AI-TEXNOLOGIYALAR YORDAMIDA INDIVIDUAL O‘QUV TRAEKTORIYASINI SHAKLLANTIRISH MEXANIZMLARI.
DOI:
https://doi.org/10.5281/zenodo.20195898Keywords:
Sun’iy intellekt, individual o‘quv trayektoriyasi, adaptiv o‘qitish, mashinali o‘qitish, o‘quv tahlili (Learning Analytics), shaxsiylashtirilgan ta’lim, kognitiv modellashtirish.Abstract
Maqolada sun’iy intellekt (SI) yordamida har bir o‘quvchi uchun shaxsiylashtirilgan ta’lim trayektoriyalarini yaratishning nazariy va amaliy asoslari tadqiq etiladi. SI algoritmlari orqali o‘quv jarayonini adaptiv boshqarish, o‘quvchi modellarini shakllantirish va ta’lim mazmunini dinamik optimallashtirish mexanizmlari tahlil qilingan. Shuningdek, ma’lumotlarga asoslangan ta’lim (Data-driven learning) muhitida o‘qituvchi va texnologiya hamkorligining istiqbollari yoritilgan.References
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Du Boulay, B. (2016). Artificial Intelligence as an Effective Gender-Neutral Strategy in Education. International Journal of Artificial Intelligence in Education.
Knewton, J. (2015). The State of Adaptive Learning. White Paper.
O‘zbekiston Respublikasi Prezidentining 2022-yil 11-maydagi PF-134-sonli Farmoni. "2022-2026-yillarda xalq ta’limini rivojlantirish bo‘yicha milliy dasturni tasdiqlash to‘g‘risida".
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence In Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Pardos, Z. (2017). Big Data in Education: The Future of Learning. Stanford University.
Abduqodirov A.A. (2021). Ta’limda innovatsion texnologiyalar va sun’iy intellekt integratsiyasi. Toshkent
UNESCO. (2021). AI and education: Guidance for policy-makers. Paris.
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Published
2026-05-15
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How to Cite
Musurmonova, M., & Murodova, F. (2026). AI-TEXNOLOGIYALAR YORDAMIDA INDIVIDUAL O‘QUV TRAEKTORIYASINI SHAKLLANTIRISH MEXANIZMLARI. Models and Methods in Modern Science, 5(8), 22-25. https://doi.org/10.5281/zenodo.20195898
