Title: ASSISTments Longitudinal Data Mining Competition [Archived Project]
Ongoing - October 1 2017
This competition uses data from a longitudinal study, now over a decade long, led by Professor Ryan Baker and Professor Neil Heffernan. This study, funded by multiple grants from the National Science Foundation, tracks students from their use of the ASSISTments blended learning platform in middle school in 2004-2007, to their high school course-taking, college enrollment, and first job out of college. Several papers have shown that behavior in ASSISTments in middle school can predict high school and college outcomes. In this competition, you will receive access to extensive (but carefully deidentified) click-stream data from middle school ASSISTments use, as well as carefully curated brand new outcome data on first job out of college, never before used in published research. Successful entries will be invited to submit both to a conference workshop (at EDM2018, in Buffalo, NY) and to a special issue of the Journal of Educational Data Mining.
Leader(s): Sam Tenka (@samtenka)
Link to the Code: https://gitlab.eecs.umich.edu/mdst/assistments
Link to the Dataset: