Student Engagement With AI Feedback: Evidence From Ethnic Minority Students in China

ABSTRACT This study explored the behavioral, cognitive, and affective engagement of 11 ethnic minority students with AI writing feedback at a Chinese research university. Using a qualitative approach, the research collected data from student drafts, screen recordings of revision processes, AI user logs, and follow‐up interviews with participants, including two Kazakh, two Uyghur, three Mongolian, and four Tibetan students. Findings revealed diverse student engagement patterns influenced by digital literacy, emotional attachment, grading expectations, and the linguistic inclusivity of AI tools. Most participants showed active behavioral and cognitive engagement with AI feedback and expressed positive attitudes, which facilitated their feedback uptake; however, one student's strong emotional attachment to AI as a “friend” hindered her behavioral and cognitive engagement. The results underscore the importance of digital literacy, educational support, and multilingual AI accessibility for improving ethnic minority students’ engagement in digital learning environments, providing implications for fostering inclusive and culturally responsive practices in higher education.