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Using metrics and cluster analysis for analyzing learner video viewing behaviours in educational videos

机译:使用度量和群集分析分析教育视频中的学习者视频观看行为

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On line video is a powerful tool for e-learning and this is evident from a number of reports, research papers and university initiatives, which portray that online video is becoming an important medium for delivering educational content. Therefore, research that focuses on how students view educational videos becomes of particular interest and in previous work we argued that in order to efficiently analyze learner viewing behavior we should deploy tools that log the learner activity and assist usage analysis and data mining. Working towards this direction, a framework for recording and analyzing learner behavior was presented together with findings of applying the framework into educational settings. In this paper, we continue this work by presenting a set of metrics that can be derived from the framework and be used to measure learner engagement and video popularity. These metrics in conjunction with the data mining method of clustering are then used to gain insights into learner viewing behavior.
机译:在线视频是一个强大的电子学习工具,这可能是若干报告,研究论文和大学举措,这是在线视频正在成为提供教育内容的重要媒介。因此,重点关注学生查看教育视频的研究成为特别令人兴趣,并且在以前的工作中我们认为,为了有效地分析学习者观看行为,我们应该部署记录学习者活动的工具,并协助使用分析和数据挖掘。朝着这个方向努力,将录制和分析学习者行为的框架与将框架应用于教育环境的调查结果一起展示。在本文中,我们通过展示可以从框架中派生的一系列指标继续这项工作,并用于衡量学习者参与和视频人气。然后,这些度量与群集的数据挖掘方法一起用于获得学习者观看行为的见解。

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