{"id":7989,"date":"2026-03-17T13:33:07","date_gmt":"2026-03-17T13:33:07","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=7989"},"modified":"2026-06-15T11:47:28","modified_gmt":"2026-06-15T10:47:28","slug":"25-3-1-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-3-1-en\/","title":{"rendered":"25.3.1 En"},"content":{"rendered":"\n

Application of machine learning methods in assessing the activities of an educational organization of a higher school<\/strong><\/h1>\n\n\n\n

A.M. Bozieva, F.M. Tseeva, D.V. Khatukhova<\/strong><\/p>\n\n\n\n

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Abstract<\/strong>:<\/strong> <\/em>This article solves the problem of developing a program code for evaluating the activities of educational institutions of higher education on the basis of a set of indicators. The indicators of previous university assessments and their final results are used as input data. Machine learning with a teacher based on a multiple linear regression algorithm is used to successfully solve the problem, which allows us to identify patterns for an adequate assessment. These patterns are revealed on the basis of data accumulated during the activities of universities, and the experience existing in educational practice in assessing universities. As a result, the developed program code based on the available data gives an assessment of the university with a certain accuracy.<\/p>\n\n\n\n

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Keywords<\/strong>:<\/em><\/strong> educational organizations, forecasting, performance evaluation, machine learning, regression<\/p>\n\n\n\n

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For citation<\/strong>.<\/strong> Bozieva A.M., Tseeva F.M., Khatukhova D.V. Application of machine learning methods in assessing the activities of an educational organization of a higher school. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 3(113). Pp. 11\u201319. DOI: 10.35330\/1991-6639-2023-3-113-11-19<\/p>\n\n\n\n

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R<\/strong>eferences<\/summary>\n
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  1. Bozieva A.M., Dzamikhova F.Kh. A model of an intelligent system based on fuzzy logic in the tasks of evaluating the activities of a higher educational institution. News of the KabardinoBalkarian Scientific Center of RAS. 2023. No. 1(111). Pp. 11\u201317. DOI: 10.35330\/1991-6639-2023-1-111-11-17. EDN: VGNLBT (In Russian)<\/li>\n\n\n\n
  2. Kotlyarova I.O. Artificial intelligence technologies in education. Vestnik Yuzhno-Ural’skogo gosudarstvennogo universiteta. Seriya: Obrazovanie. Pedagogicheskie nauki [Bulletin of the South Ural State University. Series: Education. Pedagogical Sciences]. 2022. Vol. 14. No 3. Pp. 69\u201382. EDN: JADHNV (In Russian)<\/li>\n\n\n\n
  3. Poletaeva N.G. Classification of machine learning systems. Vestnik Baltiyskogo federal’nogo universiteta im. I. Kanta. Seriya: Fiziko-matematicheskie i tekhnicheskie nauki [Bulletin of the Baltic Federal University n.a I. Kant. Series: Physical, mathematical and technical sciences]. 2020. No 1. Pp. 5\u201322. EDN: RCHVEU (In Russian)<\/li>\n\n\n\n
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  5. Brink H., Joseph W. Richards, Fetherolf M. Real-World Machine Learning. New-York: Manning Publications. 2014. 264 p.<\/li>\n\n\n\n
  6. V’yugin V.V. Matematicheskie osnovy mashinnogo obucheniya i prognozirovaniya [Mathematical Foundations of Machine Learning and Prediction]. Moscow: MTsNMO, 2022. 400 p. (In Russian)<\/li>\n\n\n\n
  7. Gelman A., Hill J., Vehtari A. Regression and Other Stories (Analytical Methods for Social Research). Cambridge: Cambridge University Press, 2020. 548 p.<\/li>\n\n\n\n
  8. Saati T. Prinyatie resheniy: metod analiza ierarkhiy [Decision Making: Hierarchy Analysis Method]. Transl. from Eng. R. G. Vachnadze. Moscow: Radio i svyaz’, 1993. 278 p.<\/li>\n\n\n\n
  9. Voronov M.V., Pimenov V.I., Nebaev I.A. Sistemy iskusstvennogo intellekta: uchebnik i praktikum dlya vuzov [Artificial intelligence systems: Tutorial and practices for High School]. Moscow: Yurayt, 2022. 256 p. (In Russian)<\/li>\n<\/ol>\n<\/details>\n\n\n\n
    Information about the authors<\/strong><\/summary>\n
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    Bozieva Asiyat Mukhtarovna<\/strong>, postgraduate student, Scientific and Educational Center of KabardinoBalkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 2 Balkarov street;
    bozieva.asya@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-1124-2289
    Tseeva Fatimat Mukhamedovna<\/strong>, Associate Professor of the Department of Mechatronics and Robotics of the Institute of Informatics, Electronics and Robotics of the KBSU;
    360004, Russia, Nalchik, 173 Chernyshevsky street;
    mfmkbsu@mail.ru, ORCID: https:\/\/orcid.org\/0000-0001-7203-3571
    Khatukhova Dana Vladimirovna<\/strong>, Senior Lecturer of the Department of Information Technologies in the Management of Technical Systems of the Institute of Informatics, Electronics and Robotics of the KBSU;
    360004, Russia, Nalchik, 173 Chernyshevsky street;
    dkhatukhova@list.ru, ORCID: https:\/\/orcid.org\/0009-0009-0190-8823<\/p>\n\n\n\n

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    <\/p>\n<\/div>\n<\/details>\n","protected":false},"excerpt":{"rendered":"

    Application of machine learning methods in assessing the activities of an educational organization of a higher school A.M. Bozieva, F.M. Tseeva, D.V. Khatukhova Abstract: This article solves the problem of developing a program code for evaluating the activities of educational institutions of higher education on the basis of a set of indicators. 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