‘Generative AI is now common in higher education, and its rise prompts questions about how students shape their own learning, including the cognitive effort involved. Rather than assuming a binary debate between cheating and assistance, we examine perceived Human-AI agency, understood empirically as students’ reported initiative, monitoring of AI outputs and final decision making in AI supported learning. We also examine whether reflection is associated with self-reported critical thinking across UK and China based higher education contexts. We used a comparative quantitative design and Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyse data from university students in the UK (n = 145) and China (n = 164). Both groups showed a similar pattern, where perceived human-AI agency was positively associated with reflective engagement, which subsequently was associated with self-reported critical thinking. However, some sample specific contextual patterns were observed in self-reported psychological outcomes. We found that UK students who reflected on their learning reported stronger academic self-concept, whereas this effect was non-significant in Chinese students’ responses. Furthermore, AI literacy was modeled as a moderator for Chinese students, with higher literacy associated with variation in the agency reflection relationship. These findings theorize an agency gap, suggesting that suggesting that students who report retaining decision making power when using AI also tend to report stronger reflective engagement and self-reported critical thinking. The findings point to the importance of context sensitive pedagogical strategies, while recognizing that cultural values, nationality, ethnicity, institutional policy, tool availability and educational socialization were not directly measured.’
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