Tongyu Su
The increasing integration of generative artificial intelligence (GenAI) into higher education has altered how students access information, complete academic tasks, and participate in learning activities. Alongside these opportunities, GenAI introduces technology-related demands that may be associated with students' learning engagement. This study examined the relationship between generative AI technostress and learning engagement, with academic adaptability examined as a statistical mediator and AI literacy as a moderator of this relationship. A quantitative cross-sectional research design was adopted. Using nonprobability convenience sampling, data were collected through an online self-report questionnaire administered via Wenjuanxing to undergraduate students with experience using GenAI for academic purposes at Northeast Normal University in China. A total of 529 valid responses were analyzed using structural equation modeling and bootstrap-based conditional process analysis. Generative AI technostress was negatively associated with academic adaptability and learning engagement, whereas academic adaptability was positively associated with learning engagement. A significant indirect association between generative AI technostress and learning engagement through academic adaptability was identified, while the direct association remained significant. AI literacy also moderated the negative association between generative AI technostress and academic adaptability, with a weaker negative association observed among students reporting higher AI literacy. The conditional indirect association through academic adaptability was stronger at lower levels of AI literacy. Taken together, the findings indicate that the relationship between generative AI technostress and learning engagement is associated with students' capacity to adapt to changing academic demands and varies according to their level of AI literacy.