Improving Discoverability and Expert Performance in Force-Sensitive Text Selection for Touch Devices with Mode Gauges

Alix Goguey 1 Sylvain Malacria 2 Carl Gutwin 1
2 LOKI - Technology and knowledge for interaction
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : Text selection on touch devices can be a difficult task for users. Letters and words are often too small to select directly , and the enhanced interaction techniques provided by the OS – magnifiers, selection handles, and methods for selecting at the character, word, or sentence level – often lead to as many usability problems as they solve. The introduction of force-sensitive touchscreens has added another enhancement to text selection (using force for different selection modes); however, these modes are difficult to discover and many users continue to struggle with accurate selection. In this paper we report on an investigation of the design of touch-based and force-based text selection mechanisms, and describe two novel text-selection techniques that provide improved discov-erability, enhanced visual feedback, and a higher performance ceiling for experienced users. Two evaluations show that one design successfully combined support for novices and experts , was never worse than the standard iOS technique, and was preferred by participants.
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Communication dans un congrès
CHI 2018 - ACM Conference on Human Factors in Computing Systems, Apr 2018, Montreal, Canada. pp.1-12, 〈https://chi2018.acm.org/〉. 〈10.1145/3173574.3174051〉
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Contributeur : Sylvain Malacria <>
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Dernière modification le : mardi 3 juillet 2018 - 11:37:20
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Alix Goguey, Sylvain Malacria, Carl Gutwin. Improving Discoverability and Expert Performance in Force-Sensitive Text Selection for Touch Devices with Mode Gauges. CHI 2018 - ACM Conference on Human Factors in Computing Systems, Apr 2018, Montreal, Canada. pp.1-12, 〈https://chi2018.acm.org/〉. 〈10.1145/3173574.3174051〉. 〈hal-01714195〉

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