Title :
Understanding Student Behaviors in Online Classroom: Data Scientific Approach
Author :
Byun, Jinsung ; Pennington, Diane ; Cardenas, Jamie ; Dutta, Suparna ; Kirwan, Jeral
Author_Institution :
Forbes Sch. of Bus., Ashford Univ., San Diego, CA, USA
fDate :
June 27 2014-July 2 2014
Abstract :
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.
Keywords :
computer aided instruction; class drop; data scientific approach; online classroom; student behaviors; Big data; Business; Communities; Educational institutions; Electronic mail; Neural networks; Big Data; Data Science; Online Education; Presence; Students Behavior;
Conference_Titel :
Big Data (BigData Congress), 2014 IEEE International Congress on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5056-0
DOI :
10.1109/BigData.Congress.2014.129
