ARTIFICIAL INTELLIGENCE IN TEACHING PHYSICS AT HIGHER EDUCATION INSTITUTIONS
Keywords:
Artificial intelligence, physics education, higher education, personalized learning, simulation-based learning, intelligent tutoring systems, data analysis, collaborative learning, interdisciplinary education, educational technologyAbstract
This thesis examines the transformative role of artificial intelligence (AI) in teaching physics at higher education institutions. AI enhances personalized learning, supports simulation-based and experimental education, enables real-time feedback, and facilitates collaborative and interdisciplinary learning. Intelligent tutoring systems, AI-driven data analysis tools, and generative language models help students develop conceptual understanding, mathematical reasoning, and practical skills. The thesis also discusses the role of educators, ethical considerations, and regional applications of AI, highlighting its potential to modernize physics education and prepare students for complex scientific and technological challenges in the 21st century.
