By Maryclare J. Heffernan, M.Ed. Associates for School Change at SERESC

Teachers are problem solvers. They make hundreds of decisions every school day constantly calculating the educational and social/emotional well being of each individual in their care. Yet for most of today’s educators their pre-service experience lacked any formal training in the use of student outcome data to guide their instructional practice. Pretty frustrating when data informed decision-making is now a required part of every educator’s life.

In our work with school teams as they analyze student data we’ve learned the value of using consistent protocols and processes for the data conversations. For starters we recommend adopting Nancy Love’s Data Driven Dialogue three step process of: 1. Predict, 2. Observe, and 3., draw Inferences or ask Questions of the data.

The immediate benefit of this approach is to slow down our natural desire to draw quick conclusions from the data before the information are carefully and neutrally analyzed by the team. It creates a safe, scientific, action research-based climate that is open to new thinking, shared insight and effective problem solving. We recommend that as teams use this process they scribe responses to create a record of the team’s thinking and conclusions.

First determine what data you want or need to analyze and organize it in a clear and manageable format. For example, percent proficient in math NECAP for all students in the school in grades 3 through 8 for the past six years. Make sure you have copies of the data set for everyone and enough uninterrupted time to focus on the data dialogue.

Begin by asking members to state what they expect the data to show. When teams predict what they expect to see in the data assumptions are put on the table that can later be reviewed against the evidence. This stage also provides a moment for the team to pose questions of the data. What do you think you know and what would you like to know?

Next the team simply observes the data, individually at first to provide some quiet “think time”, then with a partner to talk about what information they see. What important points “pop out”? What are some patterns or trends? What is surprising or unexpected? It is important not to judge the data but observe and then record what is seen. This stage is often the hardest one for data teams. Educators have knowledge of student groups, school history, community culture etc. and the tendency is to begin immediately to explain the data away. “The reason that cohort of students performed so poorly is that group of students. Trust us, they’ve been behind since first grade.”, or “I can tell you why the 6th grade results are flat…the 6th grade students lose motivation in learning…they just stop trying.” But comments like those aren’t allowed during this phase. Only the facts go here. Just record what you see. For example: “If you look at the cohort of students starting with 3rd grade in 2005 and following them until they are in grade 8 in 2010 their math scores increased from 45% in grade 3 to 67% in grade 8.” Just the facts!

Finally, the team begins to draw inferences and/or ask questions of the findings. What inferences might be made? What questions are we asking? What additional data sources do we need to explore to verify our explanations? What tentative conclusions might we draw? This conversation will lead you to initial findings that may be acted on right away or perhaps lead to a new round of investigation to gain further information. Perhaps you know now that there is a significant decrease in learning for cohorts of students as they age but you still aren’t sure why. Is the district curriculum aligned with the state’s frameworks? Are Power or Essential Standards identified for all grade levels? Are the instructional practices conducted with fidelity to the curriculum? Is it a lack of student mastery in foundational skills? Are students provided with interventions when they first demonstrate a lack of mastery? Has the staff been provided with ongoing professional development to know how to teach the skills they are expected to teach? Data discussions are always rich and thoughtful and produce collaborative decisions about what to do next to support student learning.

Educators are ready and willing to move competently into this new age of accountability. Having the specific tools and skills to do this meaningful work is critical. Using the Data Driven Dialogue process is a good way to begin learning to love the data.

For more information, please contact Kathryn Skoglund at (603) 206-6868. A consultant from ASC will be in touch with you immediately to discuss your educational needs.