AI-BASED PERSONALIZED EDUCATION: THEORETICAL APPROACHES AND ANALYSIS OF INTERNATIONAL EXPERIENCE
Keywords:
artificial intelligence, personalized education, adaptive learning, formative assessment, international experienceAbstract
The article examines the theoretical foundations of AI-supported personalized education and selected international applications. It aims to identify how individualized support relates to pedagogical principles and to propose adaptation directions for education in Azerbaijan. The study uses conceptual analysis, a targeted literature review, and comparative analysis. It considers mastery learning, cognitive load, formative assessment, and self-regulated learning. Examples from India, Singapore, and Türkiye, together with a meta-analysis of intelligent tutoring systems, are compared in terms of evidence and implementation conditions. The analysis argues that completing tasks with technological assistance should not be equated with independent learning. Teacher preparation, reliable Azerbaijani-language content, data protection, and accessibility are identified as important implementation conditions. A phased pilot approach combining diagnosis, appropriate support, and unassisted assessment is proposed for local use. The article is theoretical and comparative; it does not report a new experiment.
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