Inteligencia Artificial Generativa (IA Gen) en la Transformación Digital de la Educación Superior una Revisión Sistemática de Literatura
Resumen
Esta revisión sistemática de la literatura analiza el impacto de la inteligencia artificial generativa (IA Gen) en la transformación digital de la educación superior. Se utilizaron los lineamientos PRISMA para garantizar un proceso riguroso, transparente y replicable. La búsqueda se realizó en Scopus, ProQuest, Science Direct y EBSCO, considerando estudios publicados entre 2019 y 2024. Se seleccionaron 129 investigaciones, en su mayoría empíricas, que abordan el uso de la IA Gen en la personalización del aprendizaje, la eficiencia educativa, la innovación pedagógica y los desafíos éticos. Los resultados evidencian que la IA Gen tiene un alto potencial para personalizar la enseñanza, automatizar tareas administrativas, generar contenidos y mejorar los procesos de evaluación. Entre los avances más relevantes se encuentran los sistemas de aprendizaje adaptativo, la retroalimentación individualizada y las plataformas interactivas. Sin embargo, también emergen preocupaciones éticas como la privacidad de los datos, el sesgo algorítmico, la dependencia tecnológica y la propiedad intelectual. Se concluye que la implementación efectiva de la IA Gen requiere una planificación estratégica, reflexión crítica y compromiso ético. Además, se recomienda desarrollar marcos regulatorios, capacitar al profesorado y mantener un enfoque centrado en el estudiante para maximizar sus beneficios en la educación superior.
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Derechos de autor 2025 Mario Rafael Quiroz Martinez
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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