Study reveals you don’t have to be a math expert to become a coder

Those who learned the programming language faster and with greater accuracy tended to have a better bent towards language abilities and problem-solving prowess.

Code strings on the screen. (Pixabay)

A new study may come as a respite for those who are averse to mathematics but are still interested in becoming coders. A research by the University of Washington says a natural aptitude for learning languages are a stronger predictor than mathematics for those looking at a career in programming.

The research, which has been published in Scientific Reports, examines neurocognitive abilities of more than 36 adults as they learned Python, a common programming language.

Volunteers were subjected to a battery of tests to understand more about their executive function, language and math skills. They were then asked to complete a series of online lessons and quizzes in Python.

Those who learned the programming language faster and with greater accuracy tended to have a better bent towards language abilities and problem-solving prowess.

According to lead author Chantel Prat, there are multiple barriers to programming that include an "idea that programming relies heavily on math abilities, and that idea is not born out in our data." Prat is an associate professor of psychology at the University of Washington and at the Institute for Learning & Brain Sciences.

He went on to add that while learning to program is hard, it 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," he elaborated.

The research also asserts that coding has a foundation in human language as it involves creating meaning by stringing symbols together in rule-based ways. It concluded that the marks in language aptitude test were the strongest predictors of participants' learning rate in Python.