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Smooth and Hard or Beautiful and Elegant? Experts’ Conceptual Structure of the Aesthetics of Materials

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  • Barbara E. Marschallek
  • Thomas Jacobsen

Abstract

The present study’s aim was to examine whether interindividual differences in levels of expertise influence the aesthetic processing of materials. In particular, we elucidated experts’ conceptual structure of the aesthetics of different materials using a free list task and compared it to recent non-expert data. To this end, we asked 401 architects, designers, and interior designers to list adjectives that could be used to describe the aesthetics of materials. The experts listed a large number of sensorial as well as aesthetically evaluative terms. As measured in a supplementary study, a slight majority of the listed terms had a neutral valence, followed by a large proportion of positive terms. The term beautiful , frequently the preeminent term in aesthetics, was by no means one of the most relevant terms in both studies. The results suggest that the conceptual structure of the aesthetics of materials is multifaceted and expressive, and, to some extent, influenced by expertise. Furthermore, the findings indicate that concepts underlying materials aesthetics differ from other domains.

Suggested Citation

  • Barbara E. Marschallek & Thomas Jacobsen, 2022. "Smooth and Hard or Beautiful and Elegant? Experts’ Conceptual Structure of the Aesthetics of Materials," SAGE Open, , vol. 12(2), pages 21582440221, May.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221096130
    DOI: 10.1177/21582440221096130
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    References listed on IDEAS

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    1. Jesper W. Schneider & Pia Borlund, 2007. "Matrix comparison, Part 2: Measuring the resemblance between proximity measures or ordination results by use of the mantel and procrustes statistics," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1596-1609, September.
    2. Matthijs J. Warrens, 2016. "Inequalities Between Similarities for Numerical Data," Journal of Classification, Springer;The Classification Society, vol. 33(1), pages 141-148, April.
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