The Data Coach's Guide to Improving Learning for All Students. Katherine E. Stiles

      Figure 1.5 Connecting data to results.

      Collaborative Inquiry Is the Bridge

      Schools know that they have to improve. But they often do not know how to improve. Collaborative inquiry is the how. It is a systematic improvement process where teachers work in Data Teams to construct their understanding of student-learning problems and generate and test out solutions through rigorous and frequent use of data and reflective dialogue. When engaged in collaborative inquiry, Data Teams investigate the current status of student learning and instructional practice and search for successes to celebrate and amplify. Their ongoing investigation into how to continuously improve student learning is guided by these simple questions:

      Collaborative inquiry is the relentless pursuit of excellence and equity subjected to the rigor of evidence and results. Although it is a process, not a destination, collaborative inquiry does not roam aimlessly. Data Teams turn problems into quantifiable goals to be achieved and move purposely toward them, one at a time, sometimes in small steps, sometimes with big leaps. Schools in which staff master this process know how to get better and better. As collaborative inquiry grows, schools shift away from traditional data practices and toward those that build a high-performing Using Data Culture. These shifts are summarized in Table 1.1 and illustrated in Figure 1.5.

Table 1.1

      Our Theory of Action: Building the Bridge Between Data and Results

      Through our work as staff of the Using Data Project, the authors of this book set out to build the bridge between data and results and help to bring about the shifts in culture described earlier. The theory of action that guided us is illustrated in Figure 1.5. Our intervention, represented by the arrow pointing to the bridge, was the Using Data professional development program. The program addresses the critical capacity crisis described earlier by building the knowledge and skills of Data Coaches—education leaders especially trained to guide the use of data—to lead Data Teams in collaborative inquiry (see definitions in the sidebar). Data Teams become vital and productive centers of collaboration, meeting weekly to engage in Data-Driven Dialogue, using multiple data sources, including common and formative assessments (see Task 5 for detailed information on what kind of data to use and how often). Staff collaborate in their use of data to make critical and research-based instructional improvements. These improvements are the final and necessary step to reach the shore of improved results for students. The bridge is supported by a foundation of a collaborative school culture, a commitment to equity, and a climate of trust.

      Data Coaches are education leaders (teacher-leaders, instructional coaches, building administrators, or district staff) who guide Data Teams through the process of collaborative inquiry and influence the culture of schools to be ones in which data are used continuously, collaboratively, and effectively to improve teaching and learning. Their role is to engage others in making sense of and responding to data in ways that improve learning for all students. They facilitate the work of Data Teams, build capacity to use data well, and sustain the improvement process.

      Data Teams in this book refers to teams of four to eight teachers, other school faculty, and, ideally, their building administrator who work together to use data and improve student learning. At an elementary school, Data Teams can be grade-level teams or representatives of different grade levels and focused on a particular content area, such as mathematics, or on school improvement in general. In a middle school or junior high and high school, Data Teams are often organized by department, content area, or common courses taught.

      Collaborative inquiry is the process by which Data Coaches and the Data Teams use data to develop their understanding of a student-learning problem and test out solutions together through rigorous use of data and constructive dialogue.

      After four years of field-testing our approach in diverse schools across the country, schools putting this theory into action are building bridges between data and results: Student learning is improving; achievement gaps are narrowing; teachers are working together, making effective uses of data, and improving instruction; and their school cultures are shifting toward greater shared responsibility for all students’ learning, trust, and commitment to equity (see “Student Learning Improves in Schools Implementing the Using Data Process” later in this chapter and Handout H1.3 on the CD-ROM for Task 1). The key to their success rests on their implementation of a model for collaborative inquiry we call the Using Data Process.

      The Using Data Process: A Framework for Collaborative Inquiry

      The 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.