Preparing preservice teachers for generative AI in lesson planning: a process mining study of AI mindset and tool-only training

This study investigates how different training approaches prepare preservice teachers (PSTs) for generative AI (GenAI) use in lesson planning. Thirty-three PSTs were assigned to either an AI mindset with tools training group or a tools-only group. Using process mining of GenAI interaction events, we identified two distinct usage patterns: Reflective Iterative (mindset group) and Linear Extraction (tools-only group). The mindset group exhibited more cycles of prompting, reviewing, and refining GenAI outputs, aligned with shared regulation and pedagogical reasoning. Their lesson plans scored significantly higher on a TPACK-informed rubric. These findings highlight that effective GenAI integration in education requires not just technical training but also the cultivation of critical, reflective engagement with GenAI. The study contributes to teacher education by demonstrating the impact of mindset-oriented training on GenAI-supported instructional design and provides empirical support for the Human-AI Shared Regulation of Learning (HASRL) framework.