Publication: Vibe-coding as a Teaching Competency in the Use of Artificial Intelligence for Medical Education: A Scoping Review
Authors
Elizondo-García, Josemaria
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Publisher
Universidad de Murcia: servicio de publicaciones
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DOI
https://doi.org/10.6018/edumed.705121
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info:eu-repo/semantics/article
Description
Abstract
ntroducción: La irrupción de la Inteligencia Artificial Generativa ha dado lugar al vibe-coding, unparadigma que permite a educadores sin formación técnica desarrollar software mediante lenguajenatural. Este avance plantea la necesidad de redefinir las competencias docentes necesarias paratransitar de usuarios a creadores de herramientas educativas. Métodos: Se realizó una revisión dealcance de la literatura conforme a los lineamientos PRISMA-ScR. Se incluyeron estudiosrecuperados de las bases de datos Web of Science y Scopus que abordaran el uso del por parte de docentes en educación superior y médica. Tras el proceso de selección, se incluyeron 4publicaciones de 2025. Se aplicó un análisis temático reflexivo deductivo para clasificar loshallazgos según las dimensiones del modelo TPACK (Conocimiento Tecnológico, Pedagógico y delContenido). Resultados: El análisis cualitativo revela una reconfiguración del ConocimientoTecnológico (TK), el cual se disocia de la sintaxis de programación para centrarse en laestructuración de prompts y el diálogo iterativo con la IA. Se identificó la emergencia del rol de“clínico-desarrollador”, donde el Conocimiento del Contenido (CK) actúa como un mecanismo deauditoría indispensable para validar la precisión clínica y evitar alucinaciones en los algoritmosgenerados. El Conocimiento Tecnológico-Pedagógico (TPK) permitió a los docentes deconstruirlógicas complejas en pasos secuenciales para diseñar simuladores y herramientas personalizadas.Conclusiones: Evidencia preliminar sugiere que el vibe-coding democratiza el desarrollo desoftware educativo, permitiendo a los docentes materializar estrategias pedagógicas complejas sindependencia técnica externa. Esta competencia emergente parece exigir un dominio disciplinarrobusto para garantizar la seguridad y calidad de los recursos creados. Se recomienda fomentar lacapacitación en esta competencia emergente y desarrollar futuros estudios empíricos que evalúen elimpacto de estas herramientas en el aprendizaje estudiantil y la carga cognitiva docente
ntroduction: The emergence of Generative Artificial Intelligence has given rise to vibe-coding, aparadigm that allows educators without technical backgrounds to develop software using naturallanguage. This advancement necessitates redefining the teaching competencies required totransition from users to creators of educational tools. Methods: A scoping review of the literaturewas conducted following PRISMA-ScR guidelines. Studies retrieved from Web of Science andScopus databases addressing the use of vibe-coding by educators in higher and medical educationwere included. After the selection process, four publications from 2025 were included. A deductivereflexive thematic analysis was applied to classify findings according to the TPACK modeldimensions (Technological, Pedagogical, and Content Knowledge). Results: Qualitative analysisreveals a reconfiguration of Technological Knowledge (TK), which dissociates from programmingsyntax to focus on structuring prompts and iterative dialogue with AI. The emergence of the“clinician-developer” role was identified, where Content Knowledge (CK) acts as an indispensableauditing mechanism to validate clinical accuracy and prevent hallucinations in generatedalgorithms. Technological-Pedagogical Knowledge (TPK) enabled educators to deconstructcomplex logic into sequential steps to design simulators and personalized tools. Conclusions:Preliminary evidence suggests that vibe-coding democratizes educational software development,allowing educators to materialize complex pedagogical strategies without external technicaldependence. This competency appears to demand robust disciplinary mastery to guarantee thesafety and quality of the created resources. It is recommended to foster training in this emergingcompetency and conduct future empirical studies to evaluate the impact of these tools on studentlearning and teacher cognitive load.
ntroduction: The emergence of Generative Artificial Intelligence has given rise to vibe-coding, aparadigm that allows educators without technical backgrounds to develop software using naturallanguage. This advancement necessitates redefining the teaching competencies required totransition from users to creators of educational tools. Methods: A scoping review of the literaturewas conducted following PRISMA-ScR guidelines. Studies retrieved from Web of Science andScopus databases addressing the use of vibe-coding by educators in higher and medical educationwere included. After the selection process, four publications from 2025 were included. A deductivereflexive thematic analysis was applied to classify findings according to the TPACK modeldimensions (Technological, Pedagogical, and Content Knowledge). Results: Qualitative analysisreveals a reconfiguration of Technological Knowledge (TK), which dissociates from programmingsyntax to focus on structuring prompts and iterative dialogue with AI. The emergence of the“clinician-developer” role was identified, where Content Knowledge (CK) acts as an indispensableauditing mechanism to validate clinical accuracy and prevent hallucinations in generatedalgorithms. Technological-Pedagogical Knowledge (TPK) enabled educators to deconstructcomplex logic into sequential steps to design simulators and personalized tools. Conclusions:Preliminary evidence suggests that vibe-coding democratizes educational software development,allowing educators to materialize complex pedagogical strategies without external technicaldependence. This competency appears to demand robust disciplinary mastery to guarantee thesafety and quality of the created resources. It is recommended to foster training in this emergingcompetency and conduct future empirical studies to evaluate the impact of these tools on studentlearning and teacher cognitive load.
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Citation
Elizondo-García, J. (2026). Vibe-coding como competencia docente en el uso de Inteligencia Artificial para la Educación Médica: una revisión de alcance. Revista Española De Educación Médica, 7(2). https://doi.org/10.6018/edumed.705121
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