Exploring the Metaverse: A Novel AI-Based Approach to Medical Training for Dental Students

Salloum, Said; Shaalan, Khaled; Alfaisal, Mohammad; Salloum, Ayham; Gaber, Tarek

Abstract

The COVID-19 pandemic significantly disrupted dental education, highlighting the need for innovative remote learning solutions. This study, centered in the United Arab Emirates, explores dental students' perceptions of the Metaverse as an educational tool, contrasting it with traditional digital platforms like Zoom. Our research aims to fill the gap in understanding the effectiveness of Metaverse technology in dental education. Employing Partial Least Squares-Structural Equation Modeling (PLS-SEM) and an Artificial Neural Network (ANN) approach, we analyzed data from 833 students across various institutions. The findings reveal that user adoption decisions in the Metaverse are greatly influenced by User Mobility and Users' Accessibility. The ANN model showed superior accuracy in predicting outcomes compared to other methods. These results contribute to the broader discussion on artificial intelligence, particularly its role in environmental sustainability.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)
• Start Date: Jan 27, 2024
• End Date: Jan 29, 2024
• Acceptance Date: Jun 12, 2024
• Publication Date: Jan 27, 2024
• Deposit Date: Jun 12, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• DOI: https://doi.org/10.1109/assic60049.2024.10508013