SEM-machine learning-based model for perusing the adoption of metaverse in higher education  in UAE

Aburayyaa , Ahmad; A. Salloumb, Said; Younis Alderbashic, Khaled; Shwedeha, Fanar; Shaaland, Yara; Alfaisale , Raghad; JM Malakaf, Sawsan; Shaalan, Khaled

SEM-machine learning-based model for perusing the adoption of metaverse in higher education in UAE

Date

2023

Authors

Aburayyaa , Ahmad

A. Salloumb, Said

Younis Alderbashic, Khaled

Publisher

Directory of Open Access Journals

Abstract

The metaverse is an imaginary network of parallel universes. Using this technology might liven up dull lecture halls. By expanding synchronous communication into the "metaverse," many individuals may have meaningful conversations and exchange perspectives. This research focuses on finding out how medical students in the UAE feel about the metaverse system. The conceptual model incorporates elements from the Technology Acceptance Model (TAM), including perceived value and perceived ubiquity as adoption determinants. To test the validity of the suggested framework, a survey was developed and distributed to 369 full-time students at one of the universities in the United Arab Emirates (UAE). Machine learning (ML) and structural equation model ing using partial least squares (PLS-SEM) are used for data analysis. According to the results, the extent to which users saw value in and adoption of the metaverse system was a significant factor in whether or not they intended to participate. This study was helpful since it elucidated the relative significance of various healthcare components, allowing professionals to prioritize their efforts better.

Keywords

Metaverse Imagined World Technology Acceptance Model Perceived Value and Perceived Ubiquity

Citation

Ahmad Aburayya et al. (2023) “SEM-machine learning-based model for perusing the adoption of metaverse in higher education in UAE,” International Journal of Data and Network Science, 7(2), pp. 667–676.