An Immersive Virtual Learning Environment for the Development of Hard Skills: A Scientometric Analysis and Systematic Review

A scientometric analysis and systematic review of an immersive virtual learning environment (IVLE) designed to improve the development of hard skills comprised this study. The review focused on the period between 2016 and 2023 and was conducted using the Scopus database. This study employed a scientometrics analysis and systematic review methodology. In this study, a comprehensive analysis was conducted on a corpus of 12 scholarly articles that have been published within the last 8 years. This study looked at the aggregate magnitude and trajectory of scholarly publications and looked at a number of trends in scholarly research, including annual reports, article counts, article distribution across different sources, finding the most useful sources, keyword analysis, looking into the best collaboration groups, looking at how themes have changed over time, judging contributions, and practical implications. The primary findings regarding the data and document types indicated that a total of 12 articles were published across 10 different sources within the timeframe of 2016 to 2023. The research conducted on IVLE for the development of hard skills exhibited fluctuations in its pace, alternating between deceleration and positive acceleration. The growth rate of the articles peaked in 2022. The primary publication with the greatest of source is “Lecture Notes in Networks and Systems.” Keyword Plus growth rate for terms like “virtual reality,” “e-learning,” and “teaching” The nations exhibit a high degree of collaboration in the field of research. The findings indicated that the authors hailing from Mexico and Colombia exhibited the greatest frequency (n = 2). The thematic evolution of the study indicated two significant advancements: firstly, the emergence of e-learning studies that have propelled the field of e-learning, and secondly, the integration of virtual reality into e-learning practices. The classification of applications encompasses various components: title, solution, learning strategy, and learning tasks.