Using Generative AI to Reframe Mathematical Tasks for Personalized Learning

Academic Article

Academic article exploring how generative AI can reframe mathematical tasks for personalized learning.

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Purpose/Abstract

The authors explore how generative AI can reframe mathematical tasks for personalized learning.

Building on prior work showing that interest-based tasks, such as tasks connected to sports, movies, or video games, can boost student engagement, this study examines teachers’ use of the MagicSchool tool for K–9 students.

The article reports on teachers’ positive and negative experiences using generative AI to personalize mathematics tasks.

It also discusses AI’s affordances and limitations for personalization and evaluates the readability of AI-generated problems.

Citation
Beauchamp, T., Walkington, C., & Bainbridge, K. (2025). Using generative AI to reframe mathematical tasks for personalized learning. Ohio Journal of School Mathematics.

Areas researched: Implementation/Context, Professional Learning, AI

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