Literature Review of Personalizing Learning Recommendation Systems Using Machine Learning in Chinese Higher Education

With the rapid development of information technology, personalized education recommendation systems have gained widespread attention and rapid development in China’s education sector. These systems provide customized learning resources and course recommendations to meet the individual needs of different students by analyzing their learning behaviors, preferences, and performance. This study comprehensively searched 45, 623 literatures from 2002 to 2022, focusing on the current status, key technologies, and application practices of educational recommendation systems in China. It first investigates the basic deep learning recommendation methods used in current personalized learning recommendation systems, and then summarizes the current status of machine learning techniques applied in personalized learning recommendation systems for higher education in China. Finally, through a comprehensive analysis of the existing literature, we discuss the current challenges and future development direction of China’s educational recommendation systems, and put forward improvement suggestions for domestic educational recommendation systems, aiming to fill the research gaps and promote technological progress and innovation.