OLIY TA’LIM MUASSASALARIDA TALABALARNING O‘ZLASHTIRISHINI MONITORING QILISHDA SUN’IY INTELLEKT TIZIMLARINING O‘RNI VA MATEMATIK MODELLARI

Shoxruxbek Madaminov

GREEN ECONOMY AND DEVELOPMENT, 2026, vol. 4, issue 6, 799-804

Abstract: Ushbu tadqiqot ishida oliy ta’lim muassasalarida (OTM) talabalarning akademik o‘zlashtirishko‘rsatkichlarini real vaqt rejimida monitoring qilish va semestr yakunidagi natijalarni oldindan bashorat qilishdasun’iy intellekt (SI) tizimlarining o‘rni tahlil qilinadi. Tadqiqot obyekti sifatida OTMlardagi ta’lim jarayoniniboshqarish axborot tizimlaridan (LMS/HEMIS) olingan Big Data (katta hajmli ma’lumotlar) to‘plami olingan.Talabalarning raqamli faolligi, davomati va joriy baholari asosida “akademik xavf ostidagi” (at-risk) talabalarnierta aniqlash bo‘yicha logistik regressiya, Tasodifiy o‘rmon (Random Forest) va XGBoost algoritmlarigaasoslangan modellar qurildi. Eksperiment natijalari shuni ko‘rsatdiki, XGBoost modeli 91,4 % aniqlik (Accuracy)bilan talabalarning akademik muvaffaqiyatsizligini semestrning dastlabki to‘rtinchi haftasidayoq bashorat qilishimkonini beradi. Olingan natijalar asosida proaktiv pedagogik monitoring tizimini shakllantirish bo‘yicha ilmiy vaamaliy tavsiyalar ishlab chiqilgan

Keywords: Sun’iy intellekt; mashinali o‘qitish; ta’limiy ma’lumotlar tahlili (EDM); Random Forest; XGBoost; proaktiv monitoring; HEMIS; akademik xavf; raqamli izlar (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:teu:ged000:v:4:y:2026:i:6:id:11742

DOI: 10.5281/zenodo.21626918

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