Mapping Adaptive Learning Research and Its Contribution to SDG 4

Abstract

This study conducts a decade-long bibliometric analysis to critically map the intellectual structure, thematic evolution, and collaboration patterns within adaptive learning research. The study addresses a key gap in prior literature, where existing reviews remain predominantly narrative and fragmented, limiting systematic understanding of how adaptive learning has evolved conceptually and methodologically. Using the Scopus database, 14,009 records were initially identified, of which 141 articles met rigorous inclusion criteria. Bibliometric analysis was performed using Bibliometrix and Biblioshiny, incorporating co-authorship analysis, co-citation mapping, keyword co-occurrence, and thematic evolution techniques to ensure analytical depth and methodological robustness. The findings reveal three dominant knowledge clusters: technology-driven personalization, data-informed learning optimization, and pedagogical integration of adaptive systems. Influential authors, leading journals, and emerging research fronts highlight a shift from system development toward learning effectiveness and equity-oriented implementation. Collaboration networks indicate increasing internationalization but uneven scholarly connectivity across regions. This study contributes by providing a consolidated intellectual map, identifying emerging trajectories, and clarifying theoretical and methodological directions for future research. The findings offer practical implications for designing evidence-based adaptive learning strategies and inform policy and research agendas in data-driven education.