Sistemas automatizados para evaluar el conocimiento de los estudiantes basados en inteligencia artificial: desarrollo y verificación empírica
DOI:
https://doi.org/10.46502/issn.1856-7576/2026.20.03.9Palabras clave:
evaluación automatizada del estudiante, análisis de dominancia, educación superior, analítica del aprendizaje, retroalimentación personalizada.Resumen
El estudio tuvo como objetivo desarrollar un modelo conceptual de tres niveles de un sistema automatizado de evaluación del conocimiento basado en IA y proporcionar evidencia empírica sobre su desempeño en un contexto de educación superior. Para ello, se utilizó un diseño cuasiexperimental (pretest-postest) con la participación de 250 estudiantes de especialidades de humanidades (licenciatura: n = 163; maestría: n = 87). El conjunto de herramientas consistió en formas paralelas de la prueba de rendimiento académico (40 tareas, α = 0,83), una escala TAM adaptada. Para el análisis, se utilizaron la prueba t pareada, el análisis factorial confirmatorio, la regresión múltiple jerárquica y el análisis de dominancia. Los estudiantes demostraron un mayor rendimiento académico en el postest tras la implementación del modelo AKS. El análisis mostró una jerarquía de importancia relativa de los niveles (R² = ,61): nivel semántico-discursivo (50,8 %) > retroalimentación personalizada (31,1 %) > sintáctico-formal (18,1 %). Los estudiantes percibieron positivamente el sistema en todas las dimensiones del TAM: PU = 3,91, PEOU = 3,67, OS = 3,78. Por lo tanto, la jerarquía de predictores se convirtió en una recomendación importante para los desarrolladores del ASZ con respecto a la prioridad de las inversiones en el nivel semántico. Los hallazgos sugieren que una estrategia de implementación por fases puede representar un enfoque pedagógicamente prometedor. Los resultados son relevantes para las instituciones de educación superior que operan en formato a distancia o semipresencial.
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Derechos de autor 2026 Volodymyr Luchko, Iryna Nazarenko, Alla Horobets, Olga Serhiienko, Olena Bazyl
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
