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Parallel prototyping leads to better design results, more divergence, and increased self-efficacy

Published: 29 December 2010 Publication History

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 article outlines a theoretical foundation for why parallel prototyping produces better design results and discusses the implications for design education.

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Reviews

Alyx Macfadyen

This paper is essentially about designing visual material for persuasive advertising. The processes of iteration and prototyping are at the heart of software and systems engineering and design. As such, they seem somewhat out of context for producing advertising material designed to convince consumers to buy a product or service. Several hypotheses underpin this study, and are perhaps reasonable even when applied to this somewhat lightweight study. Click-through analytics, for example, are the stated and accepted metric for better design results, but it remains contentious to deploy them as the sole measure for "higher quality design." The authors cite research in cognitive studies, motivation, and user agency as validating factors for their study. Nevertheless, it is important to point out that the purpose of the works cited was to improve user experience rather than to influence the purchase of a product or service. The results of this study suggest that prototyping and iteration did return positive results. This is true, however, of all mentoring, testing, and extra time taken in the design process. The sequence of methods reported is certainly interesting, and those methods that support the confidence and self-efficacy of learners are important for success in industry. Design skills for Web portals, system interfaces, and online decision support systems, as well as in professional practices, are crucial for usability. I would like to have seen more focus here on design teaching that places an emphasis on contributing to the service and supporting its users and purpose. Targeted consumers quickly learn to recognize and avoid advertisements. Thus, designers must continue to develop new methods, ploys, and tricks to ensure that they obtain the click-throughs that are the measure of design success. Online Computing Reviews Service

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Published In

cover image ACM Transactions on Computer-Human Interaction
ACM Transactions on Computer-Human Interaction  Volume 17, Issue 4
December 2010
149 pages
ISSN:1073-0516
EISSN:1557-7325
DOI:10.1145/1879831
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 29 December 2010
Accepted: 01 August 2010
Revised: 01 August 2010
Received: 01 May 2010
Published in TOCHI Volume 17, Issue 4

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Author Tags

  1. Prototyping
  2. comparison
  3. critique
  4. design
  5. divergence
  6. exploration
  7. feedback
  8. iteration
  9. juxtaposition
  10. self-efficacy

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  • (2024)ProcessGallery: Contrasting Early and Late Iterations for Design Principle LearningProceedings of the ACM on Human-Computer Interaction10.1145/36373898:CSCW1(1-35)Online publication date: 26-Apr-2024
  • (2024)"It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language ModelsProceedings of the ACM on Human-Computer Interaction10.1145/36373618:CSCW1(1-26)Online publication date: 26-Apr-2024
  • (2024)When to Give Feedback: Exploring Tradeoffs in the Timing of Design FeedbackProceedings of the 16th Conference on Creativity & Cognition10.1145/3635636.3656183(292-310)Online publication date: 23-Jun-2024
  • (2024)Thinking Outside the Box: Non-Designer Perspectives and Recommendations for Template-Based Graphic Design ToolsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650967(1-9)Online publication date: 11-May-2024
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  • (2024)Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-CreationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642400(1-26)Online publication date: 11-May-2024
  • (2024)ABScribe: Rapid Exploration & Organization of Multiple Writing Variations in Human-AI Co-Writing Tasks using Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641899(1-18)Online publication date: 11-May-2024
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