エージェント・ベース・シミュレーションを用いた教員への資源配分による施策効果分析

抄録

This paper makes comparisons between two educational policies, teacher allocation and teacher retraining, to see which works better to improve academic skills of students. For this purpose, an agent-based simulation model with student agents and the teacher agents is proposed. The student agents are based on academic achievement model and learning theory whereas the teacher agents have three parameters in terms of teaching skills. The main results are as follows: First, increase in experienced teachers is helpful for the students with low academic achievement. Second, teacher retraining policy improves academic achievement of the high-leveled students.