{"title":"From technology adopters to creators: Leveraging AI-assisted vibe coding to transform clinical teaching and learning.","authors":"Minyang Chow, Olivia Ng","doi":"10.1080/0142159X.2025.2488353","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18643,"journal":{"name":"Medical Teacher","volume":" ","pages":"1-3"},"PeriodicalIF":3.3000,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Teacher","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1080/0142159X.2025.2488353","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Medical Teacher provides accounts of new teaching methods, guidance on structuring courses and assessing achievement, and serves as a forum for communication between medical teachers and those involved in general education. In particular, the journal recognizes the problems teachers have in keeping up-to-date with the developments in educational methods that lead to more effective teaching and learning at a time when the content of the curriculum—from medical procedures to policy changes in health care provision—is also changing. The journal features reports of innovation and research in medical education, case studies, survey articles, practical guidelines, reviews of current literature and book reviews. All articles are peer reviewed.