30-year trends in research on enriching education and training with virtual reality: An innovative study based on machine learning approach


Education and Information Technologies, vol.29, no.7, pp.8221-8249, 2024 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 29 Issue: 7
  • Publication Date: 2024
  • Doi Number: 10.1007/s10639-023-12130-8
  • Journal Name: Education and Information Technologies
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Communication Abstracts, EBSCO Education Source, Educational research abstracts (ERA), ERIC (Education Resources Information Center), INSPEC
  • Page Numbers: pp.8221-8249
  • Keywords: Machine learning, Research interests and trends, Topic modeling, Virtual reality
  • Karadeniz Technical University Affiliated: Yes


The aim of this study is to identify the main research interests and trends in the literature related to the integration of virtual reality into educational and training environments and to provide a potential guideline for future applications of virtual reality. For this purpose, a topic modeling analysis was conducted with a total of 16413 journal articles published in the thirty-year period between 1993–2022 indexed in the Scopus database. The findings of the topic modeling analysis based on machine learning revealed the existence of twelve topics in the field. The most voluminous -the most studied- topics are "EduVR: Advancing education through VR", "Training for safety and emergency", and "Surgical training: Enhancing skill and performance". On the other hand, topics that have shown positive acceleration in recent years and are trending compared to other topics are: "Therapeutic solutions: Addressing pain, anxiety and disorders", "Training for safety and emergency", "Motor rehabilitation solutions: Enhancing stroke recovery and functional training", and "Virtual surgical anatomy: advancing techniques and simulations". The results of the study reveal current trends in the field of virtual reality and emphasize potential future research areas. This may be useful in guiding researchers in the field.