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Database-Driven Adaptive Learning: A Systematic Analysis of AI Integration in Educational Personalization
This paper presents a systematic analysis of AI-driven database systems implemented across 47 educational institutions (K-12 and higher education) over three years, evaluating their impact on personalized adaptive learning, student engagement, and academic performance. The study examines technical integration patterns, learning outcomes, and implementation challenges of AI-enhanced learning management systems.
This article examines the transformative role of AI-driven databases in facilitating personalized learning experiences within educational institutions. Through a systematic analysis of implementations across K-12 and higher education settings, we investigate how intelligent database systems enable adaptive learning pathways and real-time intervention strategies. The article synthesizes data from 47 educational institutions implementing AI-enhanced learning management systems over a three-year pe