Visual ability predicts a computer science career: Why? And can we use that to improve learning?

I’ve raised this question before, but since I just saw Nora Newcombe speak at NCWIT, I thought it was worth raising the issue again. Here’s my picture of one of her slides — could definitely have used jitter-removal on my camera, but I hope it’s clear enough to make the point.

This is from a longitudinal study, testing students’ visual ability, then tracking what fields they go into later. Having significant visual ability most strongly predicts an Engineering career, but in second place (and really close) is “Mathematics and Computer Science.” That score at the bottom is worth noting: Having significant visual ability is negatively correlated with going into Education. Nora points out that this is a significant problem. Visual skills are not fixed. Training in visual skills improves those skills, and the effect is durable and transferable. But, the researchers at SILC found that teachers with low visual skills had more anxiety about teaching visual skills, and those teachers depressed the impact on their students. A key part of Nora’s talk was showing how the gender gap in visual skills can be easily reduced with training (relating to the earlier discussion about intelligence), such that women perform just as well as men.

The Spatial Intelligence and Learning Center (SILC) is now its sixth year of a ten year program. I don’t think that they’re going to get to computer science before the 10th year, but I hope that someone does. The results in mathematics alone are fascinating and suggest some significant interventions for computer science. For example, Nora mentioned an in-press paper by Sheryl Sorby showing how teaching students how to improve their spatial skills improved their performance in Calculus, and I have heard that she has similar results about computer science. Could we improve learning in computer science (especially data structures) by teaching spatial skills first?

Science of Spatial Learning: Nora Newcombe at NCWIT

Great to see this coverage of SILC in US News and World Report, and I’m excited to hear Dr. Nora Newcombe speak at the NCWIT Summit Tuesday of this week. As I’ve mentioned previously, SILC hasn’t looked much at computer science yet, but there are lots of reasons to think that spatial learning plays an important role in computing education.

Spatial reasoning, which is the ability to mentally visualize and manipulate two- and three-dimensional objects, also is a great predictor of talent in science, technology, engineering and math, collectively known as STEM.

Yet, “these skills are not valued in our society or taught adequately in the educational system,” says Newcombe, who also is principal investigator for the Spatial Intelligence and Learning Center.  “People will readily say such things as ‘I hate math,’ or ‘I can’t find my way when I’m lost,’ and think it’s cute, whereas they would be embarrassed to say ‘I can’t read.’

“People have a theory about this skill, that it’s innate at birth and you can’t develop it, and that’s really not true,” she adds. “It’s probably true that some people are born with a better ability to take in spatial information, but that doesn’t mean if you aren’t born with it, you can’t change.  The brain has a certain amount of plasticity.”

via Science of Spatial Learning – US News and World Report.