Individual differences in aesthetic preferences for multi-sensorial stimulation

GAO, Jie and SORANZO, Alessandro (2020). Individual differences in aesthetic preferences for multi-sensorial stimulation. Vision, 4(1) (6).

[img]
Preview
PDF
Soranzo_individual_differences_in_aesthetic(VoR).pdf - Published Version
Creative Commons Attribution.

Download (2MB) | Preview
Official URL: https://www.mdpi.com/2411-5150/4/1/6
Link to published version:: https://doi.org/10.3390/vision4010006

Abstract

The aim of the current project was to investigate aesthetics in multi-sensorial stimulation and to explore individual differences in the process. We measured the aesthetics of Interactive Objects (IOs) which are three-dimensional objects with electronic components that exhibit an autonomous behaviour when handled: e.g., vibrating, playing a sound, or lighting-up. The Q-sorting procedure of Q-methodology was applied. Data were analysed by following the Qmulti protocol. The results suggested that overall participants preferred IOs that (i) vibrate, (ii) have rough surface texture, and (iii) are round. No particular preference emerged about the size of the IOs. When making aesthetic judgment, participants paid more attention to the behaviour variable of the IOs than the size, contour or surface texture. In addition, three clusters of participants were identified, suggesting that individual differences existed in the aesthetics of IOs. Without proper consideration of potential individual differences, aesthetic scholars may face the risk of having significant effects masked by individual differences. Only by paying attention to this issue can more meaningful findings be generated to contribute to the field of aesthetics.

Item Type: Article
Identification Number: https://doi.org/10.3390/vision4010006
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 02 Jan 2020 13:10
Last Modified: 18 Mar 2021 01:08
URI: https://shura.shu.ac.uk/id/eprint/25611

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics