The Research and Practice of a Five-sided Educational Data Mining Framework

摘要：

　　In this paper,we design a five-sided educational data mining framework(5S-EDMF)to analyze college students diligence and effectiveness of study,and to recommend learning resource accordingly.We noticed data collected from students E-learning activities to reveal a lot about the attitudes and behaviors of students online as well as offline.This provides us an additional valuable tool to access and help students.We will present the 6-parameter prediction model: 5S-EDMF.We have field-tested our model.After analyzing the collected data,we concluded that our framework provides an effective learning environment; and our model is a good predictor for students performances.

关键词： Big data Educational data mining Support Vector Machine (SVM) Study evaluate Resource recommend Performance predict

作者: Ting Zeng

作者单位: School of EIE,Heyuan Polytechnic Heyuan,P.R.China(517000)

会议类型: 国际会议

会议名称: 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference(ITOEC2017)(2017 IEEE 第3届信息技术与机电一体化工程国际学术会议)

会议地点: 重庆

会议语种:英文

页码: 1050-1053

在线出版日期: 2017-10-03（万方平台首次上网日期，不代表论文的发表时间）