TАLАBАLАRNI NEYROTАRMOQ MODELI АSOSIDА OʿQITISHNING DIDAKTIK TIZIMI
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Ushbu maqolada talabalarni o‘qitish jarayoniga neyrotarmoq modellari va sun’iy intellekt texnologiyalarini tatbiq etishning nazariy hamda amaliy jihatlari yoritiladi. Tadqiqotda o‘quv jarayonini individuallashtirish, talabalarning bilim darajasini avtomatik baholash, o‘quv materiallarini moslashtirish va samaradorlikni oshirishda sun’iy neyron tarmoqlarning roli tahlil qilinadi. Taklif etilgan neyrotarmoq asosidagi o‘qitish tizimi talabalarning o‘quv faoliyatini real vaqt rejimida monitoring qilish, bilim bo‘shliqlarini aniqlash va shaxsiy ta’lim yo‘l xaritasini shakllantirish imkonini beradi.
1. LeCun, Y., Bengio, Y., Hinton, G. Deep learning // Nature. – 2015. – №521. – B. 436–444.
2. Brusilovsky, P. Adaptive and intelligent technologies for web-based education // International Journal of Artificial Intelligence in Education. – 2018. – Vol. 29(2). – P. 1–28.
3. Baker, R., Siemens, G. Learning analytics and educational data mining: Towards communication and collaboration // Proceedings of the 10th International Conference on Educational Data Mining. – 2020. – P. 1–10.
4. Luckin, R., Holmes, W., Griffiths, M., Forcier, L. Intelligence Unleashed: An Argument for AI in Education. – London: Pearson Publishing, 2021. – 56 b.
5. Abdurahmonov, M. Raqamli pedagogika: nazariya va amaliyot. – Toshkent: Innovatsion rivojlanish nashriyoti, 2021. – 210 b.
6. Ashirova A., Yusupov D. Neyrotarmoq texnologiyasi asosida baholash jarayonini avtomatlashtirish.-UzMU xabarlari.2025. №1/4/1-B.62-64.
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