Performance and user experience of touchscreen and gesture keyboards in a lab setting and in the wild
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We study the performance and user experience of two popular mainstream mobile text entry methods: the Smart Touch Keyboard (STK) and the Smart Gesture Keyboard (SGK). Our first study is a lab-based ten-session text entry experiment. In our second study we use a new text entry evaluation methodology based on the experience sampling method (ESM). In the ESM study, participants installed an Android app on their own mobile phones that periodically sampled their text entry performance and user experience amid their everyday activities for four weeks. The studies show that text can be entered at an average speed of 28 to 39 WPM, depending on the method and the user's experience, with 1.0% to 3.6% character error rates remaining. Error rates of touchscreen input, particularly with SGK, are a major challenge; and reducing out-of-vocabulary errors is particularly important. Both SGK and STK have strengths, weaknesses, and different individual awareness and preferences. Two-thumb touch typing in a focused setting is particularly effective on STK, whereas one-handed SGK typing with the thumb is particularly effective in more mobile situations. When exposed to both, users tend to migrate from STK to SGK. We also conclude that studies in the lab and in the wild can both be informative to reveal different aspects of keyboard experience, but used in conjunction is more reliable in comprehensively assessing input technologies of current and future generations.
Reyal , S M , Zhai , S & Kristensson , P O 2015 , Performance and user experience of touchscreen and gesture keyboards in a lab setting and in the wild . in CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems . ACM , New York , pp. 679-688 , The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI) , Seoul , Korea, Republic of , 18-23 April . DOI: 10.1145/2702123.2702597conference
CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
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Date of Acceptance: 15/12/2014
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