Integrating Computational Design in Interior Design: Exploring Potentials and the Environmental Setting of Adopters

Abstract

This study explores the integration of computational design (CD) within the field of interior design, which—despite its vast potential for innovation—has been somewhat limited. This research introduces educational theories as an analytical framework, drawing parallels between design processes and learning processes, to analyze the functions of both the interior design process and CD within the context of cognitive work and learning experiences. Additionally, it examines the environment surrounding CD adoption by interior design practitioners, utilizing user acceptance theories such as the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) and the Diffusion of Innovation Theory (DIT). A mixed-methods approach, combining qualitative research that analyzes the theoretical benefits of CD by comparing the design process with CD through the lens of educational theories, and quantitative research, using a survey to examine the environmental factors influencing CD adoption within the interior design industry, is employed. Through this survey, the study investigates the technological and organizational environments surrounding CD usage among interior designers. The comparative analysis reveals that CD can be beneficial for most design tasks that require various cognitive abilities and even has the potential to expand into metacognitive experiences. This finding supports the survey results on hedonic experiences. The survey also provides insights into CD adopters’ usage and professional environments, highlighting the crucial role of educational institutions in technology adoption and the appropriate conditions for its implementation. This research proposes a conceptual framework aimed at supporting the broader adoption of CD in interior design. By enhancing understanding of the practical applications of CD, this framework provides a foundational model for comprehending the various factors that influence technology adoption and its cognitive benefits.