The evaluation of interface aesthetics

Mõttus, Mati; Lamas, David; Pajusalu, Maarja; Torres, Rui

doi:10.1145/2500342.2500345

Cited by 13 publications

(3 citation statements)

References 8 publications

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“…are usually carried out by quantifying design aesthetics. They are usually directed to the result that multiple interface design features influence users' aesthetic preferences (Moshagen and Thielsch, 2010 ; Mttus et al, 2013 ) making it hard to extract further implications from the intertwined conclusions. Therefore, research from a single interface design feature (Laarni et al, 2005 ; Sheedy et al, 2005 ) is more promising and meaningful, both theoretically and practically.…”

Section: Introductionmentioning

confidence: 99%

The Implicit Aesthetic Preference for Mobile Marketing Interface Layout—An ERP Study

Wang

Xiao

et al. 2021

Front. Hum. Neurosci.

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Businesses and scholars have been trying to improve marketing effect by optimizing mobile marketing interfaces aesthetically as users browse freely and aimlessly through mobile marketing interfaces. Although the layout is an important design factor that affects interface aesthetics, whether it can trigger customer's aesthetic preferences in mobile marketing remains unexplored. To address this issue, we employ an empirical methodology of event-related potentials (EPR) in this study from the perspective of cognitive neuroscience and psychology. Subjects are presented with a series of mobile marketing interface images of different layouts with identical marketing content. Their EEG waves were recorded as they were required to distinguish a target stimulus from the others. After the experiment, each of the subjects chose five stimuli interfaces they like and five they dislike. By analyzing the ERP data derived from the EEG data and the behavioral data, we find significant differences between the disliked interfaces and the other interfaces in the ERP component of P2 from the frontal-central area in the 200–400 ms post-stimulus onset time window and LPP from both the frontal-central and parietal-occipital area in the 400–600 ms time window. The results support the hypothesis that humans do make rapid implicit aesthetic preferences for interface layouts and suggest that even under a free browsing context like the mobile marketing context, interface layouts that raise high emotional arousal can still attract more user attention and induce users' implicit aesthetic preference.

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Section: Introductionmentioning

confidence: 99%

The Implicit Aesthetic Preference for Mobile Marketing Interface Layout—An ERP Study

Wang

Xiao

et al. 2021

Front. Hum. Neurosci.

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“…Unlike other research experiment conducted in the past (Mõttus et al (2013)), we chose not to present to the participants one UI at a time and asking them to evaluate its aesthetic metrics separately ( Figure 2a) in order to minimise repetitive tasks that would lead to participant's fatigue. We noticed that this method was making each UI being evaluated independent from each other.…”

Section: Comparative Methodsmentioning

confidence: 99%

Assessing User Interface Aesthetics based on the Inter-subjectivity of Judgment

Zen

Vanderdonckt

2016

Electronic Workshops in Computing

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How to assess user interface aesthetics?" remains a question faced by many user interface researchers and designers during the user interface development life cycle since aesthetics positively influence usability, user experience, pleasureability, and trust. Visual techniques borrowed from visual design suggest that the graphical user interface layout could be assessed by aesthetic metrics such as balance, symmetry, proportion, regularity, and simplicity, to name a few. Whereas different formulas exist for computing each aesthetic metric and different interpretations to sum up their results, no consensus exists today on how to consistently evaluate these metrics in a way that is aligned with human judgement, which is intrinsically subjective. In order to address the challenging alignment of human subjectivity with machine objectivity, this paper reports on an experiment comparing the results issued from the inter-subjectivity of judgment of fifteen participants evaluating four main aesthetic metrics on a sample of ten graphical user interfaces and the values of these metrics calculated semi-automatically by a web-based application. The experiment suggests that some metrics, e.g. symmetry, proportion, simplicity, as computed from the formula are actually positively correlated with human judgment, while some other metrics, such as balance, are surprisingly not correlated with the formula computed, thus indicating that another formula or another interpretation should be determined. Therefore, a new formula for computing balance is defined that decomposes balance into horizontal and vertical balances which re-establish a correlation. This paper then provides some new insights on how to rely on these aesthetic metrics and other related metrics, whether they are interpreted manually or computed automatically.

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“…Another study (Salimun et al 2010) computed several metrics based on the prior literature (Ngo 2001;Ngo et al 2003) to conclude that some metrics, such as symmetry and cohesion, influence results more than others. A study (Mõttus et al 2013) that tested objective and subjective evaluation methods according to the prior literature (Ngo et al 2000(Ngo et al , 2003 displayed a weak correlation between the ratings.…”

mentioning

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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The evaluation of interface aesthetics

Cited by 13 publications

References 8 publications

The Implicit Aesthetic Preference for Mobile Marketing Interface Layout—An ERP Study

The Implicit Aesthetic Preference for Mobile Marketing Interface Layout—An ERP Study

Assessing User Interface Aesthetics based on the Inter-subjectivity of Judgment

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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