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...

Full description

Bibliographic Details
Main Author: Yi, Wangli
Other Authors: Nagakura, Takehiko
Format: Thesis
Published: Massachusetts Institute of Technology 2024
Online Access:https://hdl.handle.net/1721.1/157365
https://orcid.org/0009-0005-8691-1837
_version_ 1824458370344550400
author Yi, Wangli
author2 Nagakura, Takehiko
author_facet Nagakura, Takehiko
Yi, Wangli
author_sort Yi, Wangli
collection MIT
description 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.
first_indexed 2025-02-19T04:24:49Z
format Thesis
id mit-1721.1/157365
institution Massachusetts Institute of Technology
last_indexed 2025-02-19T04:24:49Z
publishDate 2024
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/1573652024-10-17T03:12:20Z Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature Yi, Wangli Nagakura, Takehiko Massachusetts Institute of Technology. Department of Architecture 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. S.M. 2024-10-16T17:46:50Z 2024-10-16T17:46:50Z 2024-05 2024-10-10T15:17:35.414Z Thesis https://hdl.handle.net/1721.1/157365 https://orcid.org/0009-0005-8691-1837 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Yi, Wangli
Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title_full Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title_fullStr Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title_full_unstemmed Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title_short Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature
title_sort data driven home workspace design interactive diy platform mediating the user and expert literature
url https://hdl.handle.net/1721.1/157365
https://orcid.org/0009-0005-8691-1837
work_keys_str_mv AT yiwangli datadrivenhomeworkspacedesigninteractivediyplatformmediatingtheuserandexpertliterature