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Wandering minds, wandering mice: Computer mouse tracking as a method to detect mind wandering

机译:徘徊的头脑,徘徊老鼠:电脑鼠标跟踪作为一种检测心灵徘徊的方法

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Mind wandering is a state in which an individual's attention is decoupled from the task at hand. Mind wandering affects performance in many tasks requiring focused attention, including online learning. Previous studies have focused primarily on investigating mind wandering in contexts which are conducive to mind wandering, that is, for highly repetitive and monotonous tasks or during tasks with very low attentional demands. However, mind wandering also occurs during highly engaging and demanding tasks. In this study, we examine whether mouse tracking can be used to predict mind wandering in an engaging task involving classical computer interfaces. Assuming that mouse trajectories towards a particular response on the screen are continuously updated by time-dependent and temporally-dynamic cognitive processes, as a behavioral methodology, mouse tracking can provide unique insights into attentional processes. In our experiment, a total of 272 students completed a mouse-based operation span task, during which their thoughts were probed and their mouse movements recorded. Naive Bayes, Linear Discriminant Analyses, K-Nearest Neighbors, Tree Bag, and Random Forest classifiers were able to predict mind wandering with F1-scores of up to 15% above a random-chance baseline. The results show that hand reach movements can be tracked to detect mind wandering in a user-independent manner in online tasks, thus providing a viable alternative to self-report methods and (neuro)physiological measures. Our finding has relevant implications for a variety of user interfaces which require hand and finger movements for the purposes of human-computer interactions.
机译:心灵徘徊是一个人的注意力与手头的任务分离的国家。介意徘徊在许多需要集中注意力的任务中影响性能,包括在线学习。以前的研究主要集中在研究中的语境中的思绪,这是有利于介意徘徊的背景下,即高度重复和单调的任务或在非常低的注意力需求期间的任务中。然而,在高度吸引力和苛刻的任务中,介意也发生。在这项研究中,我们检查鼠标跟踪是否可用于预测涉及古典计算机接口的接合任务中的心灵徘徊。假设朝向屏幕上的特定响应的鼠标轨迹被时间依赖和时间动态认知过程连续更新,作为行为方法,鼠标跟踪可以提供对注意过程的独特洞察。在我们的实验中,共有272名学生完成了基于鼠标的操作跨度任务,在此期间探测其思想并记录了他们的鼠标运动。天真的贝叶斯,线性判别分析,K到最近的邻居,树袋和随机森林分类器能够预测心灵徘徊,F1分数高达15%以上的随机机会基线。结果表明,可以跟踪手达到移动以在在线任务中以用户独立的方式检测心灵徘徊,从而为自我报告方法和(神经)生理措施提供了可行的替代品。我们的发现对各种用户界面有相关的影响,这些用户界面需要用于人机交互的手指和手指运动。

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