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AI and Student Learning in Emerging Higher Education Systems asks what AI actually does for students where bandwidth is scarce, classes are crowded, and policies are still forming. Blending multi-institution surveys, field experiments, learning analytics, and qualitative case studies, the book traces AI's effects on engagement, achievement, integrity, and well-being-showing when the average gain hides widening gaps, and how design can close them. Bridging learning science with policy, it introduces the ACCESS framework (Affordances, Capacity, Curriculum, Equity, Safeguards, Stakeholder voice) and offers practical toolkits: integrity-by-design assessment patterns, governance and risk checklists, procurement guidance for low-resource contexts, and 12- and 36 - month roadmaps for universities and ministries.