Prediction of User’s Intention to Use Metaverse System in Medical Education: A Hybrid SEM-ML Learning Approach

Almarzouqi, A; Aburayya, A; Salloum, S

Abstract

Metaverse (MS) is a digital universe accessible through a virtual environment. It is established
through the merging of virtually improved physical and digital reality. Metaverse (MS) offers enhanced
immersive experiences and a more interactive learning experience for students in learning and educational
settings. It is an expanded and synchronous communication setting that allows different users to share
their experiences. The present study aims to evaluate students’ perception of the application of MS in
the United Arab Emirates (UAE) for medical-educational purposes. In this study, 1858 university students
were surveyed to examine this model. The study’s conceptual framework consisted of adoption constructs
including Technology Acceptance Model (TAM), Personal innovativeness (PI), Perceived Compatibility
(PCO), User Satisfaction (US), Perceived Triability (PTR), and Perceived Observability (POB). The study
was unique because the model correlated technology-based features and individual-based features. The study
also used hybrid analyses such as Machine Learning (ML) algorithms and Structural Equation Modelling
(SEM). The present study also employs the Importance Performance Map Analysis (IPMA) to assess the
importance and performance factors. The study finds US as an essential determinant of users’ intention to
use the metaverse (UMS). The present study’s finding is useful for stakeholders in the educational sector
in understanding the importance of each factor and in making plans based on the order of significance of
each factor. The study also methodologically contributes to Information Systems (IS) literature because it is
one of the few studies that have used a complementary multi-analytical approach such as ML algorithms to
investigate the UMS metaverse systems.

Citation

Almarzouqi, A., Aburayya, A., & Salloum, S. (2022). Prediction of User’s Intention to Use Metaverse System in Medical Education: A Hybrid SEM-ML Learning Approach. IEEE Access, 10, 43421-43434. https://doi.org/10.1109/access.2022.3169285

• Journal Article Type: Article
• Publication Date: Apr 21, 2022
• Deposit Date: Jun 15, 2022
• Publicly Available Date: Jun 15, 2022
• Journal: IEEE Access
• Publisher: Institute of Electrical and Electronics Engineers
• Volume: 10
• Pages: 43421-43434
• DOI: https://doi.org/10.1109/access.2022.3169285
• Keywords: General Engineering, General Materials Science, General Computer Science
• Publisher URL: https://doi.org/10.1109/access.2022.3169285
• Additional Information: Additional Information : ** Article version: VoR ** From Crossref journal articles via Jisc Publications Router ** Licence for VoR version of this article starting on 01-01-2022: https://creativecommons.org/licenses/by/4.0/legalcode **Journal IDs: eissn 2169-3536 **History: published 2022 **License for this article: starting on 01-01-2022, , https://creativecommons.org/licenses/by/4.0/legalcode