My predecessor left a ton of books behind in my office, and among some of his old stuff I found a wonderful book called The Pupil as Scientist. The author, Rosalind Driver, makes the case that students develop scientific explanations of what they see long before they set foot into a science classroom. Children’s natural scientific curiosity is both an asset and a liability: teachers can tap into it to engage students in deeper scientific learning, but it can be a source of robust misconceptions, too.
Driver describes beautifully a tension I’ve observed teaching college freshmen laboratories. On the one hand, we want students to observe and discover scientific principles in the laboratory, and leaving procedures open ended is part of that goal. On the other hand, the impact of an experiment seems greatest when it’s done properly, according to a prescribed procedure that yields “good results.” Good data is typically a pre-requisite for grappling with complex scientific concepts, but inquiry-based labs open the door to bad data or incorrect conclusions. How can we properly balance these two opposing forces?
Let me offer an analogy. In some American cities, chess is a popular hobby among the homeless population. There are probably homeless guys living in LA who could give “professionally trained” International Masters a run for their money, despite never having picked up a chess book or paid for a coach in their lives. The homeless chess master is akin to a student who has grown up in inquiry-based science labs: countless opportunities to play have facilitated the development of competency. The professionally trained player is like a student who has come up through prescriptive labs: their skills have come from being told what to expect.
There are virtues to both approaches, and one player will certainly be missing some skills that the other possesses. That’s important to remember in today’s educational climate, which sometimes seems to deify inquiry-based approaches.
Most students coming to college are primed to adopt the “tell-me-what-to-do” orientation, even though professors know this mindset won’t serve them well in their future careers. Part of the issue, I’ve found, can be resolved if I’m upfront with students about errors and how to deal with them (that is, how to be a good experimentalist). Explaining errors in a satisfying way really does get one to the heart of an experiment. If a student designs an experiment poorly and it goes south, at least the discussion of why it went badly presents opportunities for learning. I’ve got to remind myself of that constantly.