IMPROVING THE QUALITY OF EDUCATION IN TECHNICAL SCHOOLS USING ARTIFICIAL INTELLIGENCE: ISSUES OF THE TEACHING PROCESS, EDUCATIONAL ACTIVITIES AND QUALITY ASSURANCE (IN THE CONTEXT OF UZBEKISTAN)
Abstract
The rapid integration of artificial intelligence (AI) into technical colleges systems has created new opportunities for enhancing educational quality. This study examines the role of artificial intelligence in improving teaching and learning practices, assessment systems, student support mechanisms, and institutional quality assurance processes. Using a qualitative conceptual research design based on a systematic review of international literature and policy documents, the paper analyzes how AI-driven tools contribute to student-centered learning, data-informed decision-making, and continuous quality improvement. Particular attention is given to the context of technical colleges reforms in Uzbekistan, where digital transformation has been identified as a strategic priority. The findings indicate that artificial intelligence can significantly enhance learning outcomes, institutional efficiency, and transparency when aligned with quality assurance frameworks. However, challenges related to ethics, data protection, digital readiness, and staff capacity remain critical. The study concludes with strategic recommendations for the effective and responsible integration of AI into technical colleges quality systems.