基于因子分析和聚类分析的学生成绩评价

Yiwei Wu, Xiaoling Xia, Jiajing Le
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引用次数: 1

摘要

评估学生的成绩包括许多科目是一个巨大的挑战。简单地把这些分数和排名加起来似乎不那么准确,因为很难区分哪个学生擅长哪个学生不擅长。数据挖掘是解决这一问题的一个很好的方法。本文采用因子分析法和聚类分析法对学生的学习成绩进行评价。首先,从众多受试者的分数中提取共同因素。然后计算因子得分和综合得分。然后,通过基于因子得分的聚类分析,将所有学生分成若干类。结果对学生进行了客观的综合评价,有利于今后的教育工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of students' achievements based on factor analysis and cluster analysis
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.
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