The Adoption of Metaverse Systems: A hybrid SEM - ML Method

A. Alhamad, K. Alomari, M. Alshurideh, B. Al Kurdi, S. Salloum, A. Q. Al-Hamad
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引用次数: 3

Abstract

seeing high-tech medical devices from other nations and witnessing surgery to learn has become nearly unattainable. The pandemic of coronavirus disease 2019 (COVID-19) has created cross-border medical education challenging. Nevertheless, to cater to the increase in non-face-to-face education, instructional techniques entailing the “metaverse” are being initiated in the medical field, since medical staff from all over the globe who frequented the UAE to acquire skills in medical technology and medical students who require to exercise have already had minimal prospects to collaborate closely with patients attributable to COVID-19. Employing video-conferencing technology like Zoom to provide effective medical education is similarly difficult. The research's goal is to learn the perception of students in the UAE towards the metaverse system (MV) used for medical training. The conceptual model includes The Technology Acceptance Model (TAM) elements and adoption aspects of perceived value. The research's conceptual model, which connects both personal-based traits and technological features, is what makes it novel. Additionally, the novel hybrid analysis approach will be applied in the present research to conduct machine learning (ML) driven structural equation modeling (SEM) evaluation.
元宇宙系统的采用:一种混合的SEM - ML方法
看到来自其他国家的高科技医疗设备,目睹手术学习几乎是不可能的。2019冠状病毒病(COVID-19)大流行给跨境医学教育带来了挑战。然而,为了满足非面对面教育的增加,医疗领域正在启动涉及“虚拟世界”的教学技术,因为来自世界各地的医务人员经常前往阿联酋学习医疗技术技能,而需要锻炼的医学生已经很少有机会与COVID-19患者密切合作。利用像Zoom这样的视频会议技术来提供有效的医学教育同样困难。该研究的目标是了解阿联酋学生对用于医学培训的元宇宙系统(MV)的看法。概念模型包括技术接受模型(TAM)要素和感知价值的采用方面。这项研究的概念模型将个人特征和技术特征联系起来,这是它的新颖之处。此外,本研究将采用新的混合分析方法进行机器学习(ML)驱动的结构方程建模(SEM)评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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