Data and Teaching: Moving Beyond Magical Thinking to Effective Practice
reviewed by Sara E. Witmer & Sarina Roschmann
Data and Teaching: Moving Beyond Magical Thinking to Effective PracticeAuthor(s):
Joseph P. McDonald, Nora M. Isacoff, & Dana KarinPublisher:
Teachers College Press, New YorkISBN:
2018Search for book at Amazon.com
Data and Teaching: Moving Beyond Magical Thinking to Effective Practice considers how the innovation of data use in teaching can be effectively incorporated within schools, especially underfunded schools. The authors highlight an unfortunate tendency among many to believe that federally mandated data collection and reporting will somehow automatically (or magically, in the authors words) promote higher quality teaching and learning. In contrast, this book emphasizes the critical and complex intermediate processes that are necessary at the local level to effectively use data in ways that will ultimately improve teaching and learning. The authors focus on the need for schools to carefully consider how federal mandates for data use and reporting can be integrated with locally-based data sources, knowledge, and resources to ultimately promote student learning. To achieve this, the authors repeatedly highlight the need for teachers to have deep curricular and pedagogical knowledge, as well as some foundational assessment knowledge, to effectively interpret and use data in their instructional practices. Additionally, the authors emphasize the importance of shared leadership and collaboration among administrators and teachers in order to be successful with this integration work.
McDonald, Isacoff, and Karin tackle these important topics on two levels: basic and deep dive. The first three chapters offer background information on their definitions of data, teaching, and data use in teaching. Most importantly, readers are introduced to the distinction between big-test data and intimate data, with big-test data being defined as those that are mandated for collection by states and used for the purposes of reporting to educational departments or administrators, and intimate data being defined as student performance data collected by teachers themselves. Additionally, the authors provide examples of effective teaching practices, as well as a background on the origins of big-test data use within teaching in the United States. Each chapter ends with a section titled New Directions, in which the authors provide a summative statement of their views for the future, as well as additional resources for readers to consider.
The second part of the book, the deep dive, consists of four chapters, each illustrating an example of data use in different New York City public schools. These case study examples stem from data collection conducted through the Research Alliance for New York City Schools (RANYCS). The deep dive is balanced with two examples of schools struggling to effectively incorporate data use into their teaching and two additional examples that illustrate how data use can be enacted more successfully to improve student learning. The authors describe what they learned about data use in teaching within these schools through interviews with teachers, principals, and various other school administrators, as well as observations in selected classrooms and school meetings. As in the first part of the book, the authors end each deep-dive chapter with a New Directions section in which they highlight key ideas and resources that may help promote more effective data use in teaching.
This book offers school leaders a great starting point for critically examining their own approaches to data use in teaching. The examples the authors present are highly engaging, and situate many of the key concepts in very down-to-earth school contexts. Many readers will likely see their own school and classroom data collection practices represented in the authors examples of both good and less helpful data practices in teaching. The sections that conclude each chapter provide excellent general guidance for improving related practices, such as thoughtfully enlisting students in the data collection, management, and interpretation process, and building a collaborative, learning-focused culture within schools.
What readers will not find in this book is clear-cut, how-to, procedural guidance on what to do. The absence of such detailed and specific guidance aligns with the authors general message that the innovation of data use in teaching must be integrated in a unique way within each district, school, and classroom setting. Several chapters do include a variety of additional resources that appear to offer more explicit guidance for those seeking it. However, readers will likely be left with a sense that the task of effectively incorporating data use in teaching will require a substantial amount of additional critical thinking, reading, discussion, and planning in order for it to be carried out according to the general principles outlined in the book.
Throughout the book, the authors link the word innovation to their definition of data use in teaching. This may work well to motivate and encourage readers within the current educational context to engage in meaningful and important changes in related practices. At the same time, it does seem to neglect the notion that what the authors call intimate data has likely been used effectively in some schools and classrooms long before the federal emphasis on the development and use of large-scale assessment programs. Technology is certainly allowing for more automated and efficient data collection, analysis, and interpretation, and mandates have correspondingly encouraged greater collection and reporting of student performance data. This most certainly represents change. However, by framing their overall topic as an innovation, the authors may have missed an opportunity to connect their ideas to basic foundational principles of quality teaching and learning that have been acknowledged for several decades, such as the helpfulness of tailoring instruction to a given students current level of knowledge and skill.
Overall, McDonald, Isacoff, and Karin offer a rich and authentic look into how student performance data are currently understood and how they are being used by teachers and school leaders in schools serving many students living in poverty. Additionally, they offer some general guidance for those school leaders aiming to engage in more effective related practices. In doing so, they communicate well the notion that effective data use in teaching is a highly worthwhile, but also a highly complex and resource-intensive, endeavor. We anticipate that Data and Teaching: Moving Beyond Magical Thinking to Effective Practice will be an engaging and thought-provoking read for school leaders looking to more effectively integrate data into their teaching practices.
Cite This Article as: Teachers College Record, 2018, p. -
http://www.tcrecord.org ID Number: 22549, Date Accessed: 11/20/2018 11:50:36 PM