Designers strive for enjoyable user experience (UX) and put a significant effort into making graphical user interfaces (GUI) both usable and beautiful. Our goal is to minimize their effort: with this purpose in mind, we have been studying automatic metrics of GUI qualities. These metrics could enable designers to iterate their designs more quickly. We started from the psychological findings that people tend to prefer simpler things. We then assumed visual complexity determinants also determine visual aesthetics and outlined eight of them as belonging to three dimensions: information amount (visual clutter and color variability), information organization (symmetry, grid, ease-of-grouping and prototypicality), and information discriminability (contour density and figure-ground contrast). We investigated five determinants (visual clutter, symmetry, contour density, figure-ground contrast and color variability) and proposed six associated automatic metrics. These metrics take screenshots of GUI as input and can thus be applied to any type of GUI. We validated the metrics through a user study: we gathered the ratings of immediate impressions of GUI visual complexity and aesthetics, and correlated them with the output of the metrics. The output explained up to 51 of aesthetics ratings and 50 of complexity ratings. This promising result could be further extended towards the creation of tLight, our automatic GUI evaluation tool

People prefer attractive interfaces. Designers strive to outmatch competitors, and create apps and websites that stand out. However, significant expenses on design are unaffordable to small companies; instead, they could adopt automatic tools of interface aesthetics evaluation, a cheaper strategy to good design. This paper describes an important step towards such a tool; it presents eight automatic metrics of graphical user interface (GUI) aesthetics. We tested the metrics in two exploratory studies -on desktop webpages (N = 62) and on iPhone apps (N = 53) -and found them to function on both GUI types and for both immediate (150ms exposure) and deliberate (4s exposure) aesthetics impressions. Our best-fit regression models explained up to 49% of variance in webpage aesthetics and up to 32% (if app genre is considered) of variance in iPhone app aesthetics. These results confirm past results and suggest the metrics are valid and reliable enough to be widely discussed, and possibly, to be embedded in our prospective GUI evaluation tool, tLight.

First impressions are formed very fast but they last. Consecutive approach-avoidance behavior is formed almost instantly and persists over time. The effect of the first impression of graphical user interfaces (GUIs) of desktop webpages on subsequent evaluation is well documented in the literature. Less research has focused on mobile interfaces. To cover this gap, this paper reports two studies. The first study confirmed the persistence of first impressions on mobile interfaces evaluation, although it suggested that exposure time may be longer. The second study extends previous work on automatic evaluation from desktop to mobile interfaces. The linking theme between the studies is that of visual complexity, which is a more objective, yet powerful, predictor of aesthetic evaluation. Using six automatic metrics (color depth, dominant colors, visual clutter, symmetry, figure-ground contrast and edge congestion), in study 2 we explained 40 of variation in subjective complexity scores and 36 of variation in aesthetics scores

Reading is fundamental to interactive-system use, but around 800 million of people might struggle with it due to literacy difficulties. Few websites are designed for high readability, as readability remains an underinvestigated facet of User Experience. Existing readability guidelines have multiple issues: they are too many or too generic, poorly worded, and often lack cognitive grounding. This paper developed a set of 61 readability guidelines in a series of workshops with design and dyslexia experts. A user study with dyslexic and average readers further narrowed the 61-guideline set down to a core set of 12 guidelines-an acceptably small set to keep in mind while designing. The core-set guidelines address reformatting-such as using larger fonts and narrower content columns, or avoiding underlining and italics-and may well aply to the interactive system other than websites.

Aalto Interface Metrics (AIM) pools several empirically validated models and metrics of user perception and attention into an easy-to-use online service for the evaluation of graphical user interface (GUI) designs. Users input a GUI design via URL, and select from a list of 17 different metrics covering aspects ranging from visual clutter to visual learnability. AIM presents detailed breakdowns, visualizations, and statistical comparisons, enabling designers and practitioners to detect shortcomings and possible improvements. The web service and code repository are available at interfacemetrics.aalto.fi.