LOAD-ORIENTED TUTORING TO ENHANCE STUDENTS EXPLANATION UNDERSTANDING - AN EXPLANATION PLANNER AND A SELF-EXPLANATION ENVIRONMENT

This paper discusses the design of an ITS to realize a load-oriented t utoring to enhance the student's explanation understanding. In the exp lanation understanding, it is to be hoped that a student not only memo rizes the new information from an explanation, but also relates the ac quired information with his/her own knowledge to recognize what it mea ns. This relating process can be viewed as the one in which the studen t structures his/her knowledge with the explanation. In our ITS, we re gard the knowledge-structuring activities as the explanation understan ding. In this paper, we propose an explanation, called a load-oriented explanation, with the intention of applying a load to the student's k nowledge-structuring activities purposefully. If the proper load is ap plied, the explanation can induce the student to think by himself/hers elf. Therefore he/she will have a chance of gaining the deeper underst anding. The important point toward the load-oriented explanation gener ation 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 th e estimation, we have built an Explanation Effect Model, EEM for short . Our ITS consists of an explanation planner and a self-explanation en vironment. The planner generates the load-oriented explanation based o n EEM. The system also makes a student explain the explanation underst anding process to himself/herself. Such self-explanation is useful to let the student be conscious of the necessity of structuring his/her k nowledge with the explanation. The self-explanation environment suppor ts the student's self-explanation. Furthermore, if the student reaches an impasse in self-explaining, the planner can generate the supportin g explanation for the impasse.