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    ARII-eL: An Adaptive, Informal and Interactive eLearning Ontology Network

    Autor: 
    Burgos, Daniel (1)
    Fecha: 
    2016
    Palabra clave: 
    user modelling; ontology; ontology network; informal learning; adaptive learning; personalization; interaction; recommendation; WOS(2); Scopus(2)
    Tipo de Ítem: 
    conferenceObject
    URI: 
    https://reunir.unir.net/handle/123456789/9964
    DOI: 
    https://dx.doi.org/10.1016/j.procs.2010.08.014
    Dirección web: 
    https://www.sciencedirect.com/science/article/pii/S1877050910003273?via%3Dihub
    Open Access
    Resumen:
    User models - the representation of user properties, preferences, goals, etc. - are crucial in modern educational applications. Several related processes, such as recommendations and user adaptations, depend on a user model. The increasing demand for new and more complex system features has resulted in an increasing complexity of user models. Ontologies are a tool to deal with this growing complexity. Well-defined and flexible ontologies can help developers cope with the inherent difficulties. In this paper, the authors present ARII-eL, an Ontology Network for Adaptive and Informal eLearning. ARII-eL defines a user model which is flexible, adaptable and scalable. ARII-eL has been developed for use in a range of educational settings including informal and interactive learning, for which there are not so many user models available for. In addition, we show the ARII-eL ontology network and user model and one application, practical case, and the user results. The massive use of social networks, wikis, collective repositories, instant messaging services, and other social applications is moving the learning process out of classrooms into informal environments, at least as a complement to the regular lessons; and learning applications should take advantage of this tendency. This work is a step forward in that direction.
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