The Impact of AI-Driven Personalized Learning Platforms on Student Outcomes: A Comprehensive Review

Abstract

Artificial Intelligence (AI)-driven personalized learning platforms have rapidly gained prominence in educational contexts, promising tailored learning experiences that align closely with individual student needs. This comprehensive review synthesizes existing literature to examine the impact of these personalized learning platforms on student outcomes. It highlights key areas including student engagement, academic performance, retention rates, and learner satisfaction. Furthermore, this paper identifies potential challenges such as technological constraints, integration difficulties, data privacy concerns, and equitable accessibility. Finally, the study suggests strategies for effectively implementing AI-driven personalized learning within diverse educational environments and outlines future research directions to optimize their educational potential.