Aplicaciones de la inteligencia artificial en la evaluación del aprendizaje en la educación superior beneficios, limitaciones y desafíos éticos
Palabras clave:
inteligencia artificial, evaluación del aprendizaje, educación superior, retroalimentación automatizada, tecnología educativaResumen
La presente revisión sistemática tuvo como objetivo analizar las aplicaciones de la inteligencia artificial (IA) en los procesos de evaluación del aprendizaje en la educación superior, identificando sus beneficios, limitaciones y desafíos actuales. Se revisaron diversas investigaciones científicas publicadas en los últimos cinco años, enfocándose en estudios que integran herramientas de IA como sistemas de retroalimentación automatizada, análisis predictivo del rendimiento estudiantil y calificación automatizada. Los resultados evidencian que la IA aporta eficiencia al proceso evaluativo, al reducir la carga docente, mejorar la retroalimentación y facilitar una evaluación más objetiva. Sin embargo, también se identifican barreras significativas, como la falta de formación docente, las desigualdades tecnológicas entre instituciones y las preocupaciones éticas relacionadas con la privacidad de los datos y la transparencia algorítmica. Además, se resalta la necesidad de un enfoque pedagógico sólido que integre la IA como apoyo y no como sustituto del juicio profesional docente. La implementación de estas tecnologías requiere políticas institucionales claras, formación continua y evaluación rigurosa de su impacto en el proceso de enseñanza-aprendizaje. Se concluye que la IA representa una herramienta con alto potencial transformador, siempre que sea aplicada de manera crítica, inclusiva y contextualizada
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Derechos de autor 2025 Roger Audes Baltazar Flores (Autor/a)
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
