Computer programming is a broad field that touches nearly every industry, but it’s most often associated with engineering. This is true in both the corporate world and academia, where math is a common pre-requisite for university-level studies.
On the surface, the association between “computer science” and “math” may seem harmless, but it could be one of the reasons the tech sector has struggled to close the gender gap.
A July 2019 study of 300,000 fifteen-year-old students from 64 countries, for example, found that while pupils of all genders demonstrate math proficiency, female students who were good at math appeared to be “much more likely” to be better at reading than their male counterparts.
Because some female students see a “competitive advantage” over males in reading, they’re more likely to deviate from math and — in turn — computer science.
But a new study out of the University of Washington (UW) suggests math may not be the best predictor of coding success.
The paper, which was published Monday in Scientific Reports, studied more than three dozen native English speakers between ages 18 and 35 as they learned the programming language Python.
Strong language skills a predictor of coding success
Participants performed a series of tests to assess their language and math skills. It was discovered that language aptitude test scores were “the strongest predictors” of their learning rate with Python, even more so than reasoning and math.
“This is the first study to link both the neural and cognitive predictors of natural language aptitude to individual differences in learning programming languages,” lead author Chantel Prat, an associate professor of psychology at the UW and at the Institute for Learning & Brain Sciences, said in a statement.
“We were able to explain over 70 per cent of the variability in how quickly different people learn to program in Python, and only a small fraction of that amount was related to numeracy.”
Gender-based assumptions may also discourage women from learning to code. The study’s authors point to other research from UW psychology professor Sapna Cheryan, which suggests the requirements for computer science programs reinforce the stereotype that programming is “masculine” and push women away.
“Many barriers to programming, from prerequisite courses to stereotypes of what a good programmer looks like, are centered around the idea that programming relies heavily on math abilities, and that idea is not born out in our data,” Prat said.
“Learning to program is hard, but is increasingly important for obtaining skilled positions in the workforce. Information about what it takes to be good at programming is critically missing in a field that has been notoriously slow in closing the gender gap.”