AI-Driven Recommendation Systems for Personalized E-Learning Platforms
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Abstract
Personalized learning is becoming increasingly important in modern education systems. This paper proposes an AI-based recommendation system that adapts learning content based on user behavior, preferences, and performance. Collaborative filtering and deep learning techniques are used to enhance recommendation accuracy. The system improves learner engagement and knowledge retention. The research demonstrates the effectiveness of AI in creating adaptive and intelligent e-learning environments.
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References
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