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Parallel Prototyping Leads to Better Design Results, More Divergence, and Increased Self-efficacy

  • Steven P. Dow
  • Alana Glassco
  • Jonathan Kass
  • Melissa Schwarz
  • Daniel L. Schwartz
  • Scott R. Klemmer
Chapter
Part of the Understanding Innovation book series (UNDINNO)

Abstract

Iteration can help people improve ideas. It can also give rise to fixation—continuously refining one option without considering others. Does creating and receiving feedback on multiple prototypes in parallel—as opposed to serially—affect learning, self-efficacy, and design exploration? An experiment manipulated whether independent novice designers created graphic Web advertisements in parallel or in series. Serial participants received descriptive critique directly after each prototype. Parallel participants created multiple prototypes before receiving feedback. As measured by click-through data and expert ratings, ads created in the Parallel condition significantly outperformed those from the Serial condition. Moreover, independent raters found Parallel prototypes to be more diverse. Parallel participants also reported a larger increase in task-specific self-confidence. This paper outlines a theoretical foundation for why parallel prototyping produces better design results and discusses the implications for design education.

Keywords

Serial Condition Graphic Design Client Site Multiple Prototype Parallel Prototype 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank Ugochi Acholonu, Lera Boroditsky, Jodi Forlizzi, Jeffrey Heer, Erik Stolterman, Ewart Thomas, and Terry Winograd for valuable discussions about this research. We thank Rachel Lopatin for analyzing the targeted critique data. The Hasso Plattner Design Thinking Research Program financially supported this work; Intel Corporation donated computers.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Steven P. Dow
    • 1
  • Alana Glassco
    • 1
  • Jonathan Kass
    • 1
  • Melissa Schwarz
    • 1
  • Daniel L. Schwartz
    • 1
  • Scott R. Klemmer
    • 1
  1. 1.Human-Computer Interaction GroupStanford UniversityStanfordUSA

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