Programming classes in universities regularly require advanced mathematical courses as prerequisites building the perception that aptitude in math is a pre-requisite for being a good coder. This expectation has caused many to shun coding as a career path.
Recent research by Chantel S. Prat has challenged that thought when they found that language aptitude is the largest predictor of individual's Python learning rate. Prat is optimistic these results could spark new discussions about who should learn to code.
Language aptitude and general cognitive abilities
Surprisingly, researchers found that 70% of the variation in Python learning rates can be attributed to language aptitude. This could be due to Python's indentation patterns that mimic “paragraph” style hierarchies present in English writing systems and its goal to be “reader friendly” coding language.
The regression analyses also showed that general cognitive abilities, including fluid reasoning ability and working memory factors (dark red), were the best average predictors of programming outcomes, explaining nearly 34% of the variance across outcome measures.
Coding is for everyone, not just "math people"
To the author of the paper, Prat, the main takeaway is that coding isn’t just for “math people.” As user-friendly languages like Python continue to become more popular, it gives educators an opportunity to reframe whom coding is for, and how it’s used in a variety of professions.
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