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 866 | PDF Downloads 795
Page 1-15
Modeling NAEP Test-Taking Behavior Using Educational Process Analysis
Abstract 1519 | PDF Downloads 754
Page 16-54
AutoML Feature Engineering for Student Modeling Yields High Accuracy, but Limited Interpretability
Abstract 1302 | PDF Downloads 1414
Page 55-79
Applying Psychometric Modeling to aid Feature Engineering in Predictive Log-Data Analytics: The NAEP EDM Competition
Abstract 814 | PDF Downloads 612
Page 80-107
Editorial Acknowledgments and Introduction to the Special Issue for the NAEP Data Mining Competition
Abstract 712 | PDF Downloads 443
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