Authors: Dr. Shalini Das
Abstract: Adaptive learning systems are transforming educational experiences by personalizing content delivery based on student behavior and performance. Reinforcement learning (RL), a subset of machine learning, offers dynamic adaptation capabilities that significantly enhance such systems. By continuously learning from user interactions, RL-driven adaptive systems optimize instructional strategies to cater to diverse learner profiles. This paper explores the integration of reinforcement learning in adaptive educational technologies, highlighting methodologies, advantages, challenges, and real-world implementations.
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