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Computer science and information processes
Main directions of data mining in the field of education
N. A. Popovaa, E. S. Egorovab a Penza State University,
440026, Russia, Penza, 40 Krasnaya street
b Penza State Technological University,
440039, Russia, Penza, 1a/11 Baidukova passage/Gagarina street
Abstract:
Data mining in education is becoming increasingly popular and many educational
institutions are increasingly applying it to improve their competitiveness. Many studies have been
conducted recently on educational data analysis on different educational topics with the use of different
methods and algorithms. Therefore, it would be useful to have a brief overview of the most used methods and approaches. For this purpose, foreign and domestic works were analyzed to identify the
most relevant research directions, important methods and algorithms in the field of educational data
analysis in modern higher education. A systematic analysis methodology consisting of 5 stages was
proposed to compile the review. Widely used topics, methods, algorithms were identified and the
relationship between them was established. The scientific novelty of the overview lies in identifying
the current research challenges in the field of educational data analysis in higher education and
discovering promising research methods and algorithms.
Keywords:
Data Mining, educational data mining, meta-analysis, business intelligence
Received: 24.09.2024 Revised: 09.10.2024 Accepted: 11.10.2024
Citation:
N. A. Popova, E. S. Egorova, “Main directions of data mining in the field of education”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 26:5 (2024), 94–106
Linking options:
https://www.mathnet.ru/eng/izkab903 https://www.mathnet.ru/eng/izkab/v26/i5/p94
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