论文标题

通过远程启发访谈了解Covid-19的用户体验

Understanding User Experience of COVID-19 Maps through Remote Elicitation Interviews

论文作者

Çay, Damla, Nagel, Till, Yantaç, Asım Evren

论文摘要

在冠状病毒大流行期间,可视化次数获得了新的知名度和意义。人们被一系列的公共卫生可视化轰炸,从简单的图表到复杂的互动仪表板。在大流行的环境中,大量世界人口在社会上疏远了,迫切需要优化远程设置的现有用户体验评估方法,以了解人们如何从相关的可视化中有意义。在评估针对公众的可视化效果时,具有截然不同的社会人口统计学背景和不同水平的技术曲折和数据素养,重要的是要了解用户反馈以外的速度,任务准确性或可用性问题等方面。作为这种更广泛的评估观点的一部分,微观验证学已用于评估静态和叙事可视化,以详细的方式揭示了生活经验。在这些研究的基础上,我们进行了一项用户研究,以了解如何在远程设置中采用启发(又称微观验证)访谈。在一项案例研究中,我们研究了参与者通过基于地图的交互式可视化的经验。我们的发现揭示了进行启发访谈的积极和负面方面。我们的结果可以为计划和执行远程启发采访以评估交互式可视化的过程提供信息。此外,我们分享了有关可视化技术和互动设计的建议,涉及公共卫生数据。

During the coronavirus pandemic, visualizations gained a new level of popularity and meaning for a wider audience. People were bombarded with a wide set of public health visualizations ranging from simple graphs to complex interactive dashboards. In a pandemic setting, where large amounts of the world population are socially distancing themselves, it becomes an urgent need to refine existing user experience evaluation methods for remote settings to understand how people make sense out of COVID-19 related visualizations. When evaluating visualizations aimed towards the general public with vastly different socio-demographic backgrounds and varying levels of technical savviness and data literacy, it is important to understand user feedback beyond aspects such as speed, task accuracy, or usability problems. As a part of this wider evaluation perspective, micro-phenomenology has been used to evaluate static and narrative visualizations to reveal the lived experience in a detailed way. Building upon these studies, we conducted a user study to understand how to employ Elicitation (aka Micro-phenomenological) interviews in remote settings. In a case study, we investigated what experiences the participants had with map-based interactive visualizations. Our findings reveal positive and negative aspects of conducting Elicitation interviews remotely. Our results can inform the process of planning and executing remote Elicitation interviews to evaluate interactive visualizations. In addition, we share recommendations regarding visualization techniques and interaction design about public health data.

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