Moodle-based data mining potentials of MOOC systems at the University of Szeged

Abstract

In today's world virtual online educational platforms emerge literally on daily bases and many offer MOOC-based courses. With the appearance of MOOC, educational platforms have gained an additional boost, a new aspect in their evolutionary process, which has opened a new field of research thanking to the extraction of logging information within the frames of data mining. It has become clear that educators will be able to tailor their courses by merging the two previously mentioned fields and by carrying out MOOC-based data mining, targeting pedagogical aspects. This field of research seems promising and important, thus a faculty at the University of Szeged has created its own MOOC educational platform which has been set to facilitate data mining by implementing a wide range of logging algorithms. The data would be processed through a complex Artificial Intelligence program, which, in the short term, could reveal new and exciting pedagogical findings, while in the long run, the supervisors could put together a platform that would help and notify educators about relevant information. It would become possible to create adaptive educational materials, as well. This work aims at clarifying how such platforms function and what the steps of data collection and evaluation are. I.

Machine Learning based analysis of users’ online behaviour

“…As part of a team, I participated in the development of a middle-level user behaviour logging component, presented in Kőrösi and Havasi (2017). It was built on the basis of Moodle which is an open-source, free, well-supported, popular e-learning platform.…”

“…• I was able to add a working analysis system to the weak analysis tools of the Moodle platform, that would serve well for similar portals to meet current measurement requirements. The system was published in Kőrösi and Havasi (2017).…”

“…Internet Usage -Tudatos és biztonságos internethasználat alapjai TÉBIA) and collaboration of two departments of the University of Szeged developed a middle-level user behavior logging component to collect the users' online activities (Kőrösi and Havasi, 2017;Kőrösi et al, 2018). In that study He analyzed the log data of pupils and students who were motivated by their teachers and schools to attend and complete the short (few-day-long) MOOC course.…”

“…The contributions of the second group of studies are related to the publications Kőrösi and Havasi (2017); Kőrösi et al (2018). Detailed discussion can be found in Chapter 4.…”