Inteligencia artificial generativa para autoaprendizaje en educación superiordiseño y validación de una máquina de ejemplos

  1. Sánchez-Prieto, José Carlos 1
  2. Izquierdo-Álvarez, Vanessa 1
  3. del Moral-Marcos, María Teresa 1
  4. Martínez-Abad, Fernando 1
  1. 1 Universidad de Salamanca, USAL (España)
Journal:
RIED: revista iberoamericana de educación a distancia

ISSN: 1138-2783

Year of publication: 2025

Issue Title: Educación en nuevos contextos digitales

Volume: 28

Issue: 1

Pages: 59-81

Type: Article

DOI: 10.5944/RIED.28.1.41548 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: RIED: revista iberoamericana de educación a distancia

Abstract

La Inteligencia Artificial (IA) generativa, como tecnología emergente y disruptiva, ha supuesto una revolución en la comunicación hombre-máquina. Esta nueva forma de interactuar con los dispositivos electrónicos abre interesantes posibilidades en el ámbito educativo. El objetivo de este trabajo fue analizar la eficacia de una máquina de ejemplos prácticos interactivos desarrollada con IA generativa para el estudio y repaso de contenidos en enseñanzas universitarias. Bajo un enfoque de investigación evaluativa, se llevó a cabo un proceso de diseño, validación e implementación piloto de cuatro prompts desarrollados en la herramienta ChatGPT. Tras el diseño de cada prompt, se validó su funcionamiento por parte de tres jueces expertos, que aplicaron un proceso de testeo sistemático. Los prompts definitivos fueron pilotados en una muestra de n=192 estudiantes de titulaciones de Ciencias de la Educación, que valoraron la utilidad y su satisfacción general con las máquinas de ejemplos a partir de escalas validadas en estudios previos. Los resultados del testeo mostraron un mejor desempeño de las máquinas de ejemplos con prompts más sencillos. Por otra parte, los estudiantes mostraron una satisfacción muy elevada con las máquinas, junto a una elevada percepción sobre su utilidad. Específicamente, mientras que las mujeres mostraron percepciones de utilidad más elevadas que los hombres en alguno de los indicadores medidos, la utilidad percibida fue más elevada en general en los grupos de estudiantes en los que la máquina cometió errores durante el pilotaje. A pesar de las limitaciones de la herramienta, los resultados obtenidos resultan prometedores.

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