Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109709
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dc.contributorDepartment of Building and Real Estate-
dc.creatorChen, X-
dc.creatorLi, S-
dc.creatorLi, G-
dc.creatorXue, B-
dc.creatorLiu, B-
dc.creatorFang, Y-
dc.creatorSeo, J-
dc.creatorKim, I-
dc.creatorKim, JI-
dc.date.accessioned2024-11-08T06:11:29Z-
dc.date.available2024-11-08T06:11:29Z-
dc.identifier.urihttp://hdl.handle.net/10397/109709-
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.rights© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Computational Design and Engineering. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following publication Xingbin Chen, Sining Li, Gengying Li, Bin Xue, Bingsheng Liu, Yuan Fang, JoonOh Seo, Inhan Kim, Jung In Kim, Effects of building information modeling prior knowledge on applying virtual reality in construction education: lessons from a comparison study, Journal of Computational Design and Engineering, Volume 10, Issue 5, October 2023, Pages 2036–2048 is available at https://doi.org/10.1093/jcde/qwad091.en_US
dc.subjectBuilding information modelingen_US
dc.subjectConstruction educationen_US
dc.subjectPrior knowledgeen_US
dc.subjectVirtual realityen_US
dc.titleEffects of building information modeling prior knowledge on applying virtual reality in construction education : lessons from a comparison studyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2036-
dc.identifier.epage2048-
dc.identifier.volume10-
dc.identifier.issue5-
dc.identifier.doi10.1093/jcde/qwad091-
dcterms.abstractApplying building information modeling (BIM) and virtual reality (VR) in construction education is an effective way to achieve better study motivation, learnability, creativity, and observation of the real world. However, whether different levels of BIM prior knowledge affect students’ VR experimental learning, if at all, has not been examined. Therefore, this study employs a teaching intervention experiment to access the VR learning process based on the BIM prior knowledge. A total of 47 students, from the Department of Architecture and Civil Engineering, City University of Hong Kong, participated in the experiment. They were grouped according to whether they had taken the prior BIM tutorial section, with 23 participants in the group having completed the tutorial and 24 participants in the group that had not. Experiment materials were created and rendered via Autodesk Revit and Iris VR; the materials supported three tasks related to the underground design review scenarios and three other tasks about site planning review scenarios. After the experiment, a comparison study was done to discuss their differences based on VR task performances and satisfaction. The results revealed that the BIM prior knowledge mediated both the two-dimensional and three-dimensional navigations when students performed the tasks. Moreover, the relationship differences within the satisfactions showed that BIM prior knowledge effectively affected the learning outcomes. In conclusion, the comparison study implies that students’ BIM prior knowledge is efficacious in the students’ VR task performance and their VR satisfaction from cognitive and memory perspectives.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of computational design and engineering, Oct. 2023, v. 10, no. 5, p. 2036-2048-
dcterms.isPartOfJournal of computational design and engineering-
dcterms.issued2023-10-
dc.identifier.scopus2-s2.0-85176909951-
dc.identifier.eissn2288-5048-
dc.description.validate202411 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextGuangdong Natural Science Foundation; Guangdong Postgraduate Education Foundation; Guangzhou Natural Science Foundation; South China University of Agriculture; City University of Hong Kong; Ministry of Land, Infrastructure and Transporten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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