Storyboard-Based Empirical Modelling of Touch Interface Performance

Abstract : Touch interactions are now ubiquitous, but few tools are available to help designers quickly prototype touch interfaces and predict their performance. For rapid prototyping, most applications only support visual design. For predictive modelling, tools such as CogTool generate performance predictions but do not represent touch actions natively and do not allow exploration of different usage contexts. To combine the benefits of rapid visual design tools with underlying predictive models, we developed the Storyboard Empirical Modelling tool (StEM) for exploring and predicting user performance with touch interfaces. StEM provides performance models for mainstream touch actions, based on a large corpus of realistic data. We evaluated StEM in an experiment and compared its predictions to empirical times for several scenarios. The study showed that our predictions are accurate (within 7% of empirical values on average), and that StEM correctly predicted differences between alternative designs. Our tool provides new capabilities for exploring and predicting touch performance, even in the early stages of design.
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CHI 2018 - ACM Conference on Human Factors in Computing Systems, Apr 2018, Montréal, Canada. ACM, CHI 2018 - ACM Conference on Human Factors in Computing Systems, 2018, 〈https://chi2018.acm.org/〉. 〈10.1145/3173574.3174019〉
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Alix Goguey, Géry Casiez, Andy Cockburn, Carl Gutwin. Storyboard-Based Empirical Modelling of Touch Interface Performance. CHI 2018 - ACM Conference on Human Factors in Computing Systems, Apr 2018, Montréal, Canada. ACM, CHI 2018 - ACM Conference on Human Factors in Computing Systems, 2018, 〈https://chi2018.acm.org/〉. 〈10.1145/3173574.3174019〉. 〈hal-01714825〉

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