AI Literacy and Student Well-Being in Higher Education: The Mediating Roles of Technostress and Emotional Engagement

Abstract

Artificial intelligence (AI) is now embedded in many university learning activities, where it can support personalised study, academic assistance, rapid feedback, and greater student autonomy. These opportunities, however, may be accompanied by psychological strain when learners do not have the knowledge, evaluative judgement, ethical awareness, or confidence required to use AI appropriately. This study examined how artificial intelligence literacy (AIL) relates to student well-being (SWB) and whether technostress (TS) and emotional engagement (EE) statistically mediate this relationship in AI-supported higher education. Data were obtained through a cross-sectional survey of 250 higher education students and analysed with partial least squares structural equation modelling (PLS-SEM) using SmartPLS 4. AIL was positively associated with EE and SWB and negatively associated with TS. EE, in turn, showed a positive association with SWB, whereas TS was negatively related to SWB. Both EE and TS carried significant indirect effects between AIL and SWB, while the direct AIL–SWB path remained significant, indicating partial mediation. The findings suggest that AIL should be understood not only as technical competence but also as a resource that may help students engage more positively with learning and experience less technology-related strain. Universities should therefore approach AI literacy as a human-centred capability that integrates conceptual understanding, critical evaluation, ethical and responsible use, and appropriate psychosocial support.