Construction Automation and Robotics Competency Benchmark and Performance Assessment Framework
Description
With the global rise in the level of advanced automation and robotics technologies deployed in construction technology and innovation practice, successful implementation of these technologies requires the inclusion of a workforce with the competencies necessary to drive automation and robotics processes. To meet the market demand for these professionals, there is a need to integrate automation and robotics technologies and processes in construction curricula. However, to ensure proper planning of the integration of automation and robotics in construction education, it is necessary to establish a consensus on the competencies required from construction technology and innovation professionals. Using the Delphi method with contributions from professionals, this chapter identifies and examines the fundamental knowledge, skills, and abilities (KSAs) that should be represented in construction education. After a semi-structured interview round and two rounds of the Delphi study, four competency groups with 99 KSA line items were identified. A consensus was measured for each line item with the importance ratings and levels of agreement attained among the professionals. By identifying these essential KSAs, an automation and robotics competency benchmark and performance assessment framework was developed to support industry professionals and educators in talent cultivation in the advancement of construction innovations in automation and robotics. The purpose of the competency benchmark and performance assessment framework is to contribute to automation and robotics curriculum, training, and competency development in industry and academia. The developed benchmark framework is intended to provide measures for organizations and academic institutions to evaluate students' success and new employees in meeting the established set of core construction automation and robotics competencies during academic and professional training.