Reinforcement learning, a subset of machine learning, focuses on how agents ought to take actions in an environment to maximize cumulative reward. By integrating these techniques into the classroom, educators aim to create adaptive learning experiences that can respond dynamically to students' needs and behaviors. This paper investigates the influence of reinforcement learning-based instructional methodologies on students' perceptions and academic outcomes within an educational setting. Preliminary findings suggest that environments enhanced by reinforcement learning not only improve academic performance but also positively influence students' attitudes towards their placement by analyzing their skill sets. By understanding these dynamics, educators and technologists can better design and implement learning systems that support personalized learning pathways, potentially transforming traditional educational practices.