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Data-Driven School: Collaborating to Improve Student Outcomes [Pehme köide]

(University of WisconsinLa Crosse, United States), (Derry Township School District, United States), , (Indiana University of Pennsylvania (Emeritus), United States)
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Teised raamatud teemal:
"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 datateams 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 with lay-flat binding for easy photocopying, the book includes learning activities and helpful reproducible forms. Purchasers get access to a companion website where they can download printable copies of the reproducible materials, plus interactive computer-based tools. Subject Areas/Key Words: school psychology, assessments, data teams, teaming, data analysis, data-based decision making, problem-solving models, data leaders, student management systems, technology tools, systems change, school consultation, academic skills problems, behavioral, social-emotional, instructional decisions, progress monitoring, intervention planning, MTSS, multi-tiered systems of support, response to intervention, RTI, testing, screening, statistical software Audience: School psychologists, school and district administrators, and teachers in grades K-12; researchers and graduate students"--

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 with lay-flat binding for easy photocopying, the book includes learning activities and helpful reproducible forms. Purchasers get access to a companion website where they can download printable copies of the reproducible materials, plus interactive computer-based tools.

This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas.

Arvustused

"Most schools are data rich and assessment poor. If you work at a school that places reams of data into three-ring binders and leaves them sitting on a shelf, this book is a 'must read.' The book shows how to build a culture of data in a school. It is applicable to most settings and provides an excellent model to analyze data for individual students and entire systems. The emphasis on leadership is unique, refreshing, and important for systems change. The systematic use of data to make better decisions is key to most reform efforts and to improving student learning--this book will make that goal a reality."--Matthew K. Burns, PhD, Rose and Irving Fein Endowed Professor of Special Education, University of Florida; Assistant Director, University of Florida Literacy Institute

"The Data-Driven School is an exquisite, timely tool to help educators use data confidently and efficiently--and to ensure that 'data-based decision making' is not just a buzz phrase. I recommend this book to any teacher or practitioner who participates on a problem-solving team. The authors provide practical strategies that educators can start using immediately to overcome common teaming challenges and successfully navigate the data inquiry process. I can't wait to share this book with my colleagues and professional network!"--Jill Battal, PhD, NCSP, Data and Research Coordinator, Comprehensive Behavioral Health Model, Boston Public Schools

"This is a 'go-to' book for any school district trying to improve collective efficacy around data-based decision making. What makes this book different is its comprehensive approach. The authors align systems-level problem solving, data analysis training, technology, and relationships, and present applications at all levels of the school community--district leadership teams, school improvement teams, grade-level teams, and problem-solving teams. Case studies and a summary of key issues in each chapter provide meaningful, job-embedded professional learning opportunities for educators. I highly recommend this book to school psychologists, school leaders, and teacher leaders who want to foster a culture of improvement based on data."--Kimberly Gibbons, PhD, Director, Center for Applied Research and Educational Improvement, University of Minnesota-This book will appeal to practitioners, trainers, and students of school psychology alike.--NASP Communiqué, 11/1/2021 "Most schools are data rich and assessment poor. If you work at a school that places reams of data into three-ring binders and leaves them sitting on a shelf, this book is a 'must read.' The book shows how to build a culture of data in a school. It is applicable to most settings and provides an excellent model to analyze data for individual students and entire systems. The emphasis on leadership is unique, refreshing, and important for systems change. The systematic use of data to make better decisions is key to most reform efforts and to improving student learning--this book will make that goal a reality."--Matthew K. Burns, PhD, Rose and Irving Fein Endowed Professor of Special Education, University of Florida; Assistant Director, University of Florida Literacy Institute

"The Data-Driven School is an exquisite, timely tool to help educators use data confidently and efficiently--and to ensure that 'data-based decision making' is not just a buzz phrase. I recommend this book to any teacher or practitioner who participates on a problem-solving team. The authors provide practical strategies that educators can start using immediately to overcome common teaming challenges and successfully navigate the data inquiry process. I can't wait to share this book with my colleagues and professional network!"--Jill Battal, PhD, NCSP, Data and Research Coordinator, Comprehensive Behavioral Health Model, Boston Public Schools

"This is a 'go-to' book for any school district trying to improve collective efficacy around data-based decision making. What makes this book different is its comprehensive approach. The authors align systems-level problem solving, data analysis training, technology, and relationships, and present applications at all levels of the school community--district leadership teams, school improvement teams, grade-level teams, and problem-solving teams. Case studies and a summary of key issues in each chapter provide meaningful, job-embedded professional learning opportunities for educators. I highly recommend this book to school psychologists, school leaders, and teacher leaders who want to foster a culture of improvement based on data."--Kimberly Gibbons, PhD, Director, Center for Applied Research and Educational Improvement, University of Minnesota-This book will appeal to practitioners, trainers, and students of school psychology alike.--NASP Communiqué, 11/1/2021

Introduction 1(8)
How This Book Is Different
4(1)
Target Audience
5(1)
Organization of the Book
6(3)
PART I THE ENGINE FOR A DATA-DRIVEN SCHOOL: SYSTEMS-LEVEL PROBLEM SOLVING
1 The Rationale and Context for a Data-Driven School
9(16)
The Need for Data-Driven Schools
14(1)
Key Tenets of a Data-Driven School
15(6)
Strong Leadership with Buy-In from Key Stakeholders
16(1)
A Comprehensive Assessment System
17(3)
Easy Access to Appropriate Data for All Staff
20(1)
The Time and Resources for All Staff to Examine the Data
20(1)
Clear Connections between Data and Potential Interventions at the District, School, and Classroom Levels
21(1)
The Data-Driven School and MTSS
21(4)
2 Systems-Level Problem Identification
25(15)
The Problem-Solving Model and Systems-Level Application
25(1)
Establishing What Is Expected
26(1)
Target Setting Using Backward Planning
27(4)
Setting Targets on Other Key Variables
31(1)
Understanding What Is Occurring
32(4)
Different Approaches to Communicating Data
32(1)
Communicating the Difference between What Is Expected and What Is Occurring
33(3)
Four Purposes of Assessment
36(2)
Conclusion
38(2)
3 Systems-Level Problem Analysis
40(15)
Problem Analysis: Understanding the "Why"
40(1)
Data in Problem Analysis
41(2)
Goal of Problem Analysis: Developing Alterable Hypotheses
43(2)
Root Cause Analysis
45(2)
Problem Analysis in Context
47(1)
A Step-By-Step Guide to Problem Analysis Using Data Inquiry
47(2)
Problem Analysis? Problem Analysis? We Don't Need No Stinking Problem Analysis!
49(3)
School Budgeting
49(1)
One Size Fits All
50(1)
Superficial Problem Analysis
51(1)
What Happens When You Skip It
52(1)
Using Problem Analysis to Address Achievement Gaps
52(3)
4 Systems-Level Plan Development, Plan Implementation, and Plan Evaluation
55(22)
Systems-Level Plan Development
56(6)
Identifying Research-Based Practices and Resources
57(1)
Planning How Progress Will Be Monitored
58(4)
Systems-Level Plan Implementation
62(4)
Systems-Level Plan Evaluation
66(3)
A Practical Tool to Guide Systems-Level Problem Solving: The Data Book PowerPoint
69(8)
PART II THE ROADMAP FOR A DATA-DRIVEN SCHOOL: DATA-ANALYSIS TEAMING ACROSS MULTIPLE LEVELS
5 Data-Driven Problem Solving at the Grade, Classroom, and Student Levels: Initial Considerations
77(18)
Team Format and Membership
78(2)
Sources of Academic Data
80(10)
Benchmark Assessments: Universal Screening
82(5)
Diagnostic (Drill-Down) Assessments
87(1)
Progress Monitoring
87(1)
Outcomes Assessment
88(2)
Sources of Behavioral Data
90(5)
Office Discipline Referrals
90(1)
Behavior Screeners
91(1)
Classroom-Level Data
92(1)
Progress Monitoring
93(1)
Functional Behavioral Assessment
93(1)
Psychoeducational Evaluations
94(1)
6 Implementing Data Teaming at the School and Grade Levels for Academic Skills
95(62)
Purposes and Aims of the Teaming Process at the School and Grade Levels
96(2)
Sources of Data
98(1)
Forms and Formats Used in Data-Analysis Teaming
98(1)
The Data-Analysis Teaming Process for Academics
98(59)
Beginning-of-Year Meetings
99(26)
Formal Follow-Up Meetings
125(32)
7 Implementing Data Teaming at the School and Grade Levels for Behavior and Social-Emotional Skills
157(20)
General Considerations
158(1)
The Data-Analysis Teaming Process for Behavior
159(11)
Beginning-of-Year Meetings
159(11)
Final Steps
170(7)
PART III BUILDING THE CAPACITY FOR A DATA-DRIVEN SCHOOL
8 Data Management Using Technology
177(22)
The Evolution of Education Technology
178(1)
Technology for Data
179(7)
Data Management
180(6)
Data Management Plans
186(1)
Interoperability
187(1)
Bringing Your Data Together
188(11)
Data Warehouse/Business Intelligence Tools
189(3)
Single-Function Software
192(1)
Statistical Software
193(2)
Spreadsheet Software
195(1)
Presentation Software
196(3)
9 Developing Data Leaders
199(18)
Characteristics of Successful Data Leaders
199(10)
Data and Intervention Literacy
200(2)
Belief in the Value of Systems-Level Data-Driven Decision Making
202(2)
Leadership Skills
204(1)
Relationships
204(5)
Identifying and Appointing Data Leaders
209(1)
Keys to Effective Training of Data Leaders
210(4)
Framework for Assessing the Context for Data-Driven Leadership
214(1)
Profiles of Data Leaders
215(2)
Appendix 1 Identifying Gaps in Your Comprehensive Assessment System 217(1)
Appendix 2 Case Example: Setting Your Own Target Scores 218(3)
Appendix 3 Data Activity 221(6)
References 227(10)
Index 237
Daniel M. Hyson, PhD, NCSP, is Assistant Professor in the School Psychology Graduate Program at the University of WisconsinLa Crosse. Previously, Dr. Hyson was a school psychologist in Minnesota public schools. He then served as Data Management Coordinator for Hiawatha Valley Education District, a consortium of 13 school districts in southeastern Minnesota. In that role, he consulted with teachers and administrators to help them access, interpret, and use data from academic and behavioral assessments to improve instruction for all students. Dr. Hyson's research interests include teacherstudent relationships and their association with student engagement and achievement, and the school psychologists role in systems-level consultation and data-driven decision making.

Joseph F. Kovaleski, DEd, NCSP, is Professor Emeritus of Educational and School Psychology at Indiana University of Pennsylvania, where he directed the Doctoral Program in School Psychology. Dr. Kovaleski has worked as a school psychologist and district administrator in school districts in Pennsylvania and New Jersey. He directed Pennsylvanias Instructional Support Team Project and has served as a university consultant for Pennsylvanias Response to Intervention and Multi-Tiered System of Support initiatives. Dr. Kovaleskis special areas of expertise include using student data to inform instructional planning and behavior change programs. He has published a number of articles and book chapters on RTI and data-based decision making and presents frequently at national and state conferences. Dr. Kovaleski is a recipient of awards from the National Association of School Psychologists, the Pennsylvania Psychological Association, the Association of School Psychologists of Pennsylvania, and The Pennsylvania State University.

Benjamin Silberglitt, PhD, is Executive Director of Research, Outcomes, and Implementation at Intermediate District 287, a consortium of 11 school districts in the Twin Cities metropolitan area in Minnesota. He has founded, launched, and led the implementation of multiple education technology products since the early 2000s. Dr. Silberglitt is a cofounder of Cedar Labs, a universal data integration platform with statewide implementations in the United States and Australia. He regularly consults with school districts and presents on the effective use of data to support decision making.

Jason A. Pedersen, PhD, NCSP, is a school psychologist in the Derry Township School District in Hershey, Pennsylvania. He has worked with school staff to develop a comprehensive K-12 curriculum to foster and promote resilience, and he previously spearheaded schoolwide positive behavior support, response to intervention (RTI), and multi-tiered systems of support (MTSS) initiatives. Dr. Pedersen is coauthor (with Joseph F. Kovaleski) of a chapter on data-analysis teaming in Best Practices in School Psychology, Sixth Edition, as well as several articles in peer-reviewed journals. He has given numerous presentations on MTSS and RTI at the local, state, and national levels, and has consulted with school districts in Pennsylvania, New York, New Jersey, and Texas.