With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular…

While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…

A socio-legal analysis of the UK governance regime for data collected from children at school for teaching and learning contrasts the government-mandated data collection by schools to inform educational policy and planning with data processed and shared with third parties by commercial EdTech providers. We find the former is effectively governed…

This brief is our fourth annual review of how states are and could make a difference in school attendance with new policies and practices. Reversing today's chronic absenteeism requires state leaders to make reducing chronic absence a priority. In our work with states, we see how state leadership, especially from governors and state education…

School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel…

The Forum Guide to Data Quality provides best practices from districts and states for maintaining quality data as these agencies regularly review and revise their methods for working with data, as well as their expectations for all staff who are responsible for education data and their quality. This resource is intended to help districts and…

Background/Context: Application Programming Interfaces (APIs) are becoming a core means to collect and disseminate data for education research and policy. Surveys can be costly, slow, and burden respondents, and manually downloading data files is slow and cumbersome when many files are needed. APIs provide a programmatic way to collect data or…

Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes…

A staff study (SS) is an administrative tool used for decision-making, involving comprehensive data gathering and analysis to resolve issues. Particularly crucial in military settings where classified information limits resources, staff studies also demonstrate their value in interdisciplinary academic fields. This article emphasizes the…

There are nearly 1 million credentials in the United States that students and workers can take advantage of, but how information about these credentials is collected and communicated is oftentimes inconsistent and hard to access. In February, we invited a group of postsecondary and workforce development experts to consider how policymakers can…

This guide provides cross-sector teams at the state, territory, tribal, and local levels with strategies for collecting and using data across the mixed delivery system of early care and education programs. (This guide uses the term "state and local" to refer to all of these levels.) Collecting and analyzing qualitative and quantitative…

The 2021-22 Civil Rights Data Collection (CRDC) is a mandatory survey of all public school districts and schools serving students in preschool through grade 12 in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico and therefore includes data from 17,704 public school districts also known as local education agencies (LEAs) and…

Digital footprints (DF) offer relevant information about educational activities and processes related to strategies of academic assessment, identification of skills and psychological traits of students, and permanence and dropout trends, etc. This study analyzes scientific evidence on the use of DF in education, and shows the results of a…

Current approaches to research in the field of Early Childhood Education and Care (ECEC), in particular in relation to methods designed to interrogate policy and practice developments, tend not to focus on gathering empirical data through collaborative networks. This article provides a critical reflection on a novel qualitative methodological…

In recent years, career and technical education (CTE) programs that include quality work-based learning (WBL) opportunities for students have gained significant traction among educators, policymakers, and stakeholders as an effective way to prepare students for the labor market. However, a lack of data on WBL--which many CTE students participate…