Priority areas for applying artificial intelligence to pedagogical education

Oʻzbekcha

RAQAMLI DIDAKTIKA SHAROITIDA INFORMATIKA TA’LIMINI RIVOJLANTIRISH: SUN’IY INTELLEKT VA ADAPTIV O‘QITISH TEXNOLOGIYALARI

Published
25.04.2026
Journal
Priority areas for applying artificial intelligence to pedagogical education
Issue
Priority areas for applying artificial intelligence to pedagogical education
Pages
880-883
DOI
10.5281/zenodo.20215884

Authors

Abstract

Mazkur maqolada informatika ta’limida sun’iy intellekt texnologiyalarini joriy etishning nazariy va amaliy asoslari yoritilgan. Xususan, adaptiv o‘qitish tizimlari, intellektual o‘quv tizimlari hamda raqamli didaktika konsepsiyalarining mohiyati, ularning ta’lim jarayonidagi o‘rni va didaktik imkoniyatlari tahlil qilingan. Sun’iy intellekt asosidagi texnologiyalar orqali ta’lim jarayonini individuallashtirish, o‘quvchilarning bilim darajasini diagnostika qilish, moslashtirilgan o‘quv kontentini shakllantirish va refleksiv baholash mexanizmlarini takomillashtirish masalalari asoslab berilgan.

Keywords

adaptiv o‘qitish intellektual tizimlar learning analytics pedagogik texnologiyalar raqamli didaktika sun’iy intellekt informatika ta’limi individuallashtirilgan ta’lim

Other language versions

Русский
В данной статье рассмотрены теоретические и практические основы внедрения технологий искусственного интеллекта в обучение информатике. Проанализированы сущность адаптивного обучения, интеллектуальных обучающих систем и концепции цифровой дидактики, а также их роль и дидактические возможности в образовательном процессе. Обоснованы возможности индивидуализации обучения, диагностики уровня знаний обучающихся, формирования адаптивного образовательного контента и совершенствования механизмов рефлексивного оценивания на основе технологий искусственного интеллекта.
адаптивное обучение интеллектуальные системы искусственный интеллект педагогические технологии цифровая дидактика обучение информатике персонализированное обучение
English
This article explores the theoretical and practical foundations of implementing artificial intelligence technologies in computer science education. It analyzes the essence of adaptive learning systems, intelligent tutoring systems, and digital didactics, as well as their role and didactic potential in the educational process. The study substantiates the opportunities for personalizing learning, diagnosing students’ knowledge levels, developing adaptive educational content, and improving reflective assessment mechanisms through AI-based technologies.
adaptive learning artificial intelligence digital didactics innovative educational technologies learning analytics computer science education intelligent tutoring systems personalized learning

References

1. Russell S., Norvig P. Artificial Intelligence: A Modern Approach. – Pearson, 2021.
2. Woolf B. Building Intelligent Interactive Tutors. – Morgan Kaufmann, 2010.
3. Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education. – Center for Curriculum Redesign, 2019.
4. Luckin R. Machine Learning and Human Intelligence. – UCL Institute of Education Press, 2018.
5. Siemens G., Baker R. Learning Analytics and Educational Data Mining. – Springer, 2012.
6. Anderson J.R. Cognitive Psychology and Its Implications. – Worth Publishers, 2015.
7. UNESCO. AI and Education: Guidance for Policy-makers. – Paris, 2021.
8. Zawacki-Richter O. et al. Systematic Review of AI in Higher Education. – IJET, 2019.
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