Analysis of Effective Resource Allocation to Teachers for Educational Policy by Agent-Based Simulation

DOI Web Site
  • Yano Katsuhiro
    Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology
  • Yamada Takashi
    Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology
  • Yoshikawa Atsushi
    Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology EduLab. Inc.
  • Terano Takao
    Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology

Bibliographic Information

Other Title
  • 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
  • エージェント ・ ベース ・ シミュレーション オ モチイタ キョウイン エ ノ シゲン ハイブン ニ ヨル シサク コウカ ブンセキ

Search this article

Abstract

<p>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.</p>

Journal

Related Projects

See more

Keywords

Details 詳細情報について

Report a problem

Back to top