A Learner-centered Semantic Web-based Architecture

In this paper the architecture of a learner-centered e-Learning system, which aims to qualify and recommend learning material using semantic web technologies, is presented. In the proposed approach, the learner has a central role in the decision-making process of the distribution of learning material. The main idea relies on gathering appropriate reputation metadata from the learning material consumers. As a result of a proper material ranking, a better matching to future searches of learners having similar profile is anticipated. An experimental implementation of the presented architecture provided interesting results that better depict the applicability and usefulness of the proposals.