CoChat
Sign Up
Cited by 121Design Education and PracticeCreativity in Education and NeuroscienceInnovative Human-Technology Interaction

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Design fixation: Classifications and modern methods of prevention

Youmans, Robert J., Arciszewski, Thomaz·2014·Artificial Intelligence for Engineering Design, Analysis and Manufacturing
DOI 10.1017/s0890060414000043
Open this paper in CoChat — free account

Abstract

The term design fixation is often used interchangeably to refer to situations where designers limit their creative output because of an overreliance on features of preexisting designs, or more generally, an overreliance on a specific body of knowledge directly associated with a problem. In this paper, we argue that interdisciplinary interest in design fixation has led to increasingly broad definitions of the phenomenon that may be undermining empirical research efforts, educational efforts to minimize fixation, and the acquisition and dissemination of transdisciplinary knowledge about fixation effects. To address these issues, we recommend that researchers consider categorizing fixation phenomena into one of three classifications: unconscious adherence to the influence of prior designs, conscious blocks to change, and intentional resistance to new ideas. Next, we distinguish between concept-based design fixation, fixation to a specific class of known design concepts, and knowledge-based design fixation, fixation to a problem-specific knowledge base. With these distinctions in place, we propose a system of orders of design fixation, recommend methods for reducing fixation in inventive design, and recommend areas that are in need of further research within the field of design science.

Overview

Integrity signals

Registry

Crossref · 10.1017/s0890060414000043

Cites

63 of 63 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 62 references

Research works printed but not linked: 12

  1. Gero, 2000, Research methods for design science research: computational and cognitive approaches
  2. Arciszewski, 1988, ARIZ 77—an innovative design method, Methods and Theories, 22, 796
  3. Weir, 1984, Another look at subliminal “facts.”, Advertising Age, 55
  4. Arciszewski, 1998, NASA Conf. Publication, 167
  5. Bellows, 2012, Proc. Human Factors and Ergonomics Society Annual Meeting, 1977
  6. Amabile, 1996, Creativity in Context
  7. Yuemin, 2011, Promoting public spaces of campus for the development of creativity, China Electric Power Education, 26, 18
  8. Clarke, 1997, TRIZ: Through the Eyes of an American TRIZ Specialist
  9. Arciszewski, 2009, Successful Education: How to Educate Creative Engineers
  10. Pratkanis, 1992, The cargo-cult science of subliminal persuasion, Skeptical Inquirer, 16, 260
  11. Zwicky, 1969, Discovery, Invention, Research Through the Morpho-logical Analysis
  12. Altshuller, 1994, The Art of Inventing (and Suddenly the Inventor Appeared)

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Youmans, R. J., & Arciszewski, T.
Affiliations
George Mason University (US)
Corresponding author
Youmans, Robert J.
Venue
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Publisher
Cambridge University Press (CUP)
Published
2014-05
Volume
28
Issue
2
Pages
129-137
ISSN
  • 0890-0604 (ISSN-L)
  • 1469-1760
DOI
10.1017/s0890060414000043
OpenAlex
W2109147217
Cited by
121
References
62
Citations by year
2026: 8 · 2025: 16 · 2024: 12 · 2023: 12 · 2022: 11 · 2021: 16 · 2020: 15 · 2019: 6 · 2018: 8 · 2017: 8 · 2016: 6 · 2015: 2 · 2014: 1
FWCI
6.60
Type
journal article
Language
en
Open access
closed
Licence
www.cambridge.org/core/terms (unspecified, 15 d)
Locations
Artificial intelligence for engineering design analysis and manufacturing (publishedVersion)
Topics
  • Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
design fixation, design creativity, inventive design, design education, transdisciplinary knowledge, resistance to new ideas

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review