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espanolEl objetivo de este articulo es proponer un metodo hibrido de recomendacion adaptativa de objetos de aprendizaje, el cual debe inicialmente realizar la seleccion de caracteristicas del perfil del estudiante que mejor lo definan. Los sistemas de recomendacion hibrida de materiales educativos digitales apoyan procesos de aprendizaje virtual y ayudan a los estudiantes a encontrar recursos relevantes que se adapten a sus necesidades y preferencias. Se seleccionan los algoritmos de recomendacion que se van a aplicar, seguido de la eleccion en la combinacion de los resultados de esas tecnicas. Finalmente, se evalua la integracion de tecnicas teniendo en cuenta la relevancia que se obtiene de las recomendaciones. Se puede concluir que al utilizar sistemas adaptativos de recomendacion hibrida se mejoran los resultados, especialmente cuando la combinacion incluye la tecnica de filtrado por conocimiento. EnglishThe aim of this paper is to propose a hybrid method for adaptive recommendation of learning objects that initially performs a selection of characteristics from the student profile that best define it. Hybrid recommendation systems of digital educational materials support virtual learning processes and help students finding relevant resources that are adapted to their needs and preferences. Then, the recommendation algorithms are selected and applied, followed by the choice of how to combine the results of these techniques. Finally, the integration of techniques is evaluated considering the relevance obtained by applying the recommendation techniques. It can be concluded that using adaptive hybrid recommendation systems, improves the generation of relevant results, especially when the combination should include the knowledge-based filtering technique.

Método Híbrido de Recomendación Adaptativa de Objetos de Aprendizaje basado en Perfiles de Usuario