ADAPTIV O’QITISH TIZIMLARI UCHUN MOSLASHUVCHAN ALGORITMNI ISHLAB CHIQISH

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Аннотация:

Maqolada mashinali o‘qitish texnologiyalari, foydalanuvchi modelini aniqlash, shaxsiy o‘quv trajektoriyalarini shakllantirish va tavsiyaviy tizimlar integratsiyasi asosida moslashuvchan tizimlar arxitekturasi taklif etiladi. Tadqiqot natijalari algoritmlarning samaradorligi, hisoblash tejamkorligi va o‘quvchilarning akademik ko‘rsatkichlariga ta’siri nuqtayi nazaridan baholanadi.

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Как цитировать:

Xaydaraliyeva, S. (2026). ADAPTIV O’QITISH TIZIMLARI UCHUN MOSLASHUVCHAN ALGORITMNI ISHLAB CHIQISH. Молодые ученые, 4(4), 35–38. извлечено от https://in-academy.uz/index.php/yo/article/view/72076

Библиографические ссылки:

Environment. arXiv preprint arXiv:2405.10476. https://arxiv.org/abs/2405.10476

Adiguzel, T., de Vries, B., & Jing, L. (2024). AI-driven adaptive learning for sustainable educational

Transformation. Sustainable Development. https://doi.org/10.1002/sd.3221

Nguyen, H. A., Stec, H., Hou, X., Di, S., & McLaren, B. M. (2023). Evaluating ChatGPT's decimal skills

Feedback generation in a digital learning game. arXiv preprint arXiv:2308.12345.

Hmelo-Silver, C. E., & Danish, J. A. (2023). NLP4Science: Designing a platform for integrating natural language processing in middle school science classrooms. In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2023).