Learning activities for/with children include rich interactions with peers, tutors, and learning materials (in digital or physical form). During such activities, children gain new knowledge and master their skills. Automatized and continuous monitoring of children's learning is a complex task, but, if efficient, can greatly enrich teaching and learning. Wearable devices, such as eye-tracking glasses, have the capacity to continuously and unobtrusively monitor children's interactions, and such interactions might be capable of predicting children's learning. In this article, we set out to quantify the extent to which children's gaze, captured with eye-tracking glasses, can predict their learning. To do so, we collected data from a case study with 44 children (8–17 years old) during a making-based coding activity. Our analysis shows that children's gaze can predict their learning with 15.79% error. Our results also identify the most important gaze measures with respect to children's learning, and pave the way for new research in this area.

中文翻译：

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通过可穿戴式眼动追踪监测儿童的学习：基于制作的编码活动案例

儿童/与儿童的学习活动包括与同龄人、导师和学习材料（数字或物理形式）的丰富互动。在这些活动中，孩子们获得新知识并掌握他们的技能。对儿童学习进行自动化和持续监控是一项复杂的任务，但如果有效，可以极大地丰富教学和学习。可穿戴设备，例如眼动追踪眼镜，能够持续且不显眼地监控儿童的互动，而这种互动可能能够预测儿童的学习情况。在本文中，我们着手量化使用眼动追踪眼镜捕捉到的儿童凝视可以预测他们学习的程度。为此，我们从 44 名儿童（8-17 岁）在基于制作的编码活动中收集的案例研究数据。我们的分析表明，儿童的凝视可以以 15.79% 的错误率预测他们的学习。我们的结果还确定了与儿童学习有关的最重要的凝视测量，并为该领域的新研究铺平了道路。