The National Assessment of Educational Progress (NAEP) is an integral measure of academic progress across the nation and over time. It is the largest nationally representative and continuing assessment of what our nation's students know and can do in various subjects, such as civics, mathematics, reading, and U.S. history. The program also…

State education agencies are sitting on rich repositories of quantitative and qualitative assessment data. This document is designed to provide a conceptual framework and implementation guidance that can help agency leadership leverage and interrogate student performance data in systematic ways for reporting, outreach, and planning purposes. The…

This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…

Recent data from statewide assessments, scores on the National Assessment of Educational Progress (NAEP), and college remediation needs show that an increasing number of K-12 students are not performing at grade level. As schools look to support these students' learning, some districts are turning to a proven strategy for identifying the students…

For the first time in 32 years, the national average scale score in mathematics dropped by seven points across the country in grades four and eight, according to the latest results of the National Assessment on Educational Progress (NAEP). The 2022 results in mathematics were staggering, in which "math performance fell for the first time in…

The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…

The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…

The EdSurvey package helps users download, explore variables in, extract data from, and run analyses on large-scale assessment data. The analysis functions in EdSurvey account for the use of plausible values for test scores, survey sampling weights, and their associated variance estimator. We describe the capabilities of the package in the context…

Researchers often assess causal effects of educational programs or policies using educational assessment data. This dissertation explores novel methods of estimating causal effects in educational assessment data and is broken into three parts. The first part proposes a regression discontinuity design with an ordinal running variable to assess the…

In every classroom across our great state--from Monroe to Manistee and Mt. Pleasant to Marquette--every Michigan student deserves access and opportunity to the educational resources and support to realize a bright future. Yet for too long, Michigan's education system has served as an engine of inequality when it should be providing opportunities…

This study examines the impact of early Algebra I coursework on advanced Carnegie credits among 12th graders from diverse racial/ethnic backgrounds, using data from the NCES HSTS (1990-2019). Findings indicate that early Algebra students, particularly Black and Latinx, earn more advanced credits, revealing a widening gap in advanced course…

The quality of students' writing skills continues to concern educators. Because writing is essential to success in both college and career, poor writing can have lifelong consequences. Writing is now primarily done digitally, but students receive limited explicit instruction in digital writing. This lack of instruction means that students fail to…

The "2nd Annual WPI-UMASS-UPENN EDM Data Mining Challenge" required contestants to predict efficient testtaking based on log data. In this paper, we describe our theory-driven and psychometric modeling approach. For feature engineering, we employed the Log-Normal Response Time Model for estimating latent person speed, and the Generalized…

In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…

The finite population correction (FPC) factor is often used to adjust variance estimators for survey data sampled from a finite population without replacement. As a replicated resampling approach, the jackknife approach is usually implemented without the FPC factor incorporated in its variance estimates. A paradigm is proposed to compare the…