“Making predictions before analyzing new data raises awareness about existing
assumptions that can influence accurate interpretation of that data.”
The Data Coach’s Guide to Improving Learning for All Students
Your school administrators have made a commitment to data-informed decision making. That most often means that they periodically provide you with reports that include state test scores, benchmark assessment scores, and more—for your state, your district, your school, and your own students. First impulse is to scan over the results to see how your students compare with others. Then you might naturally begin to draw some conclusions about who is doing well, who needs help, and what you can do about it. It’s only natural to feel urgent about finding solutions, but before your “take action” impulse kicks in, STOP!
As data-use facilitators, we offer a first-step strategy that may not occur to you, but it can contribute to a bigger pay-off down the road in pinpointing student learning problems, their causes, and next steps. Before even taking a peek at the new data you have in hand, “predict” what you expect it to tell you.
As educators, we know that making predictions is an effective strategy for teaching new concepts to students. It activates prior knowledge and uncovers understandings and misconceptions—anchoring new learning to the familiar. In much the same way, making predictions about student achievement data offers a starting point for navigating new data and engaging in dialog about what it tells you. In fact, predicting is the first in a four-step data-discovery process that is referred to as Data-Driven Dialogue (Wellman & Lipton, 2004). It is a structured process that enables a Data Team to explore predictions, present a visual representation of the date, make observations, and generate inferences and questions before offering solutions.
If you are ready to make some predictions, here’s how:
• Don’t look at your data, just start thinking…
• Reflect back on the content and skills represented in your new data set.
• Think about how, when, and for how long that material was taught. Were all students in attendance? Were they engaged with the material? Did they complete assignments? Did you need to provide remedial opportunities?
• Capture predictions about a variety of circumstances. These might include:
–overall results you expect to see for all students in the district or school
–results for specific student groups such as your ninth period class or your English language learners
–results for specific standards or skills
–results compared to previous years
–results related to attendance records.
• Once you have a complete list, read over your predictions. Do you notice any patterns in your thinking or assumptions that you have about certain students or groups of students in your class(es), or assumptions about your students compared to others in the school, district, or state?
• Stay in tune with your assumptions. When you look at your data, you will gain insights by comparing what you see with what you thought.
Using data in a meaningful way starts with teachers who understand that data are just the beginning. And to “predict” is the first step on the pathway to making data-informed instructional decisions that can lead to results. The next step is “go-visual”—making graphic representations of the data at hand. We’ll talk more about that in our next TERC Using Data Tip!