ARTIFICIAL INTELLIGENCE IN PHYSICS EDUCATION: CHALLENGES AND PERSPECTIVES ON THE PATH TO PERSONALIZED LEARNING
Abstract
This article presents a comprehensive literature review on the integration of artificial intelligence tools in physics education. The study aims to analyze how various AI technologies – from adaptive learning platforms and virtual laboratories to intelligent chatbots – can contribute to personalized learning, support the development of experimental thinking, and improve overall educational outcomes.The review synthesizes scholarly sources that highlight the numerous benefits of AI, including: the enhancement of critical thinking and problem-solving skills, increased student engagement, and a deeper understanding of abstract physics concepts. The application of AI in the educational process allows for the adaptation of task difficulty to individual needs, which promotes more effective learning. The paper also meticulously analyzes the key challenges associated with the implementation of these technologies, including issues of data privacy, algorithmic bias, and the preservation of academic integrity in an era of increasing automation.This article provides a comprehensive assessment of the pedagogical advantages and difficulties, laying the groundwork for a balanced and strategic application of AI tools. This will allow for the effective improvement of learning outcomes while minimizing associated risks and contributing to the further development of educational methodologies.
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