一个生活的个人信息学的信息学模型
Daniel A Epstein1, An Ping2, James Fogarty1
1Computer Science & Engineering, DUB Group, University of Washington.
概括
本研究介绍了生活信息学,这是个人信息系统的新模型,超出了行为改变目标. 它探讨了个人如何在各种领域将自我跟踪整合到日常生活中.
科学领域:
- 人与计算机的交互
- 个人信息学个人信息学
- 行为科学 行为科学
背景情况:
- 现有的个人信息学模型主要集中在行为改变目标上.
- 这些模型不足以捕捉个人如何将自我跟踪整合到日常生活的各个方面.
- 需要一个新的视角来理解自我跟踪工具的更广泛的使用.
研究的目的:
- 提出一种基于"生活的信息学"概念的个人信息学的新型模型.
- 描述将自我跟踪纳入日常生活中的不同目标的个体.
- 确定个人信息学领域的挑战和未来研究方向.
主要方法:
- 调查了105,99和83个过去/现在的身体活动,财务和位置的追踪器.
- 与22名自我追踪者进行了采访,以探索生活中的信息学经验.
- 开发了一个基于调查和采访的经验数据的模型.
主要成果:
- 拟议的生活信息学模型详细介绍了决定跟踪,选择工具,收集数据,整合信息和反思跟踪数据的过程.
- 该模型包括跟踪和行动,以及失效和恢复跟踪的现象.
- 在生活信息学框架内确定了尚未探索的挑战.
结论:
- 生活信息学模型提供了比行为改变更全面的个人信息学使用的理解.
- 该框架强调了自我跟踪的动态性质,包括启动,继续和停止.
- 这些发现为设计更有效和以用户为中心的个人信息系统提供了宝贵的见解,并指导了未来的研究.
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