Paper Reading #28: Experimental analysis of touch-screen gesture designs in mobile environments

Experimental analysis of touch-screen gesture designs in mobile environments

Chi '11

By:
Andrew Bragdon, Eugene Nelson, Yang Li, and Ken Hinckle.

• Andrew Bragdon is currently a PhD student at Brown University.
• Eugene Nelson is currnetly a PhD Student at Brown University.
• Yang Li is currently a researcher at Google. He also holds a PhD from the Chinese Academy of Sciences.
• Ken Hinckle is a Principal researcher at Microsoft Research. He also holds a PhD from the University of Virginia.

Summary
Hypothesis
The researchers are attempting to develop an application that uses Bezel and marker-based gestures to speed up and allow more accurate actions on touch screen based phones with less user attention.

Methods
To test and asses their applications they had 15 participants were asked to complete a series of tasks through various distractions at varying levels of intensity. Sitting and walking were the two major areas studied along the levels of distraction ranging from no distraction to complete distraction. To appropriately gather data and have a proper test, the participants were give a pre-test questionnaire along with appropriate instructions to complete their tasks.

Results
Bezel marks were by far the fastest in mean completion time, with soft and hard buttons coming in next with negligible difference in their mean completion times. While bezel marks and soft buttons performed similarly in direct action, bezel marks far outperformed soft buttons with distractions. Bezel and soft button paths had a quicker mean time compared to bezel and hard button paths.

Contents
This paper spent much time looking at the effect of having varying types of buttons, and their varying levels of effectiveness under different circumstances. The concluded that direct touch is the most accurate and the quickest regardless of input form, however with distractions, hard buttons are the most successful form of input.

Discussion
The authors did a fantastic job of attaining their objective. By the end of the experiment they had a superior understanding of distractions, their effect on user input and the best input and type of input to use during varying levels of interaction and distraction. It's a fairly relevant paper and certainly worth further research.