Dynamic Educational e-Content Selection Using Multiple Criteria in Web-based Personalized Learning Environments

In this paper we present the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects’ educational description. In this way, selection of educational content is based on dynamic data input collected at the time of the decision. This methodology is studied in the context of an agent-based framework for educational content brokering, and is engaged by the broker agents recommending learning objects to learners, according to their cognitive style.