Learning Agility, Institutional Support, and AI Governance as Predictors of Artificial Intelligence Tensions among Postgraduate Students in Uganda

Abstract

The integration of AI into higher education has sparked debates among scholars, especially regarding ethics, accountability, legitimacy, and academic practices. In this context, this study examined whether learning agility, institutional support, and AI governance could predict the level of tension among postgraduate students in Uganda's public higher education institutions. Using a quantitative design and a cross-sectional survey, the researcher collected substantial data from 88 postgraduate students; however, only 71 responses were analyzed. The data were examined through descriptive statistics, Pearson correlation, and multiple linear regression. The overall results indicate that respondents exhibited a relatively high level of learning agility, moderate institutional support, moderate levels of AI-related tension, and a low perception of AI governance. The correlation analysis showed that learning agility, institutional support, and AI governance were all positively correlated with AI tension. The only variable that emerged as a statistically significant predictor in the regression analysis was AI governance. In contrast, learning agility and institutional support did not have independent significant effects. These findings suggest that postgraduate students’ perceptions of AI tension are more influenced by the socio-institutional environment than by their adaptive abilities. The study concludes that AI tension in higher education mainly reflects socio-institutional factors, requiring clear, practical, and trust-building measures as prerequisites for responsible AI integration. The data provide context-specific evidence from Uganda and contribute to the existing literature on AI in higher education by showing that governance is not merely a background condition but a key factor shaping students' perceptions of their AI experiences in academia.