SCIENTIFIC AND PRACTICAL SIGNIFICANCE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE EDUCATION SYSTEM: THEORETICAL AND METHODOLOGICAL FOUNDATIONS

Abstract

The article examines the scientific and practical significance of artificial intelligence technologies in the education system from a theoretical and methodological perspective. The problem is considered relevant because the rapid integration of AI into educational practice has outpaced theoretical understanding of its pedagogical value. The purpose of the article is to determine the main directions, levels and criteria for evaluating the significance of AI technologies for educational theory and practice. The research is based on an analysis of recent studies on AI in education, focusing on the distinction between instrumental, methodological and systemic levels of significance. The article clarifies three key functions of AI in education: adaptive content delivery, automated assessment and feedback, and learning analytics for decision support. The main result is a three-level model of scientific and practical significance, connecting theoretical contributions (new knowledge about learning), methodological innovations (new ways of teaching), and practical outcomes (improved learning results). The study argues that the true significance of AI in education is revealed only when technological capabilities are translated into pedagogical solutions that address real educational problems.