MOT 2.0: A Case Study on the Usefuleness of Social Modeling for Personalized E-Learning Systems

In this paper, we report on our findings from the first evaluation of MOT 2.0, an Adaptive Web 2.0 e-learning tool, which supports: 1) collaborative authoring (i.e. editing content of other users, describing content using tags, rating, commenting on the content, etc); 2) authoring for collaboration (i.e., adding author activities, such as defining groups of authors, subscribing to other authors, communication between authors, etc); 3) group-based adaptive authoring via group-based privileges; 4) social annotation i.e., tagging, rating, and feedback on the content via group-based privileges; 5) adaptive authoring, by recommending related content and/or other authors; adaptive delivery based on users' activities. Our main contributions are: 1) defining a new social layer in LAOS, a five-layer model for generic adaptive hypermedia authoring; 2) removing the barrier between tutors, learners and authors, which all become authors, with different sets of privileges; 3) adding the power of group-based authoring to the course creating.