Effect of AI chatbot–assisted case-based learning on clinical reasoning in occupational therapy students: a post-test only randomized controlled trial in Parkinson’s disease education

Clinical reasoning is vital yet difficult to teach in occupational therapy education. AI chatbots may support learning, but their effect on reasoning is unclear. To determine whether chatbot-assisted case-based learning enhances occupational therapy students' cognitive, affective, and psychomotor outcomes versus traditional instructional methods. In a post-test-only randomized controlled, mixed-methods trial, 25 students (age 20–23) in a neurological rehabilitation course were allocated to a chatbot (n = 11) or classic (n = 14) group. Teams analyzed a Parkinson's disease case and drafted intervention plans; the chatbot group interacted with an AI agent simulating the client, and the classic group used conventional resources. Outcomes were a six-item written exam, analyzed with ANCOVA adjusting for Grade Point Average, and qualitative analysis of chatbot queries. Groups did not differ on total or domain-specific exam scores (p > .05). Qualitative analysis showed that chatbot queries overwhelmingly sought factual clarifications and procedural guidance, indicating that students treated the AI chiefly as an information source rather than a prompt for ethical or reflective reasoning. Chatbot-assisted learning yielded performance comparable to traditional methods. While useful for factual learning, unstructured chatbot use did not foster higher-order reasoning. Structured guidance and longitudinal research are needed to support deeper engagement and examine sustained affective benefits.Clinical Trial: NCT07045077.