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Student profiling to improve teaching and learning: A data mining approach

机译:学生配置文件以提高教学质量:一种数据挖掘方法

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Data mining is a technology used in different disciplines to search for significant relationships among variables in large data sets. In this paper, we concentrate on the application of data mining in an educational environment. This study can be used to help teachers to classify students' academic success, along with their determination measured by a grit test, and thus modify their teaching for different groups of students. According to this classification, one can arrange remedial classes or extra tests for the required students. Also students can monitor their growth from semester to semester with the help of the application made.
机译:数据挖掘是一项在不同学科中用于搜索大型数据集中变量之间的重要关系的技术。在本文中,我们专注于数据挖掘在教育环境中的应用。这项研究可用于帮助教师对学生的学业成绩进行分类,并通过沙砾测试来衡量他们的决心,从而改变他们对不同学生群体的教学方式。根据这种分类,可以为所需的学生安排补习班或额外的考试。学生还可以借助所提交的应用程序监控每个学期的成长情况。

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