OPTIMIZING TEACHER–STUDENT COLLABORATION IN INTERACTIVE LEARNING PROCESSES THROUGH ARTIFICIAL INTELLIGENCE
Abstract
This article explores the optimization of teacher–student collaboration in interactive learning processes through the application of Artificial Intelligence (AI) technologies. The study analyzes the potential of AI to create personalized learning environments, automate teachers’ methodological activities, and enhance students’ independent learning engagement. It also discusses the psychological and pedagogical mechanisms that improve educational quality through the use of interactive platforms, chatbots, adaptive learning systems, and intelligent data analysis algorithms. Additionally, the article examines the advantages, challenges, and prospects of improving teacher–student communication through digital means, based on scientific approaches and pedagogical practice.
References
1. Hoc, J. M., & Novick, L. R. (2018). Psychology of programming. Academic Press.
2. Feldt, R., & Lwakatare, L. E. (2016). Personality traits in software engineering: A systematic literature review. Information and Software Technology, 70, 141-161.
3. Jalolov, T. S. (2023). TEACHING THE BASICS OF PYTHON PROGRAMMING. International Multidisciplinary Journal for Research & Development, 10(11).
4. Jalolov, T. S. (2023). Solving Complex Problems in Python. American Journal of Language, Literacy and Learning in STEM Education (2993-2769), 1(9), 481-484.
5. Jalolov, T. S. (2023). PEDAGOGICAL-PSYCHOLOGICAL FOUNDATIONS OF DATA PROCESSING USING THE SPSS PROGRAM. INNOVATIVE DEVELOPMENTS AND RESEARCH IN EDUCATION, 2(23), 220-223.
