At just past the one-minute mark, she says:
We have to ask questions, and hard questions, to move past counting things to understanding them.This is reminiscent of the oft-used quote (usually attributed to Einstein, but he probably didn't say it),
Not everything that can be counted counts, and not everything that counts can be countedbut I sorta like this one better. Because counting things is often a good thing but we can't stop there, we have to provide the context, the understanding, the wisdom to do something good with what we've counted.
At about the 6:30 mark, she says,
this is what happens when assessments and analytics overvalue one metric — in this case, verbal communication — and undervalue others, such as creative problem-solvingThis sums up my main objection to PISA/PARCC/CMAS/fill in your own state test. We're so proud of ourselves for coming up with the metric that we've stopped asking ourselves whether it's an important metric in the first place. (I just finished Yong Zhao's new book where he goes into great detail discussing the history of education in China, and why the PISA results - and especially the conclusions assigned to those results - are almost meaningless.) We are overvaluing a metric that may (or may not) show how well you will do in school, but has very little worth in determining how well you will do in life.
At about 8:20, she brings it home,
And at this point, you might be thinking, "Okay, Susan, we get it, you can take data, you can make it mean anything." And this is true, it's absolutely true, but the challenge is that we have this opportunity to try to make meaning out of it ourselves, because frankly, data doesn't create meaning. We do. So as businesspeople, as consumers, as patients, as citizens, we have a responsibility, I think, to spend more time focusing on our critical thinking skills. Why? Because at this point in our history, as we've heard many times over, we can process exabytes of data at lightning speed, and we have the potential to make bad decisions far more quickly, efficiently, and with far greater impact than we did in the past. Great, right? And so what we need to do instead is spend a little bit more time on things like the humanities and sociology, and the social sciences, rhetoric, philosophy, ethics, because they give us context that is so important for big data, and because they help us become better critical thinkers. (emphasis mine)At various time in my life I've taught students mathematics, so in some ways I'm a big fan of data. But the mistake we've made (and are currently doubling-down on with our new state tests) is confusing data with meaning. Data is only as good as the questions you ask, the way you ask them, the way you collect it, and - critically - how you then interpret the data.
Or, as Susan says at about 10:40,
if I don't know what steps you took, I don't know what steps you didn't take, and if I don't know what questions you asked, I don't know what questions you didn't askIn education we currently have a love affair with data, without bothering to ask whether the questions we're asking are the right ones, or the only ones.
Data doesn't create meaning. We do.
Data doesn't define learning. We do. Or at least we should.