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…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

This paper sets out to explore the different uses made of Organisation for Economic Co-operation and Development Program for International Student Assessment (OECD-PISA) tests and data in mathematics education research. Through a comprehensive literature review of journals and conference papers, we show that although a large variety of topics is…

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…

One major challenge of longitudinal data analysis is to find an appropriate statistical model that corresponds to the theory of change and the research questions at hand. In the present article, we argue that "continuous-time models" are well suited to study the continuously developing constructs of primary interest in the education…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Two separate data searches underlie this analysis of how references to educational research and to PISA are used in the Swedish education debate. The data consist of 380 newspaper articles from the eight largest print media outlets in Sweden and 200 protocols from parliamentary debates (2000 to 2016) that made explicit reference to 'PISA' and/or…

Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

The main aim of this research is to display research trends in studies on augmented reality (AR) in teaching English as a foreign language by using bibliometric mapping and content analysis. For this purpose, 64 studies in total published up to 2019 were accessed for bibliometric analysis. In addition, 49 articles published between 2007 and 2019…

The Stanford Educational Data Archive (SEDA) is the first data set to allow comparisons of district academic achievement and growth from Grades 3 to 8 across the United States, shining a light on the distribution of educational opportunities. This study describes a convergent validity analysis of the SEDA growth estimates in mathematics and…

IES is the primary research, evaluation, and statistics arm of the U.S. Department of Education. Established through the Education Sciences Reform Act of 2002 (ESRA), the Institute's mission is to expand fundamental knowledge and understanding of education and to provide education leaders and practitioners, parents and students, researchers, and…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

Although International Association for the Evaluation of Educational Achievement-pioneered international large-scale assessment (ILSA) of education is now a well-established science, non-practitioners and many users often substantially misunderstand how large-scale assessments are conducted, what questions and challenges they are designed to…

This study tests a process model of learning in which trainer and trainee traits are simultaneously considered as endogenous variables of learning outcomes. The article builds on a social view of training and similarity-attraction paradigms. In this context, the authors hypothesize that trainer-trainee similarity in personality (agreeableness)…