摘要
高职院校教务管理系统长期运行中积累了大量的业务管理数据,同时也面临着有效信息缺乏的问题,未能实现对教学管理数据所隐藏的有价值信息进行分析、挖掘。关联规则技术运用到数据仓库中,对教务管理系统中的数据规则进行深入分析、挖掘,构建学生培养模型、成绩预警模型、教学质量评价模型。本文针对挖掘的数据结果进行分析,结合教务管理系统对其进行验证,从而为学校的教学管理提供决策支持,为提升教学质量管理服务。
The educational administration management system in higher vocational colleges has accumulated a large amount of business management data over a long period of time.At the same time,it also faces the problem of lack of effective information,which fails to realize the analysis and mining of the valuable information hidden in the teaching management data.Association rule technology is applied to data warehouse.Data in the administration management system were analyzed in depth.Rules in the educational administration data were excavated.Model of student training model,model of early warning of academic achievement,and model of teaching quality evaluation were constructed.In this paper,mining results were also analyzed and verified based on the educational administration management system.As a result,the mining results may be used to provide decision-making support for school teaching management and improve the management of teaching quality.
作者
张维国
ZHANG Weiguo(Dean’s Office of Nanjing Institute of Tourism&Hospitality,Nanjing,China,211100)
出处
《福建电脑》
2019年第9期33-38,共6页
Journal of Fujian Computer
基金
南京旅游职业学院科研课题“基于流程化管理的教务系统研究与应用”(No.kyc2019xky01)资助
关键词
关联规则
数据仓库
OLAP
数据挖掘
成绩预警
学生培养
Association Rules
Data Warehouse
OLAP
Data Mining
Early Warning of Academic Performance
Student Training
