Comparative Analysis of Instructors' and Practitioners' Perspective on Competencies for Implementing Sensing Technologies in the Construction Industry

Contribution: This research category full paper contributes to the body of knowledge by revealing the areas of agreement on competencies for implementing sensing technologies by instructors and industry practitioners in the construction industry. The findings will help the instructors equip the future workforce with the competencies to implement sensing technologies through integrated curriculum development. Additionally, the findings could help industry practitioners update the competencies of the current workforce in the construction industry for effective sensing technologies deployment. Consequently, this study's findings will help reduce the misalignment in competencies acquired by the future workforce and the industry-specific competencies for implementing sensing technologies. Background: Adopting data sensing technologies like laser scanners, radio frequency identification systems, cameras, and unmanned aerial vehicles in the construction industry requires a workforce with the necessary competencies. To address this, curriculum content should be balanced to train emerging workers to meet industry expectations for implementing these technologies. This balance is crucial to minimizing the resources employers spend on post-hire training. This study compares the perspectives of instructors and industry practitioners on the competencies required for implementing sensing technologies in the construction industry. Research Question: What are the perspectives of industry practitioners and instructors on the competencies for implementing sensing technologies in the construction industry? Methods: This study employed a three-round Delphi survey administered to instructors in accredited higher education institutions and construction industry practitioners in the United States. Through the successive Delphi survey rounds, the study compares the instructors' and construction industry practitioners' perspectives on essential competencies required for implementing sensing technologies in the construction industry. Findings: The first survey round shows the suitability of instructors' and industry practitioners' expertise in partaking in the study. The second survey round shows a trend toward convergence, indicating potential similarities between instructors' and industry practitioners' perspectives on specific competencies required for implementing sensing technologies in the construction industry. The third round showed the qualitative feedback from instructors and industry practitioners on their perception of the competencies for implementing sensing technologies in the construction industry.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10892865
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00

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article

Comparative Analysis of Instructors' and Practitioners' Perspective on Competencies for Implementing Sensing Technologies in the Construction Industry

Chukwuma Nnaji, Yewande S. Abraham, Alfred A. Adegoke, Abiola Akanmu et al.
BIM and Construction Integration
article

Comparative Analysis of Instructors' and Practitioners' Perspective on Competencies for Implementing Sensing Technologies in the Construction Industry

Chukwuma Nnaji, Yewande S. Abraham, Alfred A. Adegoke, Abiola Akanmu, Adedeji Olushola Afolabi
article en

Abstract

Contribution: This research category full paper contributes to the body of knowledge by revealing the areas of agreement on competencies for implementing sensing technologies by instructors and industry practitioners in the construction industry. The findings will help the instructors equip the future workforce with the competencies to implement sensing technologies through integrated curriculum development. Additionally, the findings could help industry practitioners update the competencies of the current workforce in the construction industry for effective sensing technologies deployment. Consequently, this study's findings will help reduce the misalignment in competencies acquired by the future workforce and the industry-specific competencies for implementing sensing technologies. Background: Adopting data sensing technologies like laser scanners, radio frequency identification systems, cameras, and unmanned aerial vehicles in the construction industry requires a workforce with the necessary competencies. To address this, curriculum content should be balanced to train emerging workers to meet industry expectations for implementing these technologies. This balance is crucial to minimizing the resources employers spend on post-hire training. This study compares the perspectives of instructors and industry practitioners on the competencies required for implementing sensing technologies in the construction industry. Research Question: What are the perspectives of industry practitioners and instructors on the competencies for implementing sensing technologies in the construction industry? Methods: This study employed a three-round Delphi survey administered to instructors in accredited higher education institutions and construction industry practitioners in the United States. Through the successive Delphi survey rounds, the study compares the instructors' and construction industry practitioners' perspectives on essential competencies required for implementing sensing technologies in the construction industry. Findings: The first survey round shows the suitability of instructors' and industry practitioners' expertise in partaking in the study. The second survey round shows a trend toward convergence, indicating potential similarities between instructors' and industry practitioners' perspectives on specific competencies required for implementing sensing technologies in the construction industry. The third round showed the qualitative feedback from instructors and industry practitioners on their perception of the competencies for implementing sensing technologies in the construction industry.

Rochester Institute of Technology (US), Virginia Tech (US), Texas A&M University (US)
National Science Foundation
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
BIM and Construction Integration
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