Critical thinking and technostress among university students: the mediating role of AI-related academic self-efficacy
TL;DR
Critical thinking was indirectly associated with technostress through AI-related academic self-efficacy; however, the positive direction of this pathway suggests that higher self-efficacy may be linked to greater engagement with AI-mediated academic tasks and therefore greater exposure to technology-related demands.
Abstract
The proliferation of technology in higher education has generated new forms of psychological stress that require an understanding of cognitive mechanisms. This study examined the association between critical thinking and technostress and the mediating role of AI-related academic self-efficacy among 340 Peruvian university students via partial least squares structural equation modeling (PLS‒SEM). The following validated instruments were used: Yoon’s Critical Thinking Disposition Scale (26 items administered; 13 retained after the reflective measurement-model assessment), the General Self-Efficacy Scale adapted for artificial intelligence, GSE-6AI (6 items, all retained), and the RED-Technostress scale (22 items administered; 17 retained). The results revealed the absence of a significant direct association between critical thinking and technostress (β = -0.071; p = 0.444) but confirmed a significant positive association between critical thinking and AI-related academic self-efficacy (β = 0.403; p < 0.001) and a significant positive association between AI-related academic self-efficacy and technostress (β = 0.258; p < 0.001). The indirect association between critical thinking and technostress through AI-related academic self-efficacy was significant and positive (β = 0.104, p < 0.001). The model accounted for 16.2% of the variance in self-efficacy and 5.6% of the variance in technostress. These findings do not support the expected direct protective association between critical thinking and technostress. Critical thinking was indirectly associated with technostress through AI-related academic self-efficacy; however, the positive direction of this pathway suggests that higher self-efficacy may be linked to greater engagement with AI-mediated academic tasks and therefore greater exposure to technology-related demands. Given the cross-sectional, self-report design, these associations should not be interpreted causally, and their practical implications remain preliminary.