Visual task solution strategies in tree diagrams

Abstract

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 ana lysis 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

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“…In a traditional eye-tracking study, subjects perform visual tasks while their eyes are monitored by an eye-tracker. For example, researchers studied how people recognize faces [18], how students learn from graphical content [19], or how people interpret graph visualizations [20], [21] and tree-drawings [22]. The breadth and scope of eye tracking research is growing as eye-trackers become increasingly accurate, fast, and affordable [23].…”

Exploring the limits of complexity: A survey of empirical studies on graph visualisation

“…Six studies use only Topology-based tasks when using graphs with 500 nodes or more [26,27,95,99,136]. The first three studies [26,27,95] use graphs with a simpler structure, i.e. trees.…”

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