Inteligencia Artificial en Ambientes de Aprendizaje Ubicuo: Una revisión sistemática de literatura
DOI:
https://doi.org/10.24215/18509959.37.e3Palabras clave:
Aprendizaje ubicuo, Inteligencia artificial, Revisión sistemática de literatura, Contexto de aprendizaje, Personalización, RecomendaciónResumen
El aprendizaje ubicuo (u-learning) se refiere a un aprendizaje en cualquier momento y en cualquier lugar. El u-learning se va difundiendo día a día, al punto tal que hay países donde se ha convertido en un enfoque convencional de enseñanza y aprendizaje, y muchas instituciones lo adoptan cuando los alumnos no pueden asistir a clases presenciales. Por su parte, las Ciencias de la Computación, y concretamente el campo de la Inteligencia Artificial (IA) presenta herramientas y técnicas para apoyar el crecimiento del u-learning y proporcionar recomendaciones, inferir el contexto y las situaciones de aprendizaje, generar perfiles de estudiante y adaptar el contenido, las actividades de aprendizaje, los caminos de aprendizaje, entre otras aplicaciones. El objetivo de este estudio fue realizar una revisión sistemática de trabajos de IA en entornos de aprendizaje ubicuos entre los años 2013 a 2023, con el objetivo de lograr una visión de la literatura relevante, identificar las brechas y proporcionar un alcance claro para esta área de investigación. Para ello, se aplicó un enfoque ampliamente aceptado y flexible que consta de los siguientes pasos: planificación, ejecución y resumen de resultados. Los artículos se obtuvieron de bases de datos ampliamente utilizadas, a saber, IEEExplore, ACM, Science Direct, Springer y Google Académico. Se revisaron finalmente un total de 28 publicaciones preseleccionadas para este estudio entre 993 artículos identificados a través de búsquedas en las bases de datos mencionadas. Para refinar la necesidad de la revisión se propuso un marco de análisis bidimensional, compuesto por dos vistas diferentes pero complementarias que captura un aspecto particular de los sistemas de u-learning en los que se aplica IA. A su vez cada vista se descompone en facetas que facilitan la comprensión de un aspecto particular. Considerando cada una de las facetas, los resultados obtenidos muestran que la IA se aplica principalmente para: recomendar contenido a los estudiantes en base a diferentes aspectos, detectar el entorno de aprendizaje ubicuo y reaccionar a los cambios de contextos, recomendar rutas de aprendizaje supervisadas, e inferir el nivel de conocimiento del alumno sobre un tema. Las principales técnicas de IA utilizadas resultaron ser: los agentes inteligentes, las Redes Bayesianas, las ontologías y las Reglas.
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Derechos de autor 2024 Silvina Isabel Unzaga, Elena Beatriz Durán, Margarita María Alvarez
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