Personalized Learning Systems Using AI Enhancing Adaptive Education

Abstract

Personalized learning systems use AI to make educational content fit each learner’s skills, speed, and preferences. These systems give students adaptive tests, quick feedback, and predictive analytics on their performance, therefore overcoming the difficulties of traditional education. This paper discusses AI-driven adaptive learning, NLP-based intelligent tutoring, reinforcement learning for optimal learning pathways, predictive analytics for assessing student performance, emotion recognition for measuring engagement, and the use of gamification to enhance motivation. Experimental analysis shows that the proposed framework increases student retention and engagement by more than 30%.