Technology is gradually being incorporated as an integral part of education. This technology includes the now pervasive presence of the Internet, but also the inclusion of devices that are worn by teachers and learners. Wearable devices have greatly facilitated data acquisition of educational subjects. This article provides an overview of what and how wearable devices have been used in education and in what contexts. Summaries of existing research in this area are organized according to a three-layered data framework. We begin by presenting the technical characteristics of four types of wearable devices, and comparing the data from them with physiological data and behavioral data. Based on this, the preprocessing and analysis methods of these two types of data are discussed. Following that, we identified the six main applications that wearables and data analytics are enabling education. Furthermore, three key challenges of using wearable devices have been identified. We suggest that future research should be enriched from equipment innovation, application scenarios, and feedback methods in order to make wearable devices more widely used in a production environment, and augment the analysis performed to improve teaching, learning, or the educational context where it occurs.

中文翻译：

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针对教育应用的可穿戴计算的系统调查


技术正逐渐成为教育不可或缺的一部分。这项技术包括现在无处不在的互联网，也包括教师和学习者佩戴的设备。可穿戴设备极大地方便了教育科目的数据获取。本文概述了可穿戴设备在教育中的应用内容、方式以及应用场景。该领域现有研究的总结是根据三层数据框架组织的。我们首先介绍四种可穿戴设备的技术特征，并将其数据与生理数据和行为数据进行比较。在此基础上，讨论了这两类数据的预处理和分析方法。接下来，我们确定了可穿戴设备和数据分析为教育提供支持的六个主要应用。此外，还确定了使用可穿戴设备的三个关键挑战。我们建议未来的研究应从设备创新、应用场景和反馈方式等方面进行丰富，以使可穿戴设备在生产环境中得到更广泛的应用，并增强分析以改善教学、学习或教育环境。 。