The Data Driven Classroom

Thanks to initiatives like the Common Core and Race to the Top, accountability requirements continue to be a reality for educators. Yet many are still unsure of how to use data to make well-informed instructional decisions. The Data-Driven Classroom comes to the rescue with a systematic, universal process that shows teachers how to: examine student assessment results to identify a curricular or skill area to target for individual intervention or large-group instructional revision; develop, implement, and assess the effectiveness of the intervention or revision; and develop an action plan for future instructional cycles. Author Craig A. Mertler sheds light on how teachers can make sense of overwhelming standardized test reports while avoiding pitfalls like over-interpreting data. In these pages you will also find practical classroom examples and templates designed to guide teachers of all grade levels and subject areas through the comprehensive decision-making framework.

Collect the data you need to reach every student! Veteran educators Gregory and Kuzmich provide user-friendly techniques for data-gathering, helping you to differentiate instruction. This informative book is now fully updated to support the Common Core and other key standards, and includes: Step-by-step guidance on gathering data to improve classroom dynamics, pinpoint student learning styles, adjust lessons for different learners, and inform diagnostic teaching and assessment Techniques for using data to refresh and strengthen curriculum, including numerous unit and lesson plans fully linked with the Common Core A wealth of templates for fast and simple data collection Updated differentiation strategies for the Common Core and other key standards, including the Career and College Readiness Standards and the Standards of Mathematical Practice

Connect data and instruction to improve practice 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

Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.

This indispensable practitioner's guide helps to build the capacity of school psychologists, administrators, and teachers to use data in collaborative decision making. It presents an applied, step-by-step approach for creating and running effective data teams within a problem-solving framework. The authors describe innovative ways to improve academic and behavioral outcomes at the individual, class, grade, school, and district levels. Applications of readily available technology tools are highlighted. In a large-size format for easy photocopying, the book includes learning activities and helpful reproducible forms. The companion website provides downloadable copies of the reproducible forms as well as Excel spreadsheets, PowerPoint slides, and an online-only chapter on characteristics of effective teams. This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas.

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.

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

Despite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book specifically explores the affordances of DDL for younger learners, testing its viability with teachers and students at the primary and secondary years of schooling. It features eminent and up-and-coming researchers from Europe, Asia, and Australasia who seek to address best practice in implementing DDL with younger learners, while providing a wealth of empirical findings and practical DDL activities ready for use in the pre-tertiary classroom. Divided into three parts, the volume's first section focuses on overcoming emerging challenges for DDL with younger learners, including where and how DDL can be integrated into pre-tertiary curricula, as well as potential barriers to this integration. It then considers new, cutting-edge innovations in corpora and corpus software for use with younger learners in the second section, before reporting on actual DDL studies performed with younger learners (and/or their teachers) at the primary and secondary levels of education. This book will appeal to post-graduate students, academics and researchers with interests in corpus linguistics, second language acquisition, primary and secondary literacy education, and language and educational technologies.