基于离群数据挖掘技术的高校学生学业预警研究  

Research of Academic Precaution of College Students Based on Outlier Data Mining Technology

作　　者：田文祥 Tian Wenxiang(School of Management, Hefei University of Technology, Hefei 230009, China)

机构地区：[1]合肥工业大学管理学院,合肥230009

出　　处：《黑龙江科学》2021年第7期54-56,共3页Heilongjiang Science

基　　金：合肥工业大学大学生思想政治教育工作创新实践专项(JS2017HGXJ0070)。

摘　　要：以合肥工业大学管理学院会计学专业学生学年度文化课成绩为样本,基于离群数据挖掘技术对高校学生学业数据进行处理,通过Rapidminer软件对预处理后的数据进行数据聚类,结果表明学业预警模型具有可行性,学业预警系统不局限于学业成绩,学业预警模型能够进行科学研判。构建基于离群数据挖掘技术的高校学生学业预警,能够提升教育教学质量,为高校学生学业教育管理服务过程提供参考依据,提升高校学生教育管理的服务功效和针对性。The search takes cultural course examination results of students of accounting specialty in School of Management,Hefei University of Technology as the research sample.Based on outlier data mining technology,the research handles the academic data in college students,data cluster is done after preprocessing through Rapidminer software.The results show that academic precaution model is feasible,academic precaution doesn’t limit in academic results,and the academic precaution model can study and judge science.Academic precaution of college students based on outlier mining technology can promote education teaching quality,provide reference for academic education management service of college students,and improve the service function and target of education management of college students.

关 键 词：离群数据挖掘 学业预警 建模 数据分析 

分 类 号：G647[文化科学—高等教育学] TP311.13[文化科学—教育学]