Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…

This report describes the design, methods, and results of the 2016/20 Baccalaureate and Beyond Longitudinal Study (B&B:16/20) conducted by the U.S. Department of Education's National Center for Education Statistics (NCES). It is the second follow-up with a cohort of bachelor's degree recipients originally identified during the 2015-16 National…

This technical appendix provides additional information about the sample, data, and estimation strategy that were used for a series of AEP Data Notes published by the RAND Corporation in 2018 and 2019. The Data Note series is intended to provide brief, incisive analyses of teacher and school leader survey results which may be of immediate interest…

IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…

The What Works Clearinghouse (WWC) Standards Briefs explain the rules the WWC uses to evaluate the quality of studies for practitioners, researchers, and policymakers. Attrition (loss of sample) occurs when individuals initially included in a study are not included in the final study analysis. Attrition is a common issue in education research and…

Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least…

This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…

This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…

One of the main objectives in meta-analysis is to estimate the overall effect size by calculating a confidence interval (CI). The usual procedure consists of assuming a standard normal distribution and a sampling variance defined as the inverse of the sum of the estimated weights of the effect sizes. But this procedure does not take into account…

Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…

In this article, the author discusses the use in policy analysis of models that incorporate uncertainty. He believes that all models should consider incorporating uncertainty, but that at the same time it is important to understand that sampling variability is not usually the dominant driver of uncertainty in policy analyses. He also argues that…