ARTIFICIAL INTELLIGENCE AS A STRUCTURAL COMPONENT OF THE METHODOLOGICAL SYSTEM FOR TEACHING AN EDUCATIONAL COMPONENT IN HIGHER EDUCATION

Abstract

The article substantiates the expediency of considering Artificial Intelligence (AI) not merely as a technological tool, but primarily as a modern learning medium – a structural component of the methodical system for teaching any educational subject in higher education. The purpose of the study is to analyze scientific approaches to integrating AI into the instrumental component of the methodical system, identify new didactic opportunities compared to traditional tools, and highlight the corresponding benefits, challenges, and prospects. The methodological framework is based on systems analysis, a comparative literature review, and experimental design modeling. A synthesis of international and Ukrainian sources enabled the description of the following functions of AI as a learning medium: explanatory-instructional; drills and practice; formative- evaluative; adaptive-organizational; communicative-tutoring. It is determined that these functions are cross- disciplinary. The study presents a table of trends in AI integration as a learning tool across key areas: adaptive learning, dialogue systems, formative assessment, content generation, educational simulations, and learning analytics. The analysis of benefits (personalization, immediate feedback, task variability, support for self- directed learning) and challenges (academic integrity, "hallucinations," dependency, inequality of access, data ethics) is provided. The conclusions emphasize the necessity of pedagogical design, responsible use policies, and the preparation of both faculty and students for critical interaction with AI tools. Furthermore, the study advocates for the creation of hybrid learning models that combine the analytical power of AI with the human element of teaching.