Abstract
In mechanics, it is important to understand the relationships between forces acting on objects. To help learners understand these relationships, a number of mechanics-based learning support systems have been developed. Many of these systems deal with drawing problems. Drawing problems require learners to draw the forces acting on objects in a given physical system using arrows. However, when the relationships between forces are complicated, learners may get stuck. It has been shown that providing auxiliary problems to learners who get stuck can be effective. An auxiliary problem is one that helps the learner understand the original problem. When a learner is presented with an auxiliary problem, they can solve that problem and use errors noticed in it to assist in solving the original problem as well. However, learning by solving auxiliary problems may confuse learners if they are not given ones that are appropriate to the original problem. In order to create appropriate auxiliary problems, it is necessary to create them using consistent rules. We have been working on the automatic generation of auxiliary problems for mechanics. Specifically, based on Mizoguchi et al.’s causal reasoning theory of force and motion, we investigated how to generate problems with consistent deletion. In this paper, we elaborate the rules for generating auxiliary problems, aiming for the automatic generation of them by the system.
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Aikawa, N., Koike, K., Tomoto, T., Horiguchi, T., Hirashima, T. (2022). Automatic Generation Rules for Auxiliary Problems Based on Causal Relationships for Force in a Mechanics Learning Support System. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information: Visual and Information Design. HCII 2022. Lecture Notes in Computer Science, vol 13305. Springer, Cham. https://doi.org/10.1007/978-3-031-06424-1_32
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DOI: https://doi.org/10.1007/978-3-031-06424-1_32
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