How can teachers help struggling computationalists
My Blog@CACM post for this month is about imagining the remedial teaching techniques of a school-based “Computing Lab” in the near future.
It’s becoming obvious that computing is a necessary skill for 21st Century professionals. Expressing ideas in program code, and being able to read others’ program code, is a kind of literacy. Even if not all universities are including programming as part of their general education requirements yet, our burgeoning enrollments suggest that the students see the value of computational literacy.
We also know that some students will struggle with computing classes. We do not yet have evidence of challenges in learning computation akin to dyslexia. Our research evidence so far suggests that all students are capable of learning computing, but differences in background and preparation will lead to different learning challenges.
One day, we may have “Computing Labs” where students will receive extra help on learning critical computational literacy skills. What would happen in a remedial “Computing Lab”? It’s an interesting thought experiment.
I list several techniques in the article, and I’m sure that we can come up with many more. Here’s one more each DO and DON’T for “Computer Lab” for struggling computationalists.
- DO use languages other than industry standard languages. As I’ve mentioned before in this blog, CS educators are far too swayed by industry fads. I’m a big fan of Livecode, a cross-platform modern form of HyperCard. An ICER 2016 paper by Raina Mason, Simon et al. estimated Livecode to have the lowest cognitive load of several IDE’s in use by students. If we want to help students struggling to learn computing, we have to be willing to change our tools.
- DON’T rely on program visualizations. The evidence that I’ve seen suggests that program visualizations can help high-ability students, and well-designed program visualizations can even help average students. I don’t see evidence that program visualizations can help the remedial student. Sketching and gesture are more effective for teaching and learning in STEM than diagrams and visualizations. Sketching and gesture encourage students to develop improved spatial thinking. Diagrams and visualizations are likely to lead remedial students into more misconceptions.