Study objective: The objective of this study was to determine whether integrating artificial intelligence-generated simulation scenarios into problem based learning improves medical physiology students’ understanding, engagement, and early clinical reasoning. Hypothesis: We hypothesized that artificial intelligence-enabled, simulation-integrated problem based learning would increase student interaction, psychological safety, reflective capacity, and confidence in clinical decision-making compared with traditional paper-based cases. Methodology: During the Inter-Medical College Physiology Quiz 2024, twenty-five international teams of medical undergraduates (three students per team) from ten countries participated in a structured simulation-integrated physiology learning activity. Using an artificial intelligence platform (ChatGPT 3.5), each team co-created a clinical scenario following INACSL (International Nursing Association for Clinical Simulation and Learning) standards, with three progressive triggers: patient history, physical examination, and investigations. Students produced videos demonstrating pre-briefing, simulation enactment using a peer as a standardized patient, and debriefing. Topics were randomly allocated using a digital randomizer. All submissions were evaluated on a peer-reviewed rubric and a virtual oral examination. A structured questionnaire with three questions was used for participant feedback on strengths and weaknesses of this technique along with any new learning that might had taken place. Data: A total of 25 teams submitted their feedback on google-forms questions representing over 75 participating students. They were given quantitative and qualitative feedback on rubric by trained reviewers. Summary of results: Participants reported improvement in psychological safety, clinical reasoning, teamwork and engagement. They emphasized that emotional expression by peers portraying patients increased fidelity, converting low-resource settings into high-impact learning experiences. Rubric evaluations demonstrated strong performance in scenario design, physiological reasoning, and reflective debriefing. Students reported that the video-based outputs served as reusable learning resources for global physiology learners. Conclusions: Students’ interaction, understanding of concepts and clinical diagnostic skills were said to be improved without needing a simulation lab. This scalable inclusive model offers a sustainable approach for resource-limited regions, besides aligning with global priorities in physiology education. Funding sources: This project did not receive any external funding. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
Samina Malik (Fri,) studied this question.