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Visual task solution strategies in tree diagrams

机译:树状图中的可视任务解决方案策略

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We investigate visual task solution strategies when exploring traditional, orthogonal, and radial node-link tree layouts, four orientations of the non-radial layouts, as well as varying difficulty of the task. The strategies are identified by examining eye movement data recorded in a controlled user study previously conducted by Burch et al. For detailed analysis of the spatio-temporal structures and patterns in the eye tracking data, we employ visual analytics techniques adopted from related methodology for geographic movement data by Andrienko et al. In this way, we complement the statistical analysis of task completion times and error rates reported by Burch et al. with spatio-temporal strategies that explain the variation in completion times. We identify differences between task solution strategies dependent on layout type, orientation, and task difficulty. Furthermore, we examine differences between groups of participants split according to completion time. Our analysis identifies that for all layouts it took nearly the same time to find the task solution node, but in the radial layout the solution was not confirmed directly. Instead, a more frequent cross-checking occurs afterwards, which is the main reason for the impaired performance of radial layouts.
机译:我们在探索传统的,正交的和径向的节点链接树布局,非径向布局的四个方向以及变化的任务难度时,研究视觉任务解决方案策略。这些策略是通过检查Burch等人先前进行的受控用户研究中记录的眼动数据来确定的。为了详细分析眼动数据中的时空结构和模式,我们采用了由Andrienko等人从相关方法学中获取的地理分析数据的视觉分析技术。这样,我们补充了Burch等人报告的任务完成时间和错误率的统计分析。时空策略可以解释完成时间的变化。我们根据布局类型,方向和任务难度来确定任务解决方案策略之间的差异。此外,我们研究了根据完成时间划分的参与者组之间的差异。我们的分析表明,对于所有布局,几乎都需要花费相同的时间来找到任务解决方案节点,但是在径向布局中,并未直接确定解决方案。相反,此后会发生更频繁的交叉检查,这是径向布局性能受损的主要原因。

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