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…

Online program managers (OPMs) are third-party companies that work with colleges and universities to develop, launch, and deliver online learning. Despite the prevalence of these companies in higher education, cost details are often buried or asserted with legal protections as trade secrets or business models unavailable for public review.3…

Wake Forest University (WFU) is in the midst of a 28-month student information system (SIS) transition. The authors' offices are deeply involved in this process on a daily basis. As the university collects and analyzes data, discusses operational needs with campus colleagues, builds and configures tenants, tests and validates, and implements a new…

Procrastination is a prevalent issue among university students and leads to long-term negative impacts on academic performance as well as mental health and quality of life. This paper investigated StudyTracker, a self-tracking digital application (app) that we developed for university students to use to track their study sessions. The app provided…

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…

A rich literature supports the use of data in schools to support improved teaching and learning. One widely implemented example of a data inquiry process is "Data Wise," developed at the Harvard Graduate School of Education to help instructional teams collaborate around multiple data sources, surface evidence of students' strengths and…

Written by experienced leaders in gifted education, this book is a foundational guide for supervisors, administrators, and districts seeking to create culturally responsive and equity-focused gifted policies and programs. Engaging chapters supported by real-world vignettes and interactive contemplation corners outline key elements of culturally…

The urgent need to help students -- and particularly students who are Black or Hispanic -- recover from the negative effects of the coronavirus disease 2019 (COVID-19) pandemic on mathematics learning and access equitable opportunities in mathematics will require that teachers use every available tool to diagnose student learning needs and…

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…

Black teachers (BTs) are significantly underrepresented in the US teaching profession, yet there is still little focus on how to best hire, support, and retain them. This collaborative autoethnography documents our work in an urban characteristic school district and university in the southeastern US and how we leveraged our interpersonal and…

This study investigates the extent to which paper-based data-driven learning (DDL) activities can improve Thai EFL students' grammar learning of conditional sentences (the second condition), as well as the participants' attitudes toward learning through the DDL approach. This was a two-week research using a one-group pre-test and post-test design.…

Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…