Understanding Student Behaviors in Online Classroom: Data Scientific Approach

机译：了解在线课堂中的学生行为：数据科学方法

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Students drop classes for many reasons. Some are personal such as medical conditions, family issues, or financial difficulties. Others are course specific such as course contents, instructor, or classmates. In either way, class drop is a serious problem to institutions because without students there will be no students learning. As a first step to understand students drops, this study will address the issue of students' behaviors in online classrooms.

机译：学生辍学的原因很多。有些是个人的，例如医疗状况，家庭问题或经济困难。其他的则是特定于课程的，例如课程内容，讲师或同学。无论哪种方式，辍学对于机构来说都是一个严重的问题，因为没有学生，就不会有学生学习。作为了解学生下落的第一步，本研究将解决在线教室中学生行为的问题。

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《IEEE International Congress on Big Data》|2014年|802-803|共2页
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Byun Jongbok; Pennington Diane; Cardenas Jorge; Dutta Srabasti; Kirwan Jeral;
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Big data; Business; Communities; Educational institutions; Electronic mail; Neural networks; Big Data; Data Science; Online Education; Presence; Students Behavior;

机译：大数据;商业;社区;教育机构;电子邮件;神经网络;大数据;数据科学;在线教育;存在;学生行为;

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4. Understanding Student Behaviors in Online Classroom: Data Scientific Approach [C] . Byun Jongbok, Pennington Diane, Cardenas Jorge, IEEE International Congress on Big Data . 2014

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Understanding Student Behaviors in Online Classroom: Data Scientific Approach

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