Effects of the ISIS Recommender System for Navigation Support in Self-Organized Learning Networks

Hendrik Drachsler, Hans Hummel, Bert Van den Berg, Jannes Eshuis, Wim Waterink, Rob Nadolski, Adriana Berlanga, Nanda Boers, Rob Koper

    Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review

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    Abstract

    The need to support users of the Internet with the selection of information is becoming more important. Learners in complex, self-organising Learning Networks have similar problems and need guidance to find and select most suitable learning activities, in order to attain their lifelong learning goals in the most efficient way. Several research questions regarding efficiency and effectiveness deal with adequate navigation support through recommender systems. To answer some of these questions an experiment was set up within an Introduction Psychology course of the Open University of the Netherlands. Around 250 students participated in this study and were monitored over an experimental period of four months. All were provided the same course materials, but only half of them were supported with a personalized recommender system. This study examined the effects of the navigation support on the completion of learning activities (effectiveness), needed time to comply them (efficiency), actual use of and satisfaction with the system, and the variety of learning paths. The recommender system positively influenced all measures, by having significant effects on efficiency, satisfaction and variety.
    Original languageEnglish
    Title of host publicationProceedings of Special Track on Technology Support for Self-Organised Learners
    Publication statusPublished - 3 Mar 2008

    Publication series

    SeriesCEUR Workshop Proceedings
    ISSN1613-0073

    Keywords

    • self-organized learning
    • informal learning
    • learning networks
    • navigation supportNavigation
    • personalised recommender systems
    • collaborative filtering
    • ontology
    • recommendation strategy
    • user profiling

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