La Inteligencia Artificial Generativa en la Educación Superior
Una meta-revisión de estudios bibliométricos
DOI:
https://doi.org/10.62701/revedu.v13.5514Palabras clave:
Inteligencia Artificial Generativa, Educación superior, Bibliometría, Personalización del aprendizaje, Retroalimentación automatizada, Ética, Tendencias emergentesResumen
Este estudio analiza la integración de la inteligencia artificial generativa (IAG) en la educación superior, destacando su impacto en la personalización del aprendizaje, la automatización de la retroalimentación y la creación de contenidos. A través de una meta-revisión de 28 estudios bibliométricos, se identifican tendencias emergentes, desafíos éticos y metodológicos, y se proponen futuras líneas de investigación. La bibliometría se presenta como una herramienta esencial para mapear el conocimiento en este campo dinámico.
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