Predicting Students’ Performance on MOOC Using Data Mining Algorithms

Sergey Nesterov; Elena Smolina; Tigran Egiazarov

doi:10.1007/978-981-33-6632-9_25

Predicting Students’ Performance on MOOC Using Data Mining Algorithms

Sergey Nesterov^*, Elena Smolina, Tigran Egiazarov

^*Corresponding author for this work

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019
Editors	Nikita Voinov, Tobias Schreck, Sanowar Khan
Publisher	Springer Science+Business Media
Pages	285-292
Number of pages	8
ISBN (Print)	9789813366312
DOIs	https://doi.org/10.1007/978-981-33-6632-9_25
Publication status	Published - 29 Apr 2021
Externally published	Yes
Event	1st International Scientific Conference on Telecommunications, Computing and Control, TELECCON 2019 - St. Petersburg, Russian Federation Duration: 18 Nov 2019 → 19 Nov 2019

Publication series

Series	Smart Innovation, Systems and Technologies
Volume	220
ISSN	2190-3018

Conference

Conference	1st International Scientific Conference on Telecommunications, Computing and Control, TELECCON 2019
Country/Territory	Russian Federation
City	St. Petersburg
Period	18/11/19 → 19/11/19

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Access to Document

10.1007/978-981-33-6632-9_25

Cite this

Nesterov, S., Smolina, E., & Egiazarov, T. (2021). Predicting Students’ Performance on MOOC Using Data Mining Algorithms. In N. Voinov, T. Schreck, & S. Khan (Eds.), Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019 (pp. 285-292). Springer Science+Business Media. https://doi.org/10.1007/978-981-33-6632-9_25

Nesterov, Sergey ; Smolina, Elena ; Egiazarov, Tigran. / Predicting Students’ Performance on MOOC Using Data Mining Algorithms. Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019. editor / Nikita Voinov ; Tobias Schreck ; Sanowar Khan. Springer Science+Business Media, 2021. pp. 285-292 (Smart Innovation, Systems and Technologies, Vol. 220).

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title = "Predicting Students{\textquoteright} Performance on MOOC Using Data Mining Algorithms",

abstract = "This paper describes the results of experiments in predicting students{\textquoteright} 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.",

author = "Sergey Nesterov and Elena Smolina and Tigran Egiazarov",

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series = "Smart Innovation, Systems and Technologies",

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Nesterov, S, Smolina, E & Egiazarov, T 2021, Predicting Students’ Performance on MOOC Using Data Mining Algorithms. in N Voinov, T Schreck & S Khan (eds), Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019. Springer Science+Business Media, Smart Innovation, Systems and Technologies, vol. 220, pp. 285-292, 1st International Scientific Conference on Telecommunications, Computing and Control, TELECCON 2019, St. Petersburg, Russian Federation, 18/11/19. https://doi.org/10.1007/978-981-33-6632-9_25

Predicting Students’ Performance on MOOC Using Data Mining Algorithms. / Nesterov, Sergey; Smolina, Elena; Egiazarov, Tigran.
Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019. ed. / Nikita Voinov; Tobias Schreck; Sanowar Khan. Springer Science+Business Media, 2021. p. 285-292 (Smart Innovation, Systems and Technologies, Vol. 220).

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

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Nesterov S, Smolina E, Egiazarov T. Predicting Students’ Performance on MOOC Using Data Mining Algorithms. In Voinov N, Schreck T, Khan S, editors, Proceedings of International Scientific Conference on Telecommunications, Computing and Control - TELECCON 2019. Springer Science+Business Media. 2021. p. 285-292. (Smart Innovation, Systems and Technologies, Vol. 220). doi: 10.1007/978-981-33-6632-9_25

Predicting Students’ Performance on MOOC Using Data Mining Algorithms

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