Med versus machine: Using ChatGPT in team-based learning

Abstract

To foster adaptive expertise in pre-clerkship clinical training, the use of problem-based and team-based learning has been widely implemented. However, adaptive rather than routine expertise also requires learners to respond to novel tasks and participate in self-regulation and evaluation which is challenging to incorporate into case-based learning, without significantly expanding extraneous workload on students and facilitators. Thus, we aimed to adapt an existing case-based learning session to incorporate a novel and timely clinical reasoning appraisal activity using OpenAI's ChatGPT to facilitate learning of complex topics without adding non-essential burden on participants.