Personalized AI-driven education: An AI framework for enhanced learning outcomes among school-age children

This paper presents Tutor AI, an educational platform that integrates AI-driven personalization with evidence-based pedagogical approaches for learners aged 3-17. The system features customizable 3D pedagogical agents, adaptive content delivery, and dynamic educational visualizations. Our implementation targets documented academic challenges in mathematics, reading, and science while addressing educational equity concerns. The paper outlines the theoretical framework, technical architecture, and projected impacts of the system. Based on meta-analytic evidence from comparable interventions, we project potential effect sizes ranging from 0.15-0.30 SD across core academic domains.