Knowledge Network Mapping in Education and Technology Research: A Bibliometric Analysis

Abstract

The rapid development of technology has significantly transformed the field of education, leading to an increasing number of studies on the integration of technology in learning processes. However, the growing volume of publications presents challenges in identifying research trends, thematic structures, and collaboration patterns. This study aims to map the knowledge network in education and technology research using a bibliometric approach. This research employs a quantitative bibliometric method by analyzing scientific publications obtained from reputable databases. Data were collected based on relevant keywords and processed using techniques such as co-authorship, co-occurrence, citation, and co-citation analysis. Visualization tools, including VOSviewer, were used to identify research clusters and network relationships. The results reveal a significant increase in publications, with dominant topics including digital learning, artificial intelligence in education, and online learning. Cluster mapping shows interconnected themes such as learning technology, pedagogical innovation, digital literacy, and technology-based evaluation. In addition, collaboration patterns are still largely institution-based, although international cooperation has increased. In conclusion, education and technology research continues to evolve toward intelligent technology integration, personalized learning, and the development of 21st-century skills. These findings provide valuable insights for future research directions and strategic academic development.