[2503.16558] Advancing Problem-Based Learning in Biomedical Engineering in the Era of Generative AI

Computer Science > Computers and Society arXiv:2503.16558 (cs) [Submitted on 20 Mar 2025 (v1), last revised 5 Mar 2026 (this version, v2)] Title:Advancing Problem-Based Learning in Biomedical Engineering in the Era of Generative AI Authors:Micky C. Nnamdi, J. Ben Tamo, Benoit Marteau, Wenqi Shi, May D. Wang View a PDF of the paper titled Advancing Problem-Based Learning in Biomedical Engineering in the Era of Generative AI, by Micky C. Nnamdi and 4 other authors View PDF HTML (experimental) Abstract:Problem-Based Learning (PBL) has significantly impacted biomedical engineering (BME) education since its introduction in the early 2000s, effectively enhancing critical thinking and real-world knowledge application among students. With biomedical engineering rapidly converging with artificial intelligence (AI), integrating effective AI education into established curricula has become challenging yet increasingly necessary. Recent advancements, including AI's recognition by the 2024 Nobel Prize, have highlighted the importance of training students comprehensively in biomedical AI. However, effective biomedical AI education faces substantial obstacles, such as diverse student backgrounds, limited personalized mentoring, constrained computational resources, and difficulties in safely scaling hands-on practical experiments due to privacy and ethical concerns associated with biomedical data. To overcome these issues, we conducted a three-year (2021-2023) case study implementing an ad...