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Database-Driven Adaptive Learning: A Systematic Analysis of AI Integration in Educational Personalization
This paper presents a mixed-methods study analyzing AI-driven database implementations across 47 educational institutions (K-12 and higher education) over 2021-2024, measuring student engagement and academic performance outcomes from personalized adaptive learning systems. The research evaluates technical integration patterns and learning outcomes but does not provide a reusable benchmark or dataset.
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