Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye-tracking research as an example, background information on eye-tracking and possible applications of eye-tracking in statistics education is provided. Teachers indicated that our eye-tracking research created awareness of the difficulties students have when interpreting histograms. Gaze data showed details of students' strategies that neither teachers nor students were aware of. With this discussion paper, we hope to contribute to the future usage and implementation of gaze data in statistics education by teachers, researchers, educational and textbook designers, and students.
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Graphs are ubiquitous. Many graphs, including histograms, bar charts, and stacked dotplots, have proven tricky to interpret. Students’ gaze data can indicate students’ interpretation strategies on these graphs. We therefore explore the question: In what way can machine learning quantify differences in students’ gaze data when interpreting two near-identical histograms with graph tasks in between? Our work provides evidence that using machine learning in conjunction with gaze data can provide insight into how students analyze and interpret graphs. This approach also sheds light on the ways in which students may better understand a graph after first being presented with other graph types, including dotplots. We conclude with a model that can accurately differentiate between the first and second time a student solved near-identical histogram tasks.
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In this study, we examined the effects of a defender contesting jump shots on performance and gaze behaviors of basketball players taking jump shots. Thirteen skilled youth basketball players performed 48 shots from about 5 m from the basket; 24 uncontested and 24 contested. The participants wore mobile eye tracking glasses to measure their gaze behavior. As expected, an approaching defender trying to contest the shot led to significant changes in movement execution and gaze behavior including shorter shot execution time, longer jump time, longer ball flight time, later final fixation onset, and longer fixation on the defender. Overall, no effects were found for shooting accuracy. However, the effects on shot accuracy were not similar for all participants: six participants showed worse performance and six participants showed better performance in the contested compared to the uncontested condition. These changes in performance were accompanied by differences in gaze behavior. The participants with worse performance showed shorter absolute and relative final fixation duration and a tendency for an earlier final fixation offset in the contested condition compared to the uncontested condition, whereas gaze behavior of the participants with better performance for contested shots was relatively unaffected. The results confirm that a defender contesting the shot is a relevant constraint for basketball shooting suggesting that representative training designs should also include contested shots, and more generally other constraints that are representative of the actual performance setting such as time or mental pressure.
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The traffic safety of cyclists is under pressure. The number of fatalities and injuries is increasing, and the number of single-bicycle accidents is on the rise. However, from a traffic safety perspective, the most concerning trend is the growing number of incidents between motorized vehicles and cyclists. In addition to infrastructural solutions, such as more segregated and wider bike lanes, both industry and government are exploring technological developments to better safeguard cyclist safety. One of the technological solutions being considered is the use of C-V2X communication. C-V2X, Cellular Vehicle-to-X, is a technology that enables short-range signal exchanges between road users, informing them of each other's presence. C-V2X can be used, for example, to alert drivers via dedicated in-car information systems about the presence of cyclists on the road (e.g. at crossings). Although the technology and chipsets have been developed, the application of C-V2X to improve cyclist safety has not yet been thoroughly investigated. Therefore, HAN, Gazelle, and ARK Infomotives are researching the impact of C-V2X (on cyclist safety). Using advanced simulations with a digital twin in an urban environment and rural environment, the study will analyze how drivers respond to cyclist presence signals and determine the maximum penetration rate of ‘connected’ cyclists. Based on this, a pilot study will be conducted in a controlled environment on HAN terrain to validate the direction of the simulation results. The project aligns with the Missiegedreven Innovatiebeleid and the KIA Sleuteltechnologieën, specifically within application of digital and information technologies. This proposal aligns with the innovation domain of Semiconductor Technologies by applying advanced sensor and digital connectivity solutions to enhance cyclist safety. The project fits within the theme of Sleuteltechnologieën en Duurzame Materialen of the strategic research agenda of the VH by utilizing digital connectivity, sensor fusion, and data-driven decision-making for safer mobility solutions.
