SUN'IY INTELLEKT YORDAMIDA O‘QUVCHILARNING INDIVIDUAL O‘QUV USLUBINI ANIQLASH VA DARS MATERIALLARINI AVTOMATIK MOSLASHTIRISHNING PEDAGOGIK ASOSLARI
Keywords:
sun'iy intellekt, o‘quv uslubi, adaptiv ta'lim, individuallashtirilgan ta'lim, mashinali o‘qitish, Felder-Silverman modeli, intellektual repetitorlik tizimlari, ta'limni raqamlashtirish, pedagogik texnologiya, o‘quvchi modeli.Abstract
Ushbu tezisda sun'iy intellekt texnologiyalari yordamida o‘quvchilarning individual o‘quv uslubini aniqlash va shu asosda dars materiallarini avtomatik moslashtirishning pedagogik asoslari tahlil qilindi. Shuningdek, mazkur tezisda Felder-Silverman o‘quv uslublari modeli, mashinali o‘qitish algoritmlari asosidagi aniqlash mexanizmlari, shuningdek adaptiv ta'lim platformalarining pedagogik-didaktik tamoyillari ko‘rib chiqildi. Xorijiy tadqiqotlar tahlili asosida sun'iy intellektning ta'lim samaradorligini oshirishdagi imkoniyatlari va cheklovlari yoritildi hamda, milliy ta'lim tizimida qo‘llash bo‘yicha xulosa va tavsiyalar ishlab chiqildi.
References
1. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. Systematic review of research on artificial intelligence applications in higher education – where are the educators? // International Journal of Educational Technology in Higher Education. - 2019. - Vol. 16, Article 39. - P. 1–27.
2. Felder, R. M., & Silverman, L. K. Learning and teaching styles in engineering education // Engineering Education. - 1988. - Vol. 78, No. 7. - P. 674–681.
3. Holmes, W., Bialik, M., Fadel, C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. - Boston, MA: Center for Curriculum Redesign, 2019. - 234 p.
4. Graf, S., & Kinshuk. An approach for detecting learning styles in learning management systems // Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (ICALT). - 2006. - P. 161–163.
5. Lokare, V., & Jadhav, P. Adaptive Learning through Artificial Intelligence // International Journal Publication (ResearchGate preprint). - 2024. - P. 1–14.
6. Enhancing E-Learning Adaptability with Automated Learning Style Identification and Sentiment Analysis: A Hybrid Deep Learning Approach for Smart Education // Information (MDPI). - 2024. - Vol. 15, No. 5, Article 277. — P. 1–19.
7. AI-based learning style detection in adaptive learning systems: a systematic literature review // Journal of Computers in Education (Springer). - 2024. - P. 1–35.
8. Artificial intelligence in adaptive education: a systematic review of techniques for personalized learning // Discover Education (Springer). - 2025. - Article 908. - P. 1–24.
