Computer Vision and AI, with Immersive Technologies in Education and Training: A Bibliometric Analysis
Riya Manchanda, Jitendra Sharma, Naresh Kumar, Gaurav Aggarwal
Abstract
This study examines the current academic relationship between computer vision and deep artificial intelligence (AI) in the context of virtual reality, augmented reality, and mixed reality. The analysis focuses specifically on the educational and training domains and utilizes the comprehensive Scopus research database. An in-depth analysis of the research indicates a consistent increase in production throughout the years. The investigation illuminates the regional contributions and collaboration networks offering valuable insights into worldwide trends in the utilization of computer vision and AI in novel technologies in educational settings. An analysis of prominent works, innovative and productive writers, and collaborative interactions offers valuable insights for educators, trainers, researchers, and policymakers who wish to comprehend the trajectory of immersive technology in education. The investigation highlights the profound capacity of computer vision and deep AI, demonstrating their ability to create captivating and efficient learning environments. The study examined a total of 100 publications spanning from 2013 to 2024. These documents had an annual growth rate of 22.59% and had an average of 6.64 citations per document. Additionally, there were 316 authors affiliated with these documents. Spain was the most influential country with 142 citations and an aggregate article citation of 47.3. The study also emphasized the primary sources of information, including the Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications & CEUR Workshop Proceedings. The results of this study offer valuable understanding regarding the potential growth and extension in the field of creative technologies through the integration of computer vision.