Big Data in MOOC

Presenters: Nicole Wang, Chad Evans
University of Pennsylvania
Concentration: Life Cycle of a Million MOOC
Data: 16 Penn Coursera Courses offered
between June 2012 and July 2013
Central Finding: Lots of attrition
Processing Time and Big Data
• Complicated calculations may cause
significant delays in output
• Analyses will take more time
Limited resources available to MOOC
• Coding introduces particular challenges
Ambiguous data documentation
• Examples of variable names
• ;lkjas;ldf^^^__(*KJNKH_ljllldfkas
• Transition_in_47_data
Challenges working on Secure Servers
• Frequent Crashing/Cursor Freezing
• Limitations in copying/pasting
• No access to the internet and its resources
Research team
• Laura Perna, Alan Ruby, Robert Boruch,
• Nicole Wang, Janie Scull, Chad Evans, Seher Ahmad
• MOOC Research Initiative funded by the Gates
Foundation through Athabasca University.
• Institute of Education Sciences, U.S. Department of
Education, through Grant #R305B90015 to the
University of Pennsylvania
• Quantitative Methods Division of Penn GSE
• Penn AHEAD
The opinions expressed are those of the authors
and do not represent the views of the funders.
Nicole Wang: [email protected]
Chad Evans: [email protected]

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