A Belief Net Backbone for Student Modelling
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Andes: A Coached Problem Solving Environment for Physics
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Modeling understanding level of learner in collaborative learning using bayesian network
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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In collaborative learning through the Internet, learners sometimes cannot communicate with other learners smoothly because they cannot focus on particular learners. Since a learner tends to focus on others whom he thinks understands exercise well, we have already proposed a mechanism for inferring other learners' understanding levels from their utterances using a solution network which represents understandability of knowledge contained in the exercise. However, the understandability of knowledge may differ among learners. In this paper, understanding levels for general knowledge are introduced as a permanent learner model. The permanent learner model is updated based on understanding levels acquired after each collaborative learning. Then, the understandability in the solution network is generated by using the permanent model.