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Prediction of Factors Associated with the Dropout Rates of Primary to High School Students in India Using Data Mining Tools

机译:利用数据挖掘工具预测印度初级至高中生辍学率的因素

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Recent years have revealed an increasing attention and interest in various countries about the problem of dropout of the students in the school and to find out its chief contributing factors. In our model, we attempt to demonstrate how a specific factor can affect students' academic life, which subsequently produces dropout among school students. In this paper, we propose a methodology and a specific clustering algorithm to identify the factors that results in dropout among the students at different educational levels, such as primary, secondary, and higher secondary and also their percentage of impact among the students. This research will guide the teachers and school administration to improve this dropout scenario of their school. A solution to this problem can be resolved with the use of educational data mining (EDM).
机译:近年来揭示了各国越来越多的关注和兴趣,了解学校的学生辍学问题,并找出其主要贡献因素。在我们的模型中,我们试图展示特定因素如何影响学生的学术生活,随后在学校学生之间产生辍学。在本文中,我们提出了一种方法论和特定的聚类算法,以确定在不同教育水平的学生中产生辍学的因素,例如小学,中学和更高的中学以及学生之间的影响的百分比。该研究将指导教师和学校管理局改善学校的这种辍学情景。通过使用教育数据挖掘(EDM)可以解决对此问题的解决方案。

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