XiaoMu: an AI-driven assistant for MOOCs

被引：1

作者：

Zhengyang SONG ^{[1
]}

Jie TANG ^{[2
]}

Tracy Xiao LIU ^{[3
]}

Wenjiang ZHENG ^{[4
]}

Lili WU ^{[4
]}

Wenzheng FENG ^{[2
]}

Jing ZHANG ^{[5
]}

机构：

[1] Institute for Interdisciplinary Information Sciences,Tsinghua University

[2] Department of Computer Science and Technology,Tsinghua University

[3] School of Economics and Management,Tsinghua University

[4] Center for Strategic Studies,Chinese Academy of Engineering

[5] Information School,Renmin University of China

来源：

Science China(Information Sciences) | 2021年 / 64卷 / 06期

关键词：

D O I：

暂无

中图分类号：

G434 [计算机化教学]; TP393.092 [];

学科分类号：

040110 ; 080402 ;

摘要：

<正>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.

引用

页码：222 / 224

页数：3

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