koz"Вестник Северо-Казахстанского университета имени Манаша Козыбаева"Bulletin of Manash Kozybayev North Kazakhstan University2958-003X2958-0048М. Қозыбаев атындағы СҚУ10.54596/2958-0048-2026-1-274-293koz-2582Research ArticleИНФОРМАЦИОННО-КОММУНИКАЦИОННЫЕ ТЕХНОЛОГИИINFORMATION AND COMMUNICATION TECHNOLOGIESМОДЕЛЬ И АРХИТЕКТУРА СИСТЕМЫ ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИИ ДЛЯ ОЦЕНКИ ОБЕСПЕЧЕННОСТИ МАТЕРИАЛЬНЫМИ РЕСУРСАМИ ОБРАЗОВАТЕЛЬНЫХ ОРГАНИЗАЦИЙMODEL AND ARCHITECTURE OF A DECISION SUPPORT SYSTEM FOR ASSESSING MATERIAL RESOURCE PROVISION IN EDUCATIONAL ORGANIZATIONShttps://orcid.org/0009-0009-7870-0473УтюбаевЕ. Ш.UtyubayevYe. Sh.

Павлодар

Head of the Pavlodar Regional Center of Information Technologies

Pavlodar

elnar87@mail.ruКГУ «Павлодарский областной центр информационных технологий» управления образования Павлодарской областиКазахстанKSU Pavlodar Regional Center of Information Technologies of the Department of Education of Pavlodar RegionKazakhstan20260804202601 (69)274293Copyright © Утюбаев Е.Ш., 20262026Утюбаев Е.Ш.Utyubayev Y.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.ku.edu.kz/jour/article/view/2582

Целью настоящего исследования является разработка модели и архитектуры системы поддержки принятия решений для оценки материальной обеспеченности образовательных организаций. В работе предложена архитектура информационно-аналитической системы, обеспечивающая интеграцию процессов сбора, хранения, аналитической обработки и визуализации данных о материальных ресурсах образовательных организаций. Архитектура системы включает подсистемы получения данных из различных источников, централизованное хранилище данных, аналитическое ядро обработки информации, средства визуализации показателей и модуль формирования управленческой отчетности.Методической основой исследования является применение методов математического моделирования для формализации процессов оценки обеспеченности образовательных организаций оборудованием.Предложена система количественных показателей, включающая расчет нормативной потребности в оборудовании, коэффициента обеспеченности, показателя дефицита ресурсов, интегрального индекса обеспеченности и показателя риска выбытия оборудования. Разработанная модель позволяет проводить комплексную оценку состояния материально-технической базы образовательных организаций.В отличие от традиционных систем учета запасов, используемых в образовательных организациях, предлагаемая архитектура объединяет математическую модель для расчета коэффициента обеспеченности оборудованием, интегрального показателя обеспеченности и показателя риска выхода оборудования из строя в рамках многоуровневой системы аналитической поддержки принятия решений. Такой подход позволяет осуществлять аналитический мониторинг обеспеченности инфраструктурой, а не простой учет запасов оборудования.

The aim of this study is to develop a model and architecture of a decision support system for assessing the material resource provision of educational organizations. The paper proposes the architecture of an information and analytical system that integrates the processes of data collection, storage, analytical processing, and visualization of information on the material resources of educational organizations. The system architecture includes subsystems for data acquisition from multiple sources, a centralized data warehouse, an analytical processing core, tools for visualizing indicators, and a module for generating management reports.The methodological basis of the study is the application of mathematical modeling methods to formalize the processes of assessing the provision of educational organizations with equipment. A system of quantitative indicators is proposed, including the calculation of normative equipment demand, the provision coefficient, the resource deficit indicator, the integrated provision index, and the equipment retirement risk indicator. The developed model makes it possible to conduct a comprehensive assessment of the condition of the material and technical base of educational organizations.Unlike traditional inventory accounting systems used in educational organizations, the proposed architecture integrates a mathematical model for calculating the equipment provision coefficient, the integrated provision index, and the equipment retirement risk indicator within a multi-level analytical decision support framework. This approach enables analytical monitoring of infrastructure provision rather than simple inventory accounting of equipment.

системы поддержки принятия решениймониторинг образовательной инфраструктурыкоэффициент обеспеченности оборудованиеминтегральный индекс обеспеченности ресурсамириск жизненного цикла оборудованияуправление образованием на основе данныхdecision support systemeducational infrastructure monitoringequipment provision coefficientintegrated provision indexequipment lifecycle riskdata-driven educational managementReferencesOECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en .World Bank. (2020). Realizing the Future of Learning: From Learning Poverty to Learning for Everyone, Everywhere. World Bank. https://doi.org/10/Realizing-the-Future-of-Learning-From-Learning-Poverty-to-Learning-for-Everyone-Everywhere. Available at https://docs.edtechhub.org/lib/X7NW3DD4World Bank. (2020). Realizing the Future of Learning: From Learning Poverty to Learning for Everyone, Everywhere. World Bank. https://doi.org/10/Realizing-the-Future-of-Learning-From-LearningPoverty-to-Learning-for-Everyone-Everywhere. Available at https://docs.edtechhub.org/lib/X7NW3DD4Viberg O., Hatakka M., Balter O., Mavroudi A. The current landscape of learning analytics in higher education // Computers in Human Behavior. 2020. Vol. 89. P. 98-110. https://doi.org/10.1016/i.chb.2018.07.027Viberg O., Hatakka M., Balter O., Mavroudi A. The current landscape of learning analytics in higher education // Computers in Human Behavior. 2020. Vol. 89. P. 98-110. https://doi.org/10.1016/i.chb.2018.07.027Sarker, I.H. Machine Learning: Algorithms, Real-World Applications and Research Directions. SN COMPUT. SCI. 2, 160 (2021). https://doi.org/10.1007/s42979-021-00592-xSarker, I.H. Machine Learning: Algorithms, Real-World Applications and Research Directions. SN COMPUT. SCI. 2, 160 (2021). https://doi.org/10.1007/s42979-021-00592-xLi D-P, Cheng S-J, Cheng P-F, Wang J-Q, Zhang H-Y (2018) A novel financial risk assessment model for companies based on heterogeneous information and aggregated historical data. PLoS ONE 13(12): e0208166. https://doi.org/10.1371/iournal.pone.0208166Li D-P, Cheng S-J, Cheng P-F, Wang J-Q, Zhang H-Y (2018) A novel financial risk assessment model for companies based on heterogeneous information and aggregated historical data. PLoS ONE 13(12): e0208166. https://doi.org/10.1371/iournal.pone.0208166T aheri M. et al. A fuzzy programming model for optimizing the inventory management problem // Expert Systems with Applications. - 2023. https://doi.org/10.1016/i.eswa.2023.119766T aheri M. et al. A fuzzy programming model for optimizing the inventory management problem // Expert Systems with Applications. - 2023. https://doi.org/10.1016/i.eswa.2023.119766Alinezhad, M., Mahdavi, I., Hematian, M. et al. A fuzzy multi-objective optimization model for sustainable closed-loop supply chain network design in food industries. Environ Dev Sustain 24, 8779­ 8806 (2022). https://doi.org/10.1007/s10668-021-01809-yAlinezhad, M., Mahdavi, I., Hematian, M. et al. A fuzzy multi-objective optimization model for sustainable closed-loop supply chain network design in food industries. Environ Dev Sustain 24, 8779­ 8806 (2022). https://doi.org/10.1007/s10668-021-01809-yGulia, P., Kumar, R., Kaur, G. et al. Numerical modelling using fuzzy multi-objective optimisation for environmental sustainability in green supply chain manufacturing. Int J Interact Des Manuf 19, 2061-2076 (2025). https://doi.org/10.1007/s12008-024-02043-2Gulia, P., Kumar, R., Kaur, G. et al. Numerical modelling using fuzzy multi-objective optimisation for environmental sustainability in green supply chain manufacturing. Int J Interact Des Manuf 19, 2061-2076 (2025). https://doi.org/10.1007/s12008-024-02043-2Alkahtani, B.S.T., Simic, V., Anjum, M. et al. Decision Support System for Financial and Accounting Performance Assessment in Manufacturing Industries. Int J Comput Intell Syst 18, 314 (2025). https://doi.org/10.1007/s44196-025-01066-1Alkahtani, B.S.T., Simic, V., Anjum, M. et al. Decision Support System for Financial and Accounting Performance Assessment in Manufacturing Industries. Int J Comput Intell Syst 18, 314 (2025). https://doi.org/10.1007/s44196-025-01066-1Vidal G.H. de Paula, Caiado R.G.G. Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm and neural network // Computers & Industrial Engineering.- 2022. - https://doi.org/10.1016/i.cie.2022.108777Vidal G.H. de Paula, Caiado R.G.G. Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm and neural network // Computers & Industrial Engineering.- 2022. - https://doi.org/10.1016/i.cie.2022.108777Cantini, A. (2022). A decision support system for configuring spare parts supply chains considering different manufacturing technologies. International Journal of Production Research. https://doi.org/10.1080/00207543.2022.2041757Cantini, A. (2022). A decision support system for configuring spare parts supply chains considering different manufacturing technologies. International Journal of Production Research. https://doi.org/10.1080/00207543.2022.2041757Cardeal G., Ribeiro I., Leite F. Decision-support model to select spare parts suitable for additive manufacturing // Computers in Industry. - 2023. - https://doi.org/10.1016/i.compind.2022.103798Cardeal G., Ribeiro I., Leite F. Decision-support model to select spare parts suitable for additive manufacturing // Computers in Industry. - 2023. - https://doi.org/10.1016/i.compind.2022.103798Ojo, A., Rizun, N., Walsh, G., Mashinchi, M. I., Venosa, M., & Rao, M. N. (2024). Prioritising national healthcare service issues from free text feedback: A computational text analysis & predictive modelling approach. Decision Support Systems, 181, 114215. https://doi.org/10.1016/i.dss.2024.114215Ojo, A., Rizun, N., Walsh, G., Mashinchi, M. I., Venosa, M., & Rao, M. N. (2024). Prioritising national healthcare service issues from free text feedback: A computational text analysis & predictive modelling approach. Decision Support Systems, 181, 114215. https://doi.org/10.1016/j.dss.2024.114215Xiaochao Wei, Yanfei Zhang, Xin (Robert) Luo, Modeling the evolution of collective overreaction in dynamic online product diffusion networks, Decision Support Systems, Volume 181,2024, 114232, https://doi.org/10.1016/i.dss.2024.114232.Xiaochao Wei, Yanfei Zhang, Xin (Robert) Luo, Modeling the evolution of collective overreaction in dynamic online product diffusion networks,Decision Support Systems,Volume 181,2024, 114232, https://doi.org/10.1016/i.dss.2024.114232.Fehrenbacher, D. D., & Weisner, M. (2024). Avatars and organizational knowledge sharing. Decision Support Systems, 182, 114245. https://doi.org/10.1016/j.dss.2024.114245Fehrenbacher, D. D., & Weisner, M. (2024). Avatars and organizational knowledge sharing. Decision Support Systems, 182, 114245. https://doi.org/10.1016/j.dss.2024.114245Rinaldi, G., Theodorakos, K., Garcia, F. C., Agudelo, O. M., & De Moor, B. (2025). DSS4EX: A decision support system framework to explore artificial intelligence pipelines with an application in time series forecasting. Expert Systems with Applications, 269, 126421. https://doi.org/10.1016/i.eswa.2025.126421Rinaldi, G., Theodorakos, K., Garcia, F. C., Agudelo, O. M., & De Moor, B. (2025). DSS4EX: A decision support system framework to explore artificial intelligence pipelines with an application in time series forecasting. Expert Systems with Applications, 269, 126421. https://doi.org/10.1016/i.eswa.2025.126421Богданов А. Д., Щепкин А. В. Методический подход к управлению организацией общего образования через материальное обеспечение // Вестник ЮУрГУ. Серия: Компьютерные технологии, управление, радиоэлектроника. - 2025. - № 2. - URL: https://cyberleninka.ru/article/n/metodicheskiy-podhod-k-upravleniyu-organizatsiey-obschegoobrazovaniya-cherez-materialnoe-obespechenie.Bogdanov A. D., Shhepkin A. V. Metodicheskij podxod k upravleniyu organizaciej obshhego obrazovaniya cherez material'noe obespechenie // Vestnik YuUrGU. Seriya: Komp'yuterny'e texnologii, upravlenie, radioe'lektronika. - 2025. - № 2. - URL: https://cyberleninka.ru/article/n/metodicheskiypodhod-k-upravleniyu-organizatsiey-obschego-obrazovaniya-cherez-materialnoe-obespechenieНазарова Т. С. Создание нормативно-методической системы материально-технического обеспечения основных образовательных программ ФГОС: проблемы и перспективы // Вестник Московского университета. Серия 20. Педагогическое образование. - 2017. - № 1. - URL: https://cyberleninka.ru/article/n/sozdanie-normativno-metodicheskoy-sistemy-materialno-tehnicheskogoobespecheniya-osnovnyh-obrazovatelnyh-programm-fgos-problemy-i.Nazarova T. S. Sozdanie normativno-metodicheskoj sistemy' material'no-texnicheskogo obespecheniya osnovny'x obrazovatel'ny'x programm FGOS: problemy' i perspektivy' // Vestnik Moskovskogo universiteta. Seriya 20. Pedagogicheskoe obrazovanie. - 2017. - № 1. - URL: https://cyberleninka.ru/article/n/sozdanie-normativno-metodicheskoy-sistemy-materialno-tehnicheskogoobespecheniya-osnovnyh-obrazovatelnyh-programm-fgos-problemy-i.Byvshev, V., Parfenteva, K., Panteleeva, I. et al. Methodology for assessing the effectiveness of regional infrastructure facilities to support scientific, technical and innovation activities in the context of the synergy effect: analysis, formation and study. J Innov Entrep 11, 65 (2022). https://doi.org/10.1186/s13731-022-00257-wByvshev, V., Parfenteva, K., Panteleeva, I. et al. Methodology for assessing the effectiveness of regional infrastructure facilities to support scientific, technical and innovation activities in the context of the synergy effect: analysis, formation and study. J Innov Entrep 11, 65 (2022). https://doi.org/10.1186/s13731-022-00257-wSatria, T. F. ., Hadiguna, R. A. ., Henmaidi, H., & Arief, I. . (2025). Performance measurement in local government: A systematic review towards efficient public sector management. International Journal of Innovative Research and Scientific Studies, 8(4), 1417-1428. https://doi.org/10.53894/iiirss.v8i4.8093Satria, T. F. ., Hadiguna, R. A. ., Henmaidi, H., & Arief, I. . (2025). Performance measurement in local government: A systematic review towards efficient public sector management. International Journal of Innovative Research and Scientific Studies, 8(4), 1417-1428. https://doi.org/10.53894/iiirss.v8i4.8093ГИС «Контингент»: официальный сайт. - URL: http://gis-kontingent.ru/GIS «Kontingent»: oficial'ny'j sajt. - URL: http://gis-kontingent.ru/ГИС «Образование» Челябинской области: официальный сайт. - URL: https://chiro74.ru/p/gisobrazovanieGIS «Obrazovanie» Chelyabinskoj oblasti: oficial'ny'j sajt. - URL: https://chiro74.ru/p/gisobrazovanie

The authors declare that there are no conflicts of interest present.