Didactic potential of artificial intelligent in the training of physics teacher

Abstract

Physics teacher training must consider the rise and impact of artificial intelligence in contemporary society and education. The main objective of this study is to demonstrate the didactic potential of artificial intelligence to enhance motivation and comprehensive learning in physics. The study employed theoretical, empirical, and statistical methods, emphasizing systematization, modeling, pedagogical testing, and inferential statistics, which contributed to a critical analysis of the efficient use of artificial intelligence in physics learning. The main results of the study highlight essential methodological ideas for integrating AI, realizing its didactic potential, and exploring its educational implications for guiding comprehensive physics learning in teacher training. Improvements in different dimensions of learning were observed in practice, and limitations to be overcome were identified in problem formulation, independent problem-solving, and content creation with AI assistance. The main conclusions of this work focus on the need to realize the potential of AI for its integration into physics teacher training, based on a conception that harmonizes didactic, technological, and cultural foundations.