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Transforming Teaching and Learning Through Data-Driven Decision Making

ISBN-10: 1412982049
ISBN-13: 9781412982047
Edition: 2012
List price: $37.95 Buy it from $16.10
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Description: Connect data and instruction to improve practiceThis book helps bridge the gap between classroom practice and the best of what is known from educational psychology. Teachers will find cutting-edge advances in research and theory on human learning,  More...

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Book details

List price: $37.95
Copyright year: 2012
Publisher: Corwin Press
Publication date: 4/10/2012
Binding: Paperback
Pages: 280
Size: 6.00" wide x 8.75" long x 0.75" tall
Weight: 1.232

Connect data and instruction to improve practiceThis book helps bridge the gap between classroom practice and the best of what is known from educational psychology. Teachers will find cutting-edge advances in research and theory on human learning, teaching, and instruction in an easily understood and transferable format. The authors provide detailed guidance for using data to inform practice and tools to align teacher preparation and professional development with today’s best practices and most current research. This resource will provide valuable tools for:In-service teachersPre-service teachersInstructional leadersSchool and district administrators

<span style="FONT-SIZE: 13pt; FONT-FAMILY: 'Arial','sans-serif'"> <p style="LINE-HEIGHT: normal">Sharnell S. Jackson is a nationally recognized instructional leadership consultant, coach, and executive strategist for school districts, foundations, businesses, and corporations. She has more than thirty-five years of K-12 experience as a classroom teacher, teacher leader, assistant principal, state director, chief executive officer of enterprise information and e-Learning. She has worked in rural, suburban, urban school districts, state departments and regional educational laboratories nation-wide. </p><p style="LINE-HEIGHT: normal">Sharnell is the Founder/CEO of her own company, Data-Driven Innovations Consulting, with a mission of implementing effective professional learning process and practices of formative assessment evidence to inform teachers’ instructional planning, and by using multiple forms of data to improve student achievement of instructional outcomes. </p><p style="LINE-HEIGHT: normal">Sharnell has served on a number of technical working groups, task forces, and advisory boards. She has served as a panelist on the U.S. Department of Education Institute of Education Sciences IES Practice Guide: Using Student Achievement Data to Support Instructional Decision Making, was a member of longitudinal data systems working groups commissioned by NCES, was as data model task force member for the National Forum on Education Statistics PK-12, and served on Regional Advisory Committee member to advise the U.S. Department of Education on technical assistance needs of educators. She has served as a governance board member for the Schools Interoperability Framework, CoSN board member, ISTE National Technology Standards Advisory Committee Member, Microsoft K-12 Advisory Committee Member, past president-elect of the Illinois Computing Educators, and serving as board member for the Professor Garfield Foundation.</p><p style="LINE-HEIGHT: normal">She received her Masters in Curriculum and Instruction from National Louis University, Illinois; and a Master’s in Science, Mathematics, and Instructional Technology from NASA Fellowship at Wheeling Jesuit University, Virginia; and a Master’s in Educational Administration from Lewis Jesuit University, Illinois, and completed advanced studies in high school astronomy, biology, chemistry, and environmental studies at The University of Chicago.</p></span>

Ellen Mandinach is a Senior Research Scientist at WestEd. Dr. Mandinach has been a leading expert in the area of data-driven decision making at the classroom, district, and state levels. Her work over the past several years has focused on understanding how educators are using data to inform practice. She has written and spoken widely on the topic, and has served on a number of technical working groups and advisory boards on data use. Dr. Mandinach served as an expert panelist on the IES Practice Guide for data-driven decision making and on the technical working group commissioned by NCES to understand how researchers can better use the statewide longitudinal data systems. She has led discussions, funded by the Spencer Foundation, about how schools of education and provide courses around data-driven decision making to build human capacity. Dr. Mandinach has served on the research staffs of Educational Testing Service, the Education Development Center's Center for Children and Technology, and CNA Education. Although trained in educational measurement, Dr. Mandinach's career has focused on aspects of educational technology. Dr. Mandinach has authored a number of publications for academic journals, technical reports, and four books. She wrote Data-Driven School Improvement: Linking Data and Learning. She has regularly presented at international, national, and regional conferences on education and psychology. She has served as the President of the American Psychological Association's Division of Educational Psychology. She received an AB in psychology from Smith College and a Ph.D. in educational psychology from Stanford University.

Acknowledgments
About the Authors
Introduction
How Does Educational Psychology Fit Into the Mix?
Why Do We Need Another Book on the Topic?
Why These Authors?
Outline for the Book
The Context of Data-Driven Decision Making
Answering the Questions
Some Highlighted References
Glossary
What Research Tells Us About Data-Driven Decision Making
Foundations of Data-Driven Decision Making
Components of Data-Driven Decision Making
Concluding Comments
Some Highlighted References
Glossary
Technology to Support Data-Driven Decision Making
A Caveat
Technologies Applicable Across Districts
Emerging Technologies
The Role of Statewide Longitudinal Data Systems
Summing Up
Some Highlighted References
Glossary
Continuous Capacity Building: Data-Driven Decision-Making Skills and Pedagogical Data Literacy
The Continuum From Pre-Service to Professional Development
Data-Driven Skills
Summing Up
Some Highlighted References
Glossary
Using Data for Continuous Improvement: Processes and Structures
Components of Data Use
Concluding Comments
Some Highlighted References
Glossary
Building a Culture to Use Data
Organizing for Collaborative Inquiry and Data Use
Forms of Data Use for Teachers
Supporting Teacher Data Use
Summing Up
Our Hypothetical Schools
Some Highlighted References
Glossary
Differentiated Instruction Using Formative Assessments
Forms of Differentiation
Organizing Instruction
Summing Up
Some Highlighted References
Glossary
CHOPS: Learning From Examples and Closing Thoughts
Practicing Data-Driven Decision Making
Putting Theory Into Practice: The Catch-22
Change Management: Using Data to Improve Education
Endnotes
References
Index

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