摘要
职业教育是我国教育改革与发展的重点之一,教学管理是提升高职院校教学质量的关键环节。为了提高高职院校教学质量和教学水平,应用大数据挖掘技术对教学数据进行分析。首先采用Apriori算法对学生成绩表、课堂考勤表进行数据处理,然后挖掘隐藏在学习成绩和考勤数据中的规律,分析各学期不及格科目、出勤情况与毕业状态之间的关联规则。通过结果分析与评估,为任课教师和教学管理部门提供指导,帮助科学规划各学期教学管理重点,进一步改进教学管理水平,提高教学质量。
Vocational education is one of the key points of educational reform and development in China.Teaching management is the key link to improve the teaching quality in higher vocational colleges.In order to improve teaching quality and teaching level of higher vocational colleges,this paper adopts big data mining technology to analyze teaching data.Firstly,it adopts the Apriori algorithm to deal with the students＇ scores and the attendance tables.Then,by excavating the laws hidden in the academic achievement and attendance data,we analyse the association rules among the failed subjects,attendance rates and the states of graduation.Through analysis and evaluation results,it can provide guidance for teachers and teaching management staff,and help to make scientific planning of the priorities of teaching management in every semester,and further improve the levels of teaching management and teaching quality.
作者
米保全
MI Bao-quan 1(Gansu Institute of Mechanical ＆ Electrical Engineering,Tianshui 741001,Chin)
出处
《软件导刊》
2018年第8期178-181,共4页
Software Guide
基金
甘肃省自然科学基金项目(1610RJZE132)
关键词
高职院校
数据挖掘
关联规则
APRIORI算法
教学管理
higher vocational colleges
data mining
association rules
Apriori algorithm
teaching management
