A Tool for Online Education Processes Digital Traces Analysis

In recent years online education is becoming more and more popular. Thousands of MOOCs or massive open online courses are being provided at dozens of different platforms. Leading universities joining this trend in publishing their courses. In some universities distance learning is becoming a part of curriculum. However, the scientific approaches behind creating the course material and students’ trajectories in online courses are still developing. Distance learning poses new challenges for adapting traditional education techniques. To understand better real users’ behaviour via studying their interactions with leaning management systems, that are providing these courses, educational processes can be studied more closely by the means of data science techniques. This work is focused on application of data and process mining methods to event log data from e-learning courses management systems. In this paper a tool is implemented that will help researches analyse this data from the point of view of how certain data correlations are affected by possible patterns of students’ behaviour. The paper contains 80 pages, 5 chapters, 34 figures and 35 references. Keywords: educational process mining, case clustering.