Cognitive modeling and intelligent tutoring
Artificial Intelligence - Special issue on artificial intelligence and learning environments
A role for AI in education: using technology to reshape education
Journal of Artificial Intelligence in Education
Individualized tutoring using an intelligent fuzzy temporal relational database
International Journal of Man-Machine Studies
Case-based reasoning
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Probabilistic Student Models: Bayesian Belief Networks and Knowledge Space Theory
ITS '92 Proceedings of the Second International Conference on Intelligent Tutoring Systems
A Web-Based Intelligent Tutoring System Using Hybrid Rules as Its Representational Basis
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
The Knowledge Engineering Review
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The student model is the key to providing adequate assistance in teaching and adaptive instruction by Intelligent Tutoring Systems (ITS). Student modelling has been recognized as a complex and difficult but important task by researchers. We propose a new approach to student modelling based on Case-Based Reasoning (CBR), which is simple and does not require computationally expensive inference algorithms. This paper presents the application of this approach in developing an ITS, which analyzes the student's problem solving ability in order to obtain the knowledge component of the student model. We apply the formalism of Graph with Classified Concepts and Relations (GCR), an extended model of conceptual graph previously defined by us, to represent the problems, the cases, and the knowledge component of the student model in such systems.