Abstract

This study presents a scientometric analysis of personalized learning research from 2020 to 2024. Using the Lens database, 4,463 scholarly articles were analyzed to identify key trends and patterns in this rapidly evolving field. The analysis revealed consistent publication growth over the 5 years, with journal articles dominating as the primary publication type. Hessian Normal University emerged as the most productive institution, while Jackson Steinher was identified as the most prolific author. The United States and China were the leading countries in terms of research output. Education and Information Technologies was the top journal publishing personalized learning research. Co-authorship network analysis highlighted collaborative patterns among researchers, while keyword co-occurrence networks revealed the centrality of artificial intelligence and related concepts in the field. Citation analysis identified influential documents and sources shaping the discourse. The findings suggest an increasing focus on integrating AI and machine learning into personalized learning systems and a growing emphasis on interdisciplinary approaches. This scientometric overview provides valuable insights into the current state and emerging trends in personalized learning research, which may inform future studies and applications in this domain.

This work is licensed under a Creative Commons Attribution 4.0 License.