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首页> 外文期刊>British Journal of Educational Technology >Using text mining to uncover students' technology-related problems in live video streaming
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Using text mining to uncover students' technology-related problems in live video streaming

机译:使用文本挖掘在实时视频流中发现学生的技术相关问题

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摘要

Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to improve their learning experience, we applied text mining to data culled from LVS interactions. Our findings revealed low LVS student participation, which triggered us to initiate several actions to promote more active student participation. Our findings support previous studies regarding the effectiveness of data mining in transforming raw educational data into knowledge and decision-making tools.
机译:由于能够筛选大量数据,文本挖掘和数据挖掘使高等教育机构无需借助传统的调查方法即可揭示学生学习行为中的宝贵模式。为了发现实时视频流(LVS)学生的技术相关问题并改善他们的学习体验,我们将文本挖掘应用于从LVS交互中挑选的数据。我们的发现表明LVS学生参与度较低,这促使我们采取了一些行动来促进学生更加积极地参与。我们的发现支持先前关于数据挖掘在将原始教育数据转换为知识和决策工具方面的有效性的研究。

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