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Articles

Infrastructuring Distributed Studio Networks: A Case Study and Design Principles

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Pages 580-631 | Published online: 19 Dec 2017
 

Abstract

Design educators have long used studio-based learning environments to create communities of learners to support authentic learning in design. Online social media platforms have enabled the creation of distributed studio networks (DSNs) that link studio-based learning environments into expanded communities of practice and potential networked improvement communities. As learning scientists, we do not adequately understand how to infrastructure learning and resource sharing across distributed studios. In this ethnography of the infrastructure of Design for America, a DSN, we analyzed data from interviews, online communication, and field observations as the organization grew its network of university design studios. We found that Design for America managers faced challenges of providing support and resources to address wide variation in needs across studios. Lacking an existing comprehensive network collaboration platform, managers created a proto-infrastructure to distribute support across studios. By studying their iterative adoption of communication and collaboration tools and organizational routines, we define a unique set of design principles to infrastructure DSNs: (a) surfacing local progress and problems, (b) affective crowding, (c) solution mapping, and (d) help routing. Assembling constellations of tools and designing platforms based on these principles could support learning in and the improvement of DSNs across domains.

Acknowledgments

We would like to thank Design for America for its participation; Daniel Rees Lewis, Rob Calvey, and Stacy Klingbeil for help with data collection; Alex Sher and Andre Mohring for support with data analysis; and the three anonymous reviewers and members of the Northwestern Delta Lab for their thoughtful and constructive feedback.

Additional information

Funding

This work was generously supported by the National Science Foundation, Division of Information and Intelligent Systems (Grant Nos. IIS-1320693, IIS-1530833, and IIS-1217225), Venture Well, and Northwestern University.

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