Language learning with virtual reality: A BERTopic-based analysis of nursing communication education

With the rapid advancement of technology, virtual reality (VR) in nursing education is becoming increasingly widespread. While, in communication education, which is crucial for the high-quality nursing practice and professional development of nursing students, its application remains at the exploratory stage. This study utilized Bidirectional Encoder Representations from Transformers Topic (BERTopic), an advanced and novel natural language processing (NLP) technique to systematically explore the research topics and hotspots in VR in nursing communication education. Through specific selection criteria, 35 studies were collected from five databases, including PubMed, CINAHL, Embase, Eric, and Web of Science, with a search timeframe from database inception to September 2025. Four main topics were identified: a) Interprofessional communication and team training integrating VR and AI, b) VR teaching and learning Experience, c) VR training and self-Efficacy in mental health contexts, d) effect evaluation and technology usability. The findings also revealed that the publication and growth trends of the research exhibited fluctuations but an overall upward trajectory, particularly marked by a rapid surge in the last two years. This review bridges immersive technology and language education research. It employed topic modeling to provide valuable insights for scholars and educators into the key areas of focus and emerging trends in nursing communication education, supporting future research initiatives at the intersection of applied linguistics, clinical communication, and immersive learning.