What makes icons appealing? The role of processing fluency in predicting icon appeal in different task contexts

McDougall, Siné; Reppa, Irene; Kulik, Jozef; Taylor, Alisdair

doi:10.1016/j.apergo.2016.02.006

Cited by 41 publications

(18 citation statements)

References 90 publications

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“…Most previous studies on the effect of familiarity have employed stimuli with preexisting differences in familiarity (Blalock, 2015; Cowan et al., 2015; McDougall et al., 2016; Siedenburg & McAdams, 2017). For example, McDougall et al. (2016) used preexisting icons as stimuli, dividing them into familiar and unfamiliar groups based on participants’ ratings and found that this varied considerably between individuals.…”

Section: Discussionmentioning

confidence: 99%

“…(2007) defined icon familiarity as the frequency of use, which relates directly to experience with an icon, and they believed that this form of familiarity could be trained by presenting participants with icons over a number of blocks of trials. Subsequent experimental findings of icon familiarity showed that the importance of icon characteristics changed with user experience (McDougall et al., 2016).…”

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confidence: 99%

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Icon Familiarity Affects the Performance of Complex Cognitive Tasks

et al. 2020

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The purpose of this study was to investigate whether and how users' familiarity with symbols affects the performance of complex cognitive tasks which place considerable demands on working memory resources. We combined a modified math task paradigm with our previous icon familiarity training paradigm. Participants were required to complete a mathematical task involving icons to test their ability to perform complex cognitive tasks. The complexity of the task was manipulated using three independent variables: icon familiarity (high-frequency vs. low-frequency), whether or not the equation requires substitution (substitution vs. no-substitution), and the number of steps required for solution (one step vs. two steps). The results showed that participants performed better on the equation-solving task when it used icons they were more extensively trained on. Importantly, icon familiarity interacted with the complexity of the task and the familiarity effect on performance (accuracy and response time) became greater when the complexity increased. These findings provide evidence that familiarity affects not only the ease of information retrieval but also the ease of subsequent processing activities associated with these information, which extends our understanding of how familiarity affects working memory. Moreover, our findings have practical implications for improving interaction efficiency. Before the operators formally use a digital system, they need to learn the precise meaning of those complex or unfamiliar symbols in a certain context as much as possible.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Icon Familiarity Affects the Performance of Complex Cognitive Tasks

et al. 2020

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“…Generally, findings from the current study showed that the image presented in the icon is the key point on which the perceived quality of the icon depends [ 44 , 45 ], and the preference of users for the icon may rely on this. In this case, designers may consider the cognitive features of an icon such as its familiarity, its concreteness, the complexity of the design intricated on it, its meaningfulness, and its semantic distance or its closeness to its intended meaning [ 20 , 46 , 47 ].…”

Section: Discussionmentioning

confidence: 99%

The Evaluation of Preference and Perceived Quality of Health Communication Icons Associated with COVID-19 Prevention Measures

et al. 2021

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Icons have been widely utilized to describe and promote COVID-19 prevention measures. The purpose of this study was to analyze the preference and subjective design features of 133 existing icons associated with COVID-19 prevention measures published by the health and medical organizations of different countries. The 133 icons represent nineteen different function names, such as “Wash Hands” and “Wear Face Mask”. A total of 57 participants were recruited to perform two different tests: ranking test and subjective rating test. The ranking test was conducted to elicit the preference ranking of seven icon designs representing each function name. It was followed by a subjective rating test using 13 semantic scales on the two most preferred icons to analyze their perceived quality. Spearmen correlation was applied to derive the possible correlations between users’ rankings and the semantic scales, and Friedman’s test was also performed to determine the true difference between ranking in terms of each semantic scale to provide a fully meaningful interpretation of the data. Generally, findings from the current study showed that the image presented in the icon is the key point that affects the icons’ perceived quality. Interestingly, Spearman’s correlation analysis between preference ranking and semantic scales showed that vague–clear, weak–strong, incompatible–compatible, and ineffective–effective were the four strongest semantic scales that highly correlated with the preference ranking. Considering the significant relationships between the semantic distances and the functions, images depicted in an icon should be realistic and as close as possible to its respected function to cater to users’ preferences. In addition, the results of Spearman’s correlation and Friedman’s test also inferred that compatibility and clarity of icon elements are the main factors determining a particular icon’s preferability. This study is the first comprehensive study to evaluate the icons associated with the COVID-19 prevention measures. The findings of this study can be utilized as the basis for redesigning icons, particularly for icons related to COVID-19 prevention measures. Furthermore, the approach can also be applied and extended for evaluating other medical icons.

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“…Additionally, adjective pairs related to visual qualities of graphical user interface icons were added as suggested per the previous literature. These adjectives include concrete and abstract (Arend et al 1987;Blankenberger and Hahn 1991;Dewar 1999;Hou and Ho 2013;Isherwood et al 2007;McDougall and Reppa 2008;McDougall et al 1999McDougall et al , 2000Moyes and Jordan 1993;Rogers and Oborne 1987), simple and complex (Choi and Lee 2012;Goonetilleke et al 2001;McDougall and Reppa 2008;McDougall and Reppa 2013;McDougall et al 2016) as well as unique and ordinary (Creusen and Schoormans 2005;Creusen et al 2010;Dewar 1999;Goonetilleke et al 2001;Huang et al 2002;Salman et al 2010). Furthermore, adjective pairs that measure the aesthetics of graphical user interface elements were added.…”

Section: Measure Developmentmentioning

confidence: 99%

Development of measurement instrument for visual qualities of graphical user interface elements (VISQUAL): a test in the context of mobile game icons

Jylhä

Hamari

2020

User Model User-Adap Inter

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Graphical user interfaces are widely common and present in everyday human–computer interaction, dominantly in computers and smartphones. Today, various actions are performed via graphical user interface elements, e.g., windows, menus and icons. An attractive user interface that adapts to user needs and preferences is progressively important as it often allows personalized information processing that facilitates interaction. However, practitioners and scholars have lacked an instrument for measuring user perception of aesthetics within graphical user interface elements to aid in creating successful graphical assets. Therefore, we studied dimensionality of ratings of different perceived aesthetic qualities in GUI elements as the foundation for the measurement instrument. First, we devised a semantic differential scale of 22 adjective pairs by combining prior scattered measures. We then conducted a vignette experiment with random participant (n = 569) assignment to evaluate 4 icons from a total of pre-selected 68 game app icons across 4 categories (concrete, abstract, character and text) using the semantic scales. This resulted in a total of 2276 individual icon evaluations. Through exploratory factor analyses, the observations converged into 5 dimensions of perceived visual quality: Excellence/Inferiority, Graciousness/Harshness, Idleness/Liveliness, Normalness/Bizarreness and Complexity/Simplicity. We then proceeded to conduct confirmatory factor analyses to test the model fit of the 5-factor model with all 22 adjective pairs as well as with an adjusted version of 15 adjective pairs. Overall, this study developed, validated, and consequently presents a measurement instrument for perceptions of visual qualities of graphical user interfaces and/or singular interface elements (VISQUAL) that can be used in multiple ways in several contexts related to visual human-computer interaction, interfaces and their adaption.

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What makes icons appealing? The role of processing fluency in predicting icon appeal in different task contexts

Cited by 41 publications

References 90 publications

Icon Familiarity Affects the Performance of Complex Cognitive Tasks

Icon Familiarity Affects the Performance of Complex Cognitive Tasks

The Evaluation of Preference and Perceived Quality of Health Communication Icons Associated with COVID-19 Prevention Measures

Development of measurement instrument for visual qualities of graphical user interface elements (VISQUAL): a test in the context of mobile game icons

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