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HYPOTHESIS AND THEORY article
Front. Built Environ.
Sec. Building Information Modelling (BIM)
Volume 10 - 2024 |
doi: 10.3389/fbuil.2024.1452764
Development of BIM learning model for construction sites operatives
Provisionally accepted- Obafemi Awolowo University, Ife, Nigeria
The highest level of BIM adoption is the utilization of BIM by construction site operatives who are knowledgeable and skilled in BIM. Furthermore, the full benefits of BIM cannot be achieved without construction site operatives that are knowledgeable and proficient in BIM. Despite the creation of educational models for BIM training by colleges targeting construction professionals, there is currently no specific BIM learning model for construction site operatives. The aim of this research is to develop a BIM learning model to assist construction site operatives in their BIM transformation. The study employed a positivist philosophical research design, which required the use of a quantitative technique. The BIM learning model for construction site operatives was developed by using the SAMR (substitution, augmentation, modification, and redefinition) model, Bloom's digital taxonomy, social learning theory, and design thinking theory. The hypotheses derived from the model were analyzed using structural equation modeling. The study findings indicate that the learning standards for BIM tools, BIM technologies, and BIM skills will enable construction site operatives to effectively utilize BIM tools. The most crucial factor in learning standards for BIM tools is the implementation of substantial BIM tools to modify work processes. The findings also indicated that engaging in professional role-play and interactive assignments had the greatest influence on learning results. The research asserts that the model's implementation will improve performance and efficiency on construction sites by providing construction site operatives with the necessary abilities to proficiently utilize BIM technologies.
Keywords: Bim, BIM learning model, BIM use on construction sites, BIM in construction, artificial intelligence use on construction site
Received: 21 Jun 2024; Accepted: 07 Nov 2024.
Copyright: © 2024 Olugboyega, Ojo and Olanipekun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Oluseye Olugboyega, Obafemi Awolowo University, Ife, Nigeria
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