Novel Blended Learning on Artificial Intelligence for Medical Students: Qualitative Interview Study
The evaluation demonstrated that the AI module effectively generates competences regarding AI technology, fosters a critical perspective, and prepares medical students to engage with the technology in a differentiated manner. The curriculum is feasible, beneficial, and highly accepted among students, suggesting it could serve as a teaching model for other medical institutions. Given the growing number and impact of medical AI applications, there is a pressing need for more AI-focused curricula and further research on their educational impact.
Authors
- Sebastian Kühn (ORCID: https://orcid.org/0000-0002-8031-2973)
- Florian Jungmann (ORCID: https://orcid.org/0000-0003-1561-5174)
- Kim Deutsch (ORCID: https://orcid.org/0000-0002-2642-8625)
- Daniel Tolks (ORCID: https://orcid.org/0000-0001-8597-5189)
- Zoe S. Oftring
Institutions
- Philipps University of Marburg (DE)
- Johannes Gutenberg University Mainz (DE)
- Universitätsklinikum Gießen und Marburg (DE)
- MemorialCare Health System (US)
- Hamburg Institute of International Economics (DE)
- University of Rostock (DE)
Publication Details
- Journal
- JMIR Medical Education
- Published
- 2025-05-26
- DOI
- https://doi.org/10.2196/65220
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62