Integrating AI into Problem-Based Learning to Enhance Pre-Service Teachers’ TPACK and Disposition Toward Mathematics Teaching

• In Event: AERA Roundtable Session Sunday 1:45 pm - Gold 4
  In Roundtable Session: Developing PBL futures

Abstract

This study explores the integration of artificial intelligence (AI) within a Problem-Based Learning (PBL) framework to enhance K–8 pre-service teachers’ technology pedagogical content knowledge (TPACK) and disposition toward mathematics teaching. Through inquiry-driven tasks grounded in real-world scenarios, over 250 pre-service teachers engaged in five AI-supported problem-solving cycles. Using mixed methods, data revealed significant gains in pre-service teachers’ disposition and TPACK in AI knowledge, problem solving, instructional approach with AI, critical thinking, and ethical awareness. Students evolved from exploratory AI users to intentional and critical evaluators of AI as a teaching tool. The study offers implications for responsible AI use in teacher education and highlights PBL-AI’s potential for cultivating problem solving, critical thinking, instructional creativity, and equitable teaching practices.

Authors

• Shuhua An, California State University - Long Beach

• Zhonghe Wu, National University

• Alberto Lazaro, California State University - Long Beach