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Empirical support for problem–solution coevolution in a parametric design environment

Published online by Cambridge University Press:  14 July 2014

Rongrong Yu ,
Ning Gu ,
Michael Ostwald  and
John S. Gero
Rongrong Yu*
Affiliation:
School of Architecture and Built Environment, University of Newcastle, Callaghan, New South Wales, Australia
Ning Gu
Affiliation:
School of Architecture and Built Environment, University of Newcastle, Callaghan, New South Wales, Australia
Michael Ostwald
Affiliation:
School of Architecture and Built Environment, University of Newcastle, Callaghan, New South Wales, Australia
John S. Gero
Affiliation:
School of Architecture and Department of Computer Science, University of North Carolina at Charlotte, Charlotte, North Carolina, USA
*
Reprint requests to: Rongrong Yu, School of Architecture and Built Environment, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia. E-mail: rongrong.yu@uon.edu.au
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Abstract

This paper describes the results of a protocol study exploring problem–solution coevolution in a parametric design environment (PDE). The study involved eight participants who completed a defined architectural design task using Rhino and Grasshopper software: a typical PDE. The method of protocol analysis was employed to study the cognitive behaviors that occurred while these designers were working in the PDE. By analyzing the way in which the designers shifted between “problem” and “solution” spaces in the PDE, characteristics of the coevolutionary design process are identified and discussed. Results of this research include two potentially significant observations. First, the coevolution process occurs frequently within the design knowledge level (i.e., when using Rhino) and within the rule algorithm level (i.e., when using Grasshopper) of the parametric design process. Second, the designers’ coevolution process was focused on the design knowledge level at the beginning of the design session, while they focused more on the rule algorithm level toward the end of the design session. These results support an improved understanding of the design process that occurs in PDEs.

Keywords

Designers’ Cognitive BehaviorParametric Design EnvironmentsProblem–Solution CoevolutionProtocol Analysis

Information

Type
Regular Articles
Information
AI EDAM , Volume 29 , Issue 1 , February 2015 , pp. 33 - 44
Copyright
Copyright © Cambridge University Press 2014 

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