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Government scrutiny and intensified oversight have dramatically changed the landscape of education in recent years. Observers want to know how schools compare, which district is best, which states are spending the most per student on education, whether reforms are making a difference, and why so many students are failing. Some of these questions require technical answers that educators historically redirected to outside experts, but the questions leveled at all educators have become so acute and persistent that they can no longer be outsourced. This text helps educators develop the tools and the conceptual understanding needed to provide definitive answers to difficult statistical questions facing education today.
The chief executive officer of a corporation is not much different from a public school administrator. While CEOs base many of their decisions on data, for school administrators, this type of research may conjure up miserable memories of searching for information to meet a graduate school requirement. However, the value of data-based decision making will continue to escalate and the school community—students, teachers, parents and the general public—expect this information to come from their administrators. Administrators are called on to be accountable, but few are capable of presenting the mountain of data that they collect in a cohesive and strategic manner. Most statistical books are focused on statistical theory versus application, but Statistics Made Simple for School Leaders presents statistics in a simple, practical, conceptual, and immediately applicable manner. It enables administrators to take their data and manage it into strategic information so the results can be used for action plans that benefit the school system. The approach is 'user friendly' and leaves the reader with a confident can-do attitude to communicate results and plans to staff and the community.
"Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text's integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: assessment; statistics; instructional and differentiated psychology; classroom management."--Publisher's description.
Praise for the First Edition: "Creighton′s descriptions of the applicability and helpfulness of statistics for educators is especially strong. His use of plain language and school-based examples is crucial." -Scott McLeod, Assistant Professor University of Cincinnati Improve instructional leadership practice with proven, easy-to-understand strategies for data-based decision making! Since the first edition of Schools and Data, the No Child Left Behind Act has swept the country, and data-based decision making is no longer an option for educators. Today′s educational climate makes it imperative for all schools to collect data and use statistical analysis to help create clear goals and recognize strategies for improvement. Schools and Data, Second Edition, focuses on the relevance of statistics in the lives of principals and teachers. Real-life examples and step-by-step procedures for collecting and organizing data provide every school leader with the means to facilitate more appropriate and effective decision making. With a highly practical method for statistical analysis, this comprehensive yet reader-friendly new edition places special emphasis on: Connecting statistics and educators′ daily work Integrating applied technology, including Excel and SPSS software Strengthening educators′ data interpretation skills Building strong skills in problem analysis, program evaluation, data-driven decision making, and report preparation Increasing the focus on correlation and regression Packed with easy-to-follow instructions, illustrations, and real-world examples that educators can readily understand, this is an essential resource for school leaders who want to create meaningful, data-driven decisions! *Note: The author created web site that provides information and activities paralleling the individual chapters of the second education of Schools and Data text is NO LONGER AVAILABLE.
In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students’ assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are ‘best practice’ studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.
With the new federal law, No Child Left Behind, there is ever increasing pressure on schools to be accountable for improving student achievement. That pressure is taking the form of focused efforts around data-driven decision making. However, very little is known about what data-driven decision making can really tell one about improving achievement nor is there a full explanation available about what it really takes to do this work. The few examples that do exist, while proposing to get at some of these issues, make huge assumptions about educators' knowledge base and available resources necessary for success. In this book, Philip Streifer fills the gaps by laying out how this work can be done and then explains what is knowable when one actually conducts these analyses and what follow-up steps are needed to make true improvements. He provides readers with a comprehensive understanding of what data-driven decision making can and cannot tell educators about student achievement and addresses the related issues for leadership, policy development, and accountability. Senior level district administration for policy development, school level administrators who have to put policy into practice, and graduate college professors teaching data-driven decision making will find this book most useful.
Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Streifer (educational leadership, U. of Connecticut) urges the application of data-driven decision making to educational questions. He explains the processes and methodologies involved and outlines their uses in the educational sector. Chapters concentrate on longitudinal analysis for program evaluation, equity issues, the local context, budgetary control and reallocation, school improvement and systems thinking, data extraction and analysis, and information technology. Annotation copyrighted by Book News, Inc., Portland, OR
While written for mastersÆ students in any Educational Leadership concentration, this is a core text for departments that teach action research as a primary research methodology or a supplemental text for those that place it in a range of research methods. The book provides a readable overview of the PAR process similar to professional learning communities in schools. Its design reaches out to visual learners as graphic elements guide graduate students through the research methods they need to successfully complete rigorous projects. The results of the original PAR study and continued work with educational leaders lead us to believe that this approach ultimately produces the results school leaders seek and appreciate. Key Features: o Clear process through both the PAR steps employing a research logic model throughout. This benefits the graduate student or educational leader by leading them to data driven outcomes that are valid, credible and reliableGraphic elements guide the reader through the process and aid the visual learner in keeping track of the concepts behind the theory. o Reflective questions precede each section. This increases the reflective practices and routines of the reader as appropriate to the PAR process. o Tasks, written for both groups and individuals, aid participatory teams in working towards consensus and strong research designs o Practitioner stories make the lessons real and ease the emotional unease that come from tackling research practices the first time. Intended Audience: This book represents the evolution of PAR from a soft science to a process appropriate for educators in todayÆs data driven environments or for graduate students whose thesis needs to pass the recommendations of professors steeped in positivist traditions.
This book reveals the development of students' understanding of statistical literacy. It provides a way to "see" student thinking and gives readers a deeper sense of how students think about important statistical topics. Intended as a complement to curriculum documents and textbook series, it is consistent with the current principles and standards of the National Council of Teachers of Mathematics. The term "statistical literacy" is used to emphasize that the purpose of the school curriculum should not be to turn out statisticians but to prepare statistically literate school graduates who are prepared to participate in social decision making. Based on ten years of research--with reference to other significant research as appropriate--the book looks at students' thinking in relation to tasks based on sampling, graphical representations, averages, chance, beginning inference, and variation, which are essential to later work in formal statistics. For those students who do not proceed to formal study, as well as those who do, these concepts provide a basis for decision making or questioning when presented with claims based on data in societal settings. Statistical Literacy at School: Growth and Goals: *establishes an overall framework for statistical literacy in terms of both the links to specific school curricula and the wider appreciation of contexts within which chance and data-handling ideas are applied; *demonstrates, within this framework, that there are many connections among specific ideas and constructs; *provides tasks, adaptable for classroom or assessment use, that are appropriate for the goals of statistical literacy; *presents extensive examples of student performance on the tasks, illustrating hierarchies of achievement, to assist in monitoring gains and meeting the goals of statistical literacy; and *includes a summary of analysis of survey data that suggests a developmental hierarchy for students over the years of schooling with respect to the goal of statistical literacy. Statistical Literacy at School: Growth and Goals is directed to researchers, curriculum developers, professionals, and students in mathematics education as well those across the curriculum who are interested in students' cognitive development within the field; to teachers who want to focus on the concepts involved in statistical literacy without the use of formal statistical techniques; and to statisticians who are interested in the development of student understanding before students are exposed to the formal study of statistics.