Bibliometric Mapping of Global Research Trends on Technology Integration in Japanese Language Education

Abstract

This study aims to map global trends in technology integration research in Japanese language learning using a bibliometric approach. Data were collected from the Scopus database and analyzed using VOSviewer to display network visualization, topic evolution, and keyword clusters. The results show a significant increase in publications since 2022, driven by the acceleration of post-pandemic digital transformation. Authors from China, Japan, and Indonesia dominate the contributions, with regional and international collaboration patterns. Keyword analysis identified three main clusters: conceptual approaches, digital learning experiences, and learning system development. Topics such as artificial intelligence, mobile learning, and NLP have become new trends that have been increasingly researched in the past two years. However, research is still limited to higher education and traditional pedagogical approaches. In conclusion, technology research in Japanese language teaching is developing dynamically, but there are still gaps that need to be bridged. The implication is that further research is needed at the elementary-secondary education level, collaborative approaches, and exploration of cutting-edge technologies to create adaptive and sustainable learning systems in the digital era.