Roberto Martinez-Maldonado and Jurgen Schulte
This project aims to uncover statistically significant and meaningful patterns in students’ course pathway choices and to derive individual student course-longitudinal performance indicators.
The objective is to provide support units, course and subject coordinators with longitudinal indicators that may be used to facilitate student personal-support actions (for example, on-demand or just-in-time individualised student support). The indicators may also help to support the streamlining of course and subject content. The more students can be informed about what it would take for them (individually) to master future subjects and stages in their course, the better their study experience will be and a higher overall student retention rate may be achieved. In this project, a number of educational data mining techniques will be used to find meaningful pathways of students course data.