From technology adopters to creators
Leveraging AI-assisted vibe coding to transform clinical teaching and learning
Bibliographic Data
| ID | 21448263 |
|---|---|
| Authors | Minyang Chow (0009-0004-9398-7656, Nanyang Technological University), Olivia Ng (0000-0001-7573-3725, Nanyang Technological University, corresponding author) |
| Year | 2025 |
| Volume | 47 |
| Issue | 12 |
| Pages | 1927-1929 |
| Publication date | 2025-12-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Teacher (JOURNAL) |
| Journal identifiers | ISSN: 0142-159X • E-ISSN: 1466-187X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/0142159x.2025.2488353 |
| PMID | 40202513 |
| OpenAlex | W4409291664 |
| Language | EN |
| Citations received | 5 |
| References cited | 4 |
Integrating theoretical knowledge with the practical skills essential for clinical practice remains a significant challenge in clinical education. Conventional teaching strategies often fall short in preparing clinicians to navigate the unpredictable, urgent, and multifaceted nature of clinical decision-making, while also providing limited support for the development of cognitive heuristics essential to forming independent clinical judgment. To address these challenges, we introduce vibe coding, a novel AI-assisted, no-code development approach that enables educators to create interactive, customisable learning simulations without programming expertise. By prioritising rapid prototyping and iterative refinement, vibe coding shifts the focus from technical constraints to pedagogical goals, allowing educators to generate code through intuitive, conversational prompts. We applied this approach to develop two distinct applications: the Differential Diagnosis Trainer (DDT), which enhances diagnostic reasoning through randomised clinical scenarios and AI-generated feedback, and the Insulin and Blood Sugar Simulation (IBSS), which offers real-time exploration of metabolic dynamics. Both tools were built using AI-powered no-code platforms, demonstrating significant improvements in accessibility, cost-effectiveness, and scalability. We encourage educators to transition from technology adopters to creators, leveraging AI-driven platforms to develop innovative, scalable, and personalised clinical simulations that transform learning experiences and ultimately enhance patient care
Coding (social sciences) · Early adopter · Medical education · Multimedia · Sociology · Artificial Intelligence · Clinical Reasoning and Diagnostic Skills · Computer Science · Innovations in Medical Education · Medicine · Psychology · Radiology practices and education
| Unique citing works | 5 |
|---|---|
| Citations per year | 5 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |