MECHANISMS FOR IMPROVING EDUCATION QUALITY BASED ON ARTIFICIAL INTELLIGENCE

Abstract

This article provides a comprehensive analysis of mechanisms for improving the quality of education based on artificial intelligence technologies. The study examines AI-driven adaptive learning systems, personalization of the educational process, automated assessment of student performance, and predictive analysis of learning outcomes. Special attention is given to mechanisms for identifying individual learners’ needs and abilities through the analysis of large-scale educational data. The article highlights the pedagogical effectiveness of artificial intelligence technologies, their role in supporting teachers’ professional activities, and their significance in enhancing educational management systems. The research findings demonstrate that AI-based digital tools contribute to improving educational quality, increasing the flexibility of learning processes, and enhancing the accuracy and objectivity of assessment practices. Furthermore, the integration of artificial intelligence into education enables data-driven decision-making and fosters more efficient learning environments. The results of this study have practical relevance for the implementation of innovative approaches in higher education institutions and general education systems, supporting the sustainable development of modern digital education.