In class, we worked together to make sense of data. We usually think of “data” as something that comes in numbers and graphs, like it did with pendulums and with motion data collected in lab. But it can take many forms, like this example we imagined of indentations on some sandstone:

(This is taken from a lesson often referred to as “Tricky Tracks.” An example is here, though the idea goes back a long time. This version comes from the National Research Council¹.)

The fun thing about revealing this bit by bit is that we can start to imagine the possibilities and where this collection of observations is going to lead us. We made some points in our discussion that, even though I asked “what do you see?” many times we start to go straight to what we interpret. We have to be careful about this distinction. At the same time, there’s a lot of power that our sense-making adds to the observations. We start to see patterns and possibilities, and the way that we connect these observations to other things we’ve seen (other big and small organisms, predator-prey relationships, parent-child relationships, not to mention the idea of dinosaur tracks or bird tracks in general). How we find meaning in these data is important. We have to rely on the data and be ready to change our ideas if we find new, contradictory observations; but we also get to construct a new idea that the observations don’t tell us directly.

That was the point of where I took you next, suggesting that you look at the following set of words as if they had been spilled on a parking lot and you had to reconstruct their origin:

This isn’t a real scientific situation, but it’s something that’s a lot like our Tricky Tracks scenario or the way that we figure out the Earth goes around the Sun or how we figure out how matter is made out of lots of small particles we can’t see directly. We take all this evidence and put it together into patterns, knowing about other patterns and using our knowledge of the data at hand. For example, we know that words often come from stories, and we can start to imagine how these ideas could have been strung together. We might have something out of order before we get more information; and we might even have something really backwards at some point. For example, “crane” is a piece of equipment but it’s also a bird, and it’s also a verb, something we might do with our neck and head. But in the context of movers and dangles, we start to put together a possible use of a tall crane dangling a piano. Oh, and the “stories” seem to fit well with this, as long as they’re referring to levels of a building rather than narratives and tales. Though it could be both.

We also had to know a little bit to make more sense of this. “Steinway” is a famous line of pianos, but that isn’t necessarily familiar to you. “April” could be a month or a name of a person, though we start to imagine it’s about the calendar and season when we combine it with snow—something that might be surprising and story-worthy, but still possible.

There are lots of other examples of how different meanings and interpretations can get pulled into this. We’d always want to be able to look for more data and see if those fit as well. We’d also want to be able to compare this data set to others and see if there are similar patterns. When Venus was first observed with a telescope, for example, Galileo was able to see that it went through phases, like the Moon. But the pattern of apparent sizes and phases it goes through is different than the Moon’s, and this tells us something really important about orbits and positions of planets.

One of the most interesting things about this exercise (to me, at least) is how we all come up with very similar stories based on these words, for the most part. (There’s always a new, creative solution to this puzzle, I’ve noticed. That happens in science, too; and it’s really important that we allow for these when the data support them.) Nature will never directly reveal to us the answers to all our questions—we can’t go back in time and really see what happened between the two creators of the footprints we observed—even though we get really consistent, testable explanations. In this case, though, I’m happy to reveal to you where these words came from. It’s one of my very favorite poems, written by Taylor Mali, an advocate for teachers and teaching. It’s called Undivided Attention.

I like this exercise a lot as a way to help us understand how we create explanations from observations, and how that is more interesting than you might first imagine. But I’ll admit that I love doing this in class so that I have a chance to read this poem. It’s hanging over my desk and it’s often the last thing I see before I step into a class.

1. National Academy of Sciences (1998). Teaching about evolution and the nature of science. Washington, D.C.: National Academy Press, p. 89. ↩