Workshop: Educational Data Analysis Using LearnSphere

9th International Conference on Educational Data Mining (EDM 2016)
in Raleigh, NC, USA (June 29 - July 2, 2016)


John Stamper, Carnegie Mellon University
Kenneth Koedinger, Carnegie Mellon University
Philip Pavlik, University of Memphis
Carolyn Rose, Carnegie Mellon University
Ran Liu, Carnegie Mellon University
Michael Eagle, Carnegie Mellon University
Michael Yudelson, Carnegie Mellon University
Kalyan Veeramachaneni, MIT


Contact Ran Liu—ranliu AT cmu DOT edu

LearnSphere’s goal is to support any custom analysis workflow that can be applied to educational datasets (such as those in DataShop, DiscourseDB, MOOCdb) and to produce standardized workflow outputs that facilitate quantitative and qualitative model comparisons. We invite researchers to submit 2-4 page descriptions of educational data analysis workflows/models. Strong submissions will have high level descriptions of the analysis workflow and detailed information on the format of input data and resulting outputs. Accepted participants will be eligible for a scholarship that covers the cost of EDM registration and have the opportunity to publish outcomes in the EDM workshop proceedings.

Researchers may use the following template to guide submissions. Submission are due on May 25, 2016 and will be accepted through EasyChair for EDM2016. We will notify authors of accepted submissions by June 3, 2016.

This workshop will explore the application and refinement of novel educational data mining workflows using LearnSphere, a new $5 million NSF funded data sharing and analysis portal that extends the existing DataShop infrastructure and includes teams from Carnegie Mellon, Stanford, Memphis, and MIT. Increased flexibility to accommodate custom educational analysis workflows is one of the core ways in which LearnSphere expands upon DataShop.