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Cognitive Style and Field Knowledge in Complex Design Problem-Solving: A Comparative Case Study of Decision Support Systems

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Design Computing and Cognition '18 (DCC 2018)

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Abstract

Cognitive differences between how people perceive and process information have been broadly studied in the fields of education and psychology. Previous findings show that comprehension is optimized when information presentation aligns with the cognitive abilities and preferences of an individual. On the other hand, the possession of field knowledge has also been studied to influence learning outcome and perception. This paper aims to understand the effects of individual’s information processing styles and field knowledge on design decision-making, specifically focusing on designer learning and user experience. Two distinct decision support systems interfaces were developed to better examine the effect using a mixed model design. A total of 48 college students participated in the experimental study and interacted with the two different interfaces of a satellite design system in a randomized order. Analysis results show significant impacts of field knowledge and visual processing style on both learning and user experience. Potential interaction effects with the design support system interface type and cognitive styles were also observed.

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Authors and Affiliations

  1. Cornell University, Ithaca, NY, USA

    Yuan Ling Zi Shi, Hyunseung Bang, Guy Hoffman, Daniel Selva & So-Yeon Yoon

Authors
  1. Yuan Ling Zi Shi
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  2. Hyunseung Bang
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  3. Guy Hoffman
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  4. Daniel Selva
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  5. So-Yeon Yoon
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Corresponding author

Correspondence to So-Yeon Yoon .

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Editors and Affiliations

  1. Department of Computer Science and School of Architecture, University of North Carolina at Charlotte, Charlotte, NC, USA

    John S. Gero

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Shi, Y.L.Z., Bang, H., Hoffman, G., Selva, D., Yoon, SY. (2019). Cognitive Style and Field Knowledge in Complex Design Problem-Solving: A Comparative Case Study of Decision Support Systems. In: Gero, J. (eds) Design Computing and Cognition '18. DCC 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-05363-5_19

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  • DOI: https://doi.org/10.1007/978-3-030-05363-5_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05362-8

  • Online ISBN: 978-3-030-05363-5

  • eBook Packages: EngineeringEngineering (R0)

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