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Theoretical Foundations of Design Thinking

In: Design Thinking Research

Author

Listed:
  • Julia P. A. Thienen

    (Hasso Plattner Institute for Digital Engineering, University of Potsdam)

  • William J. Clancey

    (Florida Institute for Human and Machine Cognition)

  • Christoph Meinel

    (Hasso Plattner Institute for Digital Engineering, University of Potsdam)

Abstract

Although design thinking is often understood as a practical approach to creativity and innovation in design, it builds on highly refined theories. Many influential ideas were gathered and advanced at the Mechanical Engineering department of Stanford University from the 1950s onwards, as explored in this history series. In part I we introduced the “creative engineering” theory of Stanford educator John E. Arnold. This chapter—part II—is dedicated to the need-based design theory propounded by one of his successors at the department, Robert H. McKim. His theory, first published in 1959, advanced human-centred design conceptions by providing an elaborate account of human needs, by clarifying the role of designs and designers in the process of culture development, and by providing guidelines to assess, or actively increase, design value. According to McKim, the ultimate purpose of design is to promote the well-being of people by helping to gratify their basic needs. As his overall design framework is broadly scoped, it can also serve as frame of reference to analyse and compare different present-day approaches to design, such as innovation-focused design thinking and usability-focused studies in Human-Computer Interaction.

Suggested Citation

  • Julia P. A. Thienen & William J. Clancey & Christoph Meinel, 2019. "Theoretical Foundations of Design Thinking," Understanding Innovation, in: Christoph Meinel & Larry Leifer (ed.), Design Thinking Research, pages 13-38, Springer.
    • Handle: RePEc:spr:undchp:978-3-319-97082-0_2
    DOI: 10.1007/978-3-319-97082-0_2
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    Cited by:

    1. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
    2. Selma Paco & Joji Linaugo, 2023. "Concept Retention among Senior High School Science, Technology, Engineering, and Mathematics (STEM) Students Exposed to a Strategic Intervention Material (SIM)," Technium Social Sciences Journal, Technium Science, vol. 41(1), pages 72-81, March.
    3. Migchelbrink, Koen & Raymaekers, Pieter, 2023. "Nudging people to pay their parking fines on time. Evidence from a cluster-randomized field experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 105(C).

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