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  • 标题:Examining the Influence of Saliency in Mobile Interface Displays
  • 本地全文:下载
  • 作者:Still, Jeremiah D. ; Hicks, John M. ; Cain, Ashley A.
  • 期刊名称:AIS Transactions on Human-Computer Interaction
  • 印刷版ISSN:1944-3900
  • 出版年度:2020
  • 卷号:12
  • 期号:1
  • 页码:28-44
  • DOI:10.17705/1thci.00127
  • 语种:English
  • 出版社:Association for Information Systems
  • 摘要:Designers spend more resources to develop better mobile experiences today than ever before. Researchers commonly use visual search efficiency as a usability measure to determine the time or effort it takes someone to perform a task. Previous research has shown that a computational visual saliency model can predict attentional deployment in stationary desktop displays. Designers can use this salience awareness to co-locate important task information with higher salience regions. Research has shown that placing targets in higher salience regions in this way improves interface efficiency. However, researchers have not tested the model in key mobile technology design dimensions such as small displays and touch screens. In two studies, we examined the influence of saliency in a mobile application interface. In the first study, we explored a saliency model’s ability to predict fixations in small mobile interfaces at three different display sizes under free-viewing conditions. In the second study, we examined the influence that visual saliency had on search efficiency while participants completed a directed search for either an interface element associated with high or low salience. We recorded reaction time to touch the targeted element on the tablet. We experimentally blocked high and low saliency interactions and subjectively measured cognitive workload. We found that a saliency model predicted fixations. In the search task, participants found highly salient targets about 900 milliseconds faster than low salient targets. Interestingly, participants did not perceive a lighter cognitive workload associated with the increase in search efficiency.
  • 关键词:Mobile Interface; Saliency Model; Visual Search; Cognitive Engineering; Efficiency
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