AI-Powered Adaptive Learning Systems in Higher Education: A Scoping Review of Implementation and Impact on Academic Performance

Abstract

Artificial intelligence (AI)-powered adaptive learning systems are revolutionizing higher education by delivering real-time, personalized learning experiences that align with individual student progress. This scoping review maps current evidence on the implementation of such systems in e-learning platforms and evaluates their educational impacts. Fourteen empirical studies published between 2013 and 2025 were systematically analyzed following Arksey & O’Malley and Joanna Briggs Institute methodologies. Findings reveal consistent improvements in academic performance, engagement, retention, and satisfaction across diverse disciplines including law, engineering, dentistry, and language education. Key features enhancing these outcomes include adaptive feedback, curriculum-aligned personalization, and real-time analytics. Nonetheless, barriers such as faculty resistance, ethical concerns like data privacy and algorithmic bias, and regional disparities in adoption—especially in Latin America and Sub-Saharan Africa—persist. The review underscores the transformative potential of AI-based adaptive learning systems while highlighting the need for inclusive design, long-term evaluation, and equitable implementation strategies in higher education.

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