AI-assisted autonomous learning and reduced academic accomplishment in vocational higher education: the mediating role of hardiness

As generative AI tools become increasingly embedded in students’ everyday study routines, a key question in higher education is how AI-assisted autonomous learning relates to students’ academic adaptation. Existing research has largely emphasized the benefits of AI for efficiency, access to information, and personalized support, whereas less attention has been paid to its potential associations with students’ psychological resources and self-evaluative academic outcomes. Drawing on a psychological resource perspective, this study examined the relationships among AI-assisted autonomous learning, hardiness, and reduced academic accomplishment. Survey data were collected from 1,264 students at a vocational college in China and analyzed using structural equation modeling. The results showed that AI-assisted autonomous learning was negatively associated with hardiness and positively associated with reduced academic accomplishment. Hardiness was also negatively associated with reduced academic accomplishment and partially mediated the relationship between AI-assisted autonomous learning and reduced academic accomplishment. The indirect effect accounted for a substantial proportion of the total effect. These findings extend research on AI in higher education by suggesting that AI-assisted learning may have implications beyond efficiency and convenience, particularly for students’ psychological resources and academic self-evaluation. The study contributes to understanding academic adaptation in AI-mediated learning contexts and offers implications for the responsible integration of AI into higher education.