Abstract
The complex interplay between gaze tracker accuracy and interface design is the focus of this paper. Two slightly different variants of GazeTalk, a hierarchical typing interface, were contrasted with a novel interface, Dasher, in which text entry is done by continuous navigation. All of the interfaces were tested with a good and a deliberate bad calibration of the tracker. The purpose was to investigate, if performance indices normally used for evaluation of typing systems, such as characters per minute (CPM) and error-rate, could differentiate between the conditions, and thus guide an iterative system development of both trackers and interfaces. Gaze typing with one version of the static, hierarchical menu systems was slightly faster than the others. Error measures, in terms of rate of backspacing, were also significantly different for the systems, while the deliberate bad tracker calibrations did not have any measurable effect. Learning effects were evident under all conditions. Power-law-of-practice learning models suggested that Dasher might be more efficient than GazeTalk in the long run.
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