ReMashed – Recommendations for Mash-Up Personal Learning Environments

Hendrik Drachsler, Dries Pecceu, Tanja Arts, Edwin Hutten, Lloyd Rutledge, Peter Van Rosmalen, Hans Hummel, Rob Koper

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    Abstract

    The following article presents a Mash-Up Personal Learning Environment called ReMashed that recommends learning resources from emerging information of a Learning Network. In ReMashed learners can specify certain Web2.0 services and combine them in a Mash-Up Personal Learning Environment. Learners can rate information from an emerging amount of Web2.0 information of a Learning Network and train a recommender system for their particular needs. ReMashed therefore has three main objectives: 1. to provide a recommender system for Mash-up Personal Learning Environments to learners, 2. to offer an environment for testing new recommendation approaches and methods for researchers, and 3. to create informal user-generated content data sets that are needed to evaluate new recommendation algorithms for learners in informal Learning Networks.
    Original languageEnglish
    JournalDefault journal
    Publication statusPublished - 16 Nov 2009

    Keywords

    • navigation support
    • recommender system
    • adaptation
    • informal learning
    • collaborative filtering
    • learning networks
    • Web2.0
    • remashed

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