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2021 | OriginalPaper | Chapter

Predicting Students’ Performance on MOOC Using Data Mining Algorithms

Authors : Sergey Nesterov, Elena Smolina, Tigran Egiazarov

Published in: Proceedings of International Scientific Conference on Telecommunications, Computing and Control

Publisher: Springer Singapore

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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.

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Title: Predicting Students’ Performance on MOOC Using Data Mining Algorithms
Authors: Sergey Nesterov
Elena Smolina
Tigran Egiazarov
Publisher: Springer Singapore
Book: Proceedings of International Scientific Conference on Telecommunications, Computing and Control
Print ISBN: 978-981-336-631-2

Electronic ISBN: 978-981-336-632-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-981-33-6632-9_25

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