Olatunji, O A (2019) Promoting student commitment to BIM in construction education. Engineering, Construction and Architectural Management, 26(7), pp. 1240-1260. ISSN 0969-9988
Abstract
Purpose: Industry uptake of digital modeling is improving. Recent evidence suggests building information modeling (BIM) is the commercial reality of today’s construction education, and the way of the future that has truly begun. Amongst the significance of this is BIM’s potential to revolutionize the industry. The purpose of this paper is to use the learning experiences of undergraduate students in two construction management subjects involving quantity measurement and cost estimation to explore students' motivation toward BIM education. In particular, the study investigates decision factors underlying students' selection of software for information management in a modeling environment. Design/methodology/approach: A total of 674 undergraduate students from the same institution were surveyed, out of which 153 responses were retrieved. The data provide insights into decisions taken by students while metamorphosing traditional processes into BIM-driven outcomes, in the form of commercial estimates of a real life project reported through a bill of quantities. Some 29 decision factors were analyzed. These include prior training, flair for creativity, ease of use, economic reasons, learning outcomes, on-going technical support and support infrastructure. Reductionist methods involving factor analysis and Cronbach’s α reliability estimate procedures were used to investigate the most important decision factors from amongst the decision factors analyzed. Findings: Results show all the 29 decision factors are statistically significant. Access to on-going support, the mandatory requirement to use a particular tool to complete an assessment task and the requirement to use the tool for job duties are the most significant decision factors. Vendors' persuasion and the capability of the tool to achieve better outcomes than others are least significant. Statistical correlations between the decision factors were obtained. They all suggest near-absolute correlations. Practical implications: The practical implications of these findings are vital. They help to unravel factors that promote students' interest in BIM education, and contribute toward the development of software selection models that are relevant to professionals and incipient businesses. Originality/value: Future studies on decision analysis can be built on the findings also. In particular, the decision factors help in developing creative cognitive solutions to BIM adoption issues. They also help on the challenge posed by the constraints of knowledge diffusion within and across project teams, and in designing tools that meet the requirements of non-design disciplines who also play vital roles in the BIM project environment.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | building information modelling; decision analysis; methodology |
| Index terms: | evidence, creativity, future study, commitment, decision analysis, construction education, motivation, learning experience, methodology, cost estimating, undergraduate, modelling, project team, bills of quantities, duty, factor analysis, learning outcome, estimate, building information modelling |
| Subjects: | evaluation and assessment methods, psychology, project delivery, financial and cost management, research design and methodology, information systems, curriculum development, professional education, learning methods, student development, innovation and creative processes, contractual role, analytical methods, statistical analysis, research methods, decision analysis |
| Topics: | Contract Administration, Human Resources, Digital Applications, Organizational Design, Education, Cost Management, Engineering Principles, Risk Management, Research Practice, Design Practice, Project Management |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here