By Mary Anne Mather, Managing Editor
TERC’s Using Data For Meaningful Change Blog
TERC Using Data Senior Facilitator

Many districts are heading into spring state-level testing. It’s irrefutable that the opinions surrounding the pros and cons ofthree teachers collaboratively analyzing student work samples such assessments make for heated discussions in many circles. Not the least among the disputes is the time spent on what some call “teaching to the test.” The high stakes value placed on these tests can make even the best of us do things we don’t really embrace as best practice.

At TERC, we try to look at it from a different angle. What if our day-to-day work as professional-level instructors set the stage for students to perform better on the standardized tests because we intricately understood the ins and outs of what students do and do not know? Armed with that knowledge, we can plan classroom instruction that closes the gap between misconception and success. It’s most likely going to influence test scores, while addressing essential grade-level learning goals. That’s where looking at student work samples comes in! (more…)

Guest Blogger: Dr. William L. Heller, Using Data Program Director, Teaching Matters*

There are often revelatory moments in the data inquiry process, where your analysis will lead to great insight and discovery in a way that challenges your assumptions and changes the way you think about teaching and learning in your school. There are other times when the data shows exactly what you werePen pointing to detail of bar graph showing flat results expecting, confirming your predictions and giving you valuable evidence in making your case to others. Many times, however, the data doesn’t show anything at all.

This can be somewhat dispiriting to an enthusiastic data team, but it doesn’t need to be. Sometimes the data may show nothing, but that’s still valuable information that puts you ahead of where you were before you looked. We don’t complain when our dentist finds no cavities, when the mechanic finds nothing wrong with our car, or when a medical test comes back negative. Similarly, in data inquiry, even a finding of nothing can really be something, if you know how to interpret what it means. (more…)