IMPROVING THE METHODOLOGY OF TEACHING AROMATIC HYDROCARBONS TO STUDENTS THROUGH THE INTEGRATION OF ARTIFICIAL INTELLIGENCE AND NATURAL SCIENCES

Abstract

The rapid advancement of digital technologies and artificial intelligence (AI) has significantly transformed modern educational practices, creating new opportunities for improving the quality of chemistry education. This study examines the theoretical and methodological foundations of teaching aromatic hydrocarbons through the integration of artificial intelligence technologies and natural sciences in higher education institutions. The research explores the pedagogical potential of AI-powered tools for enhancing students’ professional competencies, scientific thinking, and conceptual understanding of complex chemical phenomena.

A comprehensive instructional model integrating chemistry with physics, biology, ecology, computer science, and technology was developed and implemented. Particular attention was given to the use of ChatGPT, Gemini, Copilot, virtual laboratories, molecular visualization software, and digital learning environments in the teaching process. The proposed methodology was evaluated through pedagogical experimentation involving university students studying organic chemistry.

The findings indicate that the integration of artificial intelligence and interdisciplinary learning contributes significantly to the development of students’ cognitive activity, analytical thinking, research skills, digital literacy, and problem-solving abilities. Furthermore, the implementation of AI-supported educational technologies facilitates personalized learning, improves students’ motivation, and enhances the effectiveness of teaching aromatic hydrocarbons. The study concludes that the proposed methodological framework can serve as an effective model for modern chemistry education and may be adapted for teaching other complex scientific disciplines.