This article systematically analyzes the methodological foundations of artificial intelligence (AI) technologies in computer science education. The study examines the impact of AI integration on the individualization, adaptability, and pedagogical effectiveness of the educational process. This article examines how students’ analytical thinking and logical problem-solving skills can be developed using artificial neural networks (ANNs), targeted recommender systems (Recommender Systems), feedback and self-assessment mechanisms, and learning process monitoring capabilities using data analysis.
| Mualliflar | Ilyasova, Z.K., Ильясова, З.К., Ilyasova, Z.K. |
|---|---|
| Jurnal | Ilim ha’m ja’miyet |
| Nashr sanasi | 2026-02-16 |
| Son | 1-3 |
| Betlar | 79-81 |
| Til | uz_Latn |
sun’iy intellekt (AI), informatika ta’limi, metodologik asoslar, adabtiv o‘qitish tizimlari, sun’iy neyron tarmoqlari, maqsadli tavsiyalar tizimi, Feedback va self-assessment, analitik tafakkur, ma’lumotlar analitikasi, individualizatsiyalashgan o‘quv jarayoni, искусственный интеллект (ИИ), образование в области информатики, методологические основы, адаптивные системы обучения, искусственные нейронные сети, целевая система рекомендаций, обратная связь и самооценка, аналитическое мышление, анализ данных, индивидуализированный процесс обучения, artificial intelligence (AI), computer science education, methodological foundations, adaptive learning systems, artificial neural networks, target recommendation system, feedback and self-assessment, analytical thinking, data analysis, individualized learning process
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