Integración de la inteligencia artificial generativa para el aprendizaje de fundamentos de programación: una revisión sistemática de la literatura

Autores/as

DOI:

https://doi.org/10.62697/rmiie.v3i2.78

Palabras clave:

IntInteligencia Artificial Generativa, aprendizaje, competencias, programación

Resumen

La Inteligencia Artificial Generativa (IAG) ha mostrado un potencial significativo para revolucionar el aprendizaje de la programación en niveles educativos desde primaria hasta educación superior. Por ello, con esta revisión sistemática de literatura se analiza cómo la IAG se integra en la enseñanza-aprendizaje de fundamentos de programación, destacando tanto sus ventajas como los desafíos asociados. Las herramientas de IAG, incluyendo sistemas de tutoría inteligente y entornos de programación interactivos, ofrecen personalización del aprendizaje y retroalimentación inmediata, lo que facilita un entorno educativo más adaptativo y atractivo. Sin embargo, la revisión de literatura revela brechas en la implementación práctica y en la evaluación crítica de estas tecnologías, sugiriendo la necesidad de un enfoque más holístico que considere aspectos técnicos y humanísticos en el diseño de soluciones educativas. Así, este estudio subraya la importancia de una colaboración multidisciplinar para explorar efectivamente el uso ético y eficiente de la IAG en la educación en programación.

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Citas

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Publicado

2024-05-01

Cómo citar

Chávez-Boza, B. M., & Erazo-Moreta, O. R. (2024). Integración de la inteligencia artificial generativa para el aprendizaje de fundamentos de programación: una revisión sistemática de la literatura. Revista Mexicana De Investigación E Intervención Educativa, 3(2), 5–17. https://doi.org/10.62697/rmiie.v3i2.78