数据挖掘决策树技术在高职教学质量评价中的应用  

Application of Decision Tree Technology in Data Mining in Quality Evaluation of Higher Vocational Education

作　　者：卜阳 BU Yang(Jiangsu Union Vocational and Technical College Xuzhou Pharmaceutical Branch,Xuzhou Jiangsu 211116,China)

机构地区：[1]江苏联合职业技术学院徐州医药分院,江苏徐州221116

出　　处：《湖北开放职业学院学报》2018年第21期32-34,共3页Journal of Hubei Open Vocational College

基　　金：2016年度江苏联合职业技术学院立项课题"基于数据挖掘的五年制高职教学质量监督与评价信息化平台开发研究"(项目编号:B/2016/13/033)

摘　　要：本文基于高职教学的特点,利用学生考试成绩、教学质量调查表等各类属性通过数据挖掘的决策树技术进行特征分类。以杂乱无序的数据为根本,由决策树结构建立教学质量评价的分类模型。决策树的若干节点与各个教学质量属性相对应,其分支表示各个属性的取值判断,通过分类结果用以学校的教学质量评价。In this paper, based on the characteristics of vocational school teaching, all kinds of attributes, such as student test scores and teaching quality questionnaires, are used to classify various characteristics through the Decision Tree Technology of data mining. We apply Decision Tree to analyze random data to show the rules of classification of teaching quality. Each node represents one attribute of the teaching quality; every branch stands for its value of the attribute. Then we apply the result to assess the teaching quality of the vocational schools.

关 键 词：数据挖掘技术 决策树算法 教学质量评价 

分 类 号：G640[文化科学—高等教育学]