In this technical report, the Center for Research Use in Education (CRUE) presents the methodological design of a large-scale quantitative investigation of research use by school-based practitioners through the "Survey of Evidence in Education for Schools (SEE-S)." It documents the major technical aspects of the development of SEE-S,…

Qualitative education research is an inherently complex landscape, presenting the qualitative researcher with constant ethical and reasoned decision-making. Presented as a narrative dialogic, this paper traces and juxtaposes the method stories of two qualitative researchers who focused their work around education phenomena, but in different…

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

Across OECD countries, the increasing demand for evidence-based policy making has further led governments to design policies jointly with clear measurable objectives, and to define relevant indicators to monitor their achievement. This paper discusses the importance of such indicators in supporting the implementation of education policies.…

In tiered instructional systems (Response to Intervention [RTI]/Multitier System of Supports [MTSS]) that rely on ongoing assessment of students at risk of experiencing academic difficulties, the ability to make informed decisions using student data is critical for student learning. Prior research has demonstrated that, on average, teachers have…

Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…

Internationally, there has been a policy push for using student data for instruction. Yet, research has noted few examples of actually understanding how this data-use practice takes place. This study presents a case of an instructional data team making sense of student data. The study shares data to show how teachers' process for using data to…

Responding to the industry need for professionals to employ data-driven decision-making, educational institutions offer courses in business analytics (BA). Since BA professionals require a unique set of skills different from those found in specific business disciplines, a pedagogical framework to impart such knowledge and skills was developed. The…

This qualitative phenomenological study explored how 19 school leaders in seven California comprehensive high schools were making sense of data and using data to transform their schools by closing achievement gap for historically underrepresented students. Data is a powerful tool in the hands of school leaders to transform patterns of inequality…

"Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…

This study aims to examine the effectiveness of metacognitive scaffolding in different inquiry tasks related to optics. Two high school classes participated in this study. One class, the treatment group (n = 33), which integrated metacognitive prompts into the simulation-based inquiry, was compared to the other class, the control group (n = 34),…

In this summary article, six recommendations for the design, implementation, and interpretation of educational evaluations are presented and discussed. These recommendations are based on common "threads" that run through most, if not all, of the papers included in this special issue. The recommendations concern (1) the need for awareness…