Evaluating the Effectiveness of Tilt Gestures for Text Property Control in Mobile Interfaces
Year: 2025
Type: article
Abstract: The objective of this study is to verify the usability of gesture interactions such as tilting or shaking, rather than conventional touch gestures, on mobile devices. To this end, a prototype was developed that manipulates the text size in a mobile text messaging application through tilt gestures. In the text input interface, three types of tilt gesture interaction methods (‘Shaking’, ‘Leaning’, and ‘Acceleration’) were implemented to select the text size level among five levels (extra-small, small, normal, large, and extra-large). Along with the gesture-based interaction methods, the conventional button method was also evaluated. A total of 24 participants were asked to prepare text messages of specified font sizes using randomly assigned interaction methods to select the font size. Task completion time, accuracy (setting errors and input errors), workload, and subjective preferences were collected and analyzed. As a result, the ‘Shaking’ method was generally similar to the conventional button method and superior to the other two ‘Leaning’ and ‘Acceleration’ methods. This may be because ‘Leaning’ and ‘Acceleration’ are continuous operations, while ‘Shaking’ is an individual operation for each menu (font size level). According to subjective comments, tilting gestures on mobile devices can not only be useful if users take the time to learn them, but also provide ways to convey intentions with simple text. Although tilting gestures were not found to significantly improve text editing performance compared to conventional screen touch methods, the use of motion gestures beyond touch on mobile devices can be considered for interface manipulations such as app navigation, gaming, or multimedia controls across diverse applications.
DOI: 10.3390/mti9050041
Authors: Sang-Hwan Kim, Xuesen Liu
Institution: University of Michigan–Dearborn
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W4409946971