There is evidence that data-based decision-making (DBDM) can improve outcomes for a wide range of students. However, less is known about how special education teachers are trained to use data to inform instruction that targets academic progress for students with extensive support needs (ESN). The purpose of this systematic literature review was to…

Millions of children in the United States struggle with reading acquisition, many of whom are identified with developmental dyslexia (DD). Although experimental research indicates that evidence-based reading interventions can bring many of these children to average-range reading skills, such promising outcomes are not commonly achieved within K-12…

Evidence based decision making is essential for enabling improved student learning. Teacher motivations and beliefs about the types and use of data are critical determinants of decision making. Our research explored the types of data teachers use and consider valuable when measuring improvement in student learning. Findings from 294 teachers from…

During the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that…

This qualitative case study explored how educators in a high-poverty, urban public high school used student achievement data to inform instruction. The sample consisted of one principal, five counselors, and ten teachers across multiple departments in a Los Angeles County high school recognized for its data-driven practices and collaborative…

The digital evaluation field is a new area that arises in the core of education and studies highlight the importance of editing data as well as using ICT to drive internal school improvement. Data- Driven Decision Making (DDDM in advance) executes relatively simple models on carefully targeted data extracted through target questionnaires. This…

The purpose of this process evaluation was to evaluate how classroom teachers, campus administrators, and instructional staff differ in their perception of data usage for educational improvement in a large suburban Independent School District (ISD) in Southeast Texas. The researcher was granted permission by the superintendent of the school…

As art libraries face challenges from an evolving environment, repercussions from the COVID-19 pandemic, and static or diminishing resources, finding sustainable pathways forward becomes an increasing priority. An important option for art research collections in achieving long-term sustainability is collaboration. This report explores…

Background/Context: The importance attached to practicing data use is evident in its inclusion in federal law, competitive grant programs, state teaching license requirements, and professional development (PD) workshops around the world. Yet, practitioners and scholars have identified misconceptions clouding data use practice, questioned its…

As a digital learning medium, serious games can be powerful, immersive educational vehicles and provide large data streams for understanding player behavior. Educational data mining and learning analytics can effectively leverage big data in this context to heighten insight into student trajectories and behavior profiles. In application of these…

This guide describes how community college presidents can embed strategic enrollment management (SEM) into mission fulfillment. It emphasizes the importance of setting a vision, ensuring adequate resources, and fostering collaboration. By leveraging data-driven strategies and continuous improvement, colleges can enhance student recruitment,…

The following case studies explore how emerging and established Statewide Longitudinal Data Systems have used the Education-to-Workforce Indicator Framework (E-W Framework) to support their data system efforts. Developed by Mathematica in partnership with the Gates Foundation, the framework offers guidance on how states can use data to…

A "Cone of Uncertainty" has become ubiquitous in hurricane forecasting, encompassing the likeliest possible path that a storm might take as it approaches landfall. These forecasts are crucial because they help government agencies at all levels prepare even in these far-from-certain future conditions. Although individual institutions have…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

Using data to inform decision-making in the educational environment has increased over the last decade due to accountability requirements at the federal, state, and local level (Bernhardt, 2013; Datnow & Hubbard, 2016; Garland, 2014; Mandinach & Gummer, 2016; McKay, 2018; Wayman, 2005). While research supported the inclusion of data in…