基于教育数据挖掘的大学生大学英语四级考试成绩分析

Ruixuan Ji
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引用次数: 0

摘要

高校管理系统中积累了大量的数据,这些数据中隐藏的信息没有得到充分的挖掘和应用。在教育研究中使用数据挖掘技术有助于从数据中提取出许多有价值的模式。本文的目的是利用支持向量机分析学生的大学英语四级考试总分与各部分考试成绩之间的线性关系。e (SVM)对学生在各部分的四级成绩进行分类。本研究采用问卷调查的方式收集数据,并利用SPSS软件进行分析。结果显示,影响英语四级成绩的主要因素是以前的英语学习经历、对考试的态度和每天学习英语的时间。关键词:大学英语四级成绩;教育数据挖掘;支持向量机分类;影响因素
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing students’ college english test-band 4(CET-4) scores based on educational data mining
There is a large amount of data accumulated in management systems in universities and information hidden in these large amounts of data is not fully tapped and applied. Using data mining techniques in education research can help in the extraction of many valuable patterns from the data. The purpose of this article is to analyze the linear relation between the students’ total score of College English Test-Band 4 (CET-4) and scores in each part of the test, using Support vector machin.e (SVM) to classify students' CET-4 performance in each part. The research collected data with questionnaires and analysis was carried out with the help of SPSS. The result showed that the main factors that affect the CET-4 results are previous experience of learning English, attitudes toward the test and time spent on learning English per day.   Keywords: CET-4 score; Educational data mining; SVM classification; Influence factors
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