ReMashed - Recommendations for Mash-Up Personal Learning Environments

نویسندگان

  • Hendrik Drachsler
  • Dries Pecceu
  • Tanja Arts
  • Edwin Hutten
  • Lloyd Rutledge
  • Peter van Rosmalen
  • Hans G. K. Hummel
  • Rob Koper
چکیده

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.

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تاریخ انتشار 2009