Читать книгу The Data Coach's Guide to Improving Learning for All Students - Katherine E. Stiles - Страница 34
The Using Data Process: A Framework for Collaborative Inquiry
ОглавлениеThe Using Data Process of Collaborative Inquiry (Using Data Process) offers Data Coaches and Data Teams a structured process for ongoing investigation of data with the goal of improving teaching and learning. The approach incorporates multiple safeguards to prevent data disasters and keep the team focused on each step across the bridge. In this book, Data Coaches are provided with the materials and guidance to lead Data Teams through this process.
Figure 1.6 The Using Data Process components and tasks.
Copyright © 2008 Corwin Press. All rights reserved. Reprinted from The Data Coach’s Guide to Improving Learning for All Students by Nancy Love, Katherine E. Stiles, Susan Mundry, and Kathyrn DiRanna. Thousand Oaks, California. Reprodution authorized for only for a school site or nonprofit organization that has purchased this book.
As depicted in Figure 1.6, the Using Data Process is made up of five components. Within each component is a sequence of tasks that Data Coaches carry out with Data Teams. The first component is Building the Foundation; it includes Tasks 1–4. Here, Data Coaches lay important groundwork with the Data Teams to get them off to a good start. The team focuses on establishing the culture and commitment to equity that will serve as the foundation of the bridge of collaborative inquiry. They establish their purpose as a team, learn about the Using Data Process, and make commitments to each other. They reflect on their school by examining demographic data and assessing where their school is on the road to creating a high-performing Using Data Culture. They raise their awareness of cultural proficiency and begin a process of open dialogue about issues of race/ethnicity, class, culture, gender, and diversity. Finally, they envision a desired future for their school and plan for moving toward it. The themes that are introduced in this component—norms of collaboration, Data-Driven Dialogue (Wellman & Lipton, 2004), cultural proficiency, vision, values, and high-performing culture—are recurrent throughout the Using Data Process.
The second component is Identifying a Student-Learning Problem; it includes Tasks 5–12. Guided by the Data Coach, the team members develop data literacy and examine multiple sources of student-learning data. They learn to use tools to make sense of the data and surface assumptions and frames of reference. The outcome of this component is a clearly articulated student-learning problem that can be supported with evidence from multiple data sources, including student work.
The third component, Verifying Causes, includes Tasks 13 and 14. This component is critical because it is the one often omitted in other improvement processes. Here the team members look carefully at the possible causes of their student-learning problems and examine data about their own practices as well as relevant research before drawing conclusions. The goal here is to make sure that the causes that are being acted upon are supported in research and focused on policies, practices, and beliefs that are within educators’ control to act upon—not on blaming students or their circumstances.
Generating Solutions, the fourth component, includes Tasks 15–17. Here, Data Teams apply logic-model thinking to generate valid solutions to improve results. They draw on best practices in their own school and nationally as well as on research to create action plans that are clearly linked to improved student learning. They also identify the evidence that they will use to monitor implementation of new practices and measure impact on student learning.
Finally, in the fifth component, Implementing, Monitoring, and Achieving Results (Tasks 18 and 19), the Data Team implements new practices to solve the student-learning problem. The team gathers data to monitor implementation and results and identifies any mid-course corrections needed. As evidence is produced that the school is achieving or progressing toward the goal, Data Teams organize celebrations to recognize the people and practices that are making a difference for students.