Supplementary file 1_Perceived educational value, ethical risk, and support for responsible AI governance in higher education: an embedded mixed-methods study.docx

Qualitative open-ended responses from 179 participants were subsequently analyzed using a codebook-based thematic analysis. Quantitative data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).</p>Results<p>Participants reported above-midpoint levels of PEV, AERP, and RAGS. The structural model explained 59.1% of the variance in RAGS.

Both PEV [β = .255, p < .001, 95% bias-corrected CI (.117,.377)] and AERP [β = .627, p < .001, 95% bias-corrected CI (.485,.748)] were positively associated with governance support, with AERP showing the larger association. AERP did not significantly moderate the PEV–RAGS relationship [β = −.030, p = .370, 95% bias-corrected CI (−.098,.037)]. MICOM established full measurement invariance for PEV and AERP but not compositional invariance for RAGS; therefore, structural student–instructor comparisons involving RAGS were not interpreted.

Thematic analysis identified responsible conditional integration as the central interpretive frame, with learning enhancement, governance expectations, academic integrity, over-reliance, and critical-thinking concerns among the salient themes.</p>Discussion<p>These findings provide preliminary empirical support for a model in which perceived educational value and ethical risk perception are each associated with governance endorsement.

The stronger association between ethical risk perception and governance support suggests that transparent attention to ethical risks may be relevant to institutional governance communication, a possibility that requires intervention-based research. Practical implications include risk-aware AI literacy programs, transparent and contestable governance policies, stakeholder engagement, and human-in-the-loop oversight mechanisms in AI-mediated assessment.</p>