Learning analytics based on educational data mining methods as a way to improve the effectiveness of the education management system-Reference-Cited by-同舟云学术

Learning analytics based on educational data mining methods as a way to improve the effectiveness of the education management system

Published:2020-06-29 Issue:2 Volume: Page:16-33
ISSN:2073-2635
Container-title:Moscow University Pedagogical Education Bulletin
language:
Short-container-title:Vestn. Mosk. univ., Ser. 20, Pedagog. obraz.

Author:

Barannikov Kirill Anatolevich¹,Suleymanov Ruslan Suleymanovich¹,Lesin Sergey Michailovich¹,Kupriyanov Roman Borisovich¹

Affiliation:

1. Moscow Pedagogical State University

Funder

Russian Foundation for Basic Research

Publisher

Faculty of Educational Studies of Lomonosov Moscow State University

Reference16 articles.

1. Belonozhko P.P., Karpenko A.P., Khramov D.A. Analiz obrazovatel'nyh dannyh: napravlenija i perspektivy primenenija [Elektronnyj resurs] [Algorithm of rangovy optimization of access to data in information system]. Internet-zhurnal «Naukovedenie» Vol. 9, №4 (2017). Available at: http://naukovedenie.ru/PDF/15TVN417.pdf (Accessed: 26.03.2020). (In Russ.).

2. Zaslavskiy A.A. Napravleniya razvitiya informacionnogo prostranstva obrazovatel'noj organizacii dlya povysheniya e'ffektivnosti vnutrennego upravleniya [Directions for the development of the information environment of an educational organization to improve the effectiveness of internal management]. Vestnik Moskovskogo gorodskogo pedagogicheskogo universiteta. Seriya: Informatika i informatizaciya obrazovaniya. 2017. № 1 (39). pp. 76-82. (In Russ.).

3. Kanashevich T.N. Obshhaya xarakteristika organizacii processa monitoringa rezul'tatov uchebnoj deyatel'nosti studentov [General characteristics of the organization of the process of monitoring the results of educational activities of students]. Sbornik materialov II Mezhdunarodnoj nauchnoj konferencii «Informatizaciya obrazovaniya i metodika e'lektronnogo obucheniya» – Sibirskij federal'nyj universitet. 2018. pp. 168-172. (In Russ.).

4. Lucenko E.V., Korzhakov V.E. Prognozirovanie urovnya predmetnoj obuchennosti studentov putem SK-analiza dannyx ob ix social'nom statuse [Elektronnyj resurs] [Predicting the level of subject learning of students by means of SC-analysis of data on their social status]. Vestnik Adygejskogo gosudarstvennogo universiteta. Seriya 3: Pedagogika i psixologiya. 2007. №3. Available at: https://cyberleninka.ru/article/n/prognozirovanie-urovnya-predmetnoy-obuchennosti-studentov-putem-sk-analiza-dannyh-ob-ih-sotsialnom-statuse (Accessed: 10.03.2020). (In Russ.).

5. Proshkina E.N., Balashova I.Yu. Analiz i prognozirovanie uspevaemosti studentov na osnove radial'noj bazisnoj nejronnoj seti [Elektronnyj resurs] [Analysis and prediction of students' academic performance based on a radial basic neural network]. Texnicheskie nauki: tradicii i innovacii. Kazan': Molodoj uchenyj, 2018. pp. 24-28. Available at: https://elibrary.ru/item.asp?id=32629327 (Accessed: 10.03.2020). (In Russ.).