Serious Games in a Graduate-Level Human Physiology Course

Healthcare, like most industry sectors, is facing the transformative implications of Artificial Intelligence (AI). We do not yet fully understand the benefits and pitfalls of AI, so it is critical that training in healthcare-related fields includes opportunities to learn how to leverage the former while being alert to the latter. We aim to evaluate the integration of serious games, as scenario-based teaching strategies, into a graduate-level human physiology course. Students use a publicly available large language model to diagnose a series of tailored medical case studies that have been carefully crafted to highlight the utility of AI while revealing its limitations. The course modality is online, alternating between asynchronous and synchronous instruction. Asynchronous course material includes video presentations and group discussions of peer-reviewed medical case studies, which serve to prepare the students for a tailored case study with a similar or related condition. Synchronous course meetings include an individual readiness assurance test, which covers the preparation materials, to incentivise students to develop a robust understanding of the relevant pathophysiology prior to meeting. Individuals are then grouped into randomised teams, using AI to interpret a case within a serious game framework. Teams are prompted with questions and respond using a scratch ticket-style scoring sheet that allows partial credit in a point-based game. Teams navigate hallucinated responses, apply prior knowledge, and prompt AI toward correct diagnoses. Evaluation of course participants’ attitudes and opinions of the course methods will be conducted by survey. In addition to the course, the process for developing effective case studies that fit into this model is described, and the potential for extending this strategy to an undergraduate human anatomy and physiology curriculum is also explored. Moreover, opportunities for raising ethical considerations with the use of AI in healthcare are considered. Together, this study is an effort to respond to the rapid changes AI is bringing to healthcare education and may serve as a model for highlighting the utility and pitfalls of AI in other fields.