Classification of Prompts to Generative AI and Relationship to Structural Understanding in Concept Map-Based History Learning

In this study, we classified the prompts that students entered to receive feedback from generative AI whilecreating concept maps with its support in a social studies history lesson. Next, we divided the student ’s structuralunderstanding of inter-event relationships within the learning unit into four levels and applied our classification itemsto examine the relationship between each level and the occurrence rates of these prompt categories. Consequently, wefound differences in the occurrence rates of prompt categories between students who had a structural understanding ofevent relationships and those who did not.These findings suggest that prompt patterns can indicate students’structuralunderstanding and inform tailored feedback.

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Publication Details

Journal
Transactions of the Japanese Society for Artificial Intelligence
Published
2025-10-31
DOI
https://doi.org/10.1527/tjsai.40-6_c-p72
Primary Topic
Educator Training and Historical Pedagogy
Type
article
Field-Weighted Citation Impact
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article

Classification of Prompts to Generative AI and Relationship to Structural Understanding in Concept Map-Based History Learning

Keitaro Tokutake, Dai Sakuma, Masao Murota
Transactions of the Japanese Society for Artificial Intelligence
Educator Training and Historical Pedagogy
article

Classification of Prompts to Generative AI and Relationship to Structural Understanding in Concept Map-Based History Learning

Keitaro Tokutake, Dai Sakuma, Masao Murota
article en

Abstract

In this study, we classified the prompts that students entered to receive feedback from generative AI whilecreating concept maps with its support in a social studies history lesson. Next, we divided the student ’s structuralunderstanding of inter-event relationships within the learning unit into four levels and applied our classification itemsto examine the relationship between each level and the occurrence rates of these prompt categories. Consequently, wefound differences in the occurrence rates of prompt categories between students who had a structural understanding ofevent relationships and those who did not.These findings suggest that prompt patterns can indicate students’structuralunderstanding and inform tailored feedback.

Transactions of the Japanese Society for Artificial IntelligenceVol. 40(6)
Toyo University (JP), Shanghai Institute for Science of Science (CN), Yamagata University Hospital (JP), Institute of Science Tokyo (JP)
Openalex Percentile: Top 58%
Educator Training and Historical Pedagogy
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Classification of Prompts to Generative AI and Relationship to Structural Understanding in Concept Map-Based History Learning — Keitaro Tokutake, Dai Sakuma, et al. · Transactions of the Japanese Society for Artificial Intelligence (2025) | TGRS Research Map | TGRS