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Ushbu maqolada sun’iy intellekt texnologiyalarining oliy ta’limdagi baholash tizimlariga ilmiy asosda integratsiyalashuvi tahlil qilinadi. An’anaviy baholashdagi subyektivlik, statiklik va inson omiliga kuchli bog‘liqlik kabi cheklovlar ko‘rib chiqiladi. Sun’iy intellekt yordamida baholashni avtomatlashtirish, shaffoflikni ta’minlash, aniqlikni oshirish va talaba faoliyatini real vaqt rejimida tahlil qilish imkoniyatlari yoritiladi. Shuningdek, baholash tizimiga sun’iy intellekt vositalarini joriy etish zarurati, ilg‘or xorijiy tajribalar va algoritmlar asosida baholovchi modellar yaratish bo‘yicha tavsiyalar beriladi.

  • Read count 42
  • Date of publication 27-06-2025
  • Main LanguageO'zbek
  • Pages25-32
Ўзбек

Ushbu maqolada sun’iy intellekt texnologiyalarining oliy ta’limdagi baholash tizimlariga ilmiy asosda integratsiyalashuvi tahlil qilinadi. An’anaviy baholashdagi subyektivlik, statiklik va inson omiliga kuchli bog‘liqlik kabi cheklovlar ko‘rib chiqiladi. Sun’iy intellekt yordamida baholashni avtomatlashtirish, shaffoflikni ta’minlash, aniqlikni oshirish va talaba faoliyatini real vaqt rejimida tahlil qilish imkoniyatlari yoritiladi. Shuningdek, baholash tizimiga sun’iy intellekt vositalarini joriy etish zarurati, ilg‘or xorijiy tajribalar va algoritmlar asosida baholovchi modellar yaratish bo‘yicha tavsiyalar beriladi.

Русский

В данной статье научно анализируется интеграция технологий искусственного интеллекта в системы оценки в высшем образовании. Рассматриваются проблемы традиционной оценки, такие как субъективность, статичность и зависимость от человеческого фактора. Обоснована возможность применения инструментов искусственного интеллекта для автоматизации оценки, повышения прозрачности и точности, а также анализа учебной активности студентов в режиме реального времени. Также предложены направления разработки оценочных моделей на основе передового зарубежного опыта.

English

This article presents a scientific analysis of the integration of artificial intelligence technologies into assessment systems in higher education. It examines the challenges of traditional assessment, such as subjectivity, rigidity, and dependence on the human factor. The potential of artificial intelligence tools to automate assessment, increase transparency and accuracy, and analyze student performance in real time is substantiated. The article also provides proposals for developing assessment models based on advanced international practices.

№ Author name position Name of organisation
1 Aliqulov A.. -- Tashkent State University of Economics
№ Name of reference
1 Aliqulov, A. B. (2024). Masofaviy taʼlim jarayonini samarali tashkil etishda sunʼiy intellekt texnologiyalarining oʻrni. European Journal of Life Safety and Stability, 35, 145–150. https://in academy.uz/index.php/EJLFAS/article/view/24966
2 Khlaif, Z. N., et al. (2025). Redesigning assessments for AI-enhanced learning: A framework for educators in the generative AI era. Education Sciences, 15(2), 174. https://doi.org/10.3390/educsci15020174
3 Ogunleye, B., et al. (2024). Higher education assessment practice in the era of generative AI tools. arXiv preprint arXiv:2404.01036. https://arxiv.org/abs/2404.01036
4 Perkins, M., et al. (2023). The AI Assessment Scale (AIAS): A framework for ethical integration of generative AI in educational assessment. arXiv preprint arXiv:2312.07086. https://arxiv.org/abs/2312.07086
5 Pulatova Z.A., Ikanova L. (2025). Assessment for learning with artificial intelligence. Journal of New Century Innovations, 73(2), 330–335.
6 Qi Xia, et al. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21(40). https://educationaltechnologyjournal. springeropen.com/articles/10.1186 /s41239-024-00468-z
7 Robert, J., Pelletier, K., McCormack, M., Reeves, J., Wellington Baker, K., & Strain, M. (2025). Higher generative AI readiness assessment. EDUCAUSE. https://library.educause.edu/resources/2024/4/higher-education-generative-ai-readiness assessment
8 Song D., et al. (2024). The Rise of Artificial Intelligence in Educational Measurement: Opportunities Ethical Challenges. arXiv preprint arXiv:2406.18900. https://arxiv.org/abs/2406.18900
9 Tozhiboev I.T. (2024). The Role of Artificial Intelligence in Higher Education Management (Comparative Analysis). SSRN. https://ssrn.com/abstract=4973755
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