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Methodological Innovations and Advanced Applications Using National and International Databases
Sat, April 15, 9:50 to 11:20am CDT (9:50 to 11:20am CDT), Chicago Marriott Downtown Magnificent Mile, Floor: 6th Floor, Great America IISession Type: Paper Session
Abstract
This paper session features papers using advanced parametric models such as multilevel models and multilevel structural equation models, as well as machine learning methods such as random forest, to address educational research questions.
Sub Unit
Chair
Papers
Applying and Extending QuantCrit: Research Investigation on Overrepresentation in Special Education - Nicholas S. Bell, University at Albany - SUNY; Verónica Nelly Vélez, Western Washington University; Zachary K. Collier, University of Connecticut
Using Artificial Intelligence in R to Help Selecting Sampling Weights for Early Childhood Longitudinal Study–Kindergarten Data Analysis - Huade Huo, American Institutes for Research; Paul D. Bailey, American Institutes for Research; Ting Zhang, American Institutes for Research; Emmanuel Sikali, U.S. Department of Education
Do Classroom and School Characteristics Matter in Teachers' Feedback Behavior? An Application of Random Forest - Meereem Kim, Korea Institute for Curriculum and Evaluation; Eun Hye Ham, Kongju National University
Do Engagement, Motivation, and Self-Regulation Predict Freshman Academic Performance Above and Beyond High School Academic Preparedness? - Gregory J. Palardy, University of California - Riverside