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An Empirical Study of Icon Recognition in a Virtual Gallery Interface

Ashe, Denise E, EARDLEY, Alan and FLETCHER, Bobbie (2018) An Empirical Study of Icon Recognition in a Virtual Gallery Interface. Advances in Science, Technology and Engineering Systems Journal, 3 (6). pp. 289-313. ISSN 2415-6698

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Abstract or description

This paper reports on an empirical study (an extension of a pilot study) that analyses the design of icons in a German 3-D virtual art gallery interface. It evaluates the extent to which a sample of typical computer users from a range of ages, educational attainments and employments can interpret the meaning of icons from the virtual interface taken ‘out of context’ and ‘in context’. The study assessed a sample of 21 icons representing the ‘action’, ‘information’ and ‘navigation’ functions of the virtual interface using a new Icon Recognition Testing method (IRT) developed by the researchers from existing usability test methods. The Icon Recognition Rate (IRR) of the icons was calculated and they were classified as ‘identifiable’, ‘mediocre’ or ‘vague’ in a novel and useful classification system. The IRT results show that the IRR of almost a quarter of the icons was below the ‘identifiable’ standard, which could seriously compromise the usability of a virtual interface. A comparison is made, using textual and thematic analysis, between the participants’ understanding of the icons’ meaning in and out of context and of the effect of positioning icons in relation to their virtual surroundings and of grouping them in tool bars. From the findings of the study, conclusions are drawn, and recommendations are made for economical icon redesign and replacement. It is suggested in the conclusions that further research is needed into how designers’ conceptual models can be better matched to users’ mental models in the design of virtual interfaces by bringing user profiles into the study.

Item Type: Article
Uncontrolled Keywords: Interface usability, Icon recognition. Icon intuitiveness. Icon design.
Faculty: School of Computing and Digital Technologies > Computing
Depositing User: Alan EARDLEY
Date Deposited: 07 Dec 2018 15:26
Last Modified: 07 Dec 2018 15:26
URI: http://eprints.staffs.ac.uk/id/eprint/4973

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