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Storyboard-Based Empirical Modeling of Touch Interface Performance

Published: 21 April 2018 Publication History

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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    cover image ACM Conferences
    CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
    April 2018
    8489 pages
    ISBN:9781450356206
    DOI:10.1145/3173574
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 21 April 2018

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    1. modelling
    2. performance prediction
    3. touch interaction

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    CHI '18 Paper Acceptance Rate 666 of 2,590 submissions, 26%;
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    • (2023)�GeT: Multimodal eyes-free text selection technique combining touch interaction and microgesturesProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3614131(594-603)Online publication date: 9-Oct-2023
    • (2023)�Glyph: a Microgesture NotationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580693(1-28)Online publication date: 19-Apr-2023
    • (2022)Towards a Unified and Efficient Command Selection Mechanism for Touch-Based Devices Using Soft Keyboard HotkeysACM Transactions on Computer-Human Interaction10.1145/347651029:1(1-39)Online publication date: 7-Jan-2022
    • (2021)Resource Choreography in Cyber-Physical-Social Systems: Representation, Modeling and ExecutionIEEE Transactions on Services Computing10.1109/TSC.2021.3138637(1-1)Online publication date: 2021
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    • (2019)RL-KLMProceedings of the 24th International Conference on Intelligent User Interfaces10.1145/3301275.3302285(476-480)Online publication date: 17-Mar-2019
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    • (2018)Storyboard-Based Empirical Modelling of Touch Interface PerformanceExtended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3170427.3186479(1-4)Online publication date: 20-Apr-2018

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