AI-Driven Learning Analytics and Student Retention Among International Students in Chinese Universities

Herin Ratnaningsih (College of International Studies, Yangzhou University, Jiangsu, China)
Zhang Jiasheng (Australian Research Center, College of International Studies, Yangzhou University, Jiangsu, China)
Yue Zhao (School of Management, Wuxi University of Technology, Jiangsu, China)
Hu Xun (School of International Education, Wuxi University of Technology, Jiangsu, China)

Journal of Technology-Assisted Learning
Vol. 2 No. 2 (2026): Journal of Technology-Assisted Learning

Artificial Intelligence (AI) and learning analytics are rapidly reshaping the modern landscape of higher education, impacting academic engagement, personalised learning experiences, and student retention in the learning environment. In recent years, Chinese universities have been more and more implementing AI technologies in education to enhance institutional responsiveness, adaptability, and predictive academic support for students from domestic and abroad. Despite the widespread use of AI in HEIs, there is, however, little qualitative research that has examined the perceptions and experiences of international students in the context of AI-mediated learning environments in Chinese HEIs. Hence, this research aimed to explore how AI-powered learning analytics affects student attrition among international students at Chinese Universities. The study used a qualitative exploratory research design, following an interpretivist paradigm. Twenty-five international students at undergraduate, master’s, and doctoral levels at various universities in China were interviewed using semi-structured interviews. Descriptive thematic analysis was applied in the analysis of data in this study, based on the analytical framework of Braun and Clarke. The results indicated that AI learning analytics had a positive impact on academic engagement, educational organisation, adaptation of personal learning, and institutional support, which was enabled by predictive academic monitoring and intelligent feedback systems. In general, the participants considered that the use of AI-supported educational technologies can be beneficial in terms of increasing awareness about learning, participation in learning, and persistence in learning. The research also revealed a number of challenges encountered in cultural adaptation, language barriers, emotional stress, privacy concerns, and digital surveillance in the context of AI in education. The study shows that AI learning analytics, in combination with ethically responsible, culturally inclusive, and human-centred education, can make a significant contribution to international student retention. The results add to the current body of knowledge by offering qualitative insight into the impact of AI-enhanced education in higher education institutions in China.