XiaoMu: an AI-driven assistant for MOOCs

作     者：Zhengyang SONG Jie TANG Tracy Xiao LIU Wenjiang ZHENG Lili WU Wenzheng FENG Jing ZHANG Zhengyang SONG;Jie TANG;Tracy Xiao LIU;Wenjiang ZHENG;Lili WU;Wenzheng FENG;Jing ZHANG

作者机构：Institute for Interdisciplinary Information SciencesTsinghua University Department of Computer Science and TechnologyTsinghua University School of Economics and ManagementTsinghua University Center for Strategic StudiesChinese Academy of Engineering Information SchoolRenmin University of China 

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

年 卷 期：2021年第64卷第6期

页      面：222-224页

核心收录：

学科分类：0810[工学-信息与通信工程] 0401[教育学-教育学] 04[教育学] 0808[工学-电气工程] 08[工学] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 040110[教育学-教育技术学（可授教育学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Key Research and Development Program of China (Grant No. 2018YFB1004503) National Natural Science Foundation of China (Grant No. 61702522) 

主　　题：MOOCs Concept Extraction Question Answering Course Recommendation Video Navigation 

摘      要：Nowadays, massive open online courses(MOOCs), are attracting widespread interest as an alternative education model. Several MOOCs platforms, such as Coursera, edX,and Udacity have been built and they provide low-cost opportunities for anyone who needs to access a massive number of courses from the worldwide top universities. However, the learning completion rate of the learners via MOOCs is extremely low compared with that in real classroom learning.Thus, this study builds a system, called XiaoMu, to design intelligent intervention strategies for the learning process of learners and improve the learning efficiency through automatic analysis of courses and learners. We deployed our system on the website1), which is one of the largest MOOCs in China.