Uniendo la motivación y la IA en educación: una perspectiva de la teoría de la actividad
DOI:
https://doi.org/10.1344/der.2024.45.59-67Palabras clave:
motivación intrínseca, enfoque de actividad, Teoría de la Actividad, Inteligencia Artificial, educaciónResumen
Tras la pandemia, la investigación sobre la Inteligencia Artificial (IA) en educación ha crecido globalmente. Aunque no es un tema nuevo, pocos estudios pre-pandémicos abordaron cómo apoyar la motivación interna de los estudiantes, esencial para la calidad del aprendizaje y la retención del conocimiento. Este estudio, mediante una revisión interdisciplinaria y el marco de la Teoría de la Actividad (TA), explora qué tan abordado ha sido este tema, enfocándose en las relaciones dentro del sistema de actividad educativa, especialmente entre el Sujeto (estudiantes) y el Objeto, destacando su importancia motivacional. Se analizaron 69 artículos de Scopus desde 2020. Los resultados muestran que solo algunas relaciones están cubiertas, como Sujeto-Herramientas (interacción de estudiantes con tecnología de IA), mientras que la relación clave entre Sujeto y Objeto sigue sin explorarse. Las implicaciones prácticas sugieren desarrollar herramientas de IA que fomenten la motivación intrínseca, resaltando el significado personal. Teóricamente, se propone investigar cómo mantener la motivación intrínseca de los estudiantes en relación con la IA.
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