Research+Practice Collaboratory

Supporting Students’ Perceptions of Fraction Relevance through Personalized Content

Teomara (Teya) Rutherford
Role: Researcher
Organization: University of Delaware

Project Description:

There is evidence that personalizing math content, such as examples and practice problems, improves student perceptions of relevance, engagement, and math performance. Doing this in the classroom, however, is time-consuming and is a heavy lift in terms of creativity. Generative AI, like Chat GPT, can help with this task. Some teachers are already experimenting with Chat GPT in classrooms and noting both its potential and challenges.
We would like to understand how teachers can use Chat GPT to generate personalized fraction content for students in third through fifth grades. Based on theory and prior research, we hypothesize this content will enhance students’ perceived relevance of fractions and result in better engagement and performance.
Teachers will partner with researchers to “prompt engineer” Chat GPT to produce personalized fraction content for their students and will implement this content in their classes. Researchers and teachers will work together to design how this will be implemented and how student outcomes will be assessed.
We are looking to start this study in the 2023-2024 school year. Specific logistics will be decided between teachers and the research team.