Collaborative Recommendation of E-Learning Resources: An Experimental Investigation.

Repositories with educational resources can support the formation of online learning communities by providing a platform for collaboration. Users (e.g. teachers, tutors and learners) access repositories, search for interesting resources to access and use, and in many cases, also exchange experiences and opinions. A particular class of online services that take advantage of the collected knowledge and experience of users are collaborative filtering ones. The successful operation of such services in the context of real-life applications requires careful testing and parameterization before their actual deployment. In this paper, the case of developing a learning resources' collaborative filtering service for an online community of teachers in Europe was examined. More specifically, a data set of evaluations of learning resources was collected from the teachers that use the European Schoolnet's learning resource portal. These evaluations were then used to support the experimental investigation of design choices for an online collaborative filtering service for the portal's learning resources. A candidate multi-attribute utility collaborative filtering algorithm was appropriately parameterized and tested for this purpose. Results indicated that the development of such systems should be taking place considering the particularities of the actual communities that are to be served.