Conati

  • Affiliations:

  • Department of Computer Science, University of British Columbia, Vancouver, B.C., Canada, e-mail: bunt@cs.ubc.ca;Department of Computer Science, University of British Columbia, Vancouver, B.C., Canada, e-mail: conati@cs.ubc.ca

  • Venue:
  • User Modeling and User-Adapted Interaction
  • Year:
  • 2003

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Abstract

This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learner's exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learner's exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation.