ReMashed - An Usability Study of a Recommender System for Mash-Ups for Learning

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

    Research output: Contribution to conferencePaperAcademic

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    Abstract

    The following article presents a Mash-up Personal Learning Environment called ReMashed that recommends items from the emerging information of a Learning Network. In ReMashed users can specify certain Web 2.0 services and combine them in a Mash-Up Personal Learning Environment. The users can rate information from an emerging amount of Web 2.0 information of a Learning Network and train a recommender system for their particular needs. ReMashed therefore has three main goals: 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
    Publication statusPublished - 26 Oct 2009

    Keywords

    • mupple
    • mashup
    • navigation
    • recommender system
    • informal learning
    • learning networks
    • emergence
    • remashed

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