This research focuses on recent studies of AI-Enhanced Personalized Learning, organized into three main sections: understanding key aspects, investigating practical methodologies, and elucidating motivations for AI integration into personalized learning to provide insights for future research in learning science. The methodology involves a rapid literature review, emphasizing eligibility criteria and a precise study selection process. The conclusion underscores the importance of seamlessly integrating AI analytics with humancentric approaches in personalized learning, enriching data, and training algorithms for efficiency, alongside emphasizing the role of human oversight.
A Review of AI-Enhanced Personalized Learning Systems: Implications for the Learning Sciences
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