The growing use of tablet-based applications in education increases the importance of testing them in an effective way. Eye tracking devices can now be used to serve this purpose, but these evaluations require valid ecological testing contexts that can affect data quality and validity. The focus of this paper is to propose setup guidelines that will maximize data quality and validity by optimizing the trade-off between steadiness of the visual attention data and natural interaction of the child with a digital educational product. The guidelines are based on three different eye tracking educational studies conducted with children participants.
While most traditional user experience (UX) evaluation methods (e.g., questionnaires) have made the transition to the "wild", physiological measurements still strongly rely upon controlled lab settings. As part of an ongoing research agenda, this paper presents a novel approach for UX research which contributes to this transition. The proposed method triangulates GPS and physiological data to create emotional maps, which outline geographical areas where users experienced specific emotional states in outdoor environments. The method is implemented as a small portable recording device, and a data visualization software. A field study was conducted in an amusement park to test the proposed approach. Emotional maps highlighting the areas where users experienced varying levels of arousal are presented. We also discuss insights uncovered, and how UX practitioners could use the approach to bring their own research into the wild.
In this paper, we present an off-the-shelf UX evaluation tool which contextualizes users' physiological and behavioral signals while interacting with a system. The proposed tool triangulates users' gaze data with inferred users' cognitive and emotional states to produce user experience (UX) heatmaps, which show where users were looking when they experienced specific cognitive and emotional states. Results show that for a given cognitive state (i.e., cognitive load), the proposed UX heatmap was able to effectively highlight the areas where users experienced different levels of cognitive load on an interface. The proposed tool enables the visual analysis of users' various emotional and cognitive states for specific areas on a given interface, and also to compare users' states across multiple interfaces, which should be useful for both UX researchers and practitioners.
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