Contribution of Artificial Intelligence to the Development of Metaverses: A Bibliometric Review Study on its Impact on Immersive Learning in Higher Education
Abstract
In the current post-pandemic scenario, the integration of artificial intelligence (AI) and metaverses in higher education has gained significant relevance, transforming learning experiences towards more immersive and personalized approaches. Identifying the way in which these technologies impact university teaching-learning is essential to understanding their true contribution. This bibliometric review study focuses on analyzing the trend in scientific production, as well as the implications of its impact on higher education. Through a mixed and descriptive methodological approach, 63 scientific documents from the Scopus database were reviewed. The findings show that scientific production increased during the pandemic; however, in the post-pandemic context, research has maintained an upward trend. Furthermore, the implications of AI’s contribution to metaverses—representing a positive impact on higher education—have been grouped into five categories, the most prominent of which is “Interactivity for improving student movement”, which covers 42.86% with respect to the other categories identified in the reviewed studies. Therefore, it is concluded that the integration of AI in the development of metaverses presents a significant potential to transform higher education, offering personalized immersive learning experiences that are redefining the way in which students interact with knowledge. Nevertheless, gaps persist that require attention from the scientific community, especially in terms of evaluating the long-term impact of these technologies and their equitable adaptation in various educational contexts. Future research should be directed towards understanding the effectiveness of these environments in the development of specific competencies in higher education, as well as in the creation of strategies that promote inclusive accessibility.
https://doi.org/10.26803/ijlter.23.12.17
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