数据关联规则挖掘在高校试卷质量评价中的应用研究  

Application of Relevance Rule to Test Paper Quality Assessment in Colleges and Universities

作　　者：彭菊香[1] 何许腾[1] 刘向红[1] 

机构地区：[1]湖南工程学院,湖南湘潭411104

出　　处：《湖南工程学院学报（社会科学版）》2010年第2期110-112,共3页Journal of Hunan Institute of Engineering(Social Science Edition)

基　　金：湖南工程学院校级教改课题"数据关联规划挖掘在高校试卷质量评价中的研究与实践"(校教字[2008]34号)

摘　　要：关联规则挖掘是数据挖掘中最活跃的研究方法之一。以高校教务信息管理系统为应用背景对采用改进的Apriori算法成绩数据库进行分析,得出课程相关性规则,在此基础上建立试卷质量综合包含评价指标体系,为高校试卷质量评价提供科学依据。该评价体系使不同专业的学习效果具有综合可比性,突破以往单一的平均成绩进行评价的局限性。Relevance rule is one of the most active research methods in data mining. Taking information management system in colleges and universities as an example, the students＇ score is analyzed by the improved Apriori algo- rithm, by means of which a reasonable and reliable course relevance rule is obtained. Based on relevance rule, a comprehensive assessment system of test paper quality is established. This system can supply a comprehensive com- parison of the learning results for students in different majors. It breaks though the limitaions of the simple assessment in terms of the average performances and provides a scientific basis for the comprehensive assessment of teaching quality.

关 键 词：数据挖掘 关联规则 试卷分析 

分 类 号：G434[文化科学—教育学]