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

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.