NevelésRLs
NevelésRLs refers to a theoretical framework within reinforcement learning that focuses on educational applications. It proposes the use of reinforcement learning agents to personalize and optimize learning experiences for students. The core idea is to treat the educational process as a sequential decision-making problem. An RL agent would observe a student's current state, such as their knowledge level, engagement, and learning style, and then choose an action. These actions could involve presenting specific learning materials, offering different types of exercises, providing targeted feedback, or adjusting the difficulty of a task. The goal of the agent would be to maximize a long-term reward signal, which is typically defined as student learning progress, understanding, or mastery of a subject.
The development of NevelésRLs involves several key components. Firstly, defining the state space accurately is crucial,