Impacto de la inteligencia artificial generativa en el rendimiento académico y la autonomía de estudiantes de educación secundaria: una revisión sistemática
DOI:
https://doi.org/10.71112/c0ccex62Palabras clave:
Inteligencia artificial generativa, educación secundaria, rendimiento académico, aprendizaje autorregulado, autonomía cognitiva, revisión sistemática.Resumen
Esta revisión sistemática bajo la metodología PRISMA 2020 analiza el impacto de la Inteligencia Artificial Generativa (IAG) en el rendimiento académico y la autonomía de estudiantes de educación secundaria. Se evaluó una muestra de 32 estudios empíricos. Los resultados revelan un predominio de los modelos de lenguaje de gran escala de carácter conversacional (68.8%), seguidos de tutores inteligentes adaptativos (18.8%) y entornos multimodales (12.5%). Se constató un incremento significativo en el desempeño escolar en el 71.9% de los casos cuando existió mediación pedagógica activa, frente a un 9.4% con efectos negativos atribuibles a la copia literal. Asimismo, el 65.6% de la evidencia indica que la IAG favorece el aprendizaje autorregulado mediante el andamiaje de metas, mientras que el 34.4% advierte riesgos de dependencia cognitiva por descarga analítica desmedida (cognitive offloading). Se concluye que la efectividad de la IAG depende directamente de la intencionalidad pedagógica y del compromiso metacognitivo asumido por el estudiante.
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Derechos de autor 2026 Betsy Juliana Chávez Mera, Jhonny Leonidas Tigua Peñafiel, Rebeca Scarly Aurea Tutivén, Andrea Estefanía Arreaga Muñoz, Bélgica Anet Delgado Santos (Autor/a)
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
