Load-Oriented Tutoring to Enhance Student's Explanation Understanding: An Explanation Planner and a Self-explanation Envitonment
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This paper discusses the design of an ITS to realize a load-oriented tutoring to enhance the student's explanation understanding. In the explanation understanding, it is to be hoped that a student not only memorizes the new information from an explanation, but also relates the acquired information with his/her own knowledge to recognize what it means. This relating process can be viewed as the one in which the student structures his/her knowledge with the explanation. In our ITS, we regard the knowledge-structuring activities as the explanation understanding. In this paper, we propose an explanation, called a load-oriented explanation, with the intention of applying a load to the student's knowledge-structuring activities purposefully. If the proper load is applied, the explanation can induce the student to think by himself/herself. Therefore he/she will have a chance of gaining the deeper understanding. The important point toward the load-oriented explanation generation is to control the load heaviness appropriately, which a student will bear in understanding the explanation. This requires to estimate how an explanation promotes the understanding activities and how much the load is applied to the activities. In order to provide ITS with the estimation, we have built an Explanation Effect Model, EEM for short. Our ITS consists of an explanation planner and a self-explanation environment. The planner generates the load-oriented explanation based on EEM. The system also makes a student explain the explanation understanding process to himself/herself. Such self-explanation is useful to let the student be conscious of the necessity of structuring his/her knowledge with the explanation. The self-explanation environment supports the student's self-explanation. Furthermore, if the student reaches an impasse in self-explaining, the planner can generate the supporting explanation for the impasse.
This research is supported in part by Grant-in-Aid for Scientific Research No. 05780163 from the Ministry of Education, Science and Culture of Japan.
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