From evidence to assessment: Developing a scenario-based computational design algorithm to support informed decision-making in primary care clinic design workflow. (September 2022)

• Record Type: Journal Article
• Authors: Rastegar, Raha M; Saghafi Moghaddam, Sara; Haghnazar, Ramtin; Zimring, Craig
• Other Names: Gómez Paula Z guest-editor.; Braida Frederico guest-editor.; Lima Fernando guest-editor.; Loyola Mauricio guest-editor.
• Is Part Of: International journal of architectural computing. Volume 20:Number 3(2022)
• Page Start: 567
• Page End: 586
• Publication Date: 2022-09
• Subjects: Computer-aided architectural design -- evidence-based design methods -- informed decision-making -- user experience design -- design evaluation tools -- performance analysis; Architecture -- Data processing -- Periodicals; Architecture -- Informatique -- Périodiques; Virtual reality in architecture -- Periodicals; Computer-aided design -- Periodicals; Architecture -- Data processing; Periodicals; 720.2840285536
• DOI: 10.1177/14780771221121031
• Languages: English
• ISSNs: 1478-0771

Abstract

This paper describes a method to tailor computational design algorithms to evaluate human-centric outputs in architectural projects by presenting a case study that evaluates teamwork affordance for primary care clinics. We argue that computational design assessment techniques fall short of evaluating those human experiences that stem from multiple interactions between individuals and the surrounding environment. This research suggests that future computational design algorithms could benefit from incorporating scenario-based methods developed in the field of evidence-based design, in which studies are concerned about improving qualitative goals. Through this case study, we describe the process of prototyping a computational design algorithm based on the Functional Scenario Analysis approach, applying the algorithm to evaluate case studies, visualizing findings, and extracting design strategies based on the analysis results. This method offers a new vision of how computational design can benefit informed decision-making processes and generate design alternatives aligned with a project's design goals.