The purpose of this manuscript is to share the work of a collaboration between professional development providers and university faculty as they created, implemented and refined a professional development series focused on supporting primary teachers' use of data-based decision making in reading. Using a formative and design-based approach,…

This Guide provides universities with a road map to initiate or bolster current efforts to create a robust system for ensuring effective public access to high-quality research data. The Guide aims to assist universities and their senior administrators in crafting consistent and uniform approaches to all aspects of research data management and…

The "Forum Guide to Data Governance" highlights how data governance programs benefit education agencies and provide timely and useful best practices, examples, and resources for agencies implementing or updating their data governance programs. This resource is intended to address the needs of federal, state, and local agencies related…

A growing interest in more equitable education, particularly regarding historical contributions of racial and ethnic communities, has heightened advocacy for adopting ethnic studies. The focus of ethnic studies courses can vary across the nation. Some courses prioritize the accomplishments and contributions of racial and ethnic minorities in the…

Early education leaders--inside and outside of government--are looking for new ways to improve quality, accountability, and efficiency across many different programs serving young children and their families, and they see investment in data systems as a pivotal part of that effort. However, it can be challenging to develop and implement effective…

This chapter provides a conceptual model that academic leaders can use to navigate the complex, and often contentious, organizational terrain of academic program development. The model includes concepts related to the institution's external environment, as well as internal organizational structures, cultures, and politics. Drawing from the…

Launched in 2008, the Strategic Data Project, housed at the Center for Education Policy Research at Harvard University, seeks to bridge the divide between educational research and practice in order to transform the use of data in education to improve student achievement. Through the project, the authors build robust research partnerships with…

Data centric applications, an important effort of software development in large organizations, have been mostly adopting a software methodology, such as a waterfall or Rational Unified Process, as the framework for its development. These methodologies could work on structural, procedural, or object oriented based applications, but fails to capture…

Emphasis on improving student learning has brought increased attention to the execution of schoolwide instructional reforms in general and the use of data by teacher teams in particular as an expected element of a school's instructional reform strategy. With this in mind, the purpose of this article is to focus important attention on the work…

Continuing and professional education units are faced with the constant need to keep pace with dynamic labor markets when assessing program offerings and content. Real-time labor-market data derived from detailed analysis of online job postings offers a new tool for more easily aligning programs to local labor-market demand. The authors describe a…

Higher level vocational education and training (VET) programmes are facing rapid change and intensifying challenges. What type of training is needed to meet the needs of changing economies? How should the programmes be funded? How should they be linked to academic and university programmes? How can employers and unions be engaged? The country…

The Australian Vocational Education and Training Management Information Statistical Standard (AVETMISS) for vocational education and training (VET) providers (referred to as "the Standard") is currently being reviewed by the National Centre for Vocational Education Research (NCVER). The Standard is the framework that underpins the…

A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…

Nearly every high-priority item in national, federal, state, and local discussions about education--and policy proposals across the political spectrum--requires high-quality longitudinal data to inform its design, implementation, and evaluation. This factsheet shares Data Quality Campaign's (DQC's) analysis of what "Data for Action 2011:…

The use of data for making educational decisions and to assess educational outcomes has been legislated by political bodies and codified by accreditation. Faculty have always used data to inform the grading process--data is gathered throughout the term to inform the letter grade assigned at the end. However, in today's educational environment,…