Research on Assessing the Quality of Students’ Training Using Data Mining Methods

УДК 519.6:004.89

  • Tatyana V. Mikheeva Altai State University, Barnaul, Russia Email: mikheeva@math.asu.ru
DOI_disc_logo https://doi.org/10.14258/izvasu(2024)1-16
Keywords: data mining, correlation, classification, regression, clustering, logistic regression, decision trees, k-nea-rest neighbors method, k-means method

Abstract

The article is devoted to the application of data mining methods to assess the quality of general education using the official data of the final examination results in the Altai Region. The methods ofdescriptive data analysis, correlation data analysis, data clustering, classification, and regression are used in the study. The obtained results identify the best data mining algorithms for the considered problem. The most dependent patterns are revealed during the education quality assessment using methods of intellectual analysis. The conducted study utilizes the computer and graphical methods of computational mathematics and provides the results with theoretical and applied significance. The developed programs can serve as the basis for prospective research plans to assess the quality of education using the analysis of the final examination results, as well as to provide the foundation for the quantitative assessment of such analysis.

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Author Biography

Tatyana V. Mikheeva, Altai State University, Barnaul, Russia

Candidate of Sciences in Technology, Associate Professor of the Department of Computer Science

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Published
2024-04-05
How to Cite
Mikheeva T. V. Research on Assessing the Quality of Students’ Training Using Data Mining Methods // Izvestiya of Altai State University, 2024, № 1(135). P. 114-119 DOI: 10.14258/izvasu(2024)1-16. URL: http://izvestiya.asu.ru/article/view/%282024%291-16.
Issue
No 1(135) (2024): Известия Алтайского государственного университета
Section
Математика и механика

Copyright (c) 2024 Татьяна Викторовна Михеева

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