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Educational data mining and learning analysis

机译:教育数据挖掘与学习分析

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摘要

These days' data mining is an emerging trend, which is presently used in different areas especially in student educational and learning analytics. It is very hard and time consuming to analyze data and finding the hidden information manually. To improvise educational data mining, clustering will be used in the paper. As we need to improvise performance as well as unambiguousness of obtained models. We have used 84 under-graduate student data and grouped students according to their final marks they achieved in the course and this we have done by using clustering approach. The result which we get shows that the clarity of specific model is much better than the general model and the unambiguousness of the model is also increase.
机译:这些日子挖掘是一种新兴趋势,目前在不同领域用于特别是在学生教育和学习分析中。分析数据并手动查找隐藏信息非常努力和耗时。为了即兴创作教育数据挖掘,将在论文中使用聚类。由于我们需要即使所获得的模型的表现和明确的效果。根据他们在课程中实现的最终标记,我们使用了84名课外学生数据和分组的学生,我们通过使用聚类方法完成了这一点。我们得到的结果表明,特定模型的清晰度比一般模型要好得多,模型的明确性也增加。

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