TY - GEN
T1 - Venturing Into the Metaverse
T2 - 2nd International Conference on Intelligent Metaverse Technologies and Applications, iMETA 2024
AU - Salloum, Ayham
AU - Alimour, Shirin Abdallah
AU - Tahat, Dina
AU - Salloum, Said
AU - Alfaisal, Raghad
AU - Tahat, Khalaf
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Dental Education
KW - Environmental Sustainability
KW - Machine Learning Analytics
KW - Metaverse Technology
KW - PLS-SEM
UR - https://www.scopus.com/pages/publications/85215977669
UR - https://www.scopus.com/pages/publications/85215977669#tab=citedBy
U2 - 10.1109/iMETA62882.2024.10808068
DO - 10.1109/iMETA62882.2024.10808068
M3 - Conference contribution
AN - SCOPUS:85215977669
T3 - 2024 2nd International Conference on Intelligent Metaverse Technologies and Applications, iMETA 2024
SP - 44
EP - 49
BT - 2024 2nd International Conference on Intelligent Metaverse Technologies and Applications, iMETA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 November 2024 through 29 November 2024
ER -