GUI & expert interaction

Paper session

会議の名前
CHI 2020
Optimizing User Interface Layouts via Gradient Descent
要旨

Automating parts of the user interface (UI) design process has been a longstanding challenge. We present an automated technique for optimizing the layouts of mobile UIs. Our method uses gradient descent on a neural network model of task performance with respect to the model's inputs to make layout modifications that result in improved predicted error rates and task completion times. We start by extending prior work on neural network based performance prediction to 2-dimensional mobile UIs with an expanded interaction space. We then apply our method to two UIs, including one that the model had not been trained on, to discover layout alternatives with significantly improved predicted performance. Finally, we confirm these predictions experimentally, showing improvements up to 9.2 percent in the optimized layouts. This demonstrates the algorithm's efficacy in improving the task performance of a layout, and its ability to generalize and improve layouts of new interfaces.

キーワード
Optimization
data-driven design
gradient descent
deep learning
mobile interfaces
LSTM
performance modeling
著者
Peitong Duan
Intel AI, Santa Clara, CA, USA
Casimir Wierzynski
Intel AI, Santa Clara, CA, USA
Lama Nachman
Intel Labs, Santa Clara, CA, USA
DOI

10.1145/3313831.3376589

論文URL

https://doi.org/10.1145/3313831.3376589

動画
UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User Perception
要旨

A Dark Pattern (DP) is an interface maliciously crafted to deceive users into performing actions they did not mean to do. In this work, we analyze Dark Patterns in 240 popular mobile apps and conduct an online experiment with 589 users on how they perceive Dark Patterns in such apps. The results of the analysis show that 95% of the analyzed apps contain one or more forms of Dark Patterns and, on average, popular applications include at least seven different types of deceiving interfaces. The online experiment shows that most users do not recognize Dark Patterns, but can perform better in recognizing malicious designs if informed on the issue. We discuss the impact of our work and what measures could be applied to alleviate the issue.

キーワード
Dark Patterns
Ethical Design
User Experiments
著者
Linda Di Geronimo
University of Zürich, Zürich, Switzerland
Larissa Braz
University of Zürich, Zürich, Switzerland
Enrico Fregnan
University of Zürich, Zürich, Switzerland
Fabio Palomba
University of Zürich, Zürich, Switzerland
Alberto Bacchelli
University of Zürich, Zürich, Switzerland
DOI

10.1145/3313831.3376600

論文URL

https://doi.org/10.1145/3313831.3376600

動画
Keep it Simple: How Visual Complexity and Preferences Impact Search Efficiency on Websites
要旨

We conducted an online study with 165 participants in which we tested their search efficiency and information recall. We confirm that the visual complexity of a website has a significant negative effect on search efficiency and information recall. However, the search efficiency of those who preferred simple websites was more negatively affected by highly complex websites than those who preferred high visual complexity. Our results suggest that diverse visual preferences need to be accounted for when assessing search response time and information recall in HCI experiments, testing software, or A/B tests.

キーワード
Visual appeal
visual complexity
user interface
design
usability
search efficiency
information recall
著者
Amanda Baughan
University of Washington, Seattle, WA, USA
Tal August
University of Washington, Seattle, WA, USA
Naomi Yamashita
NTT Communication Science Laboratories, Keihanna, Japan
Katharina Reinecke
University of Washington, Seattle, WA, USA
DOI

10.1145/3313831.3376849

論文URL

https://doi.org/10.1145/3313831.3376849

Investigating the Necessity of Delay in Marking Menu Invocation
要旨

Delayed display of menu items is a core design component of marking menus, arguably to prevent visual distraction and foster the use of mark mode. We investigate these assumptions, by contrasting the original marking menu design with immediately-displayed marking menus. In three controlled experiments, we fail to reveal obvious and systematic performance or usability advantages to using delay and mark mode. Only in very constrained settings – after significant training and only two items to learn – did traditional marking menus show a time improvement of about 260~ms. Otherwise, we found an overall decrease in performance with delay, whether participants exhibited practiced or unpracticed behaviour. Our final study failed to demonstrate that an immediately-displayed menu interface is more visually disrupting than a delayed menu. These findings inform the costs and benefits of incorporating delay in marking menus, and motivate guidelines for situations in which its use is desirable.

キーワード
marking menu
delay
著者
Jay Henderson
University of Waterloo, Waterloo, ON, Canada
Sylvain Malacria
Inria & University of Lille, UMR 9189 - CRIStAL, Lille, France
Mathieu Nancel
Inria & University of Lille, UMR 9189 - CRIStAL, Lille, France
Edward Lank
University of Waterloo & Inria, Waterloo, ON, Canada
DOI

10.1145/3313831.3376296

論文URL

https://doi.org/10.1145/3313831.3376296

動画
KeyMap: Improving Keyboard Shortcut Vocabulary Using Norman's Mapping
要旨

We introduce a new shortcut interface called KeyMap that is designed to leverage Norman's principle of natural mapping. Rather than displaying shortcut command labels in linear menus, KeyMap displays a virtual keyboard with command labels displayed directly on its keys. A crowdsourced experiment compares KeyMap to Malacria et~al.'s ExposeHK using an extension of their protocol to also test recall. Results show KeyMap users remembered 1 more shortcut than ExposeHK immediately after training, and this advantage increased to 4.5 more shortcuts when tested again after 24 hours. KeyMap users also incidentally learned more shortcuts that they had never practised. We demonstrate how KeyMap can be added to existing web-based applications using a Chrome extension.

キーワード
interaction techniques
learning
keyboard shortcuts
著者
Blaine Lewis
University of Toronto, Toronto, ON, Canada
Greg d'Eon
Universiy of British Columbia, Vancouver, BC, Canada
Andy Cockburn
University of Canterbury, Christchurch, New Zealand
Daniel Vogel
University of Waterloo, Waterloo, ON, Canada
DOI

10.1145/3313831.3376483

論文URL

https://doi.org/10.1145/3313831.3376483

動画