Modeling understanding level of learner in collaborative learning using bayesian network

Authors:
Akira Komedani;Tomoko Kojiri;Toyohide Watanabe
Affiliations:
Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Nagoya, Japan;Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Nagoya, Japan;Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Nagoya, Japan
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

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Abstract

In the collaborative learning, the learner often focuses on the particular person based on the person's understanding level. If the information about particular person whom the learner focuses on is acquired automatically, the learner is able to understand the target person easily. So, it is necessary to estimate the understanding levels of others. However, in the collaborative learning environment, since the learner does not utter all the knowledge that he knows, to externalize explicitly the understanding levels of the learners is difficult. The understanding level about the knowledge which is not uttered by the learner is also estimated from the uttered information. So, in this paper, we define solution network which represents the relations of knowledge in the exercise with their strengths. When the utterance is generated, the understanding level of the uttered knowledge and its related knowledge is estimated by means of the solution network.