Many students persistently misinterpret histograms. This calls for closer inspection of students’ strategies when interpreting histograms and case-value plots (which look similar but are diferent). Using students’ gaze data, we ask: How and how well do upper secondary pre-university school students estimate and compare arithmetic means of histograms and case-value plots? We designed four item types: two requiring mean estimation and two requiring means comparison. Analysis of gaze data of 50 students (15–19 years old) solving these items was triangulated with data from cued recall. We found five strategies. Two hypothesized most common strategies for estimating means were confirmed: a strategy associated with horizontal gazes and a strategy associated with vertical gazes. A third, new, count-and-compute strategy was found. Two more strategies emerged for comparing means that take specific features of the distribution into account. In about half of the histogram tasks, students used correct strategies. Surprisingly, when comparing two case-value plots, some students used distribution features that are only relevant for histograms, such as symmetry. As several incorrect strategies related to how and where the data and the distribution of these data are depicted in histograms, future interventions should aim at supporting students in understanding these concepts in histograms. A methodological advantage of eye-tracking data collection is that it reveals more details about students’ problem-solving processes than thinking-aloud protocols. We speculate that spatial gaze data can be re-used to substantiate ideas about the sensorimotor origin of learning mathematics.
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Background: Deceptive movements occur when an actor seeks to fake, hide or delay kinematic information about their true movement outcomes. The purpose of deceptive movements is to impair the perception of opponents (the ‘observer’) to gain an advantage over them. We argue though that a lack of conceptual clarity has led to confusion about what deception is and in understanding the different approaches by which an actor can deceive their opponent. The aim of this article is to outline a conceptual framework for understanding deceptive movements in sport. Main body: Adopting Interpersonal Deception Theory from the field of communication, we define deception as when an actor deliberately alters their actions in an attempt to impair the ability of an observer to anticipate their true action outcomes. Further, deception can be achieved either by what we define as deceit, the act of providing false information, or disguise, the act of concealing the action outcome. Skilled athletes often have actions that are difficult to anticipate, but an action is only classified as containing deception if the actor has explicit intent to deceive an observer. Having outlined the conceptual framework, we then review existing empirical findings on the skilled perception of deceptive movements considering the framework. This approach includes a critical evaluation of the mechanisms known to facilitate the perceptual ability to prevent being deceived, including a consideration of visual search strategies, confidence, the contribution of visual and motor experiences, and the influence of response biases and action capabilities on perceptual performance. Conclusion: The distinction between deceit and disguise particularly helps to show that most research has examined deceit, with little known about how an actor can more effectively disguise their action, or about how an observer can improve their ability to anticipate the outcome of disguised actions. The insights help to identify fruitful areas for future research and outline implications for skill acquisition and performance enhancement.
Introduction: Falling causes long term disability and can even lead to death. Most falls occur during gait. Therefore improving gait stability might be beneficial for people at risk of falling. Recently arm swing has been shown to influence gait stability. However at present it remains unknown which mode of arm swing creates the most stable gait. Aim: To examine how different modes of arm swing affect gait stability. Method: Ten healthy young male subjects volunteered for this study. All subjects walked with four different arm swing instructions at seven different gait speeds. The Xsens motion capture suit was used to capture gait kinematics. Basic gait parameters, variability and stability measures were calculated. Results: We found an increased stability in the medio-lateral direction with excessive arm swing in comparison to normal arm swing at all gait speeds. Moreover, excessive arm swing increased stability in the anterior–posterior and vertical direction at low gait speeds. Ipsilateral and inphase arm swing did not differ compared to a normal arm swing. Discussion: Excessive arm swing is a promising gait manipulation to improve local dynamic stability. For excessive arm swing in the ML direction there appears to be converging evidence. The effect of excessive arm swing on more clinically relevant groups like the more fall prone elderly or stroke survivors is worth further investigating. Conclusion: Excessive arm swing significantly increases local dynamic stability of human gait.