1. Predicting Students’ Performance on MOOC Using Data Mining Algorithms
- Author
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Sergey Nesterov, Tigran Egiazarov, and Elena M. Smolina
- Subjects
Multimedia ,business.industry ,Computer science ,Data management ,Massive open online course ,Online course ,E-learning (theory) ,ComputingMilieux_COMPUTERSANDEDUCATION ,business ,computer.software_genre ,computer ,Data mining algorithm ,Course (navigation) - Abstract
This paper describes the results of experiments in predicting students’ performance on a massive open online course (MOOC). Grade reports from MOOC “Data management” on the Russian platform openedu.ru were used for the analysis. It is well known that only a small percent of students who enrolled in MOOCs pass them through. Data mining methods could help to understand the causes of this problem. We tried to predict whether the student will finish an online course or not based on his results during the first weeks. Such prediction if it was performed early enough could help to keep students in the course.
- Published
- 2021
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