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Exploring AI’s Potential in Architectural Education: An Explorative Approach Towards Assessments of Technical Working Drawings (87262)

Session Information: Innovative Technologies in Education
Session Chair: Xiao Xu
This presentation will be live-streamed via Zoom (Online Access)

Friday, 1 November 2024 11:50
Session: Session 2
Room: Live-Stream Room 2
Presentation Type:Live-Stream Presentation

All presentation times are UTC + 9 (Asia/Seoul)
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In architectural education, the evaluation of technical working drawings is a critical component for preparing students for professional practice. These drawings reflect the technical competencies required in the field for Architectural Technologists. However, current assessment rubrics often lack consistency and alignment with industry standards
This paper builds on the findings of the study presented at the 40th AEAA conference, which introduced a criteria-based evaluation rubric for technical drawings in Architectural education that aligns with industry standards such as municipal submission checklists and SANSXA10400. This study explores how AI, through tools such as Optical Character Recognition (OCR) and computer vision, could enhance the efficiency and objectivity of evaluating technical working drawings in architectural education.
This study presents an exploratory framework for using AI to assist in the evaluation of technical drawings, aligning assessments with municipal submission checklists and industry standards such as the SANSXA10400. The focus is on how AI could potentially automate aspects of the evaluation process, offering educators a more objective and consistent means of providing feedback.
The findings suggest that integrating AI into architectural education has the potential to transform the way technical competencies are evaluated. By providing timely, objective feedback, AI-based frameworks can improve learning outcomes while ensuring that assessments remain aligned with professional standards. This study serves as a foundation for future exploration of AI’s role in bridging the gap between academic assessment and professional practice.

Authors:
Reetumetsi Malefane, Nelson Mandela University, South Africa


About the Presenter(s)
I am an early career academic at Nelson Mandela University. My research interests range from addressing practical issues in the profession to advancing academic discourse in architectural pedagogy.

Connect on Linkedin
https://www.linkedin.com/in/tumi-malefane-633a29b8/

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00