Computer science and information processes

Main directions of data mining in the field of education

N. A. Popova^a, E. S. Egorova<sup>b

a</sup> 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

UDC: 004.89

MSC: 68T09

Received: 24.09.2024
Revised: 09.10.2024
Accepted: 11.10.2024

DOI: 10.35330/1991-6639-2024-26-5-94-106

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