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Big Data in MOOCs
Presenters: Nicole Wang, Chad Evans
University of Pennsylvania
Our Study
Concentration: Life Cycle of a Million MOOC users
Data: 16 Penn Coursera Courses offered between June 2012 and July 2013
Central Finding: Lots of attrition
Four Central Problems
1) Processing Time and Big Data• Complicated calculations may cause
significant delays in output• Analyses will take more time
2) Limited resources available to MOOC researchers• Coding introduces particular challenges
Four Central Problems
3) Ambiguous data documentation• Examples of variable names• ;lkjas;ldf^^^__(*KJNKH_ljllldfkas• Transition_in_47_data
4) Challenges working on Secure Servers • Frequent Crashing/Cursor Freezing• Limitations in copying/pasting• No access to the internet and its
resources
Tentative solution 1: create a community to collaborate
Tentative solution 2: data dictionary
Tentative solution 3:better data
collection/management
Tentative solution 4: communications with tech team
AcknowledgementsResearch team
• Laura Perna, Alan Ruby, Robert Boruch, • Nicole Wang, Janie Scull, Chad Evans, Seher Ahmad
Funding• 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.
