Venturing Into the Metaverse: Innovative AI-Driven Strategies for Advancing Dental Education

the onset of the COVID-19 pandemic brought about significant disruptions in dental education, impeding direct interaction with avant-garde dental practices and sophisticated global equipment. In this scenario, the rise of Metaverse-oriented teaching methods stands out as a creative resolution, meeting the escalating demand for distance learning options in dentistry. Conventional digital learning tools, notably Zoom, have fallen short in delivering an all-encompassing educational experience in the dental realm, steering a transition to more dynamic, immersive learning environments. This shift is notably pronounced in the dental education sphere of the United Arab Emirates (UAE). This study explores dental students' perceptions of the impact of Metaverse technology on meeting their educational goals within the UAE. Our analytical structure spotlights vital elements influencing technology adoption, specifically User Mobility and User Accessibility. An extensive dataset encompassing 291 responses was gathered from several academic institutions. To thoroughly scrutinize our research framework, we employed Partial Least Squares-Structural Equation Modelling (PLS-SEM) alongside a sophisticated Machine Learning (ML) technique, drawing on data from our student survey. The findings accentuate the fundamental role of the Metaverse in shaping decisions regarding technology adoption, heavily influenced by aspects such as User Mobility and Users' Accessibility. Notably, the ML approach showcased superior predictive accuracy in determining the dependent variable compared to other analytical methodologies. This study enriches the academic discussion surrounding artificial intelligence, particularly its nexus with environmental sustainability, and provides critical insights for industry participants, policymakers, and AI developers. The results form a basis for crafting AI-driven solutions that harmonize with user preferences and ecological requirements.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/imeta62882.2024.10808068
Citations
1
Primary Topic
Dental Research and COVID-19
Type
article
Field-Weighted Citation Impact
0.85
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article

Venturing Into the Metaverse: Innovative AI-Driven Strategies for Advancing Dental Education

Raghad Alfaisal, Said A. Salloum, Khalaf Tahat, Dina Tahat et al.
1 citations
Dental Research and COVID-19
0.85
article

Venturing Into the Metaverse: Innovative AI-Driven Strategies for Advancing Dental Education

Raghad Alfaisal, Said A. Salloum, Khalaf Tahat, Dina Tahat, Ayham Salloum, Shirin Abdallah Alimour
article en
1 citations

Abstract

the onset of the COVID-19 pandemic brought about significant disruptions in dental education, impeding direct interaction with avant-garde dental practices and sophisticated global equipment. In this scenario, the rise of Metaverse-oriented teaching methods stands out as a creative resolution, meeting the escalating demand for distance learning options in dentistry. Conventional digital learning tools, notably Zoom, have fallen short in delivering an all-encompassing educational experience in the dental realm, steering a transition to more dynamic, immersive learning environments. This shift is notably pronounced in the dental education sphere of the United Arab Emirates (UAE). This study explores dental students' perceptions of the impact of Metaverse technology on meeting their educational goals within the UAE. Our analytical structure spotlights vital elements influencing technology adoption, specifically User Mobility and User Accessibility. An extensive dataset encompassing 291 responses was gathered from several academic institutions. To thoroughly scrutinize our research framework, we employed Partial Least Squares-Structural Equation Modelling (PLS-SEM) alongside a sophisticated Machine Learning (ML) technique, drawing on data from our student survey. The findings accentuate the fundamental role of the Metaverse in shaping decisions regarding technology adoption, heavily influenced by aspects such as User Mobility and Users' Accessibility. Notably, the ML approach showcased superior predictive accuracy in determining the dependent variable compared to other analytical methodologies. This study enriches the academic discussion surrounding artificial intelligence, particularly its nexus with environmental sustainability, and provides critical insights for industry participants, policymakers, and AI developers. The results form a basis for crafting AI-driven solutions that harmonize with user preferences and ecological requirements.

Sultan Idris Education University (MY), Al Ain University (AE), United Arab Emirates University (AE), University of Sharjah (AE), Yarmouk University (JO)
Quality Education
Openalex Percentile: Top 19%
Dental Research and COVID-19
0.85
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