Vol 13 No 2 (2021): Scientific Findings from the NAEP Data Mining Competition
Special issue on the NAEP Data Mining Competition.
Ryan S. Baker, Neil T. Heffernan, Thanaporn Patikorn, Carol M. Forsyth, and Irvin R. Katz, Editors
Published: 2021-08-26
Scientific Findings from the NAEP 2019 Data Mining Competition
Process Mining Combined with Expert Feature Engineering to Predict Efficient Use of Time on High-Stakes Assessments
Abstract 954 | PDF Downloads 845
Page 1-15
Modeling NAEP Test-Taking Behavior Using Educational Process Analysis
Abstract 1568 | PDF Downloads 795
Page 16-54
AutoML Feature Engineering for Student Modeling Yields High Accuracy, but Limited Interpretability
Abstract 1405 | PDF Downloads 1512
Page 55-79
Applying Psychometric Modeling to aid Feature Engineering in Predictive Log-Data Analytics: The NAEP EDM Competition
Abstract 859 | PDF Downloads 660
Page 80-107
Editorial Acknowledgments and Introduction to the Special Issue for the NAEP Data Mining Competition
Abstract 752 | PDF Downloads 477
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