阿联酋高等教育采用元宇宙的基于sem -机器学习模型

A. Aburayya, S. Salloum, Khaled Younis Alderbashi, Fanar Shwedeh, Yara Shaalan, Raghad M. Alfaisal, Sawsan JM Malaka, K. Shaalan
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引用次数: 4

摘要

元宇宙是一个假想的平行宇宙网络。使用这种技术可能会使沉闷的讲堂活跃起来。通过将同步通信扩展到“元空间”,许多个人可以进行有意义的对话并交换观点。这项研究的重点是找出阿联酋医科学生对超宇宙系统的感受。概念模型结合了技术接受模型(TAM)的元素,包括作为采用决定因素的感知价值和感知普遍性。为了测试所建议的框架的有效性,对阿拉伯联合酋长国(UAE)一所大学的369名全日制学生进行了调查。机器学习(ML)和结构方程建模使用偏最小二乘法(PLS-SEM)用于数据分析。根据结果,用户在多大程度上看到了meta系统的价值并采用了它,这是决定他们是否打算参与的一个重要因素。这项研究是有益的,因为它阐明了各种医疗保健成分的相对重要性,使专业人员能够更好地优先考虑他们的努力。
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SEM-machine learning-based model for perusing the adoption of metaverse in higher education in UAE
The metaverse is an imaginary network of parallel universes. Using this technology might liven up dull lecture halls. By expanding synchronous communication into the "metaverse," many individuals may have meaningful conversations and exchange perspectives. This research focuses on finding out how medical students in the UAE feel about the metaverse system. The conceptual model incorporates elements from the Technology Acceptance Model (TAM), including perceived value and perceived ubiquity as adoption determinants. To test the validity of the suggested framework, a survey was developed and distributed to 369 full-time students at one of the universities in the United Arab Emirates (UAE). Machine learning (ML) and structural equation modeling using partial least squares (PLS-SEM) are used for data analysis. According to the results, the extent to which users saw value in and adoption of the metaverse system was a significant factor in whether or not they intended to participate. This study was helpful since it elucidated the relative significance of various healthcare components, allowing professionals to prioritize their efforts better.
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来源期刊
CiteScore
5.80
自引率
0.00%
发文量
163
审稿时长
8 weeks
期刊最新文献
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