The ability to understand how computer programs work is arguably a central part of a well-rounded modern education, in the same way that people once needed to know a bit about horses. Logically, as a friend of mine once argued, programming should probably be taught sooner than calculus, because it develops the same kinds of analytic reasoning skills but is useful to more people. Perhaps one of the reasons that programming isn’t more widely taught is that (apparently) many students have terrible trouble learning it. Others find it utterly straightforward.

A remarkable little working paper by Saeed Dehnadi and Richard Bornat provides intriguing data which illuminates the underlying cognitive step that is taken by those who can learn to program and missed by those who cannot. It turns out that while this mode of thinking is loosely correlated with general educational achievement, the link is not determinate. Some high achievers cannot program, and some low achievers can. Most remarkably, there are other kinds of abstract analytical tasks where performance is very well predicted by educational achievement. Programming just isn’t one of them.

The article is tentatively titled The Camel Has Two Humps. Be sure to get to the last set of graphs.

It appears that these results should open up an entire new field of research on testing the authors’ proposed explanation, polishing the tests that predict ability to learn programming, and — most importantly — figuring out ways to teach programmatic rule structures to those who do not understand them intuitively.