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Evaluation of students' achievements based on factor analysis and cluster analysis

机译:基于因子分析和聚类分析的学生成绩评估

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Evaluating students' achievements which including many subjects is a great challenge. It seems not so accurate that simply adding these scores and ranking, because it is difficult to distinguish which one is a student good at and which one is not. Data mining is a good way to solve this problem. In this paper, students' achievements are appraised based on factor analysis and cluster analysis. First, common factors are extracted from scores of multitudinous subjects. Then factor scores and comprehensive scores can be computed. After that, all students can be segregated into several clusters by cluster analysis based on factor scores. The result shows objective synthetical evaluation of students, which will benefit education in the future.
机译:评估包括许多学科在内的学生的成就是一个巨大的挑战。仅仅将这些分数和排名相加似乎并不那么准确,因为很难区分哪个是学生擅长的,哪个不是学生擅长的。数据挖掘是解决此问题的好方法。本文基于因子分析和聚类分析对学生的成绩进行评估。首先,从众多主题的分数中提取公共因素。然后可以计算因子得分和综合得分。之后,可以基于因子得分通过聚类分析将所有学生分为几个聚类。结果表明,对学生进行客观的综合评价,将有利于今后的教育。

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