Pre-course student performance prediction with multi-instance multi-label learning

作     者：Yuling MA Chaoran CUI Xiushan NIE Gongping YANG Kashif SHAHEED Yilong YIN 

作者机构：Software College Shandong University School of Information Engineering Shandong Yingcai College School of Computer Science and Technology Shandong University of Finance and Economics 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2019年第62卷第2期

页      面：200-205页

核心收录：

学科分类：0401[教育学-教育学] 04[教育学] 0808[工学-电气工程] 08[工学] 040102[教育学-课程与教学论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 081202[工学-计算机软件与理论] 

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 61671274, 61573219, 61701281) Science and Technology Plan Project of Shandong Higher Education Institutions (Grant No. J15LN55) Shandong Provincial Natural Science Foundation (Grant No. ZR2017QF009) Fostering Project of Dominant Discipline and Talent Team of Shandong Province Higher Education Institutions China Postdoctoral Science Foundation (Grant No. 2016M592190) 

主　　题：KNN DT Pre-course student performance prediction with multi-instance multi-label learning SVM Figure BCS 

摘      要：Dear editor,Studying courses is one of the most basic and important tasks for college students. For each new course, the initial period of learning is crucial for students, and seriously influences subsequent learning activities. However, given a large number of classes in universities, it has become impossible for teachers to keep track of the individual performance of each student. In these circumstances, it is desirable to predict each student’s performance on a certain course prior to its commencement.