Visual Analytics for MOOC Data

被引:33
|
作者
Qu, Huamin [1 ]
Chen, Qing [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China
关键词
Current practices - End users - Learning behavior - Massive open online course - Traditional educations - Visual analytics - Visual analytics systems;
D O I
10.1109/MCG.2015.137
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
With the rise of massive open online courses (MOOCs), tens of millions of learners can now enroll in more than 1,000 courses via MOOC platforms such as Coursera and edX. As a result, a huge amount of data has been collected. Compared with traditional education records, the data from MOOCs has much finer granularity and also contains new pieces of information. It is the first time in history that such comprehensive data related to learning behavior has become available for analysis. What roles can visual analytics play in this MOOC movement? The authors survey the current practice and argue that MOOCs provide an opportunity for visualization researchers and that visual analytics systems for MOOCs can benefit a range of end users such as course instructors, education researchers, students, university administrators, and MOOC providers. © 1981-2012 IEEE.
引用
收藏
页码:69 / 75
页数:7
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