The Research Hotspots and Future Trends of Adaptive Learning in the Age of Artificial Intelligence: A Bibliometric Analysis From 2014 to 2024

Aims: To examine the research status and developmental trend within the adaptive learning. Background: Adaptive learning provides personalized learning paths based on the unique needs of each learner. However, a comprehensive bibliometric analysis of this field remains limited. Methods: A bibliometric analysis was conducted. Our search within the Web of Science database targeted articles on adaptive learning published from January 1, 2014, to November 16, 2024. The dataset encompassed publication counts, participating countries, institutions, authors, cited journals, references, and keywords, with CiteSpace facilitating the bibliometric analysis. Results: The review encompassed 561 articles by 288 authors across 240 institutions in 68 countries. These publications showed an upward trend over the decade, with the United States of America leading with 214 articles (38.15%). The University of Toronto topped institutional contributions with 16 articles (2.85%). Computers and Education emerged as the most cited journal in adaptive learning, with 244 articles. Timeline analysis and burst detection identified key research hotspots, including the theoretical and technological underpinnings of adaptive learning, its educational applications, and its efficacy. Emerging trends suggest a shift toward intelligent optimization and outcome‐focused adaptive learning, as well as its integration with higher education. Conclusions: The study provides a comprehensive view of adaptive learning research from the past decade, offering insights and indicating future research directions within the field. Implications for Nursing Management: Nursing administrators leverage adaptive learning mechanisms to intelligently identify knowledge gaps in nursing practice, develop personalized training programs and simulation exercises, and optimize nursing management models.