Experiments are a critical part of science—perhaps even the central feature. But middle school and high school science experiments don’t teach students how experiments are supposed to work.

The way I did science experiments in school went something like this:

  1. Learn about some natural phenomenon.
  2. Teacher explains an experiment intended to test the natural phenomenon or at least vaguely relate to it.
  3. We run the experiment, with the ostensible goal of observing the natural phenomenon.
  4. We get results totally different from what the laws of nature predict.
  5. Whatever, let’s move on to the next subject.

For example, I remember in physics class we learned about how acceleration due to gravity changes when an object rolls down an incline based on the steepness of the incline. Then we did an “experiment” to test this by rolling marbles down inclines and measuring how far they got in a fixed amount of time. The results we got were inconsistent with the laws of mechanics, but nobody questioned ths. We all assumed that our experiment was not sufficiently well-controlled to produce reliable results (which was accurate).

This is the antithesis of how experiments are supposed to work. The point of running an experiment is to learn something about the world. Experiments should be well controlled so you can be confident that you are learning something.

Running a good experiment is not easy. Experiments can easily fail to produce good results, so they must be designed carefully. Designing good experiments is a skill. And the way experiments are done in school does nothing to teach this skill.

If you know in advance that you have bad methodology and you’re going to throw away the results of your experiment, what’s the point? Experiments as they are done in school don’t teach about natural laws (because you ignore whatever results you get), and they don’t teach how to design good experiments (because no effort is made to produce consistent results).

I can imagine an effective science class that focused on teaching students how to design experiments. You could perhaps start by providing students a simple natural law, such as an object’s acceleration on an inclined plane, then challenge them to produce an experiment that replicates the results. If they don’t produce consistent results, push them to figure out why, and refine their experimental conditions until they can get reliable measurements.

But the point of an experiment isn’t (usually) to reproduce known results—it’s to figure out something unknown. A good experiment should be able to falsify a hypothesis; you shouldn’t just keep changing your experiment until you get the expected results. (The process I described in the previous paragraph is basically P-hacking.) I don’t know how you would teach people to get from “design an experiment that can consistently replicate a known natural law” to “design an experiment that can tell you something you don’t already know, and be confident that it’s correct.” But I’ve only been thinking about it for a few minutes. We are collectively wasting tens of millions of hours per year having students run experiments while learning nothing about how to run experiments, and I’m sure we can do better.

Let me throw out a slightly more sophisticated idea for how to teach experiments. Give students a natural phenomenon to investigate; it should be something they probably don’t already know (so they don’t know what result to expect), but that isn’t too hard to test. Divide the students into groups and have them design and implement experiments to figure out the phenomenon. Then challenge them to peer review each other’s experiments and look for flaws. Refine the experiments until most of the class agrees on the correct methodology and can replicate each other’s results.

This also provides a natural way to teach students statistics. If you need to develop good experimental methodologies, you need to have a way of knowing how reliable your results are and how many trials to run. Some students will try to understand how to do this, and as they begin to think more deeply about it, they will inevitably ask the same questions that inferential statistics is meant to answer. This is the perfect time to equip them with some statistics knowledge that they can use to improve their understanding of science.

I’m tempted to get overzealous about how significant it would be if we consistently ran science classes this way. I would like to say that it would solve the replication crisis, bring an end to shoddy news reporting, and revolutionize politics. Probably none of that would happen, and maybe this whole thing isn’t even a good idea. I’m just theorizing, I haven’t tested any of these ideas experimentally.