Design of Personalized AI Examination System Based on Reinforcement Learning
Yixuan Du, Song Wei, Ying Coa, Xuxiang Chen, Guan Huang · 2024
In contemporary educational concepts, the value of personalized learning is widely recognized, emphasizing the need to cater to the unique needs and abilities of each student. As a crucial component of evaluating educational effectiveness, examinations are gradually transitioning to more efficient and convenient online modes in line with technological advancements and the demands of the times. In light of this, this article proposes a personalized online examination system design based on reinforcement learning algorithms. This system relies on the MySQL database to provide data support, implements the required system functions interface using the Spring Boot framework, and utilizes the Vue framework for the front-end interface. The reinforcement learning algorithm enables the system to continuously optimize the adaptive learning path, personalized assessment, exam process optimization, question generation, difficulty adjustment, and automatic paper setting, aiming to promote academic progress.