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Mining learning behavioral patterns of students by sequence analysis in cloud classroom

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成果类型:
期刊论文
作者:
Sanya Liu;Zhenfan Hu;Xian Peng;Zhi Liu;Hercy N. H. Cheng;...
作者机构:
[Jianwen Sun; Sanya Liu; Zhenfan Hu; Xian Peng; Zhi Liu; Hercy N. H. Cheng] National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China
语种:
英文
关键词:
Curricula;E-learning;Education;Teaching;Behavioral patterns;Conceptual frameworks;Learning Analytics;Learning behavior;Massive open online course;Online learning;Sequence analysis;Sequential analysis;Students
期刊:
International Journal of Distance Education Technologies
ISSN:
1539-3100
年:
2017
卷:
15
期:
1
页码:
15-27
机构署名:
本校为第一机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
In a MOOC environment, each student's interaction with the course content is a crucial clue for learning analytics, which offers an opportunity to record learner activity of unprecedented scale. In online learning, the educators and the administrators need to get informed with students' learning states since the performance of unsupervised learning style is difficult to control. Learning analytics considered as a key process is to provide students and educators with evidence-based, analytical and contextual outcomes in a way of making sense of their learning engagements. In this conceptual fra...

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