The Data Coach's Guide to Improving Learning for All Students. Katherine E. Stiles
plan to launch Data Teams, meet with your district and building administrators to clarify the role of the team and its decision-making authority. For example, can the team decide to implement interventions to address student-learning problems, or are they responsible for recommendations to someone else who makes that decision? What ongoing feedback should be provided and to whom about the Data Team’s findings? What resources are needed, and how will they be provided? The following checklist can guide you in clarifying roles and responsibilities of Data Teams.
Table 2.3
Create Time for Collaboration
Teaching is a three-part act—planning, doing, and reflecting. Unfortunately, school schedules often reflect the assumption that if teachers are not in the classroom in front of students, they are not doing their job. The school day typically has provided time for teaching, but not for the equally important functions of planning and reflecting. Stigler and Hiebert (1999) create an image of a teacher’s day that is not unlike a college professor’s, with time for teaching and research, collaborative planning and reflecting with colleagues, and “office hours” with individual students. Although this vision may not become a reality in schools in the near future, changing the school schedule somewhat to create time for teacher collaboration is a requirement for collaborative inquiry. A growing body of research linking teacher collaboration with student achievement (Darling-Hammond, 2004; Little, 1990; Louis, Kruse, & Marks, 1996; McLaughlin & Talbert, 2001) makes this conclusion inescapable and urgent: Time for teacher collaboration is not a luxury—it is a necessity for schools that want to improve.
How much time? Along with other school improvement experts, we recommend a minimum of 45 minutes per week of uninterrupted, protected time for collaboration. Many schools participating in the Using Data Project were able to carve out weekly or even daily time for teachers to work together by creative use of specialists, block scheduling, or reallocation of teacher contract time. Others convened the Data Team quarterly for a full release-day of analyzing common benchmark assessment results, along with two- to three-day data retreats in the summer. The growing number of schools across the country that now schedule time for teacher collaboration during the school day prove that finding time is a solvable problem when the will is present to do so.
Ensure Timely Access to Robust Data Sources: The Democratization of Data
By the end of the 2004–2005 school year most grade levels had given some common assessments and had tried to compile the data. We did this using Math-and-Science Partnership project time during the school day. This was a long process because we had to compile the data by hand. We had no time left to actually dive into it and discover what we needed to change in terms of instructional strategies. All that changed with the purchase of the Principia software package. Now we are able to use that same time to make data-driven decisions.
—Ann Wacker, Mathematics and Data Coach Plain Local Schools, Canton, Ohio
In the early days of the Using Data Project, staff confronted a confounding obstacle: The very people who could make the best use of student-learning data—the teachers—had the least access to the data. Test data were “under lock and key” and were the “private property” of the research, assessment, or other district office. Teachers often did not receive assessment data at all, or received them so long after the tests were administered that they were not even teaching the same children. Project staff and district and school-based collaborators had to advocate strongly to “democratize the data,” giving teachers access to their students’ results. Thankfully, times are changing as more districts put timely data systems into place that make a variety of school data readily available to teachers.
However, even with the best data management systems, data access can still be problematic. For example, many states do not report data at the item level or release test items for teachers to analyze. Yet item-level data (see Task 9), when used in conjunction with the actual test items, are among the most useful data teachers have to improve their instruction.
One way around this problem is for schools to make or buy their own assessments and assure that teachers have just-in-time access to both the item-level results and the items themselves. This is one reason why common benchmark assessments are so important to improvement. Because they lend themselves to item analysis, are administered periodically throughout the school year, and align with local standards and curriculum, they can fuel collaborative inquiry.
But the data access problem may not yet be solved. The next challenge is to get results from common assessments to teachers fast, within a few days—in time for them to actually do something about them. Fortunately, this problem has a simple technological solution: inexpensive software programs and scanners, which can scan about 200 tests per hour, placed in easy access of the Data Coach. When put in place in participating Using Data schools, these machines removed the data bottleneck and got collaborative inquiry moving.
The good news is that much of the data that fuels collaborative inquiry is not dependent on expensive data management systems. Simple scanners will do the job of churning out the item-level data on local assessments. Some of the most robust data sources, formative classroom assessments and common assessments such as student work, mathematics problems of the week, and science journals, require no data management system at all—just teachers collecting their students’ work and sharing it with colleagues. While data management systems facilitate data access, they are not a prerequisite for collaborative inquiry.
Summary
As you lay the groundwork for implementing collaborative inquiry in a school, district, or educational improvement project, remember the adage “Go slow to go fast.” It is well worth the time to create the conditions for success: an effort that is aligned and integrated with other initiatives and data management; buy-in from key stakeholders; well-prepared Data Coaches with authority and time to carry out their role; Data Teams of teachers and administrators established at the school, grade, department, and/or course level; a minimum of 45 minutes weekly for Data Teams to work together; and the mechanisms for giving teachers timely access (within days of the assessment) to student-learning data, especially at the item level.
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