Interfaces adaptativas personalizadas para brindar recomendaciones en repositorios de objetos de aprendizaje
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Universidad Distrital Francisco José de Caldas. Colombia
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Contexto: existen muchos repositorios de recursos educativos que permiten buscar y recuperar objetos de aprendizaje, de esta forma se puede tener acceso a millones de recursos educativos; sin embargo, se requiere mejorar la presentación, visualización y satisfacción de uso de dichos objetos de aprendizaje, teniendo en cuenta las preferencias y necesidades de los estudiantes.Método: el objetivo de este artículo es incorporar una interfaz adaptativa personalizada a un sistema multiagente con el fin de recomendar objetos de aprendizaje, desde repositorios locales y remotos utilizando el perfil cognitivo de los estudiantes.Resultados: la validación del prototipo se realizó a través de un caso de estudio en el cual la interfaz adaptó tanto la presentación como la visualización de los objetos de aprendizaje a través de las preferencias, necesidades y características de los estudiantes.Conclusiones: se puede concluir que las interfaces adaptativas personalizadas demuestran su eficacia y representan entonces un gran aporte en los entornos de e-learning, debido a que modifican en tiempo real la visualización y la presentación, teniendo en cuenta el perfil cognitivo del aprendiz.
Context: There are many repositories that allow searching and retrieving learning objects, so a lot of learning resources can be accessed. However, it is required to improve the presentation and visualization of those learning resources considering the student’s preferences, needs, and cognitive features.Method: The aim of this paper is to incorporate a customized interface with an adaptive multi-agent system for learning objects recommendation from local and remote repositories based on the student’s cognitive profile.Results: The prototype validation was made through a case study in which the interface has adapted not only the presentation but the visualization of learning objects taking into account the student’s preferences, needs and cognitive features.Conclusions: We can conclude that personalized adaptive interfaces demonstrate their efficacy and represent a great contribution to e-learning environments since they modify in real time the visualization and presentation of educational resources using the student’s cognitive profile.
Context: There are many repositories that allow searching and retrieving learning objects, so a lot of learning resources can be accessed. However, it is required to improve the presentation and visualization of those learning resources considering the student’s preferences, needs, and cognitive features.Method: The aim of this paper is to incorporate a customized interface with an adaptive multi-agent system for learning objects recommendation from local and remote repositories based on the student’s cognitive profile.Results: The prototype validation was made through a case study in which the interface has adapted not only the presentation but the visualization of learning objects taking into account the student’s preferences, needs and cognitive features.Conclusions: We can conclude that personalized adaptive interfaces demonstrate their efficacy and represent a great contribution to e-learning environments since they modify in real time the visualization and presentation of educational resources using the student’s cognitive profile.
Palabras clave
Learning styles, multi-agent systems, personalized adaptive interfaces, recommendation systems, repositories of learning objects, student profiles, estilos de aprendizaje, interfaces adaptativas personalizadas, perfiles de estudiante, repositorios de objetos de aprendizaje, sistemas de recomendación, sistemas multiagente