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首页> 外文期刊>International journal of human-computer studies >Fitbit for learning: Towards capturing the learning experience using wearable sensing
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Fitbit for learning: Towards capturing the learning experience using wearable sensing

机译：用于学习的Fitbit：用于使用可穿戴传感来捕获学习体验

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摘要

The assessment of learning during class activities mostly relies on standardized questionnaires to evaluate the efficacy of the learning design elements. However, standardized questionnaires pose additional strain on students, do not provide "temporal" information during the learning experience, require considerable effort and language competence, and sometimes are not appropriate. To overcome these challenges, we propose using wearable devices, which allow for continuous and unobtrusive monitoring of physiological parameters during learning. In this paper we set out to quantify how well we can infer students' learning experience from wrist-worn devices capturing physiological data. We collected data from 31 students in 93 class sessions (3 class sessions per student), and our analysis shows that wrist data can predict the learning experience with 11% error. We also show that 6.25 min (SD = 3.1 min) of data are needed to achieve a reliable estimate (i.e., 13.8% error). Our work highlights the benefits and limitations of utilizing wearable devices to assess learning experiences. Our findings help shape the future of quantified-self technologies in learning by pointing out the substantial benefits of physiological sensing for self-monitoring, evaluation, and metacognitive reflection in learning.
机译：在课堂活动期间学习的评估主要依赖标准调查问卷来评估学习设计要素的疗效。但是，标准化问卷对学生造成额外的压力，在学习经验期间不提供“颞态”信息，需要相当大的努力和语言能力，有时是不合适的。为了克服这些挑战，我们建议使用可穿戴设备，其在学习期间允许对生理参数的连续和不引人注目的监测。在本文中，我们旨在量化我们如何从捕获生理数据的腕带设备推断学生的学习经验。我们在93级课程中收集了31名学生的数据（每个学生的3个课程），我们的分析表明，手腕数据可以预测11％错误的学习体验。我们还表明，需要6.25分钟（SD = 3.1分钟）数据来实现可靠的估计（即13.8％错误）。我们的工作突出了利用可穿戴设备来评估学习经验的好处和限制。我们的研究结果通过指出生理感官对学习中的自我监测，评估和元认知反思的实质性好处来说，在学习中塑造了量化的自我技术的未来。

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