Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature

After COVID-19, some employees have opted to continue working from home (WFH) or have chosen a hybrid working mode. Previous research has shown that satisfaction with the physical environment and characteristics of home workspaces are directly related to mental health, which can affect productivity and well-being. This underscores the need for better designed WFH environments. This study explores the use of data-driven tools in interior design to enhance WFH setups. It posits that these tools can transcend traditional design limitations by incorporating professional expertise and facilitating user- driven design processes. The tool's backend is built on a comprehensive collection and classification of research literature on WFH environments, creating an interactive platform where users can engage directly in the design process. This is achieved through real-time, machine-mediated suggestions that enhance well-being without the need for professional human designers. Employing a user-centered design framework, the study develops and tests a prototype to assess its effectiveness in empowering users to intentionally and sensitively redesign their home workspaces. Results show that participating graduate students became more aware of their WFH environment during the design process, but largely it did not change their existing workspace decisions. This observation indicates the potential benefit of this interactive machine-mediated system as a design education tool. Further test on other demographic groups, such as those who need to focus for long hours professionally at home as well as those who are specifically concerned with mental health issues, is anticipated as the next step for the evaluation of this platform.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Architecture

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Yi, Wangli

Advisor dc:contributor.advisor

• Nagakura, Takehiko

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/157365

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/157365