Understanding student behaviors in online classroom: data scientific approach

Jongbok Byun, Diane Pennington, Jorge Cardenas, Srabasti Dutta, Jeral Kirwan

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)
9 Downloads (Pure)


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.
Original languageEnglish
Number of pages2
Publication statusPublished - 25 Sep 2014
Event3rd IEEE International Congress on Big Data, BigData Congress 2014 - Washington, DC, United States
Duration: 27 Jun 20142 Jul 2014


Conference3rd IEEE International Congress on Big Data, BigData Congress 2014
Country/TerritoryUnited States
CityWashington, DC


  • Big Data
  • Data Science
  • online education
  • students Behavior
  • distance education
  • Drops
  • education
  • social networking (online)
  • teaching
  • student learning
  • students' behaviors

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