Data. That is the basic outcome teachers are expected to provide. We do this through teaching. And although the general consensus is that educators are paid to teach, virtually all schools require student data of some measure. Throughout the year, we grade assignments, quizzes, and tests, all culminating in a report card at the end of the year. For certain ages, students are required to take province or state-wide exams. All with the expected results of turning out one thing: data. And usually once a year, teachers, along with administrators, sit down and attempt to unpack this data, pinpointing their school’s deficiencies across demographical lines. But other than accounting for our accountability in order to validate our pay checks, just what are we doing with this data?
The phenomenon of data accumulation has evolved in recent times. Over the last few decades, the breadth and depth in student data has grown exponentially. But why does it seem as though little has changed in terms of student outcomes despite the abundance of information we are now receiving? We know that if a student fails a third-grade literacy test she is likely to fail it again in the 6th grade and, if so, even more likely to struggle in high school. So what? We are at the point of using data to make somewhat-accurate predictions but it seems as though that is all we are doing. But the data should be able to tell us more.
What exactly is the data telling us? Is it telling us that are children are less scholastic? Our teachers are worse than in prior decades? Our standardized tests are not calibrated with current modes of teaching? The questions, at this point, have to be rhetorical. That is because by merely collecting more and more data there is no way of knowing the answers. Right now, all we have is a collection of information – without exactly knowing what we are looking for in it. We have gone beyond looking for the needle in the haystack. It seems as though we are looking for a specific needle in a pile of needles.
To take from statistician and writer, Nate Silver, we must decipher between the “signal” and the “noise”. Meaning, we must use the data beyond our Monday morning quarterback readings of student outcomes and instead become proactive with our teaching and learning, figuring out what are the key statistics in the data and what is just “noise”. We must look at this data that we have collected to determine trends; trends that go beyond the “boys fall behind girls in reading and writing by third grade”. And if we do want to stick to the conclusions we have made, we must be more proactive in correcting our fault lines. It is great to know things, but it means little if we do nothing about it. I don’t know if I have any of the answers to what the data is telling us. But I do think our first step is knowing just what the data even means before we can attempt to utilize it.
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