Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

This report presents findings from a study conducted by The George Washington University Center for Equity and Excellence in Education (GW-CEEE) under the sponsorship of the National Center for Educational Statistics (NCES). The purpose of the study is to describe and analyze school-based decision-making practices relevant to the inclusion and…

Current plans to use National Assessment of Educational Progress (NAEP) results to compare and rank states may lead to a perception of NAEP as a national achievement test representing a national curriculum. NAEP procedures should be reformulated to enhance curriculum coherence, instruction, and participation by local and state educators. (TJH)