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

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

    31 Downloads (Pure)

    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
    Title of host publicationLearning in the Synergy of Multiple Disciplines
    Subtitle of host publicationEC-TEL 2009
    DOIs
    Publication statusPublished - 16 Nov 2009

    Publication series

    SeriesLecture Notes in Computer Science
    Volume5794
    ISSN0302-9743

    Keywords

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

    Fingerprint

    Dive into the research topics of 'ReMashed – Recommendations for Mash-Up Personal Learning Environments'. Together they form a unique fingerprint.

    Cite this