This study investigated the process of instructional change required to translate data on student progress along learning trajectories (LTs) into relevant instructional modifications. Researchers conducted a professional development session on ratio LTs, which included analyzing 3 years of district-level data from Math-Mapper 6-8, a digital…

In an increasingly data-driven society, making decisions with data is a requirement not only for research scientists but also for navigating life more generally (Kjelvik & Schultheis, 2019). An informed citizenry must be prepared to discover patterns, predict outcomes, make decisions with data, and evaluate data-based claims for legitimacy and…

The profound advancements in technology have rendered novel forms of data and data visualisation increasingly accessible to individuals within society, thereby influencing daily decision-making processes. To address this change, this study sets out to review recent research on data-driven inquiries at the K-12 level from two perspectives:…

Data literacy enables teachers to use information collected about students and their learning to take data-informed instructional action. This article outlines two approaches developed by teachers to provide teaching targeted to the immediate needs of specific students that moved beyond "gap-filling". The pre-teaching and "fresh…

Data-based individualization (DBI) is a framework that allows educators to make timely and informed decisions about student progress in academics or behavior. In this article, we focus on the DBI framework as applied to math intervention within a tiered support model for students experiencing math difficulty. We review how DBI starts with an…

Data-based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple single-subject design was used to measure effects of a 2-year training, in which entire school teams learned how…

Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…

In March 2022, RAND researchers administered the fourth and final Learn Together Surveys (LTS) via the RAND Corporation's American Educator Panels. The 2022 LTS differs in two key ways from its predecessors. First, the 2022 sample includes K-12 educators whereas previous administrations of the LTS sampled only educators in schools serving grade 6…

Response to intervention, direct instruction, and data-based decision-making are all effective teaching practices that can impact student math performance. When educational technology is implemented in classroom settings, it can address both the needs of teachers and students. However, there is little information detailing how educational…

Formative assessment helps teachers make effective instructional decisions to support students to learn mathematics. Yet, many teachers struggle to effectively use formative assessment to support student learning. Therefore, teacher educators must find ways to support teachers to use formative assessment to inform instruction. This case study…

Grounded in the belief that data will drive instructional change, data-driven decision making continues to be a prevalent reform strategy in schools. However, the use of data does not always prompt teachers to change their instructional practices, particularly in low-performing schools where accountability pressures loom large. Drawing on in-depth…

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…

Ever-growing expectations exist for educators to use assessments to collect, analyze, and interpret data, but how, if at all, are these processes affecting instruction? This descriptive case study of one team of second grade teachers offers an analysis of the links between teachers' use of data within their collaborative team meetings and…

Statistical modeling is a core component of statistical thinking and has been identified by several countries as a curricular goal for secondary education. However, many secondary teachers have minimal preparation for teaching this topic. The goal of this research study is to learn about teachers' perceptions of the role statistical models play in…

An important goal in the design and development of Intelligent Tutoring Systems (ITSs) is to have a system that adaptively reacts to students' behavior in the short term and effectively improves their learning performance in the long term. Inducing effective pedagogical strategies that accomplish this goal is an essential challenge. To address…