摘要
本文基于某学院教务系统中关于大学生英语四级成绩的相关数据,利用数据挖掘技术对其进行了挖掘研究。通过决策树技术建立了成绩预测模型并对其进行了剪枝,然后提取分类规则。对性别、专业、成绩等多个因素进行了详细分析,得到了各个因素对四级成绩的影响,并提出了针对性意见。通过数据测试验证了该模型剪枝后的准确率高达86.32%。该模型可以为教学管理和英语课程设计提供理论依据,有助于提高全体学生的英语水平。
Based on the relevant data of college students'English test scores in the academic affairs system of a certain college,this paper uses data mining technology to study it.A performance prediction model is established and pruned using decision tree technology,and then classification rules are extracted.The factors such as gender,specialty,and performance of different attributes were analyzed in detail,and the influence of each factor on the grade 4 performance was obtained,and targeted opinions were put forward.The data test verifies that the accuracy of the model after pruning is as high as 86.32%.This model can provide theoretical basis for teaching management and English course design,and help improve the English level of all students.
作者
梁玮
Liang Wei(Public basic teaching department,Zhaoqing Medical College,Guangdong Zhaoqing,526020,China)
出处
《现代科学仪器》
2019年第6期138-140,150,共4页
Modern Scientific Instruments
基金
广东省高职教育医药卫生专业教学指导委员会教育教学改革课题项目中高职英语课程衔接与网络教学平台建设(项目编号:20171035)。
