By design, randomized experiments (XPs) rule out bias from confounded selection of participants into conditions. Quasi-experiments (QEs) are often considered second-best because they do not share this benefit. However, when results from XPs are used to generalize causal impacts, the benefit from unconfounded selection into conditions may be offset…

Scoring high-dimensional assessments (e.g., > 15 traits) can be a challenging task. This paper introduces the multilabel neural network (MNN) as a scoring method for high-dimensional assessments. Additionally, it demonstrates how MNN can score the same test responses to maximize different performance metrics, such as accuracy, recall, or…

The purpose of this National Assessment of Educational Progress (NAEP) Achievement Levels Validity Argument Report is to synthesize evidence currently available to address the validity of the interpretations and uses of the NAEP Achievement Levels. Validity is the extent to which theory and evidence supports or refutes proposed and enacted test…