[1R5-OS-10b] AI諸技術の発展に基づく学びのモデルの高度化と展望

[1R5-OS-10b-03] Development of an Automatic Generation System for Auxiliary Problems Based on Causality of Force for Mechanics

〇Nonoka Aikawa¹, Shintaro Maeda¹, Kento Koike¹, Takahito Tomoto², Tomoya Horiguchi³, Tsukasa Hirashima⁴ (1. Graduate School of Engineering, Tokyo Polytechnic University, 2. Faculty of Engineering, Tokyo Polytechnic University, 3. Graduate School of Maritime Sciences, Kobe University, 4. Graduate School of Advanced Science and Engineering, Hiroshima University)

Keywords:Auxiliary Problem, Automatic Generation, Leaning Support System

In learning, learners sometimes make mistakes on the same problem repeatedly and get stuck. Helping stalled learners with auxiliary problems can be effective. Auxiliary problems are problems that help the learner understand the original problem. The learner who is presented with an auxiliary problem can also notice errors in the original problem while solving the problem. The authors have been working on the automatic generation of auxiliary problems for mechanics. Specifically, we have studied ``how to generate problems with consistent deletion'' based on the causal inference theory of force and motion by Mizoguchi et al. and created rules for the automatic generation of auxiliary problems. In this paper, we implement the rules in a system and develop a system that can generate auxiliary problems automatically.