Proposed Model for Training Building Information Modeling (BIM) in Metaverse Technology Using a Mixed Method
نویسندگان
1 Department of Business Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran
2 Department of Knowledge and Information Science, Islamic Azad University, Science and Research Branch, Tehran, Iran
doi
چکیده
The Fourth Industrial Revolution and the advancement of technology necessitate all industries integrate their operations with cutting-edge technology to grow and stay ahead of global changes. Considering AEC (architecture, engineering, and construction) industry, this research focuses on integrating building information modeling (BIM) training using Metaverse, the world's leading technology, because education is crucial for the growth of individuals in all fields.A mix-method approach was employed, which entails qualitative meta-synthesis and quantitative methods, such as questionnaires and structural equation modeling (SEM) using SmartPLS. Through various databases, 181 relevant studies were identified, and 30 were selected for further analysis. The selected studies were thoroughly analyzed qualitatively using the MAXQDA 2020 software. The process involved initial coding, axial coding and pattern coding to identify overall patterns and trends within the data. The extracted codes, comprising nine categories and 82 indicators, were validated by a panel of experts using the Fuzzy Delphi method in two rounds of feedback and discussion among the experts to reach consensus on the validity and appropriateness of the codes. Following these results, a comprehensive questionnaire was conducted to assess the factors that influenced BIM training in metaverse. A carefully designed questionnaire was distributed to 300 participants. The quantitative data was analyzed with the aid of descriptive statistics and structural equation modeling (SEM). Both qualitative and quantitative phases resulted in the division of findings into nine categories: technology data and information, education technology infrastructure, team capacity, socio-cultural factors, behavioral factors, applied technologies, functional results, practical features, and environmental configuration.
