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Data Driven Differentiation in the Standards-Based Classroom

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ISBN-10: 0761931589

ISBN-13: 9780761931584

Edition: 2004

Authors: Gayle H. Gregory, Linda M. Kuzmich

List price: $36.95
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Description:

`Reminds educators of their commitment to children and reassures them that the tasks they must complete are doable' -Maria Elena Reyes, Associate Professor, School of Education, University of Alaska, FairbanksIn this comprehensive guide to using data-driven strategies for curriculum, instruction, and assessment, the authors present step-by-step techniques and planning tools for designing instruction with student success in mind.Topics include using data to assess classroom climate and create optimal learning conditions; using data to assess student learning styles and multiple intelligences; using data for diagnostic teaching before, during, and after instruction; using curriculum mapping…    
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Book details

List price: $36.95
Copyright year: 2004
Publisher: Corwin Press
Publication date: 2/6/2004
Binding: Paperback
Pages: 224
Size: 7.00" wide x 10.00" long x 0.50" tall
Weight: 0.880
Language: English

Gayle Gregory is an internationally known consultant who has specialized in brain compatible learning and differentiated instruction and assessment.She presents practical teacher/student-friendly strategies grounded in sound research that educators find easy to use in the classroom or schoolhouse tomorrow. Her interactive style and modeling of strategies help teachers and administrators transfer new ideas with ease.She has had extensive experience in elementary, middle and secondary schools, community colleges and universities. Gayle has also had district leadership roles including curriculum coordinator and staff development director. She has worked with Instructional Leadership Teams in…    

Lin Kuzmich , of KCS, Inc., is an educational consultant, professor, and author from Loveland, CO. She served the Thompson School District in several roles as the assistant superintendent, executive director of secondary and elementary instruction, director of professional development, and a building principal. Her school was named a 2000 winner of the John R. Irwin Award for Academic Excellence and Improvement. In addition, for the past decade she has been involved in staff development through several universities and the Tointon Institute for Educational Change. Kuzmich is an adjunct professor at both Colorado State University and University of Northern Colorado. She is a senior…    

Preface
About the Authors
Introduction: Differentiating With Data for Student Growth and Achievement
What Is Our Target?
Why Differentiate?
Theaters of the Mind: Learning Systems and the Brain
Learning Systems and Student Growth
Connecting Data to Learning
Using Classroom Data to Plan Differentiated Instructional Strategies
Targeting Growth for All Students
Collecting Data to Create a Positive Classroom Climate
Positive Classroom Connections
Assessing the Learning Environment
Using Feedback
Ritual, Respect, and Cultural History
Differentiating Classroom Climate
Differentiating Celebration and Praise
Summary
Collecting Data to Know the Learner
Going With the Flow
Different Learning Styles
Different Intelligences
Student Contracting for Reflective Learning
Intelligent Behaviors
Reflections
Collecting and Using Assessment Data for Diagnostic Teaching
Diagnostic Teaching
Pre-Assessment
Formative Assessment
Final Assessment
Assessing Our Assessments
Summary
Curriculum Approaches for Data Driven Instruction
Curriculum Mapping and Data Driven Instruction
Standards-Based Unit Planning: Sample Math Unit on Data Analysis and Probability, "The Survey Says. . . ," Grades 3 to 5
Critical Questions for Unit Planning
Pre-Assessing the Learning Gap for Unit Planning
Chunking the Learning
Summary
Other Sample Unit Plans
Adjustable Assignments for Differentiated Learning
Options for Differentiated Learning
Adjustable Learning Grids
Adjustable Learning Elements
Flexible Grouping
Differentiating Pairs
Differentiating Small Groups
Summary
Instructional Strategies That Increase Student Learning
The Art and Science of Teaching
Memory Processes and the Cognitive Learning System
Differentiating Instructional Strategies
Recognizing Similarities and Differences/Using Metaphors and Analogies
Summarizing and Note Taking
Homework and Practice
Nonlinguistic Representations
Cooperative Group Learning
Summary
Data Driven Lesson Planning for Differentiated Learning
Using Data for Lesson Planning
Essential Elements for Data Driven Lesson Planning
Chunking the Learning for Sample Unit Plans
Summary
Conclusion: Putting It All Together for Student Growth and Achievement
How Do We Do All This Without Running From the Room Screaming?
What Can We Learn From the Errors and Successes of the Best Teachers?
Why Is It Always About the Student?
References
Index