In August and September, teachers have assembled for their first faculty meeting. In smaller districts, the Superintendent has welcomed everyone back, introduced new members of the staff and talked briefly to highlighting the districts’ goals, student achievement challenges, and new programs being implemented in the district. When the meeting adjourned, teachers re-assembled in their schools for a similar meeting led by their building principal, and everyone received their class lists. As teachers headed out of the meeting, they left on a note of optimism and promise for the year to come and with data sheets in hand from which they can began to assess the range of learning levels in their classes.  And at this point teachers, individually,  sat in their respective classrooms and thought about their students’ learning needs and this year’s curriculum…Sound familiar?

Compare this image to schools that began their school year in a two to three-day “data retreat” where several years of data were analyzed in a process that supported a deep level of inquiry about what the data means and the implications for what is to be taught, and how it needs to be taught. As school opened and students returned, teachers continued their planning process by meeting regularly to examine student work and to continue asking the hard questions of themselves. The “de-privatization” of teaching has occurred, and using data is a routine part of each professional’s reflection on what’s working and what isn’t.

At a recent three-day Using Data session teams of teachers examined aggregate, disaggregate, strand and item data from their state assessments to identify specific student learning problems. From analyzing their disaggregated their data, they learned that their students from low socio-economic homes and their special needs students represented the largest populations of students scoring below proficiency levels. After making observations of each kind of data charted, the data teams suggested potential causes behind what they were seeing and raised additional questions about the learning experiences of students who were performing below proficiency. It wasn’t long before they looked at grouping practices, use of their DIBEL’s assessments,  alignment of their curriculum to the state’s learning standards, and perhaps most importantly, their own assumptions and beliefs about their students’ learning potential. To answer these questions, they still need to go through a causal analysis phase of the work.

Stay tuned. We’ll learn together.