<![CDATA[General Background: The growing integration of Artificial Intelligence (AI) in higher education has introduced new opportunities for digital learning and academic support. Specific Background: Along with AI adoption, students’ academic achievement is also associated with internal learning capacity such as self-regulated learning, digital literacy, and the management of study load. Knowledge Gap: However, limited studies examine these variables simultaneously within a single analytical framework to understand their relationship with academic achievement. Aims: This study analyzes the relationship between Artificial Intelligence usage frequency, self-regulated learning, digital literacy, study load, and student academic achievement. Results: The findings indicate that the frequency of AI usage does not show a significant relationship with academic achievement, while self-regulated learning, digital literacy, and study load show significant positive relationships with student academic achievement. Digital literacy and study load also do not moderate the relationship between AI usage frequency and academic achievement. Novelty: This study proposes an integrated conceptual examination of Artificial Intelligence usage together with self-regulated learning, digital literacy, and study load in explaining student academic achievement. Implications: The results suggest that universities should prioritize strengthening self-regulated learning, improving critical digital literacy, and designing proportional study loads to support the optimal use of AI in the academic learning process. Highlights • Self-regulated learning shows a positive relationship with student academic performance.• Digital literacy and study load are associated with higher academic achievement levels.• Artificial intelligence usage frequency is not the primary determinant of academic scores. Keywords Artificial Intelligence; Self-Regulated Learning; Digital Literacy; Study Load; Academic Achievement]]>
