Examining Teacher-AI Teaming Through the Use of a Generative AI Assessment Creation Tool in High School Mathematics Classrooms (Poster 49)

• In Event: AERA Poster Session Sunday 8:00 a.m.
  In Poster Session: Integrating Generative AI in Education: Challenges and Opportunities

Abstract

This paper describes research examining high school mathematics teachers’ use of [MLLM], a Generative AI tool, in their teaching. Given natural language prompts (from teachers), [MLLM] generates the code (in WeBWorK format) for the corresponding interactive, isomorphic auto-gradable along with hints and a solution. Writing such code would normally require programming skills. Working with teachers in a dual-enrollment program from high schools across Indiana, this project studies teachers’ experiences using [MLLM], on prompt engineering, and the factors that influence these experiences. The paper also examines the impact of this experience on teachers’ math practice and their views about AI. The promising results have important implications for AI in education, and the science of teacher-AI teaming and prompt engineering.

Authors

• Shuchi Grover, Looking Glass Ventures

• Brittany Runge, Indiana University