Online courses assessment through measuring and archetyping of usage data

Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, regression analysis is proposed as a first step in the methodology in order to explore how e-learning contents and characteristics of the course (such as a theory or lab course, a first- or second-year course, etc.) influence performance. Further investigation of each course, according to learners' usage, is achieved by archetypal analysis, which pinpoints the typical usage. The proposed methodology was successfully applied to LMS data from a Greek University. The results confirmed the validity of the approach and showed a relationship between the educational content which was provided and its usage by the learners.