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- Herausgeber: John Wiley & Sons
- Kategorie: Bildung
- Sprache: Englisch
The bestselling guide for school leaders--updated in a new edition Data-driven instruction is the philosophy that schools should focus on two simple questions: how do you know if are students learning? And when they are not, what do you do about it? Driven by Data 2.0 is a practical guide that answers these questions to empower schools to achieve significant gains in student achievement. Rooted in a proven framework that has been implemented in thousands of schools, the book presents what makes schools successful along with tools to put the framework into place to make data work for your schools: * Assess--set the roadmap for learning * Analyze--identify why students struggle * Act--teach more effectively what students need * Build the culture--train and develop your staff so that data-driven instruction can thrive If you're a K - 12 leader, coach, or teacher looking to implement data-driven instruction in your school district, Driven by Data 2.0 has the tools to train your staff: PD materials, videos of exemplar practice and all the resources you need to achieve remarkable results.
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Veröffentlichungsjahr: 2019
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Table of Contents
Cover
Video Content
Additional Materials
About the Author
Acknowledgments
Foreword
Introduction
THE FRAMEWORK: WHAT IS THIS ALL ABOUT?
THE SEVEN MISTAKES THAT MATTER
THE KEY PRINCIPLES OF DATA-DRIVEN INSTRUCTION
HOW TO USE THIS BOOK
CONCLUSION
PART ONE: The Roadmap to Results
Chapter 1: Assessment: Set Your Landmarks (and Your Mile Markers)
AN OPENING STORY
TOWARD MEANINGFUL RIGOR: CREATING THE ROADMAP
ASSESSMENT MYTHS DISPELLED
IMPLEMENTATION: FIRST STEPS FOR TEACHERS AND LEADERS
Chapter 2: Analysis: Where and Why We Left the Route
A CASE STUDY
FOUNDATIONS OF EFFECTIVE ANALYSIS
DATA MEETINGS, PART I: LOCKING IN DEEP ANALYSIS
IMPLEMENTATION: FIRST STEPS FOR TEACHERS AND LEADERS
Chapter 3: Action: Charting a Better Path
ACTION PLANS: ALIGNING THE “WHY” TO THE “HOW”
ACTION IN THE CLASSROOM: EFFECTIVE RE-TEACHING
DATA MEETINGS, PART II: LOCKING IN QUALITY ACTION
ACCOUNTABILITY: FOLLOW UP ON ACTION PLANS
IMPLEMENTATION: FIRST STEPS FOR TEACHERS AND LEADERS
Chapter 4: A Data-Driven Culture: Clearing the Road for Rigor
CONDITIONS FOR SUCCESS
IMPLEMENTATION: FIRST STEPS FOR TEACHERS AND LEADERS
PART TWO: Where the Rubber Hits the Road
Chapter 5: Overcoming Obstacles: Answers to Frequently Asked Questions
DDI IMPLEMENTATION RUBRIC
WHAT TO DO WHEN THERE'S A “2”
FREQUENTLY ASKED QUESTIONS
Chapter 6: Leading PD for Adults
FIVE FREQUENT ERRORS ASSOCIATED WITH ADULT PD
FOLLOW THE DATA … AND JUST DO IT
LIVE THE LEARNING
FOLLOW-UP
Chapter 7: All PD Workshop Materials and Key Documents
HOW TO USE THE RUBRICS AND ONE-PAGERS
HOW TO USE THE WORKSHOP MATERIALS
PREVIEW: DATA-DRIVEN INSTRUCTION
Bibliography
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Assessment Evaluation Worksheet
Chapter 2
Table 2.1 North Star Interim Assessment Results Analysis Template
Chapter 5
Table 5.1 What To Do When There's a “2”: Recommended Action Steps to Increase...
List of Illustrations
Chapter 1
Figure 1.1 Advanced Placement (AP) Exam: North Star Washington Park High Scho...
Figure 1.2 Minnesota Comprehensive Assessment (MCA): Yinghua Academy, Reading...
Figure 1.3 The ripple effect
Figure 1.4 Texas State Assessment (STAAR): Nathaniel Hawthorne Elementary Sch...
Figure 1.5 Washington, DC, PARCC Assessment: Whittier Education Campus, ELA P...
Chapter 2
Figure 2.1 North Carolina End of Course Test: Nations Ford Elementary School,...
Figure 2.2 New Mexico PARRC Assessment: Northeast Elementary School, ELA Perc...
Figure 2.3 New Jersey PARRC Assessment: North Star Clinton Hill Middle School...
Figure 2.4 Texas State Assessment (STAAR): IDEA Brownsville Academy, 2017 Mat...
Chapter 3
Figure 3.1 North Carolina End of Course Test: Whitewater Middle School, Math ...
Figure 3.2 Texas State Assessment: Leonore Kirk Hall Elementary School, Math ...
Figure 3.3 Louisiana End of Course (EOC) Test: Cohen College Prep High School...
Figure 3.4 New Jersey PARRC Assessment: Alexander Street Elementary School, M...
Figure 3.5
Figure 3.6 Utah State SAGE Assessment: Northwest Middle School, Math Percenta...
Chapter 4
Figure 4.1 New York State Exam: Achievement First Middle Schools, ELA Percent...
Figure 4.2 New York State Exam: Achievement First Middle Schools, Math Percen...
Figure 4.3 Minnesota Multiple Measurements Rating (MMR): Friends of Education...
Figure 4.5 Texas State Assessment (STAAR): Dan D. Rogers Elementary School, E...
Figure 4.6 Minnesota Comprehensive Assessment (MCA): Eagle Ridge Academy, Mat...
Figure 4.7 School Performance Framework: Denver Green School, School Report C...
Guide
Cover
Table of Contents
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Praise for Driven by Data 2.0
“This gem of a book is one of the most important books to come out on American education in years. Paul Bambrick-Santoyo speaks from a platform of immense credibility given the tremendous results of low-income students under his leadership. Three cheers to a front-line educator for kicking off a new genre of non-fiction writing in education: a practical guide for dramatic school improvement that proves that children from every background can achieve at high levels when we as adults get our part right.”
– Jon Schnur, Chairman and Chief Executive Officer of America Achieves
“This book superbly describes the change process a leader can go through with faculty to make data driven instruction a reality in their school. Amazingly practical. There's nothing like it out there!! You'll also find the rationale and all the structures for data analysis, scripts of how to analyze student thinking and come up with appropriate re-teaching strategies for weak areas, and precise guidance on how to run effective data meetings. This is the whole package.”
– Jon Saphier, Founder and President of Research for Better Teaching and Chairman Emeritus of Teachers 21
“Paul Bambrick-Santoyo's book is a triple threat to the achievement gap: not only has he presided over dramatic achievement gains at the schools he leads in Newark, NJ, but he has helped scores of other schools make similar gains in New York City, Chicago, New Orleans, Oakland, and elsewhere around the country–and he has been able to distil the lessons learned into a brilliant, tightly organized, and highly practical book. Bravo to Paul for an amazing contribution to the field!”
– Kim Marshall, Leadership consultant and author of the Marshall Memo
“Driven by Data 2.0 is a stand-out among the million books principals have cluttering their shelves on leadership and student achievement. This one won't collect dust! Bambrick-Santoyo provides an unequivocal blueprint on implementing effective change that will bolster student achievement in an actionable way.”
– Nakia Haskins, Principal, Brooklyn Brownstone School
DRIVEN BY DATA 2.0
A Practical Guide to Improve Instruction
Paul Bambrick-Santoyo
Copyright © 2019 John Wiley & Sons. All rights reserved. Videos © 2019 by Uncommon Schools. All rights reserved.
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Library of Congress Cataloging-in-Publication Data
Names: Bambrick-Santoyo, Paul, 1972- author.
Title: Driven by data 2.0 : a practical guide to improve instruction / Paul Bambrick-Santoyo.
Other titles: Driven by data two point zero | Driven by data two point ott
Description: Second Edition. | San Francisco, California : Jossey-Bass, [2019] | Includes bibliographical references and index.
Identifiers: LCCN 2019000175 (print) | LCCN 2019002524 (ebook) | ISBN 9781119524779 (Adobe PDF) | ISBN 9781119524762 (ePub) | ISBN 9781119524755 | ISBN 9781119524755¬(paperback) | ISBN 9781119524779¬(eBook) | ISBN 9781119524762¬(eBook)
Subjects: LCSH: Education—United States—Data processing—Case studies. | Educational tests and measurements—United States—Case studies. | Educational evaluation—United States—Case studies. | School improvement programs—United States—Case studies. | School management and organization—United States—Case studies.
Classification: LCC LB1028.43 (ebook) | LCC LB1028.43 .B35 2019 (print) | DDC 370.285—dc23
LC record available at https://lccn.loc.gov/2019000175
Cover image: Courtesy of Uncommon Schools
Cover design: Wiley
SECOND EDITION
Video Content
How to Access the Videos
Here is an overview of the video clips for your quick reference.
Analysis—Where and Why We Left the Route (Chapter 2)
Clip
Technique
Description
1
See It (Success)—Weekly Data Meeting
“I’d like to start with what I noticed is strong…”
Paul Bambrick-Santoyo praises a specific achievement in classrooms and connects the teacher action to the successes.
2
See It (Standard)—Weekly Data Meeting
“What would a student need to know and be able to do to show mastery …?”
Mary Ann Stinson has her teachers begin their weekly data meeting by analyzing a Common Core State Standard for writing, a teacher exemplar, and a student exemplar.
3
See It (Standard & Exemplar)—Weekly Data Meeting
“One of our favorite power standards …”
Na'Jee Carter works with teachers to unpack the standard, to analyze the teacher and student exemplar, and to create a robust know/show chart before analyzing the student work for the gap.
4
See It, Name It (Gap)—Weekly Data Meeting
“Using the language of the standard …”
Juliana Worrell works with a team of teachers to utilize the language of the standard and the exemplar to determine the highest-leverage gap.
5
See It, Name It. (Gap)—Weekly Data Meeting
“We want to ground ourselves in the language of the chart.”
Na'Jee Carter leverages the know/show chart to identify the highest leverage conceptual and procedural gap in the student work.
6
See It, Name It. (Gap)—Weekly Data Meeting
“… What are the key misconceptions demonstrated in this student work?”
Mary Ann Stinson and her teachers identify the highest leverage gap that needs to be re-taught using student work.
Action—Charting a Better Path (Chapter 3)
Clip
Technique
Description
7
Re-Teach Modeling—Set the Task (Teaching Clip)
“I want you to write down what I'm doing.”
Art Worrell prepares his students to take notes during the think-aloud.
8
Re-Teach Modeling—Model the Thinking (Teaching Clip)
“When I think about the Era of Good Feelings, right away I'm thinking about nationalism.”
Art Worrell walks his students through the thought process he uses to read a history text effectively, modeling annotation skills and providing the rationale for them step-by-step.
9
Re-Teach Guided Discourse (Teaching Clip)
“… one-third black, one-third white, one-third gray …”
Andrew Shaefer shows students three different examples of how their classmates have solved a math problem, pushing them to determine through discourse which one is correct.
10
Aggressive Monitoring: Mark Up Student Work and Cue Students (Teaching Clip)
“How did you know to use addition?”
Sari Fromson aggressively monitors as her students complete their independent practice in math, giving meaningful feedback to each student multiple times in one lesson.
11
Do It (Plan)—Weekly Data Meeting
“Create the best re-teach plan possible.”
Juliana Worrell works with a team of teachers to collaboratively plan a re-teaching script.
12
Do It (Plan)—Weekly Data Meeting
“It's time to consider the re-teach plan … ”
Denarius Frazier plans a re-teach alongside his teacher, and then they compare their plans to craft a final re-teach plan for a geometry class.
13
Do It (Practice)—Weekly Data Meeting
“We want to get through the model succinctly.”
Mary Ann Stinson has her teachers practice the re-teach plan.
14
Do It (Practice)—Weekly Data Meeting
“What is the conceptual understanding that [your students] would need?”
Laura Garza works with her teachers to determine the key understanding for a reteach lesson, planning side-by-side before they practice.
15
Do It (Practice)—Weekly Data Meeting
“Now we are going to take this practice live.”
Denarius Frazier gives specific feedback while his teacher practices the re-teach lesson.
16
Do It (Follow Up)—Weekly Data Meeting
“I am going to come in on Friday at 9 a.m.”
Mary Ann Stinson asks her teachers to list all the action items at the end of the weekly data meeting and to schedule the follow-up.
17
Do It (Follow Up)—Weekly Data Meeting
“We can spiral this task …”
Denarius Frazier works with his teacher to identify multiple opportunities for assessing the identified re-teach skill, and they establish a comprehensive timeline for next steps.
Leading PD (Chapter 6)
Clip
Technique
Description
18
See It, Name It—Leading PD
“Let's put all of these three comments together.”
Paul Bambrick-Santoyo prompts participants to unpack a video of an effective weekly data meeting and stamps the key points and core idea.
19
Do It (Plan)—Leading PD
“You've just walked through the beginning of a weekly data meeting.”
Paul Bambrick-Santoyo asks participants to plan the know/show chart for the case study embedded in the weekly data meeting PD.
20
Do It (Practice)—Leading PD
“What are the key actions they could take to improve?”
Paul asks the group of leaders in Dallas to practice the See It, Name It of the weekly data meeting they planned.
21
Reflect—Leading PD
“Take two minutes in your school teams: what are the key actions we can take to improve our meeting?”
Paul Bambrick-Santoyo prompts the group to reflect on their own gaps in implementation and name key takeaways.
To access the videos online, please visit www.wiley.com/go/drivendata2.
Additional Materials
How to Access Additional Materials
Here is a quick overview of additional materials available online.
Description:
All the materials needed to lead a professional development session for instructional leaders on data-driven instruction:
Session plan for Data-Driven Instruction 101
PowerPoint Presentation for Data-Driven Instruction 101
Logistics Memo—Order of DDI Materials
Handouts:
Introduction to DDI
DDI Reflection Template
Handout
Interim Assessment Case Study, 5
th
Grade Literacy
Literacy 5-3 Assessment
Literacy 5-3 Results
Analysis and Action Plan Template
Interim Assessment Case Study, 4
th
Grade Math
Math 4-2 Assessment
Math 4-2 Results
Analysis and Action Plan Template
Interim Assessment Case Study, 9
th
Grade Algebra
Algebra 1-2 Assessment
Algebra Results
Analysis and Action Plan Template
Exemplar Analysis
Exemplar Math ES Analysis and Action Plan
Exemplar Literacy MS Analysis and Action Plan
Exemplar Math MS Analysis and Action Plan
Exemplar English HS Analysis and Action Plan
Leading Analysis Meetings
One-pager—Weekly Data Meetings
Cheatsheet—Weekly Data Meetings
Action
Re-teaching One-pager
Follow-up Accountability Measures
Student Assessment Reflection Template
Teacher Video-Date Case Study
Elem Case Study Assessment Results
Douglass Street Case Study
Douglass Street School Case Study
Calendars
MS Assessment Calendar
HS Assessment Calendar
ES Assessment Calendar
Monthly Map Blank Template
How to Create Monthly Map
Monthly Map—Data-Driven Instruction Sample
Rubrics
Implementation Rubric for Data-Driven Instruction
Implementation Rubric—What to do When You're a 2
Results Meeting Protocol
To access the videos online, please visit www.wiley.com/go/drivendata2
About the Author
Paul Bambrick-Santoyo is the Chief Schools Officer for Uncommon Schools and the Founder and Dean of the Leverage Leadership Institute, creating proofpoints of excellence in urban schools worldwide. Author of multiple books, including Driven by Data, Leverage Leadership 2.0, Get Better Faster, A Principal Manager's Guide to Leverage Leadership, and Great Habits, Great Readers, Bambrick-Santoyo has trained over 20,000 school leaders worldwide in instructional leadership, including multiple schools that have gone on to become the highest-gaining or highest-achieving schools in their districts, states, and/or countries. Prior to these roles, Bambrick-Santoyo co-founded the Relay National Principals Academy Fellowship and spent 13 years leading North Star Academies in Newark, NJ, whose results are among the highest-achieving urban schools in the nation. He also taught for six years in a bilingual school in Mexico City.
Acknowledgments
The ideas in Driven by Data 2.0 were formed and shaped through the work with thousands of schools across the country. Each interaction with a school leader—and each opportunity to give a workshop—helped sharpen the focus of the model presented here and allowed it to be tested in a wide variety of environments. All of those who put it to the test and gave me feedback along the way had a profound influence on the end product. Along the way, Alyssa Ross was our writer extraordinaire who deftly managed the revisions of this book with a sharp mind and gift for the right words, and David Deatherage brought his clear vision to the creation of the videos that accompany the text. Thank you, Alyssa and David, for working alongside me on so many of these books! Thanks as well to Sam, Judy, Jacque, Angelica, Jesse, Christine, Brett and everyone who supported me along the way.
Uncommon Schools was the first laboratory where we honed data-driven instruction. From my early work with Jamey Verrilli, Mike Mann, and Julie Jackson to the nearly one hundred leaders who have put this work to the test every day in the last 20 years.
The real heroes of this book are all the school leaders who have launched this work successfully and are transforming urban education nationwide. Only 22 of those school leaders were able to be highlighted in this book's success stories, but there are so many more!
While the school leaders are the heroes of the book, the heroes of my heart are my wife and children. Ana, Maria, and Nicolas were all quite young when I started on this journey, and they have watched this work grow while I have seen them head to middle school, high school, and now college. All along, they endured many an afternoon of me writing on the computer or staring thoughtfully off into space! Gaby stood by me through it all, supporting me in my weakest moments and providing me daily inspiration of how to love and listen.
Thank you to each and every one of you who have had an impact in the field. With your help, we will improve and re-shape education worldwide.
Foreword
If you've ever taught in an American public school, you know the drill. The principal alerts you to her upcoming annual trip to “observe” your class. You sweat the preparation of what you hope is your best lesson. She jots notes in the back of your room. Your kids muster their least disruptive behavior, perhaps on account of the rare presence of two additional humongous eyeballs on their necks.
A few weeks later (if all goes well, not a few months later), there's the post-observation conference. The principal slides a comprehensive teacher evaluation rubric in standard-issue form across her desk. She's rated you “satisfactory” in most of the boxes, “needs improvement” in a few. Should you dispute the recommendations in the space allotted on the bottom of the template or smile and pledge to do better? Best-case scenario: the principal supports you, knows her stuff, and shares helpful feedback on your craft—for example, how you can be more engaging in your delivery. More typically, she encourages you to pick up the pace so that you can “cover” the required curriculum by year's end or urges you to “integrate technology” per the district mandate to modernize. You sign your review, close your classroom door, and resume teaching, relieved you won't have to relive these rituals for another year. As both professional development and accountability, this has been our education system's losing playbook for as long as the oldest teachers you can remember can themselves remember.
Then came Paul Bambrick-Santoyo—a brilliant instructional leader and trainer of principals—charging onto the field like a middle linebacker with the game-changing volume you're holding in your hands, now updated and revised: Driven by Data 2.0. Mr. Bambrick—as he's known to students—has the instructional equivalent of linebacker eyes. His peripheral vision catches all the subtle teacher moves in any one lesson, and he's peripatetic, ranging widely across a school, weaving in and out of classrooms. Gone are the set-piece annual observations. But what's really significant here—in light of the broken observational paradigm—is that Bambrick has trained his eyes on the students as much as the teachers. The first question provoked by his work is ontological, the schooling equivalent of the fabled tree-forest conundrum:
If there's teaching going on, but the students aren't learning, is it really teaching?
I first met Bambrick in the late summer of 2002, when he arrived at North Star Academy. Five years earlier, I had co-founded and then co-led North Star with one of the greatest teachers and principals of our generation, James Verrilli. It was one of New Jersey's very first charter public schools, located in the city of Newark, a troubled district that had been taken over by the state. We'd begun with seventy-two fifth and sixth graders, picked from a random lottery, 90% of whom were eligible for a subsidized lunch, 99% of them black or Latino, and who scored—on average—worse than their Newark peers on the state test. North Star was immediately successful at generating huge demand from low-income families, creating an electric student culture that was celebrated in the media and copied by countless other schools, and posting initial test state results that were well above the district average.
Bambrick had been sent to us by an organization with which I'd been involved—New Leaders for New Schools—as the principalship equivalent of a medical resident. He was supposed to spend the year with us and learn how to be a school leader. Had he been born a century ago, my hunch is that Bambrick would have been a priest. Instead he's tethered his humble but deep commitment to social justice—most manifest in two years of Jesuit Community Service as a campus minister in Mobile, Alabama—to the work of closing the achievement gap, one of the most pressing issues of our day. At the same time, he generated a strong sense of academic rigor and the value of high educational expectations and standards during six years as an AP English teacher, basketball coach, and assistant principal at an International Baccalaureate high school in Mexico City, where his wife is from and where he started his family. A 1994 graduate of Duke University, Bambrick is a chronically curious student of how humans learn and a habitual problem solver. He found in North Star a school committed to innovation and excellence.
At North Star and literally hundreds of other schools, I'd watched teachers covering an ambitious geometry curriculum, the Diary of Anne Frank, an entire earth science textbook; observed teachers standing in front of the classroom covering World Wars I and II, or assigning students to write e-mails on laptops to pen pals in Australia. But what math, science, reading, writing, and history had the students really learned? What portion of the intended skills and covered knowledge had lodged in their brains? Where did the lessons fail to meet their mark? Who wasn't getting what?
Many strong teachers know the answers to these questions because they constantly “check for understanding” throughout their classes, and the very best adjust their instruction to meet the learning objectives. But it's hard even for the best teachers, and nearly impossible for novices, to track student progress in an organized, effective way in real time. Novice teachers are, after all, learning to teach, but are they teaching to learn? It's a well-worn convention for teachers to give weekly quizzes or unit tests, which should ostensibly address our core problem, except when those assessments—as is so often the case in the vast majority of schools—lack alignment with the meaningful standards for which students are meant to gain mastery.
As a result, for decades, American public schools have given students passing marks, promoted them to the next grade, and then (in the summer) received state test scores showing an alarming number of those promoted students lack basic proficiency, much less mastery, of the concepts they were supposed to learn. Come the fall, even when enterprising teachers use those state test results to inform their instruction, it's already too late. Students have moved on to new teachers and teachers have moved on to new students. Such a vicious cycle tragically harms precisely those children who need the greatest attention: those who come into the lowest-performing public schools with the weakest skills and the most challenging social and economic circumstances. Without the ability to diagnose and support their progress toward meeting college-prep learning standards on a systematic basis, too many adults consign too many of our children to a destiny based on their demography.
About the same time Bambrick started at North Star, another young leader named Doug McCurry had begun to build data systems to track student learning at Amistad Academy, a high-performing charter school serving low-income students in New Haven, Connecticut. Every six weeks, Amistad administered “Curriculum-Based Measurements”—aligned with the state standards—to track student progress. One day I watched as McCurry's team, teacher by teacher, came to see him armed with data on which students had learned which state standards. They used the data to diagnose, for example, which individual students were struggling with multiplying fractions.
To me, it looked like McCurry had created the school equivalent of what data-driven leaders had done to revolutionize public service, business, politics, and sports. In the mid-1990s, for instance, Oakland A's General Manager Billy Beane armed his scouts with new metrics to find productive, undervalued baseball players. Money Ball was born, and it launched a new era of data analytics that has revolutionized every sport from basketball to swimming to tennis.
Not long after, I encouraged my colleagues to spend time watching McCurry's data meetings in New Haven. Bambrick did that—and he also went to school on the whole subject. He looked at how the public schools across the country had been quietly doing similar work over the preceding decade. He led a team of teachers in writing a set of interim assessments aligned with the New Jersey state standards; used the assessments to push our program toward increasing levels of college-ready rigor and expectation for all students; designed an effective spreadsheet system for tracking student progress; and, along with co-leader and co-founder James Verrilli, changed the culture of the school so that our leaders and teachers gathered around data to drive student learning. Our teachers began to engage and own responsibility for upping the rigor of student learning, re-teaching failed lessons, analyzing errors in understanding, and creating better assessment tools. Their meetings moved from the sad convention of post-observation conferences to data meetings in which they fought as tenaciously for student achievement gains in their classrooms as the A’s did to land the best player.
Fast forward to today, and the idea of data-driven instruction has caught on in a larger educational universe. Bambrick has become a pathfinder on the entire subject, having trained more than twenty thousand school leaders serving millions of children in cities all over the country and across the globe. The results can be seen not only in the twenty-two case studies in this book but in schools and classrooms worldwide.
Legendary principals like Nikki Bridges at Leadership Prep Ocean Hill, a USDOE Blue Ribbon School, pioneered weekly data meetings, in which they met with each teacher once a week to look carefully at student work and the details of student learning patterns. Dallas Independent Schools Principal Laura Garza (featured in this book) followed suit, with weekly data meetings held in her “data room” that helped them visualize student progress against the standard. They paved the way for other leaders to follow.
As it happens, leaders and teachers often arrive at his sessions highly skeptical about an over-tested culture. They imagine that data-driven instruction is an elaborate stratagem for promoting “test prep.” They often show up because under the accountability pressure generated by federal law, they are desperate to find a magic formula to improve their state test results and avoid public censure. At the highest conceptual level, this accountability—despite all its faults—has indeed focused educators' minds on accountability for student achievement in low-income communities. If accountability gets them through the door, Bambrick is waiting for them on the other side with meaningful strategies and ideas that are at the heart of this wonderfully accessible and practical book. What's most remarkable about his training—and it's captured in this book—is that Bambrick gets the adults to “live the learning.” Instead of lecturing or hectoring his audience, he creates a highly energetic learning environment where his audience does the heavy intellectual work. (His subsequent books have shared all the details of that success!)
We are very fortunate that Bambrick has codified his work in Driven by Data 2.0. Data-driven instruction is not a panacea. But—developed and used in the way that Bambrick describes—we have here one of the more important tools to ensure that America's classrooms are not simply filled with teaching but are assuredly alive with learning, growth, and meaningful achievement for all students.
October 2018
Norman Atkins
Norman Atkins is the CEO of Together Education. He is the Founder and Board Chair of Uncommon Schools, Co-Founder and former President of Relay Graduate School of Education, and Co-Founder of Zearn.
Introduction
In fall 2013, Lincoln Elementary School in Ogden, Utah, was struggling. Fewer than 20% of the students were proficient in math and only marginally more were proficient in reading. Ross Lunceford, the new principal who arrived mid-year, could sense how unhappy the staff was, resigned to accept low performance. When he first shared the vision with them that Lincoln could be the highest achieving school in the state, they scoffed.
Flash forward just four years: Lincoln Elementary School had doubled their proficiency rates, making 30 point gains in math achievement and nearly the same in reading. The results earned Ross the distinction of Utah Distinguished Principal of the Year and the school a National Distinguished Title I School award. The work Ross and his colleagues were doing had changed the game.
How did they do it? Ross sums it up in five words: implementing data-driven instruction without fail. “We started making some clear goals,” says Ross, “and really just getting everybody focused on the student work.”
Over the past decade, “data-driven instruction” (DDI) has become one of the most widely discussed concepts in education—and among the most misunderstood. For some, a data-driven school is simply one that conforms to the dictates of federal or state education legislation. For others, it is any school which uses assessments. At worst, calling a school “data-driven” conjures up images of educators sacrificing genuine learning in a single-minded focus on “teaching to the test.”
But the experiences of Lincoln Elementary School's students—and thousands like them across the globe—tell a very different story. Since Driven by Data was originally published in 2010, more and more educators have adopted the practices behind data-driven instruction. Their results reveal that this shift has been extraordinarily powerful. When leveraged properly, data-driven instruction is an incredibly effective pathway to academic achievement.
Data-Driven Success StoryLincoln Elementary School, Ogden, Utah
The Results
Figure I.1 Utah State SAGE Assessment: Lincoln Elementary School, Percentage at or Above Proficiency
The Story
Ross Lunceford is the kind of principal who stands out as a superstar to the families at Lincoln Elementary School in Ogden, Utah: he knows his students' names, communicates fluently with families who primarily speak Spanish, and even picks up trash outside the school building in the morning. But Ross didn't just know his students' names: he knew exactly what they were learning—and what they weren't.
He describes Lincoln as “chaotic” at the time when he took on leadership of the school. “There was a lot of unhappiness with the way things were going,” Ross recalls. “So we started making some clear goals and really just getting everybody focused on the student work.” From the very beginning, Ross recalls pinpointing the results of specific students and classes and making immediate action plans for them. “We told teachers,” says Ross, “that this is the percentage of your kids who were proficient last year on state assessment, so we need to grow to this percent now,” Ross says.
Ross also created explicit time for his teachers to focus on data, reframing pre-existing professional learning community meetings as opportunities to review student work. Ross didn't run these weekly data meetings, but he attended nearly every one of them. He allowed the teachers to drive the meeting, but he jumped in whenever they could go deeper in identifying the student gaps.
After teachers got better at analyzing student work, Ross says the next step was to plan how to act on it. “We would formulate a group of topics for re-teaching that teachers would work on for the next week,” he recalls. “Then we would look at the next week's standard to be taught, and how it would be assessed. Then we would plan our week.”
This cycle continued, week after week. Just in the first 18 months, Lincoln's results took off, with gains so significant that Ross was named Utah's National Distinguished Principal in 2015. But the success didn't end there—results continued to climb and Lincoln was named a National Distinguished Title I School in 2017. Today, his staff are in awe of their own collective growth. “Teachers would say, ‘Wow! When we set our goals, I didn't really believe that we could do it,’” recalls Ross. They turned aspirations into reality.
Key Drivers from the Implementation Rubric
Implementation calendar:
begin school year with a detailed calendar that includes time for assessment creation/adaptation, interim assessment analysis, weekly data meetings, and re-teaching (
flexible
enough to accommodate district mandates/changes).
Teacher-owned:
teacher analyzes own student work supported by instructional leaders.
Test and student work in hand:
start from the exemplar and identify the gaps.
Re-teach:
use guided discourse or modeling strategies to re-teach difficult standards.
These numbers in Figure I.1 represent hundreds of additional students reaching proficiency, greatly increasing the likelihood that they will go on to succeed in college and life beyond.
How did these schools facilitate such tremendous student achievement? They focused on the core drivers that affect student learning, separating themselves from schools that didn't. At the heart of it all is data-driven instruction.
THE FRAMEWORK: WHAT IS THIS ALL ABOUT?
Data-driven instruction is a philosophy for schools that focuses on two simple questions:
How do we know if our students are learning?
And if they're not, what do we do about it?
Core Idea
The key questions that drive effective data-based instruction are:
How do we know if our students are learning?
And if they're not, what do we do about it?
By making these two questions the center of their work, successful schools made a fundamental break from traditional education. What matters is not whether the teacher taught it, but whether the students learned it. By following this premise, successful schools create a powerful paradigm to drive academic excellence.
But how do these methods diverge from those of the thousands of other schools across the nation that assess student learning—something nearly every school does in some way or another? Let's consider what separates schools like the ones in Ogden from schools that assess data without seeing comparable gains in achievement.
The Road to Rigor: What Sets the Success Stories Apart?
There are so many resources about data that it can be difficult to know what is effective and what is not. Driven by Data 2.0 takes the guesswork out of deciding which drivers to prioritize, basing its entire framework on the actions of schools where leaders have succeeded on the ground.
These schools are home to students who have an overwhelming tendency to struggle within the US educational system: those who qualify for free or reduced lunch, belong to groups that are considered racial minorities, or speak English as a second language. In too many cases, schools fail to meet the needs of students like these, starting at an incredibly early age: by fourth grade, black public school students in the United States already receive lower academic scores than their white peers by 27 points in reading and 26 points in math; for Hispanic students, the gap is 25 points in reading and 21 in math.1 Overwhelmingly, these disparities only grow as students continue through primary and secondary school.
But at the schools featured in this book, leaders used data-driven instruction to make their students some of the highest-achieving in their respective districts or states. It is from this small subset of outstanding schools that the guidelines in this book were built—schools like Yinghua Academy, a Chinese immersion language school in Minnesota that has become a superlative school by any metric; and Denver Green School, that rose to being 8th of 203 schools in their district; and Northeast Elementary School, that transformed education for students in New Mexico.
What are the core action steps that these incredibly successful schools have taken to guarantee student achievement? Which action steps are consistent across multiple schools in different cities, suggesting far-reaching applicability? The answers to these questions are the core drivers for data-driven instruction presented in this book.
To get a sense of how this plays out on the ground, imagine planning a long road trip. Unless you're following in the path of Jack Kerouac, your road trip will include a clear destination, be it a major city, a national park, or a family member's front door. Chances are you wouldn't hit the road without a clear destination—and the pace you'd need to set to reach your destination by the desired time. In fact, for a longer road trip you'd probably set out with multiple destinations to keep you on the right path. You'd have a few major landmarks to hit: nightly places to sleep, tourist attractions to visit, and so on. And between those stops, you'd check exit signs and mile markers along the highway to make sure you stuck to your route, knowing that a wrong turn would take you further away from your goal.
Education is no different. To teach our students what they need to be successful, we need to clearly define what they must learn and be able to do; set clear progress points they'll need to meet along the way; and keep an eye on other signs that show whether they're learning so we can course-correct sooner rather than later if they aren't. That's the heart of data-driven instruction and the ultimate roadmap to rigor.
THE SEVEN MISTAKES THAT MATTER
The actions described in this book will get you and your students on the road to rigor. Before we turn to those, however, it's worth considering a few key actions that won't, so as to be able to avoid them. Here are the seven mistakes that matter most when you set out to implement data-driven instruction in your school.
Inferior Interim Assessments:
Interim assessment of students is the lifeblood of data-driven instruction. Without well-thought-out and carefully written tests, effective analysis of student strengths and weaknesses is impossible. Unfortunately, many schools employ inferior interim assessments that suffer from serious shortcomings, including setting bars that are too low, failing to align to end-goal tests, and neglecting the art of writing. Effective data-driven instruction is impossible unless schools invest in creating/acquiring excellent interim assessments. Particularly since the introduction of the Common Core State Standards, schools have scrambled to meet the raised bar on their own state tests—whether adopting Common Core or not—and begun using assessments that meet new levels of rigor. This is a step in the right direction—but it's only effective when those assessments are college-ready. Too often, educators roll out assessments that aren't sufficiently rigorous only to be shocked and dismayed when their students don't do well on state tests, AP exams, or SATs. Those results only change when we are vigilant about avoiding inferior assessments.
Secretive Interim Assessments:
As we shall posit later in the text, if interim assessments drive rigor, then teachers and schools must know the end goal in order to work toward it. Unfortunately, most schools and districts prefer to be secretive. There are many reasons for this. For one, it costs money to develop new assessments, so if you believe (questionably) that you cannot re-use an interim assessment, then it's economically unviable to release interim assessments. The result is that educators hit the road without a clear destination.
Too-frequent Assessments:
