INFORMATION-POLYLOGICAL APPROACH: TRANSFORMING THE TRAINING OF PHYSICS TEACHERS TO BUILD FUNDAMENTAL KNOWLEDGE FOR FUTURE ENGINEERS IN THE ARTIFICIAL INTELLIGENCE ERA

Abstract

The article substantiates the necessity for a systemic transformation in the training of future physics teachers, driven by the challenges of educational digitalization and the widespread adoption of artificial intelligence (AI) technologies. These developments threaten the formation of deep fundamental knowledge in school students, which is critically important for their successful education in engineering universities. As a methodological solution, the development and practical implementation of the information-polylogical approach (IPA) is proposed. Within this approach, knowledge acquisition occurs through active interaction (polylogue) among students, the teacher, artificial intelligence, and digital resources. Its goal is to equip educators with the competencies for critical information analysis and for organizing an educational process in which AI is used as a tool to develop fundamental scientific thinking, not to replace it. The authors elaborate on two key areas of its application: theoretical and methodological training for instructors (through workshops) and for students (through the introduction of a special module and the modernization of the curriculum). The study focuses on detailed examples of fostering critical thinking through dialogue with classical sources and AI-generated content, demonstrating how a future teacher can lay the foundations of engineering thinking in school students. It is shown how the IPA can shift the study of physics from the passive assimilation of formulas to an active dialogue with information. The authors have developed a comparative table of the evolution of memory, thinking, and cognition, which clearly illustrates the transformation of cognitive processes. The methodological foundation of the work is based on philosophical and pedagogical concepts of dialogism, the principles of problem-based dialogic learning, and systemic and activity-based approaches.