Report Elite Chinese Computer Scientists Don't Outperform Average Americans

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Three years ago, former President Barack Obama went all-in on the growing digital economy. His $4 billion “Computer Science for Allinitiative set out to empower students, from kindergartners to high schoolers, with computer science skills. The program also quietly addressed the growing concern among policymakers that the US isn’t producing enough top-tier computer experts relative to emerging peers like China and India. Fortunately, a new study suggests those fears may be overblown.

“There has been little understanding of how well computer science programs in college – where most of the training of computing professionals seriously starts – have been doing at equipping students with computer science skills,” Stanford researcher Prashant Loyalka tells Inverse.

The results of the new study show that American computer science graduates are still vastly outperforming peers in China, Russia, and India, the three countries who, along with the United States, produce more than half of the computer science graduates worldwide. It’s a finding that should come as some comfort to those who worry that America’s competitive advantage in technology, particularly with regards to China, might be closing. Over the weekend, the New York Times published a new report suggesting as much.

To arrive at these new findings, published Monday in Proceedings of the National Academy of Sciences, Loyalka, along with researchers from Berkeley, the World Bank, and the Education Testing Service, spent nearly three years evaluating the skill levels of international undergraduate seniors majoring in computer science. For data, the researchers looked at scores from more than 8,000 students who sat for a two-hour exam designed by the non-profit Education Testing Service (ETS). Rather than a specific language like Python, ETS lead Lydia Liu explained to Inverse that ETS used “pseudo-code” testing, too, to assess information management skills, software engineering, and deftness with programming algorithms, as well as other complexities. The idea was to develop a framework for how test takers approached “the underlying principles of coding.”

 
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