There is transfer between programming and other subjects: Skills overlap, but it may not be causal

A 2018 paper by Ronny Scherer et al. “The cognitive benefits of learning computer programming: A meta-analysis of transfer effects” was making the rounds on Twitter. They looked at 105 studies and found that there was a measurable amount of transfer between programming and situations requiring mathematical skills and spatial reasoning. But here’s the critical bit — it may not be casual. We cannot predict that students learning programming will automatically get higher mathematics grades, for example. They make a distinction between near transfer (doing things that are very close to programming, like mathematics) and far transfer, which might include creative thinking or metacognition (e.g., planning):

Despite the increasing attention computer programming has received recently (Grover & Pea, 2013), programming skills do not transfer equally to different skills—a finding that Sala and Gobet (2017a) supported in other domains. The findings of our meta-analysis may support a similar reasoning: the more distinct the situations students are invited to transfer their skills to are from computer programming the more challenging the far transfer is. However, we notice that this evidence cannot be interpreted causally—alternative explanations for the existence of far transfer exist.

Here’s how I interpret their findings. Learning program involves learning a whole set of skills, some of which overlap with skills in other disciplines. Like, being able to evaluate an expression with variables, once you know the numeric value for those variables — you have to do that in programming and in mathematics. Those things transfer. Farther transfer depends on how much overlap there is. Certainly, you have to plan in programming, but not all of the sub-skills for the kinds of planning used in programming appear in every problem where you have to plan. The closer the problem is to programming, the more that there’s an overlap, and the more we see transfer.

This finding is like a recent paper out of Harvard (see link here) that shows that AP Calculus and AP CS both predict success in undergraduate computer science classes. Surprisingly, regular (not AP) calculus is also predictive of undergraduate CS success, but not regular CS. There are sub-skills in common between mathematics and programming, but the directionality is complicated.

We have known for a long time that we can teach programming in order to get a learning effect in other disciplines. That’s the heart of what Bootstrap does. Sharon Carver showed that many years ago. But that’s different than saying “Let’s teach programming, and see if there’s any effect in other classes.”

So yes, there is transfer between programming and other disciplines — not that it buys you much, and the effect is small. But we can no longer say that there is no transfer.