Metodologías activas con IA generativa y aprendizaje significativo: una revisión sistemática
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https://doi.org/10.5281/zenodo.23221171Palabras clave:
Metodologías con IA, aprendizaje significativo, revisión sistemáticaResumen
La incorporación de inteligencia artificial generativa en la educación superior abrió nuevas posibilidades para desarrollar metodologías activas, aunque su contribución al aprendizaje significativo requirió un examen más preciso. Esta investigación tuvo como objetivo realizar una revisión sistemática y bibliometría de la producción científica sobre metodologías activas potenciadas por inteligencia artificial generativa y su relación con el aprendizaje significativo en el ámbito universitario. Se desarrolló un estudio documental analítico conceptual y cuantitativo. La búsqueda se realizó entre febrero y mayo de 2026 en Scopus, Web of Science y SciELO, y consideró publicaciones aparecidas desde 2017 hasta mayo de 2026. Se siguieron las directrices PRISMA 2020 para documentar la identificación y selección de los estudios. El análisis bibliométrico examinó la evolución temporal de las publicaciones, la afiliación del primer autor y las revistas científicas; la lectura de los artículos permitió caracterizar las estrategias pedagógicas y los resultados de aprendizaje abordados. Se observó una mayor concentración de publicaciones en 2024, así como una distribución de los trabajos entre instituciones de diferentes contextos geográficos y revistas especializadas en educación y tecnología. Los estudios examinaron usos de la inteligencia artificial generativa en tutorías, actividades colaborativas y procesos de retroalimentación, pero emplearon criterios distintos para valorar el aprendizaje. Se concluyó que su integración en metodologías activas ofreció oportunidades para enriquecer las experiencias universitarias; sin embargo, la participación o el rendimiento no demostraron por sí solos un aprendizaje significativo.
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