As artificial intelligence (AI) becomes more prevalent in higher education, bringing potential benefits, student perceptions of AI, especially in contexts that have been understudied, such as Somalia, are relatively uncharted terrain. In this study, we examined attitudes towards AI among 474 Somali university students, exploring possible links to gender, age, and self-assessed AI experience. The data collection took place during the period from January 23 to February 18, 2025.. Applying a cross-sectional survey approach with convenience sampling through online questionnaires, we first carried out bivariate analyses (Mann-Whitney U, Kruskal-Wallis, Spearman correlation) to examine these relations. Initial analysis revealed no statistically significant differences across gender (p=0.887) or age group, nor a significant correlation across AI experience (p=0.587). Acknowledging that bivariate tests might not adequately capture multifaceted influences, multivariate analysis using Quade ANCOVA, however, revealed a statistically significant effect of age group on AI attitudes after controlling for AI experience (p0.001), suggesting that older students held more positive attitudes compared to their younger peers. In contrast, gender remained a non-significant predictor even after adjusting for experience. In conclusion, these findings reveal that covariates such as AI Experience must be controlled in the assessment of attitudes towards artificial intelligence. Therefore, AI education programs and awareness studies to be implemented in universities should be structured to take into account the different needs of age groups; in addition, personalised learning strategies should be developed by considering individual experience levels.
Sancar et al. (Mon,) studied this question.