This chapter presents an innovative, cross-disciplinary methodological approach to systematically reviewing and comparing large bodies of literature using big data, Natural Language Processing, network analysis, and supplementary qualitative analysis. The approach is demonstrated through an analysis of the literature surrounding four common…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

Though statistics is covered in secondary-school curricula, it is usually limited to few lessons and mainly taught in a procedural approach. There seems to be a gap between the education of mathematics teachers and the demands on their practice. Learning statistics from a mathematical perspective does not qualify to teach the subject properly.…

Large-scale assessment programs, such as the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS), employ item response theory (IRT) and marginal estimation methods to estimate student proficiency in specific subjects such as mathematics, science, or reading. Each of these…

Imagine a student using an intelligent tutoring system. A researcher records the correctness and time of each of your attempts at solving a math problem, nothing more. With no names, no birth dates, no connections to the school, you would think it impossible to track the answers back to the class. Yet, class sections have been identified with no…

As many districts in Pennsylvania pivot to hybrid or virtual models of education in response to Covid-19, it is hard to think about what "attendance" means or how to track it. Yet attendance is more important than ever. Students need to stay engaged to continue their learning and to access the myriad supports that districts are offering.…

This study aims to explore the extent of intergenerational social mobility in the United States for the population as a whole, as well as differentiated by gender and race/ethnicity. Study of intergenerational social mobility is important because it shows whether individuals can prosper in a society regardless of their socioeconomic background, as…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

This paper examines the development of data infrastructure in Australian schooling with a specific focus on interoperability standards that help to make new markets for education data. The conceptual framework combines insights from studies of infrastructure, economic markets and digital data. The case of the Australian National Schools…

This study evaluated the effectiveness of a family-centered feeding intervention, Easing Anxiety Together with Understanding and Perseverance (EAT-UP™), for promoting food acceptance of children with autism spectrum disorder at home. A concurrent multiple-baseline design was used with systematic replication across three families. Baseline was…

Each edition of the IDRA Newsletter strives to provide many different perspectives on the issues in education topics discussed and to define its significance in the state and national dialogue. This issue focuses on Using Data for Action and includes: (1) Community and School Use of Data for College Readiness and Postsecondary Success (Karmen…

The State Family Outcomes Measurement System Framework (S-FOMS) is a framework originally developed by the Early Childhood Outcomes (ECO) Center that identifies seven key components of a high-quality family outcomes measurement system at the state level. This document contains background information about the framework's seven components, 15…

The U.S. Department of Education's Office of English Language Acquisition (OELA) helps to ensure that ELs attain English proficiency and achieve academic success. OELA accomplishes these goals by administering discretionary grant programs to prepare professionals for teaching and disseminating information about educational research, practices, and…

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will…

The Office of Inspector General (OIG) works to promote efficiency, effectiveness, and integrity in the programs and operations of the U.S. Department of Education (Department). Through OIG's audits, inspections, investigations, and other reviews, they continue to identify areas of concern within the Department's programs and operations and…