Inproceedings,
ReMashed - Recommendations for Mash-Up Personal Learning Environments
Learning in the Synergy of Multiple Disciplines, Proceedings of the EC-TEL 2009, volume 5794 of Lecture Notes in Computer Science, Berlin/Heidelberg, Springer, (October 2009)
Abstract
The following article presents an evaluation tool for recommendation algorithms and strategies for learners in informal Learning Networks. The Evaluation tool called ReMashed is intended for the evaluation of pedagogical contextualised recommender systems. It is inspired by on the MovieLens system which does similar things for movie recommendations. In ReMashed asks its users to specify certain Web2.0 sources and combine them in a Mash-Up Personal Learning Environment. The users can rate the Web2.0 sources of other members and train a recommender system for their particular needs. ReMashed therefore has three main goals: 1. to provide a recommendation system for Web2.0 sources of learners, 2. to offer researchers a system for the evaluation of recommendation algorithms and strategies for learners in informal Learning Networks, and 3. to create user-generated-content data sets for multiple learning domains that are needed for research on recommender systems for learners in informal Learning Networks.
