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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.
Sigirtmac et al. (Thu,) studied this question.