How Recommender Systems in Technology-Enhanced Learning depend on Context

    Activity: Talk or presentation typesOral presentationProfessional

    Description

    Technology-Enhanced Learning (TEL) can roughly be differentiated into formal and non-formal learning settings. Both settings offer a rather different context that has to be taken into account by recommender systems in order to offer most suitable information to individual learners.Formal learning, being usually organized according to some curriculum, traditionally occurs in teacher-directed environments with person-to-person interactions. Non-formal learning is described as a learning phase of lifelong learners who are not participating in any formal learning context. They are acting more self-directed and they are responsible for their own learning pace and path. In addition, the learning content for their learning nowadays come from many different Web 2.0 sources like blogs, social bookmarking tools, or sildeshare. The learning process is also not designed by an institution or responsible teachers like in formal learning, but it depends to a large extent on individual preferences learners have or choices that learners take.Depending on the learning settings, the aims of TEL systems, their environmental conditions, and the tasks that they support also change. Thus, considering the way TEL context variables vary according to the adopted setting, the information needs of the targeted users change. This can greatly affect the design of recommender systems for the different learning settings.
    Period30 Nov 2009
    Event titleSTELLAR Alpine Rendez-Vous 2009: Education in the wild: contextual and location-based mobile learning in action
    Event typeWorkshop
    LocationGarmisch-Patenkirchen, Germany, Bavaria
    Degree of RecognitionInternational