AI-Supported Learning and Academic Performance: The Mediating Role of Student Engagement
Juan Carlos Quijandria Lavarello, Julio Andres Palomino Silva, Pedro Liberato Valladares Jara, Lucio Alberto Sosa Bitulas
Artificial intelligence (AI) is increasingly transforming teaching and learning in higher education, creating new opportunities for personalized instruction, academic support, and learning enhancement. However, unequal access to AI-based educational technologies may reinforce existing academic inequalities among students from different socioeconomic backgrounds and institutional contexts. This article examines how disparities in access to, use of, and support for AI-enhanced learning technologies may contribute to unequal educational opportunities in higher education. It develops a conceptual framework connecting digital access, AI literacy, institutional readiness, and students’ opportunities to benefit from AI-supported learning. The framework also considers the role of institutional policies, digital infrastructure, and educational support in shaping the relationship between AI adoption and academic inequality. Rather than presenting unverified empirical findings, the article identifies conceptual relationships and proposes directions for future empirical investigation. The framework aims to support researchers, educators, and higher education policymakers in evaluating the equity implications of AI integration and in designing strategies that promote inclusive, responsible, and equitable access to educational technologies.