面向移动设备的专注、双向MOOC学习

Xiang Xiao, Jingtao Wang
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引用次数: 30

摘要

AttentiveLearner是一个移动学习系统,针对大规模开放在线课程(MOOCs)和翻转课堂的讲座视频进行了优化。AttentiveLearner通过实时分析学习者指尖透明度的变化,将移动设备的内置摄像头转换为有形的视频控制通道和隐式心率感知通道。在本文中,我们报告了严谨的研究工作,使AttentiveLearner在现实世界中真正实用。通过两项18人参与的用户研究和跟踪分析,我们发现1)有形的视频控制界面使用直观,操作高效;2)由AttentiveLearner隐式捕获的心率信号可以用来推断学习者对相应学习主题的兴趣和感知困惑程度;3) AttentiveLearner通过预测极端的个人学习事件和聚合学习事件,可以获得显著更高的准确率。
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Towards Attentive, Bi-directional MOOC Learning on Mobile Devices
AttentiveLearner is a mobile learning system optimized for consuming lecture videos in Massive Open Online Courses (MOOCs) and flipped classrooms. AttentiveLearner converts the built-in camera of mobile devices into both a tangible video control channel and an implicit heart rate sensing channel by analyzing the learner's fingertip transparency changes in real time. In this paper, we report disciplined research efforts in making AttentiveLearner truly practical in real-world use. Through two 18-participant user studies and follow-up analyses, we found that 1) the tangible video control interface is intuitive to use and efficient to operate; 2) heart rate signals implicitly captured by AttentiveLearner can be used to infer both the learner's interests and perceived confusion levels towards the corresponding learning topics; 3) AttentiveLearner can achieve significantly higher accuracy by predicting extreme personal learning events and aggregated learning events.
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