The Relationship Between AI Anxiety and Academic Motivation Among University Students: The Mediating Role of Emotion Regulation and the Moderating Role of Gender

Synthesis: Yuanchang Zhang, Yantao Shi, and Jing Lu (2026) examined whether AI anxiety constitutes a psychological barrier to university students' motivational adaptation to AI-supported learning, using a cross-sectional survey of 1,484 Chinese undergraduates analyzed with moderated-mediation models. Generative AI is increasingly embedded in students' writing, information retrieval, and knowledge organization, yet the psychological responses to that integration remain under-studied relative to educational affordances and ethical challenges. The study found AI anxiety negatively associated with both emotion AI Regulation in Education and academic motivation, while emotion regulation was positively associated with academic motivation; bootstrap analyses confirmed a significant negative indirect path from AI anxiety to academic motivation through emotion regulation. Gender moderated the emotion-regulation–motivation link, with a stronger positive association among male students.

Key Findings

• AI anxiety correlates with lower motivation and poorer regulation: AI anxiety was negatively correlated with emotion regulation (r=−0.172) and academic motivation (r=−0.175), whereas emotion regulation was positively correlated with academic motivation (r=0.457), all p<0.001.
• Emotion regulation partially mediates the path: Bootstrap analysis (5,000 resamples) confirmed a significant negative indirect association between AI anxiety and academic motivation through emotion regulation (indirect effect=−0.076, 95% CI −0.108 to −0.047), with the direct path also remaining significant.
• Gender moderates the regulation–motivation link: The positive association between emotion regulation and academic motivation was stronger among male students, making gender a boundary condition for this pathway.
• Weak and cautious use-duration signal: Daily AI use showed only a weak positive correlation with academic motivation (r=0.053), interpreted cautiously given most students reported under one hour of use per day — exposure duration alone does not capture purpose or quality of AI engagement.
• Practical implication for AI literacy education: Findings suggest AI literacy education should integrate emotion-regulation and metacognitive support with differentiated, gender-aware learning assistance.

What this means for practice

• Instructors. Treat AI anxiety as a motivational risk rather than a comfort issue: it correlated negatively with academic motivation (r = −0.175) and with emotion regulation (r = −0.172), both p < 0.001.
• Instructors. Teach emotion-regulation, metacognitive, and confidence-building strategies alongside AI literacy, because emotion regulation was the pathway linking anxiety to lower motivation (indirect effect = −0.076, 95% CI −0.108 to −0.047).
• Faculty developers. Avoid one-size-fits-all support: the regulation–motivation association was stronger for male students (B = 0.519) than for female students (B = 0.358), so differentiate by student.
• Administrators. Stop reading usage time as engagement: daily AI use correlated only weakly with motivation (r = 0.053), and 72.6 percent of these students used AI less than an hour a day.

Limitations

• The design is cross-sectional, so it cannot establish causal direction or temporal ordering among AI anxiety, emotion regulation, and academic motivation; reverse relationships remain possible.
• Participants were 1,484 Chinese university students recruited by convenience sampling through an online platform, so the single-country, non-probability sample limits generalization.
• All three measures are self-report and PROCESS models them as observed composite scores without accounting for measurement error, leaving the results open to common method bias.
• The three instruments were administered in a fixed order — emotion regulation, then academic motivation, then AI anxiety — so order, priming, and fatigue effects cannot be excluded, and students' pre-existing AI literacy was never measured or controlled.

Citation

Zhang, Y., Shi, Y., & Lu, J. (2026). The relationship between AI anxiety and academic motivation among university students: The mediating role of emotion regulation and the moderating role of gender. Frontiers in Psychology, 17, 1918525.