Chapter
Jun 17, 2014

Enhancing Spatial and Temporal Cognitive Ability in Construction Education Through Augmented Reality and Artificial Visualizations

Publication: Computing in Civil and Building Engineering (2014)

Abstract

It is essential to provide the future industry workforce the opportunity to fully develop the learning abilities to effectively solve construction problems. The Construction Management (CM) students' ability to solve problems is hindered by the lack of exposure to construction processes on the job-site, which results in the students' lack of understanding of the dynamic complex spatial constraints (e.g., how construction products are related to one another in a particular contextual space) and the temporal constraints (e.g., the dependencies for coordinating subcontractors' processes). As the spatial-temporal-constraint problems pervade projects during the construction phase, their full understating to solve CM problems will significantly enable students to improve productivity levels. This research uses Augmented Reality Technology (ART) and a layer of artificial visualizations to simulate the environmental context and spatial temporal constraints. The superimposition of images serves as an instructional mechanism to virtually incorporate jobsite experiences. The assumption is that the enhancement of spatial-temporal constraints enables learners to visualize context and hidden processes. Therefore, this research expects to demonstrate a significant improvement of the perception of the reality through the combination of two layers (the real environment and the computer-generated information) including the learners' ability to understand the complexity of construction products (e.g., assemblies) and associated process in the jobsite.

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Go to Computing in Civil and Building Engineering (2014)
Computing in Civil and Building Engineering (2014)
Pages: 2079 - 2086

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Published online: Jun 17, 2014

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Center for Advanced Construction Information Modeling (CACIM), Rinker School of Construction Management; University of Florida; PO Box 115703; Gainesville, FL 32611-5703. E-mail: [email protected]
Raja R. A. Issa [email protected]
Center for Advanced Construction Information Modeling (CACIM), Rinker School of Construction Management; University of Florida; PO Box 115703; Gainesville, FL 32611-5703. E-mail: [email protected]

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