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Why Computer Science Classes Should Double Down on AI and Data Science


If you don’t know, artificial intelligence and data science can sound like particularly nerdy subsets of the pocket-friendly computer science field.

But anyone serious about expanding computer science education—a list that includes Fortune 500 company CEOs and policymakers on both sides of the aisle—needs to think hard about emphasizing AI, where machines are trained to perform tasks that mimic some of what the human brain can do, and data science, where students learn to recording, storing, and analyzing data.

That means making sure kids have access to well-designed resources to learn the subjects, strengthening professional development for those who teach them, exposing career counselors to information on how to help students who can pursue jobs in those fields, and more.

That requirement is central to a list of recommendations by CSforALL, an education advocacy group presented last month at the annual conference of the International Society for Technology in Education.

Leigh Ann DeLyser, co-founder and executive director of CSforALL, spoke to Education Week about some big ideas around the push for a greater focus on AI and data science within science education. computer. Here are some key takeaways from that conversation.

Teaching computer science—including AI and data science—will help the next generation solve big societal problems.

These are the tools that will give students the best chance to crack challenges in areas such as health care and climate change.

“Our world is complex and chaotic and full of big problems,” DeLyser said. AI and data science are fast-growing areas when it comes to work, but “they’re also the fastest-growing tools that entrepreneurs, nonprofits, and governments use every day. No matter what you do in life , if you want to tackle the big problems we have in the world, you need to understand these things and how to use them, even if you’re not the programmer who writes the code that makes them work.”

Students from all different backgrounds need to get a grounding in computer science.

It is especially important to increase socioeconomic, racial, and gender diversity in the field.

“Research shows that teams with diverse backgrounds are better problem solvers, because they think about problems from different ways,” DeLyser said. “If everyone comes with the same vision, you tend to miss some ideas or the big challenges that come along the way. … We [want to] provide equal access, regardless of ZIP code [students] growing up, to high-paying careers and opportunities later in life.”

There are already good models of how to teach AI and data-science.

It’s possible to see school districts already experimenting with how to do this well, if you know where to look, DeLyser said. “Usually, we frame [computer science access] as a deficit account. Nothing happened in education, or education failed.”

But that is not the case, he added. For example, the large school district of Gwinnett County outside of Atlanta, is preparing to open a high school that will focus on artificial intelligence. And in Bentonville, Ark., where Walmart is headquartered, local high school students interning at the company got a first-hand look at how the retail giant uses AI to configure layouts in the store, with an eye on maximizing profits.

It’s never too early to start teaching artificial intelligence.

Believe it or not, children as young as kindergarten or even preschool can be familiar with the basics of AI, DeLyser said.

“AI is pattern recognition. One of the most important pre-school skills for developing algebra and math for kids in kindergarten, and even preschool, is pattern recognition. ‘This is a circle, this is a square,'” DeLyser said. Teaching AI is “taking the learning they do for pattern recognition one step further. Like, OK, ‘I’ll teach you, you teach a friend. Now I’m going to teach computers.’ It’s not too far from the work they do.”





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