O‘ZBEKISTONDA OLIY TA’LIM BOSHQARUVI UCHUN SUN’IY INTELLEKTNING KENGAYTIRILGAN BASHORATLI TAHLILI

O‘ZBEKISTONDA OLIY TA’LIM BOSHQARUVI UCHUN SUN’IY INTELLEKTNING KENGAYTIRILGAN BASHORATLI TAHLILI

Авторы

  • Shohida Esanova

DOI:

https://doi.org/10.5281/zenodo.17524432

Ключевые слова:

sun’iy intellekt, VAR modeli, oliy ta’lim boshqaruvi, bashoratli tahlil, raqamli transformatsiya, ma’lumotlar tahlili, boshqaruv innovatsiyasi

Аннотация

Ushbu tezisda O‘zbekiston oliy ta’lim tizimida sun’iy intellekt (AI) va vektor avtoregressiya (VAR) modeliga
asoslangan gibrid yondashuv orqali boshqaruv samaradorligini oshirish imkoniyatlari tahlil qilingan. Tadqiqot natijalari
ta’lim budjeti, raqamli infratuzilma va AI texnologiyalarini joriy etish ko‘rsatkichlari o‘rtasida ijobiy bog‘liqlik mavjudligini
ko‘rsatdi. AI–VAR modeli bashoratli tahlil vositasi sifatida raqamli transformatsiyani rejalashtirishda va boshqaruv
qarorlarini optimallashtirishda yuqori aniqlikni ta’minlaydi

Биография автора

Shohida Esanova


Toshkent davlat iqtisodiyot universiteti
mustaqil tadqiqotchisi

Библиографические ссылки

Arora, M., Singh, G., Ather, D., Chaudhary, N., & Kler, R. (2023, January). Forecasting inbound tourism in

Uzbekistan: Leveraging AI and ARIMA models for economic growth insights. In 2023 4th International Conference

on Computation, Automation and Knowledge Management (ICCAKM) (pp. 267–272). IEEE. https://doi.org/10.1109/

ICCAKM56905.2023.10065376

Bakieva, G. Kh., & M. K. Sh. (2019, November). Enhancing ICT technologies in teaching, learning and assessment

of foreign languages in Uzbekistan. In 2019 International Conference on Information Science and Communications

Technologies (ICISCT) (pp. 1–5). IEEE. https://doi.org/10.1109/ICISCT47635.2019.9011875

Gnoh, H. Q., Keoy, K., Iqbal, J., Anjum, S. S., Yeo, S. F., et al. (2024). Enhancing business sustainability through

technology-enabled AI: Forecasting student data and comparing prediction models for higher education institutions

(HEIs). PaperASIA.

Hakimova, M., Shaturaev, J., Turabekov, F., & Khakimova, K. (2023). Modernization of management system of higher

education institutions: An empirical perspective from Uzbekistan. Indonesian Journal of Multidisciplinary Research,

(1), 45–53.

Hemachandran, K., Verma, P., Pareek, P., Arora, N., Rajesh Kumar, K. V., et al. (2022). Artificial intelligence: A

universal virtual tool to augment tutoring in higher education. Computational Intelligence and Neuroscience. https://

doi.org/10.1155/2022/1234567

Ivanchenko, I. (2023). Assessing the prospects for using artificial intelligence in higher education system. Science for

Education Today, 13(1), 5–21. https://doi.org/10.15293/2658-6762.2301.01

Jain, G., & Asanov, A. (2023). Examining the impact of teachers’ assessment competency on learners in academia: A

study of selected HEIs of Uzbekistan. ECE Official Conference Proceedings.

Mattingly, K., Rice, M., & Berge, Z. (2020). Learning analytics as a tool for closing the assessment loop in higher

education. Online Journal of Distance Learning Administration, 23(4), 1–13.

Mishra, R. (2019, February). Usage of data analytics and artificial intelligence in ensuring quality assurance at higher

education institutions. In 2019 Amity International Conference on Artificial Intelligence (AICAI) (pp. 542–546). IEEE.

https://doi.org/10.1109/AICAI.2019.8701271

Setiawan, A. Y. I., Inayah, I., Muhtar, M. I., Saputra, F. A., & Abu Samra, A. N. J. (2024). Sarf ibtida’iy assessment with

Opexams among university students based on artificial intelligence. Al-Ta’rib: Jurnal Ilmiah Program Studi Pendidikan

Bahasa Arab IAIN Palangka Raya, 12(2), 233–247.

Shilbayeh, S., & Abonamah, A. (2021). Predicting student enrollments and attrition patterns in higher educational

institutions using machine learning. The International Arab Journal of Information Technology, 18(5), 743–751.

Загрузки

Опубликован

2025-10-15
Loading...