Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103265
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dc.contributorDepartment of Building and Real Estateen_US
dc.creatorAbbas, Aen_US
dc.creatorSeo, Jen_US
dc.creatorKim, Men_US
dc.date.accessioned2023-12-11T00:32:47Z-
dc.date.available2023-12-11T00:32:47Z-
dc.identifier.isbn978-0-7844-8288-9 (PDF)en_US
dc.identifier.urihttp://hdl.handle.net/10397/103265-
dc.descriptionConstruction Research Congress 2020, March 8-10, 2020, Tempe, Arizona, USAen_US
dc.language.isoenen_US
dc.publisherAmerican Society of Civil Engineersen_US
dc.rights© ASCEen_US
dc.rightsThis material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at at https://ascelibrary.org/doi/10.1061/9780784482865.048.en_US
dc.titleExploring the construction task performance and cognitive workload of augmented reality-assisted rebar inspection tasksen_US
dc.typeConference Paperen_US
dc.identifier.spage448en_US
dc.identifier.epage456en_US
dc.identifier.doi10.1061/9780784482865.048en_US
dcterms.abstractAugmented reality (AR) is capturing increasing attention as a way to provide cognitive assistance in many fields. Inspiring from the benefits of AR, architecture, engineering, and construction industries and researchers are interested to apply AR technologies for various construction tasks such as design review, assembly, inspection, or facility maintenance, etc. However, even though AR technologies are designed to support users’ cognitive capability by providing superimposed information on real-world scenes, this information from AR may lead to one’s cognitive overload, causing an adverse effect on task performance. As a result, it is important to understand how AR would affect one’s cognitive load, and in turn, task performance for better use of AR systems in construction. As a preliminary investigation, this research compared task performance and cognitive loads during traditional paper-based and AR-assisted rebar inspection tasks in the laboratory setting. Participants’ task performance was measured by task completion time and the number of rebars correctly detected, whereas cognitive load was measured by the NASA task load index (TLX). Based on the result, we discussed the impact of AR application on rebar inspection tasks from a cognitive perspective.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn D Grau, P Tang, & M El Asmar (Eds), Construction Research Congress 2020 : Project Management and Controls, Materials, and Contracts : Selected Papers from the Construction Research Congress 2020, March 8–10, 2020, Tempe, Arizona, p. 448-456. Reston, Virginia: American Society of Civil Engineers, 2020en_US
dcterms.issued2020-
dc.relation.ispartofbookConstruction Research Congress 2020 : Project Management and Controls, Materials, and Contracts : Selected Papers from the Construction Research Congress 2020, March 8-10, 2020, Tempe, Arizonaen_US
dc.relation.conferenceConstruction Research Congress [CRC]en_US
dc.publisher.placeReston, Virginiaen_US
dc.description.validate202312 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBRE-0431-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextStart-up Fund project, Hong Kong Polytechnic University.en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS48342523-
dc.description.oaCategoryGreen (AAM)en_US
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