Reinforcement Learning in Education: Applications, Challenges, and Future Directions

This paper explores how reinforcement learning (RL) can be used in education, looking at how it works, its challenges, and where it might be headed in the future. Reinforcement learning is a way to create personalized, adaptive learning experiences by adjusting educational content based on each student’s progress. While RL shows promise for boosting student engagement and improving learning outcomes, it also faces challenges, such as limited data, slow feedback, and ethical concerns. By reviewing recent studies, this paper highlights potential future directions, including integrating reinforcement learning with other approaches, leveraging offline reinforcement learning, and establishing ethical guidelines to ensure equitable access for all students.