Inteligencia artificial y aprendizaje en estudiantes universitarios peruanos: revisión sistemática de la literatura científica 2019-2024
Artificial Intelligence and Learning in Peruvian University Students: Systematic Literature Review 2019-2024Contenido principal del artículo
Este estudio analizó sistemáticamente la inteligencia artificial (IA) en el aprendizaje de estudiantes universitarios peruanos mediante una revisión sistemática siguiendo PRISMA 2020. Se consultaron bases indexadas como Scopus, SciELO, Redalyc, EBSCO, ProQuest y Google Académico entre 2019-2024. De 210 artículos identificados, se seleccionaron 32 que cumplieron criterios de inclusión establecidos. La evidencia muestra que la IA personaliza la enseñanza, optimiza evaluación y retroalimentación, y amplía acceso a recursos educativos digitales. Se identifican beneficios en motivación estudiantil, desarrollo de competencias digitales y gestión del aprendizaje autónomo. Persisten limitaciones por brecha digital, capacitación docente insuficiente y dilemas éticos relacionados con privacidad y integridad académica. Los hallazgos revelan aplicaciones emergentes en sistemas tutoriales inteligentes, evaluación automatizada y aprendizaje adaptativo. La IA representa un recurso transformador para educación superior peruana, aunque requiere superar desafíos tecnológicos, pedagógicos y éticos. Esta revisión aporta un marco analítico comprensivo para políticas educativas, práctica docente y futuras investigaciones en el contexto latinoamericano.
This study systematically analyzed artificial intelligence (AI) in Peruvian university student learning through a systematic review following PRISMA 2020 guidelines. Indexed databases including Scopus, SciELO, Redalyc, EBSCO, ProQuest, and Google Scholar were consulted between 2019-2024. From 210 identified articles, 32 met established inclusion criteria. Evidence shows AI personalizes teaching, optimizes assessment and feedback, and expands access to digital educational resources. Benefits were identified in student motivation, digital competence development, and autonomous learning management. Limitations persist due to digital divide, insufficient teacher training, and ethical dilemmas related to privacy and academic integrity. Findings reveal emerging applications in intelligent tutoring systems, automated evaluation, and adaptive learning. AI represents a transformative resource for Peruvian higher education, though requiring overcoming technological, pedagogical, and ethical challenges. This review provides a comprehensive analytical framework for educational policies, teaching practice, and future research in the Latin American context.
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