Understanding higher education students’ reluctance to adopt GenAI in learning in Latvia and Ukraine

This study investigates the factors driving students’ reluctance to adopt generative artificial intelligence (GenAI) in higher education in Latvia and Ukraine. Although GenAI tools are rapidly diffusing across educational settings, little empirical research has examined why students choose not to use them or how these reasons differ across institutional and demographic contexts. A cross-sectional survey (N = 945) was conducted across three universities, and data were analysed using descriptive statistics and binary logistic regression. The findings show that 22% of students do not use GenAI in their studies, with part-time students, distance learners, older students, and graduate students showing the highest rates of non-use. The leading reasons for non-adoption were disbelief in GenAI effectiveness (46.9%), insufficient information (26.5%), and lack of knowledge about how to use GenAI tools (19.7%). Regression results indicate that learning format, age, and disciplinary affiliation significantly predict GenAI use in Ukraine, whereas only learning format predicts use in Latvia, suggesting that institutional context moderates students’ technological engagement. These findings provide one of the first cross-national, quantitatively grounded analyses of GenAI non-use in Europe and Central and Eastern Europe. They highlight the importance of targeted institutional interventions, including structured training, explicit guidelines, and discipline-specific support, to ensure equitable and informed GenAI adoption and to better prepare students for an AI-transformed labor market.