Abstract:

Nowadays, Learning Management Systems (LMS) collect vast amounts of data in their log files. Data mining techniques have already been applied in these log files. The usage of LMSs platforms and web applications in general, can be measured with the use of indexes and metrics. There are now appropriate indexes and metrics, which would facilitate their qualitative and quantitative measurement in LMSs. In this respect, having assessed and measured the courses' usage by the students, it is possible to mark and rank them, according to their student's activity. On the other hand, students are assessed in the final exams of the courses and they are assigned with a grade according to their performance in the course.
The purpose of the paper is to use association rule mining in order to associate the students’ usage of a typical LMS with their corresponding performance in exams and deduce useful conclusions. Some known indexes and metrics for course usage measurement are used. Apriori algorithm is also used for association. The data in which the method was applied, originated from LMS log files of the Information Management Department of TEI Kavala.
Furthermore, the application of the Apriori algorithm provided useful insights to the usage of the LMS platform. It was proved that courses with high values of interest, enrichment and homogeneity lead to higher grades in the exams. This remark is useful for an instructor, since s/he can pay more attention to the courses with low values of interest, enrichment and homogeneity. As a result, the instructor can be motivated to increase the quality and the quantity of the educational material.

Keywords:

LMS usage, exams assessment, association rule mining.