Data Tip #2: "Making predictions before analyzing new data raises awareness about existing assumptions that can influence accurate interpretation of that data."
(Love, Nancy et al., The Data Coach’s Guide to Improving Learning for All Students, 2008)
Capture Your Predictions Before You Analyze Data
School administrators have made a commitment to data-informed decision making. Often this means that periodically you will see reports that probably include state test results, benchmark assessment scores, and more. Your first impulse might be to scan the results and draw conclusions: who is doing well, who needs help, and what you can do about it. But before your 'take action' impulse kicks in, STOP!
Before you even take a peek at the new data you have in hand, predict what you expect the data to tell you. This first-step strategy can help guide your analysis of the data and contribute to a bigger pay-off down the road by helping you to more clearly pinpoint student learning problems, their causes, and next steps.
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 familiar concepts. In much the same way, making predictions about student achievement data offers a starting point for navigating new data and engaging in dialogue about what it tells you. In fact, predicting is the first step in a four-phase data-discovery process called Data-Driven Dialogue (Wellman & Lipton, 2004). This structured process enables a Data Team to explore predictions, present a visual representation of the date, make observations, and generate inferences and questions before forming solutions.
If you are ready to make some predictions, here’s how:
• 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?
• Now, make predictions about what the data is going to tell you. Record each prediction as a list on chart paper or in a journal.
• Organize your predictions in categories. For example:
--Overall results you expect to see for all students,
--Results for specific student groups, such as your third 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, review your predictions and look for patterns in your thinking or assumptions about students as individuals or as groups.
• 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 it would report.
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 Using Data Tip!
Diana Nunnaley, Using Data Director
Mary Anne Mather, Using Data Facilitator
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