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¿Si y cuándo podría la IA generativa mejorar el compromiso de aprendizaje de los estudiantes universitarios?
Fei Guo1, Lanwen Zhang2, Tianle Shi1
1School of Education, Tsinghua University, Haidian District, Beijing 100084, China.
Behavioral sciences (Basel, Switzerland)
|August 28, 2025
Resumen
El uso de IA generativa (GenAI) entre los estudiantes universitarios chinos es común, lo que afecta el compromiso de aprendizaje. Su efectividad depende del diseño del curso, con beneficios vistos en entornos de alto desafío y alto apoyo.
Área de la Ciencia:
- Tecnología educativa
- La inteligencia artificial en la educación
- Estudios de educación superior
Sus antecedentes:
- La adopción de IA generativa (GenAI) está muy extendida entre los estudiantes universitarios.
- La evidencia empírica sobre el impacto de GenAI en las experiencias de aprendizaje de los estudiantes es limitada.
- Comprender el papel de GenAI en la educación superior es crucial.
Objetivo del estudio:
- Investigar la relación entre el uso de GenAI y el compromiso de aprendizaje de los estudiantes en la educación superior china.
- Explorar cómo los diferentes entornos de aprendizaje moderan los efectos de GenAI en el compromiso.
- Proporcionar conocimientos empíricos sobre la integración efectiva de GenAI en entornos académicos.
Principales métodos:
- Datos de la encuesta de 72,615 estudiantes de pregrado en 25 universidades y colegios chinos.
- Análisis de los patrones de uso de GenAI y su correlación con el compromiso de aprendizaje cognitivo, emocional y activo.
- Examen del impacto de GenAI en diversos entornos de aprendizaje (por ejemplo, alto desafío / alto apoyo frente a bajo desafío / alto apoyo).
Principales resultados:
- Más del 60% de los estudiantes universitarios chinos utilizaron GenAI en el año académico 2023-2024, con aplicaciones académicas dominantes.
- El uso académico de GenAI se correlacionó con un mayor compromiso cognitivo y emocional, pero potencialmente disminuyó el aprendizaje activo y la motivación.
- La asociación positiva de GenAI con el compromiso fue más fuerte en los cursos de "alto desafío y alto apoyo", y negativa en los cursos de "bajo desafío y alto apoyo".
Conclusiones:
- GenAI puede mejorar el compromiso de aprendizaje de los estudiantes universitarios, particularmente en contextos académicos bien estructurados.
- La efectividad de GenAI depende del diseño de la instrucción y el papel del maestro en la creación de entornos de aprendizaje de apoyo.
- La aplicación estratégica de GenAI, guiada por principios pedagógicos, es clave para maximizar sus beneficios en la educación superior.
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