The Data Coach's Guide to Improving Learning for All Students. Katherine E. Stiles
activities. Then consult the CD-ROM for other materials relevant to the tasks. As you prepare to implement each task, it will be important to read all of the material related to that task in detail. For the first time through, we suggest working through the tasks in order. It is not necessary or even recommended, however, to conduct all activities for all tasks for every Data Team. Instead, customize the process by considering the knowledge, skills, beliefs, and experiences of your Data Team and the time and data available. The guide includes a variety of assessments of data literacy and school practices that will help you tailor your own approach to these materials.
Another pathway through the book is for readers who already have an established continuous improvement process in place in their schools. You can use this guide to strengthen that process by implementing specific components of the Using Data Process. For example, your Data Teams may want to go directly to the “Verifying Causes” chapter (Chapter 5) if that is a stage you have been overlooking. Other readers may be looking for ways to bring equity issues to the forefront of school improvement work. For this, Chapter 3 (“Building the Foundation”) is a good place to start, especially Task 3 (Raise Awareness of Cultural Proficiency). Then you can use the Equity Lens icons to follow how cultural proficiency and equity are woven throughout the process.
For those who prefer to see the whole picture before getting into the details, consider starting off by reading Chapter 8, the case study about Clark County, Nevada. Finally, some readers may want to go directly to the Toolkit on the CD-ROM and scan for specific tools to use with their Data Teams or faculty. Whatever pathway you take, please use this guide to inspire your own creativity and to unleash the power of collaborative inquiry to make a better future for each and every student.
1 The Power of Collaborative Inquiry
What the best and wisest parent wants for his own child, that must the community want for all of our children.
—John Dewey
Lea is a spunky fourth grader who loves geography, expressive writing, gymnastics, and her friends, but homework is a constant struggle for her.
Bethany loves gymnastics and is highly kinesthetic. She is catching up on her reading and, after some difficulty, is expected to be at grade level by the end of this year.
Brianna’s strength is her intelligence about nature; she can name and give great details about all the fauna and flora in the neighborhood. A seventh grader, she struggles in school and now attends a school for students with exceptional needs.
Jared is going into second grade. His strength is his sense of identity and what it means to be Navajo. He loves to draw; his challenge is reading. This past school year he had to work very hard on his reading skills.
Chinua just graduated from high school and received a full scholarship to Morehouse College. He is extremely bright and loves science and mathematics. He gets bored easily if he is not challenged.
We begin this book with images of children we know because they inspire us to do the work we do (see Figure 1.1). It could be so easy to get lost in the numbers—student identification numbers, scale scores, proficiency cut points (see Figure 1.2)—and forget that the numbers represent the hope and future of real children with strengths as well as challenges, each deserving the kind of education we want for our very own children (see Figure 1.3).
When asked what they would want for their own children, most educators inevitably say they expect the highest levels of education. Do other people’s children deserve any less?
—Johnson, 2002, p. 320
Figure 1.2
Figure 1.3
We care about data because we care about children learning and succeeding. Data can sound the alarm when someone is not learning and activate an immediate response. The data give us a powerful entrée into dialogue about the toughest issues, such as confronting how well our schools are working for all children and the inequitable practices that persist. They challenge and help us rethink basic assumptions. They hold a mirror up to instructional practice to pinpoint what is and is not working. Data help to set the right goals for action and, once changes are implemented, they provide constant feedback to guide mid-course corrections and monitor results.
Data also give us cause for celebration and opportunity to recognize teachers and students for a job well done. Using data to guide action is the most powerful lever we have to improve our schools; and yet, despite the increasing quantity now available, data are woefully underutilized as a force for change.
Schools are gathering more and more data, but having data available does not mean that data are used to guide instructional improvement. Many schools lack the process to connect the data that they have with the results they must produce.
—Love, 2004, p. 23
Bridging the Data Gap
Increasing the effective use of data to improve learning is the problem the authors set out to solve. Imagine two shores with an ocean in between (see Figure 1.4). On one shore are data—the myriad data now inundating schools: state test data sliced and diced every which way, local assessments, demographic data, dropout rates, graduation rates, course-taking patterns, attendance data, survey data, and on and on. On the distant shore are the desire, intention, moral commitment, and mandate to improve student learning and close persistent achievement gaps. But often there is no bridge between the shores and a wide ocean in between. Sadly, it is children who are drowning in the data gap, particularly children of color, English Language Learners, children living in poverty, and those with exceptional needs.
Why is there such a wide data gap? Although there are many contributing factors, the authors of this book agree with Richard Elmore that the data gap is primarily a problem of capacity:
With increased accountability, American schools and those who work in them are being asked to do something new—to engage in systematic, continuous improvement in the quality of the educational experience of students and to subject themselves to the discipline of measuring their success by the metric of students’ academic performance. Most people who currently work in public schools weren’t hired to do this work, nor have they been adequately prepared to do it either by their professional education or by their prior experience in schools. (Elmore, 2002, p. 5)
When you combine lack of adequate preparation with intense accountability pressures, poor use and even abuses of data abound. For example, if educators do not thoroughly understand their content and how to teach it, they can incorrectly diagnose student-learning problems and resort to drilling students on test items or tutoring “bubble” students—those who just missed a proficiency-level cut point—just to pass the test (Abrams & Madaus, 2003; Love, 2003). On the other hand, as Ann Lewis asserts, “There is plenty of evidence around that, when teachers know their content and know how to teach it at high levels to all students, ‘teaching to the test’ fades into the background of everyday instruction and learning” (as quoted in Sparks, 2005, p. 90).
Figure 1.4 The data gap.
If educators do not believe in all children’s capacity to reach challenging standards, they can react with complacency or resignation when they see achievement gaps among racial/ethnic and economic groups; or even worse, they can choose to institute practices