From technology adopters to creators: Leveraging AI-assisted vibe coding to transform clinical teaching and learning.

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 deci...

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Publicado en:Medical Teacher Vol. 47; no. 12; pp. 1927 - 1930
Autores principales: Chow, Minyang, Ng, Olivia
Formato: questions and answers Journal Article
Publicado: Taylor & Francis Ltd Dec2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2025
      vid: 47
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      pub: Taylor & Francis Ltd
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        10.1080/0142159X.2025.2488353
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        atl: From technology adopters to creators: Leveraging AI-assisted vibe coding to transform clinical teaching and learning.
      aug:
        au:
          Chow, Minyang
          Ng, Olivia
        affil: Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
      sug:
        subj:
          Artificial Intelligence
          Simulations
          Education, Clinical
          Learning Methods
          Teaching Methods
          Educational Technology
          Education, Theory-Based
          Patient Care
          Clinical Reasoning
          Coding
          Empowerment
          Software Design
          Clinical Competence
      ab: 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.
      pubtype: Academic Journal
      doctype:
        questions and answers
        Journal Article
      ougenre: Article
    language: English
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