While this competition is now over, and this " Workshop on Scientific Findings from the ASSISTments Longitudinal Data Competition" was held during The 11th Conference of Educational Data Mining in Buffalo, NY on July 15-18, 2018, we are currently organizing a special issue of the Journal of Educational Data Mining. You can find Special Issue Call for Papers: Scientific Findings from the ASSISTments Longitudinal Data Competition here.
There has been ongoing concern about early developments in students’ academic careers preventing them from having later access to a broad range of careers. In recent years, early-warning systems have emerged at the K-12 level. However, these systems typically warn school districts about only some potential forms of risk, most commonly dropout or school violence. While some efforts have extended to predicting college enrollment or SAT score, a student can graduate from high school, attend college, achieve an acceptable SAT score, and still find that their earlier learning experiences shape their opportunities to choose a broad range of careers.
In 2017-2018, researchers at Worcester Polytechnic Institute and the University of Pennsylvania released an 11-year longitudinal data set spanning from middle school usage of a blended learning system for mathematics (ASSISTments) to the students’ eventual choice of career, focusing on whether experiences in mathematics class corresponded to eventually choosing a STEM (Science, Technology, Engineering, and Mathematics) job or graduate program after college. This data set was released as part of a competition affiliated with the NSF Northeast Big Data Hub and the Spoke on Big Data for Education. Over two hundred participants registered in the competition and 74 participants eventually submitted solutions.
https://sites.google.com/view/assistmentsdatamining/data-mining-competition-2017
In this workshop, we invite participants in the competition to share their findings, both in terms of data mining and education research, with each other and with the broader scientific community. Relevant paper topics may include but are not limited to:
Submissions due: April 25, 2018, 11.59pm Hawaii time
Notification of acceptance: May 9, 2018
Papers must be submitted in the EDM conference format (not the JEDM format) http://educationaldatamining.org/EDM2018/submission/
Papers are single-blinded, and may be either 4-6 pages (short paper) or 6-10 pages (full paper).
Submit papers to: assistmentscomp2018 [at] wpi.edu
Dr. Ryan Baker
Associate Professor, University of Pennsylvania
Dr. Neil Heffernan
Professor at Worcester Polytechnic Institute and the co-creator of ASSISTments
Dr Ivon Arroyo
Associate Professor, Worcester Polytechnic Institute
Dr. Beverly Woolf
Research Professor, University of Massachusetts Amherst
With Assistance From
Thanaporn "March" Patikorn
Ph.D. student, Worcester Polytechnic Institute
If you have any questions or concerns, please contact us at assistmentscomp2018 [at] wpi.edu