Supplementary file 1_Measuring attitudes of ethical use of GenAI in the work of university educators in Slovakia.docx

Parallel non-parametric analyses were conducted as robustness checks. The analyses were performed in Python 3.14.6 in the Google Colab environment. Mean responses favored ethically safer alternatives for all 31 dilemmas (all p < 0.001; |d| = 0.36–2.02).

Significant differences between dilemmas were found within every academic domain (all p < 0.001; η² = 0.032–0.194), while post hoc analyses identified both comparable subsets and distinct ethical concerns. These findings demonstrate that educators' concerns constitute a differentiated hierarchy rather than a homogeneous set. The study provides an empirically grounded basis for universities, policymakers, and ethics committees to develop ethical codes for AI use, prioritize AI-governance provisions, address comparable dilemmas through shared rules, and develop dedicated principles or implementation guidance for conceptually distinct concerns.</p>