Inteligencia artificial generativa (IAG) en la enseñanza de la Física: una revisión sistemática de literatura
Resumen
La IAG ha comenzado a incorporarse en la enseñanza de la Física, pero la evidencia empírica disponible sigue siendo fragmentaria. Este estudio presenta una revisión sistemática de literatura, complementada con un análisis bibliométrico descriptivo, sobre aplicaciones de IAG en contextos formales de enseñanza de la Física entre 2018 y 2025. La búsqueda se realizó en Web of Science, Scopus, IEEE Xplore, ERIC y OpenAlex, siguiendo las directrices PRISMA 2020. Se extrajeron datos sobre tipo de herramienta, contenidos físicos abordados, nivel educativo, diseño metodológico y resultados de aprendizaje. Los hallazgos muestran un campo emergente, con crecimiento marcado a partir de 2023, concentrado en experiencias que utilizan modelos de lenguaje de gran escala como apoyo a la programación de simulaciones, la realización de prácticas de laboratorio y la visualización de fenómenos cuánticos en entornos inmersivos. Con este estudio, se lograron identificar lagunas en torno a evaluaciones controladas a gran escala, impactos sostenidos en el aprendizaje y marcos pedagógicos y éticos explícitos para integrar la IAG en el currículo de Física.
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Derechos de autor 2026 Angel Leonel Ortiz Herrera , Karina Mariela Figueroa Mora
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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