基于模糊关联规则的学生学业预警方法  

Early Warning Method of Students'Academic Performance Based on Fuzzy Association Rules

作　　者：苏锦 SU Jin(Guangxi Electrical Polytechnic Institute,Nanning Guangxi 530007)

机构地区：[1]广西电力职业技术学院,广西南宁530007

出　　处：《软件》2022年第7期27-29,共3页Software

基　　金：2021年广西高校中青年教师科研基础能力提升项目“基于数据挖掘的学生学业预警分析应用研究”阶段性研究成果(2021KY1325)。

摘　　要：由于影响学业的因素具有明显的复杂特征,导致对学业问题预测的准确性较低,为此,提出基于模糊关联规则的学生学业预警方法。利用Apriori算法对影响因素进行作用广度优先搜索,并设置了以支持度和置信度为基础的学业影响因素模糊关联规则,最终选定以课堂为主的出勤情况、未听课总时长、玩手机总时长、参与课堂互动频度,以及以课下为主的考试成绩、挂科数量、补考成绩、重修次数、重修成绩作为学生学业预警的主要参考因素,通过关联规则对其进行个性化赋权,并考虑因素动荡对学业发展的影响,引入了校正机制,结合影响因素的综合作用强度完成对学业的预警。测试结果表明,设计方法学业预警的准确率可以达到94.0%,具有较高可靠性。Due to the obvious complex characteristics of the factors affecting academic performance,the accuracy of academic problem prediction is low.Therefore,this paper puts forward an early warning method for students'academic performance based on fuzzy association rules.The Apriori algorithm is used to search the influencing factors first,and the fuzzy association rules of academic influencing factors based on support and confidence are set up.Finally,the attendance mainly in class,the total time of not attending classes,the total time of playing mobile phones,the frequency of participating in classroom interaction,and the test scores mainly after class,the number of failed subjects,the make-up test scores,the number of retakes and retakes are selected as the main reference factors for students'academic early warning.Individualized weight is given to them by association rules,and the influence of factors turbulence on academic development is considered.A correction mechanism is introduced,and the early warning of academic performance is completed by combining the comprehensive strength of influencing factors.The test results show that the accuracy of academic early warning of the design method can reach 94.0%,and it has high reliability.

关 键 词：模糊关联规则 学业预警 APRIORI算法 支持度 置信度 赋权 校正机制 

分 类 号：G434[文化科学—教育学]