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As the United States continues to be a nation of immigrants and their children, the nation's school systems face increased enrollments of students whose primary language is not English. With the 2001 reauthorization of the Elementary and Secondary Education Act (ESEA) in the No Child Left Behind Act (NCLB), the allocation of federal funds for programs to assist these students to be proficient in English became formula-based: 80 percent on the basis of the population of children with limited English proficiency1 and 20 percent on the basis of the population of recently immigrated children and youth. Title III of NCLB directs the U.S. Department of Education to allocate funds on the basis of the more accurate of two allowable data sources: the number of students reported to the federal government by each state education agency or data from the American Community Survey (ACS). The department determined that the ACS estimates are more accurate, and since 2005, those data have been basis for the federal distribution of Title III funds. Subsequently, analyses of the two data sources have raised concerns about that decision, especially because the two allowable data sources would allocate quite different amounts to the states. In addition, while shortcomings were noted in the data provided by the states, the ACS estimates were shown to fluctuate between years, causing concern among the states about the unpredictability and unevenness of program funding. In this context, the U.S. Department of Education commissioned the National Research Council to address the accuracy of the estimates from the two data sources and the factors that influence the estimates. The resulting book also considers means of increasing the accuracy of the data sources or alternative data sources that could be used for allocation purposes.
Children are already learning at birth, and they develop and learn at a rapid pace in their early years. This provides a critical foundation for lifelong progress, and the adults who provide for the care and the education of young children bear a great responsibility for their health, development, and learning. Despite the fact that they share the same objective - to nurture young children and secure their future success - the various practitioners who contribute to the care and the education of children from birth through age 8 are not acknowledged as a workforce unified by the common knowledge and competencies needed to do their jobs well. Transforming the Workforce for Children Birth Through Age 8 explores the science of child development, particularly looking at implications for the professionals who work with children. This report examines the current capacities and practices of the workforce, the settings in which they work, the policies and infrastructure that set qualifications and provide professional learning, and the government agencies and other funders who support and oversee these systems. This book then makes recommendations to improve the quality of professional practice and the practice environment for care and education professionals. These detailed recommendations create a blueprint for action that builds on a unifying foundation of child development and early learning, shared knowledge and competencies for care and education professionals, and principles for effective professional learning. Young children thrive and learn best when they have secure, positive relationships with adults who are knowledgeable about how to support their development and learning and are responsive to their individual progress. Transforming the Workforce for Children Birth Through Age 8 offers guidance on system changes to improve the quality of professional practice, specific actions to improve professional learning systems and workforce development, and research to continue to build the knowledge base in ways that will directly advance and inform future actions. The recommendations of this book provide an opportunity to improve the quality of the care and the education that children receive, and ultimately improve outcomes for children.
Dual language education is a program that combines language minority and language majority students for instruction through two languages. This book provides the conceptual background for the program and discusses major implementation issues. Research findings summarize language proficiency and achievement outcomes from 8000 students at 20 schools, along with teacher and parent attitudes.
The first comprehensive examination of the field, this book brings together stakeholders representing a variety of perspectives to explore how educators actually use data and technology tools to achieve lasting improvement in student performance. Contributors: David V. Abbott, Carrie Amon, Jonathan Bertfield, Cornelia Brunner, Fred Carrigg, Jere Confrey, Katherine Conoly, Valerie M. Crawford, Chris Dede, John Gasko, Greg Gunn, Juliette Heinze, Naomi Hupert, Sherry P. King, Mary Jane Kurabinski, Daniel Light, Lisa Long, Michael Merrill, Liane Moody, William R. Penuel, Luz M. Rivas, Mark S. Schlager, John Stewart, Sam Stringfield, Ronald Thorpe, Yukie Toyama, Jeffrey C. Wayman, and Viki M. Young. “If you want to understand usable knowledge, read Data-Driven School Improvement.” —Ellen Condliffe Lagemann, Harvard University “It is reassuring to know that at least some of the data being generated in our data-driven age are being used to make wiser decisions. We can all learn from these illustrative accounts.” —David C. Berliner, Mary Lou Fulton College of Education, Arizona State University “Replete with examples from real schools and districts, this volume provides a multi-layered portrait of what it takes to establish a culture of data use. Readers will come away with an appreciation of the systemic changes needed to reap the full potential of data-driven decision making.” —Barbara Means, Center for Technology in Learning, SRI International