SCIENTIFIC AND METHODOLOGICAL BASIS FOR THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN TEACHING PHYSICAL ELECTRONICS

Authors

  • Nodira Mustafoeva University of Information Technologies and Management, Karshi city, Uzbekistan

Keywords:

artificial intelligence, physical electronics, adaptive learning, virtual laboratory, STEM, digital pedagogy.

Abstract

This article analyzes the scientific and methodological foundations of using artificial intelligence technologies in teaching physical electronics. The integration of AI-based adaptive learning systems, virtual laboratories, and intelligent support systems into the educational process is examined. The research results indicate that the use of AI technologies is an important factor in improving the effectiveness of education and deepening students’ knowledge.

 

References

Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education. Center for Curriculum Redesign.

Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.

Yunusova, D. I. (2022). Modern technologies of teaching mathematics in higher education. Tashkent: Innovatsiya-Ziyo.

Anderson, J. R. (2010). Cognitive Psychology and Its Implications. Worth Publishers.

Woolf, B. P. (2010). Building Intelligent Interactive Tutors. Morgan Kaufmann.

Downloads

Published

2026-03-26

How to Cite

Nodira Mustafoeva. (2026). SCIENTIFIC AND METHODOLOGICAL BASIS FOR THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN TEACHING PHYSICAL ELECTRONICS. Ethiopian International Journal of Multidisciplinary Research, 13(03), 1082–1083. Retrieved from https://www.eijmr.org/index.php/eijmr/article/view/5750