Epstein Daniel A, Kang Jennifer H, Pina Laura R, Fogarty James, Munson Sean A
Computer Science & Engineering, DUB Group, University of Washington.
The Information School, DUB Group, University of Washington.
Proc ACM Int Conf Ubiquitous Comput. 2016 Sep 12;2016:829-840. doi: 10.1145/2971648.2971656.
People stop using personal tracking tools over time, referred to as the stage of their tool use. We explore how designs can support people when they lapse in tracking, considering how to design data representations for a person who lapses in Fitbit use. Through a survey of 141 people who had lapsed in using Fitbit, we identified three use patterns and four perspectives on tracking. Participants then viewed seven visual representations of their Fitbit data and seven approaches to framing this data. Participant Fitbit use and perspective on tracking influenced their preference, which we surface in a series of contrasts. Specifically, our findings guide selecting appropriate aggregations from Fitbit use (e.g., aggregate more when someone has less data), choosing an appropriate framing technique from tracking perspective (e.g., ensure framing aligns with how the person feels about tracking), and creating appropriate social comparisons (e.g., portray the person positively compared to peers). We conclude by discussing how these contrasts suggest new designs and opportunities in other tracking domains.
随着时间的推移,人们会停止使用个人追踪工具,这被称为他们工具使用的阶段。我们探讨了在人们停止追踪时设计如何提供支持,考虑如何为停止使用Fitbit的人设计数据表示方式。通过对141名停止使用Fitbit的人进行调查,我们确定了三种使用模式和对追踪的四种看法。参与者随后查看了他们Fitbit数据的七种可视化表示以及构建这些数据的七种方法。参与者的Fitbit使用情况和对追踪的看法影响了他们的偏好,我们通过一系列对比揭示了这一点。具体而言,我们的研究结果指导从Fitbit使用中选择合适的汇总方式(例如,当某人数据较少时汇总更多),从追踪角度选择合适的构建技术(例如,确保构建方式与该人对追踪的感受一致),以及进行适当的社会比较(例如,与同龄人相比正面描绘该人)。我们通过讨论这些对比如何在其他追踪领域提出新的设计和机会来得出结论。