Evaluation of the interactivity of students in virtual learning environments using a multicriteria approach and data mining

This work seeks to provide a new multicriteria approach to evaluate and classify the level of interactivity of students in learning management systems (LMS). We describe, step by step, the complete methodological development process of the evaluation model as well as detailing the results obtained when applying it to a higher education teaching experience. This research demonstrates that the combined use of multicriteria decision methodologies and data mining prove to be particularly suitable for identifying behavioural patterns of the users through the analysis of records generated in LMS. The results reveal that the behavioural patterns in LMS offer certain indicators as to students’ academic performance, although the study does not permit to state that those students who adopt passive attitudes in these spheres may necessarily produce low academic performance.