E-Learning Process Characterization using data driven approaches

This paper summarizes the outcomes of different data driven analyses. The data used are authentic data coming from an European E- Learning Project. The paper is aimed at presenting the approaches used for learners' profiles characterization. Learners' profiles characterization is here intended with respect to the learning strategies used by learners from one side; from the other, with respect to different ways of non linear navigation. In both cases the focus is on the effectiveness of data driven approaches in detecting individual differences. It is shown that, in both cases, data driven approaches are able to detect such individual differences. Therefore, it can be concluded that data driven approaches are effective for learners' profiling, and that their employment can be beneficial for improving personalization of learning environments.