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Assessing demand for intelligibility in context-aware applications

机译:评估上下文感知应用程序中的清晰度要求

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Intelligibility can help expose the inner workings and inputs of context-aware applications that tend to be opaque to users due to their implicit sensing and actions. However, users may not be interested in all the information that the applications can produce. Using scenarios of four real-world applications that span the design space of context-aware computing, we conducted two experiments to discover what information users are interested in. In the first experiment, we elicit types of information demands that users have and under what moderating circumstances they have them. In the second experiment, we verify the findings by soliciting users about which types they would want to know and establish whether receiving such information would satisfy them. We discuss why users demand certain types of information, and provide design implications on how to provide different intelligibility types to make context-aware applications intelligible and acceptable to users.
机译:可理解性可以帮助揭示上下文感知应用程序的内部工作和输入,这些应用程序由于隐含的感知和动作而对用户而言是不透明的。但是,用户可能对应用程序可以产生的所有信息不感兴趣。使用跨越上下文感知计算的设计空间的四个实际应用程序的场景,我们进行了两个实验,以发现用户感兴趣的信息。在第一个实验中,我们得出用户具有的信息需求类型以及在何种条件下进行调节他们有他们的情况。在第二个实验中,我们通过向用户征询他们想知道的类型并确定接收此类信息是否可以使他们满意来验证发现。我们讨论了为什么用户需要某些类型的信息,并就如何提供不同的可理解性类型以使上下文感知的应用程序可被用户理解和接受提供了设计方面的含义。

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