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Using Generative AI to Reframe Mathematical Tasks for Personalized Learning

Abstract

The authors explore how generative AI can reframe mathematical tasks for personalized learning. Building on prior work showing that interest-based tasks (e.g., sports, movies, video games) boost student engagement, this study examines teachers’ use of the MagicSchool tool for K–9 students. It reports on teachers’ positive and negative experiences, discusses AI’s affordances and limitations for personalization, and evaluates the readability of AI-generated problems.

Keywords

Generative Artificial Intelligence, Personalized Mathematics Tasks, Teacher Practice

How to Cite

Beauchamp, T., Walkington, C. & Bainbridge, K., (2025) “Using Generative AI to Reframe Mathematical Tasks for Personalized Learning”, Ohio Journal of School Mathematics 99(1), 6--18. doi: https://doi.org/10.18061/ojsm.5051

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Theodora Beauchamp, Candace Walkington, Katie Bainbridge

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Authors

Theodora Beauchamp
Candace Walkington
Katie Bainbridge

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Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0

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Peer Review

This article has been peer reviewed.

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