Editorial Acknowledgments and Introduction to the Special Issue for the NAEP Data Mining Competition

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Published Aug 26, 2021
Ryan S. Baker Neil T. Heffernan Thanaporn Patikorn Patikorn Carol M. Forsyth Irvin R. Katz

Abstract

The NAEP Data Mining Competition was sponsored by the Big Data for Education Spoke of the Northeast NSF Big Data Innovation Hub and Educational Testing Service. The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, is the only assessment that measures U.S. student knowledge nationwide across academic subjects. The NAEP has collected data since 1969 and measures student success in urban, suburban and rural areas. In 2019, The National Center for Educational Statistics (NCES) gave permission for ETS to provide a NAEP dataset for an educational data mining competition. The release of this data was part of a competition co-sponsored by the Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS. Over 89 participants entered the competition, with a total of 723 submissions. The goal of this competition was to understand effective and in-effective test-taking behaviors and determine how quickly these behaviors can be detected. In this special issue of the Journal of Educational Data Mining, researchers share their findings related to the competition's publicly released data sets, both in terms of data mining and education research, with the broader scientific community.

How to Cite

Baker, R. S., Heffernan, N. T., Patikorn, T. P., Forsyth, C. M., & Katz, I. R. (2021). Editorial Acknowledgments and Introduction to the Special Issue for the NAEP Data Mining Competition. Journal of Educational Data Mining, 13(2), i. https://doi.org/10.5281/zenodo.5275308
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