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Data Wise in Action: Stories of Schools Using Data to Improve Teaching and Learning


reviewed by Linda H. Pickett - July 30, 2008

coverTitle: Data Wise in Action: Stories of Schools Using Data to Improve Teaching and Learning
Author(s): Kathryn Parker Boudett and Jennifer L. Steele (Ed.)
Publisher: Harvard University Press, Cambridge
ISBN: 1891792806, Pages: 192, Year: 2007
Search for book at Amazon.com


In 2005 faculty members, school administrators, and doctoral students from the Harvard Graduate School of Education joined school leaders from the Boston Public Schools to produce Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning. Edited by Kathryn Boudett, Elizabeth City, and Richard Murnane, the book “offered a practical model for using data to identify common student learning needs, to generate and implement instructional solutions, and to measure those solutions’ effectiveness at raising student achievement within a department, grade-level, or school” (p. vii). While the Data Wise model was widely disseminated, there were calls from school leaders for stories from real schools implementing it. Data Wise in Action responds to such requests by presenting case studies from eight very different schools to demonstrate how each implements a different phase of the eight step collaborative, evidence-based Data Wise instructional improvement process.


With many school improvement models, authors commonly present examples of schools that simply follow the prescribed steps and seem to attain the desired results with relative ease. This can be discouraging to school leaders and faculties who face unexpected setbacks in their attempts to implement an evidence-based culture. The perspectives and stories presented in Data Wise in Action provide a sharp contrast by offering the reader examples of eight very different schools, with diverse demographics, struggling to overcome challenges in using data to improve teaching and learning.


In Chapter 1, David Ronka tells the story of a faculty organizing for collaborative work. In an affluent suburban elementary school, school leaders search for ways to use data after an unsuccessful state formative assessment system left many teachers feeling burned out and as though they were only teaching to the test. A data team is formed to help reengage the faculty in using data to improve instruction as they focus on reading comprehension. This case study illustrates the struggle to be patient and thoughtfully plan during the preparation phase of the Data Wise improvement process while still finding a way to improve student performance during the school year.


Building assessment literacy is described by Rebecca Thessin in Chapter 2. To close the achievement gap in a high performing suburban high school, a multidisciplinary team is formed to gather and analyze the school’s data. To build a trusting culture for collaborative data analysis, the team prepares an understandable data summary and teaches the faculty how to interpret test scores and other measures of student performance. This approach contrasts sharply with what can happen in a school when teachers get piles of data and, without proper instruction on what it all means, file it away unused.


Creating a data overview is the focus of Chapter 3. Mark Teoh tells the story of a new principal in an award winning urban Title I school who is disheartened when he finds that the language arts scores have fallen and the school has not made Adequate Yearly Progress. Over a three-year period, the principal develops a shared leadership process that produces collaborative analyses of student achievement data collected from multiple sources. The faculty develops a better understanding of the data; they learn several means to discuss the data and use it to guide and inform their instruction.


The case study presented by Thomas Tomberlin in Chapter 4 demonstrates dig into data. In a suburban elementary school, with a strong culture of collaboration and working with data, the school principal and faculty are concerned about students not living up to their academic potential. Learner-centered problems, or common areas of student weakness, are identified and teachers expand the data sources for more information about the problems. Focal students are identified to help gauge how well all students are progressing.  


Chapter 5 presents examining instruction. Trent Kaufman tells the story of a newly hired veteran teacher’s adjustment to the system of peer observation used in a successful urban K-8 school. The chapter describes how the teachers analyze the data, identify a learner-center problem in each grade level, and examine their instruction in order to increase student learning. This practice empowers the teachers to model instructional strategies, learn from each other’s experiences and engage in meaningful conversations about their teaching to better address the learning problems.  


The case study in Chapter 6 recounts a two-year process to develop an action plan to use data to improve instruction in an urban charter school. Michelle Forman describes how the leadership team narrows its efforts to the development and implementation of an action plan that allows “the entire school to study a single strategy in depth” (p. 114). This narrowed focus allows the faculty’s professional development to focus on a problem of practice, a particular teaching challenge contributing to the learner-centered problem that emerges from an area of student weakness in the data.  


The importance of planning to assess progress is illustrated in Chapter 7 by the story of an urban elementary school working to help students write critically about their reading. Written by Sarah Fiarman, this case study demonstrates all eight steps of the Data Wise improvement process and “shows teachers working together frequently to interpret and act upon their data” (p. 125). Short-term data (assessed weekly), medium-term data (gathered three times a year), and long-term data (collected annually) are collected to triangulate conclusions about student performance. Teachers feel a renewed sense of empowerment and take ownership of student learning.  


Chapter 8 illustrates the final step in the Data Wise improvement process – act and assess. Jennifer Steele shares the story of a new principal of an urban alternative high school who works to overcome the school’s difficult history. Challenged by the school’s poor daily attendance, high dropout rate, and poor performance on state assessments, the school leadership team encourages a greater emphasis on student academic performance. The faculty works the first year to develop the action plan collaboratively and to plan how it will be implemented and assessed. In the second year, the plan is fully implemented and positive results are documented by triangulating different data sources over several months. However, with a large number of new students entering the alternative high school right before state tests are administered, the action plan begins to unravel and the faculty has to adapt the plan “to respond to the reality of student mobility” (p. 162).  


In the final chapter of the book, Kathryn Parker Boudett comments on building learning organizations and challenges school leaders to reflect on four questions. Boudett makes the point that the Data Wise improvement process is never over. After the first cycle, school teams “can build on the strong foundation of assessment literacy and collaborative norms that they have worked hard to establish. They can analyze data more effectively, examine practice more critically, and brainstorm solutions more creatively than they did the first time around” (p. 168).


The eight stories illustrate the importance of customizing school improvement models to meet the needs of individual schools. Schools must also be given enough time to implement action plans and to allow them to have an effect. This is in direct opposition to “shotgun” approaches often implemented in school districts. District administrators seem to be puzzled when these efforts do not work and teachers become frustrated with yet another failed program.


The authors of Data Wise in Action underscore the importance of empowering teachers to assume collective responsibility for student achievement as well as a commitment to each other. School leaders are encouraged to involve school faculties in collaborative development of learning goals for students, demonstrating respect for teachers. In this process, teachers are engaged and committed to the improvement process instead of simply following mandated “top down” approaches. The creativity of teachers is encouraged and expanded as they lead their own inquiry into their practice.


Data Wise in Action also includes many important implications for the professional development of teachers. Concrete evidence of the effect of a particular instructional strategy is collected and used as the basis of peer observations and discussions. Teachers are pushed to “evaluate their own work in terms of student learning” (p. 126). Principal Janet Palmer-Owens comments: “All of our professional development, our teaching, our planning – it all has to be based on the students in front of us and what the data say they need. We keep coming back to the data to measure our progress” (p. 126).


The authors of Data Wise in Action offer an insightful collection of case studies that will likely inspire school leaders--whether administrators, teachers, or other faculty members--to create an evidence-based culture to improve teaching and learning in their own schools. Through the collaborative systematic methods of examining their practice using the Data Wise process of prepare, inquire, and act, faculties may also reap the benefits of an increased sense of professionalism and confidence from knowing that their hard work will indeed result in increased student learning.




Cite This Article as: Teachers College Record, Date Published: July 30, 2008
https://www.tcrecord.org ID Number: 15327, Date Accessed: 10/23/2021 2:32:19 PM

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About the Author
  • Linda Pickett
    Winthrop University
    E-mail Author
    LINDA H. PICKETT is an Assistant Professor of Education in the Richard W. Riley College of Education at Winthrop University. Her research interests include mentoring, science and literacy, multidisciplinary instruction, and instruction for English Language Learners. Before teaching at Winthrop University, she taught science at multiple grade levels in traditional and alternative school settings and conducted professional development for teachers in the Miami-Dade County Public School District in Miami, Florida.
 
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