基于数据挖掘的成绩相关性实证分析  

Empirical Analysis of Grade Correlation Based on Data Mining

作　　者：吴飞青[1] 吴成玉[1] 方伟[1] 孙炯[1] 王媛媛[1] WU Fei-qing;WU Cheng-yu;FANG Wei;SUN Jiong;WANG Yuan-yuan(Ningbo Institute of Technology Zhejiang University,Ningbo 315000,China)

机构地区：[1]浙江大学宁波理工学院

出　　处：《电气电子教学学报》2019年第4期1-3,13,共4页Journal of Electrical and Electronic Education

基　　金：宁波市教育规划重点课题《面向工程教育认证的电路原理课程教学改革及示范》(2018YZD012);国家级大学生创新创业训练计划项目(201813022009)

摘　　要：高校人才培养方案中,课程设置非常重要,课程结构合理性直接影响到人才培养的质量。合理科学地设置电类基础课程是一个非常复杂的问题。本文使用数据挖掘分析方法,以某一专业的学生学习成绩为研究对象,挖掘出电类基础课对其专业课的支撑作用,为教学管理、课程设置及学时安排提供支持与参考。In the talent training program of universities,the curriculum is very important,and whether the curriculum structure is reasonable will directly affect the quality of talent training.Reasonable scientific setting of the basic course of electricity is a very complicated problem.This paper uses the data mining analysis method to study the academic performance of one major,and explores the supporting role of the basic class of power generation for its professional courses,and provides decision information support and reference for teaching management,curriculum setting and time schedule.

关 键 词：APRIORI算法 关联规则 相关性分析 

分 类 号：TM15[电气工程—电工理论与新技术]