Inteligencia artificial generativa en la educación: un análisis bibliométrico
DOI:
https://doi.org/10.18800/educacion.202601.A008Palabras clave:
Bibliometría, Competencia, Educación, Inteligencia artificial generativaResumen
Este artículo analiza la aplicación de la Inteligencia Artificial Generativa (IAGen) en la educación mediante un enfoque bibliométrico y cualitativo. La investigación identifica temas emergentes y destaca los impactos de la IAGen en contextos educativos. Se utilizaron datos de la base Scopus, analizados con VOSviewer, Gephi y Bibliometrix para examinar coocurrencias de palabras clave, temas centrales y artículos más citados. Los resultados se agruparon en tres clústeres: ChatGPT, Inteligencia Artificial Generativa y Educación Tecnológica, abordando cuestiones de ética, integridad académica y transformación digital. El análisis muestra que, aunque la IAGen ofrece oportunidades como mayor accesibilidad y eficiencia, también genera preocupaciones sobre sesgos, privacidad y pérdida de habilidades críticas. Este estudio aporta al entendimiento de las implicaciones de la IAGen en la educación y brinda perspectivas para futuras investigaciones y prácticas.
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