Subgroup discovery in an e-learning usage study based on Moodle

This paper presents an experimental study with several subgroup discovery algorithms using data from a web-based education system. The main objective of this contribution is to extract unusual subgroups to describe possible relationships between the use of the e-learning platform and marks obtained by the students. The results obtained by the best performing algorithm, NMEEF-SD, are also presented. Finally, the most representative results obtained by this algorithm are analised, in order to obtain knowledge that can allow teachers to take actions to improve student performance.