25gma250 10.3205/25gma250 urn:nbn:de:0183-25gma2502 Meeting Abstract Papan Papan Cihan C

University Hospital Bonn, Institute for Hygiene and Public Health, Bonn, Germany

author Kamboj Kamboj Ocima O

University Hospital Bonn, Institute for Hygiene and Public Health, Bonn, Germany

author Landsberg Landsberg Marek M

University Hospital Bonn, Institute for Hygiene and Public Health, Bonn, Germany

author Molitor Molitor Ernst E

University Hospital Bonn, Institute of Medical Microbiology, Immunology and Parasitology, Bonn, Germany

author Ganschow Ganschow Rainer R

University Hospital Bonn, Department of Pediatrics, Bonn, Germany

author Raichle Raichle Nico N

University Bonn, Medical Faculty, Dean of Studies Office, Bonn, Germany

author Raupach Raupach Tobias T

University Hospital Bonn, Institute of Medical Education, Bonn, Germany

author Mutters Mutters Nico T. NT

University Hospital Bonn, Institute for Hygiene and Public Health, Bonn, Germany

author German Medical Science GMS Publishing House

Düsseldorf

610 20250908 engl This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). M0626 250 Jahrestagung der Gesellschaft für Medizinische Ausbildung (GMA) P-07 eTeaching / eLearning 1 Düsseldorf 20250908 20250910 P-07-10 TextBackground: Clinical reasoning (CR) is a critical skill for medical students to develop in order to provide high-quality patient care and reduce error rates. CR is a complex cognitive process involving data collection, cue interpretation, data analysis, planning and implementing interventions, patient communication, and reflection on decision-making. The advent of large language models (LLMs) has opened new possibilities for education. At the Institute for Hygiene and Public Health at the University Hospital Bonn, we are developing a course on CR, specifically focused on antibiotic treatment and antimicrobial resistance, using an inverted classroom format and LLMs to enhance students’ reasoning skills.Methods: In this e-learning course, students are introduced to various reasoning strategies and common biases. Virtual Patients (VPs), which are effective tools for teaching CR, have been integrated into the course. Human-curated VPs are hosted on the eCampus platform, allowing students to practice their skills. We use LLMs to generate virtual patient vignettes for student interaction. These AI-generated vignettes are reviewed by an interdisciplinary expert panel. The chat capabilities of LLMs are leveraged to simulate Patient-Doctor and Doctor-Doctor interactions, which are crucial for clinical reasoning. A feasibility study is being conducted to evaluate whether LLMs can function as tutors, testing students’ reasoning abilities, providing feedback, and assessing their performance.Results: The development of the course began in 2024. Initial results and materials will be presented at the GMA annual conference in 2025.Discussion: LLMs have the potential to transform clinical reasoning education by simulating realistic medical interactions and providing personalized feedback, thereby enhancing decision-making skills in a scalable and adaptive manner. This approach offers a pathway for medical education to better meet the needs of individual learners, especially in complex decision-making contexts like clinical reasoning 0 0 0 0