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在大规模开放式网络课程,采用隐马尔可夫模型预测学生保留

Predicting Student Retention in Massive Open Online Courses using Hidden Markov Models
作者:Girish Balakrishnan 作者单位:Electrical Engineering and Computer Sciences 加工时间:2013-11-07 信息来源:EECS 索取原文[12 页]
关键词:隐马尔科夫模型;预测;学生保留;
摘 要:A Massive Open Online Course (MOOC) is a large-scale web-based course that is offered to a very large number of participants. In the last few years, MOOCs have seen an increase in popularity due to the emergence of several well-designed online-education websites, such as edX and Coursera, and rising interest from top universities, such as MIT, Stanford and UC Berkeley, to open a variety of their courses to the wider public. The appeal for end consumers lies in the accessibility of high-quality education from any location regardless of personal background. MOOCs typically contain short lecture videos (10-15 minutes), as well as quizzes and homework assignments to assess students’ understanding of subject matter.
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