Examining Elementary School Pre-Service Teachers’ Use of Artificial Intelligence to Explore Differentiation in Mathematics

This study leverages both Kolb’s experiential learning theory and technological pedagogical content knowledge (TPACK) to explore elementary school pre-service teachers’ experiences using generative artificial intelligence (GenAI) to provide ideas to differentiate instruction. Findings from this exploratory study indicate that pre-service teachers (PSTs) found GenAI tools helpful and aligned to research-based approaches taught in the course. Additionally, PSTs who had more robust background knowledge made more connections to differentiating mathematics strategies with reference to a progression of supports from concrete to pictorial to abstract activities. Implications from this study include the need for teacher educators to thoughtfully consider the use of GenAI and for scholars to systematically examine the potential benefits and drawbacks of these tools.