Using Generative AI to Reframe Mathematical Tasks for Personalized Learning

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.

See the Resource

Previous
Previous

UpGrade: An Open Source Tool to Support A/B Testing in Educational Software

Next
Next

Using multi-agent system and evidence-centered design to integrate educator expertise within generated feedback