Building Information Modeling-Powered Augmented Reality and User Study for Learning Architectural Representations

Ziad Ashour, Zohreh Shaghaghian, Wei Yan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Advances in computational technology provide opportunities to explore new methods to improve spatial abilities and the understanding of buildings in architecture education. This research devised and tested a learning approach that utilizes Augmented Reality (AR), Building Information Modeling (BIM), and physical buildings for architecture education. The research employed our developed BIMxAR, which is a BIM-enabled AR educational tool to support the learning and understanding of building construction systems, materials configuration, and 3D section views of complex building structures. BIMxAR utilizes our novel and accurate AR registration method (DL-3S-BIM) for the scale of buildings and the novel visualization mode, which is designed to improve users' spatial awareness. We validated the research approach through a test case based on a quasi-experimental research design, in which BIMxAR was used as an intervention. Two study groups were employed - non-AR and AR. The test case utilized a longitudinal study approach as a data collection strategy, i.e., pretest phase-learning phase-posttest phase, with multiple tests including a novel architectural representation test developed by the researchers. The user study observations indicate that BIMxAR (AR version) was easier to use since participants did not spend any effort in matching the orientation of the BIM virtual model with the physical building. Participants favored the novel visualization mode in AR - the rendering of the surrounding environment in front of and around the section cutting plane. The results reveal that the overall workload associated with the use of BIMxAR was significantly lower in the AR group. Also, participants in the AR group perceived higher performance of BIMxAR. Therefore, BIMxAR (AR version) is considered an easy and convenient learning tool.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PublisherIEEE Computer Society
ISBN (Electronic)9798350320695
DOIs
StatePublished - 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2023-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand
CityAuckland
Period26/08/2330/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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