Student Simulation

Student simulation uses computational models to replicate student learning behaviors, aiming to improve educational practices and research by providing realistic virtual learning environments. Current research focuses on leveraging large language models (LLMs) and reinforcement learning algorithms to generate diverse and nuanced student responses, often incorporating cognitive science principles and integrating structured data to enhance realism and adaptability. This approach holds significant potential for personalized learning, curriculum development, and evaluating the effectiveness of educational interventions across various fields, from medical training to robotics education.