DocumentCode
249532
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
fYear
2014
fDate
June 27 2014-July 2 2014
Firstpage
802
Lastpage
803
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data (BigData Congress), 2014 IEEE International Congress on
Conference_Location
Anchorage, AK
Print_ISBN
978-1-4799-5056-0
Type
conf
DOI
10.1109/BigData.Congress.2014.129
Filename
6906873
Link To Document