Abstract
The use of generative artificial intelligence (AI) is becoming more prevalent in the context of university learning, but its connection to students' engagement in learning is still not fully understood. This research aimed to explore the relationship between the academic use of generative AI and academic engagement among university students in Algeria. The study adopted a quantitative cross sectional survey design based on Student Engagement Theory and Technology Acceptance Model. A total of 217 students from public and private universities were used to collect data. Academic use of generative AI and academic engagement were measured using a structured questionnaire with multi-item scales. Data was analysed with descriptive statistics, Pearson correlation and regression analysis in SPSS. The mean scores for academic use of generative AI (M = 3.76, SD = 0.67) and academic engagement (M = 3.64, SD = 0.71) were high. Academic engagement was highly correlated with academic use of generative AI (r = .491, p < .001). Simple linear regression revealed that AI use was a significant predictor of engagement, accounting for 24.1% of the variance in engagement (β = .491, p < .001). Academic AI use was the strongest predictor regardless of demographic characteristics, frequency of AI use, or prior AI experience (β = .432, p < .001), accounting for 34.5% of variance. The results indicate that generative AI can be a learning aid and not a replacement to independent learning to support engagement. AI literacy, critical evaluation and responsible use should be encouraged at universities. Causality cannot be inferred from the data as they were cross-sectional and self-reported.