Why Computer Science Classes Should Double Up on AI and Data Science
If you are not aware, artificial intelligence and data science might seem like particularly cheesy subsets of the field of computing already infused with handheld protectors.
But anyone who is serious about growing computer science education — a list that includes Fortune 500 CEOs and decision makers from both sides of the aisle– should think carefully about emphasizing AI, in which machines are trained to perform tasks that simulate some of what the human brain can do, and data science, in which students learn to record, store and analyze data.
This means ensuring that children have access to well-designed resources for learning these subjects, enhancing the professional development of those who teach them, exposing guidance counselors to information on how to help students seek a employment in these fields, and much more.
This imperative is at the heart of a list of recommendations by CSforALL, an education advocacy group presented at the annual conference of the International Society for Technology in Education last month.
Leigh Ann DeLyser, co-founder and executive director of CSforALL, spoke to Education Week about some general ideas about wanting to focus more on AI and data science in computer science education. Here are some key takeaways from that conversation.
Computer science education, including AI and data science, can help the next generation tackle big societal issues.
These are the tools that will give students the best chance of tackling challenges in areas such as healthcare and climate change.
“Our world is complex and messy and full of big problems,” DeLyser said. AI and data science are fast growing fields for employment, but “they are also the fastest growing tools used daily by business people, non-profit organizations and governments. No matter what you do for a living, if you want to tackle the big problems we have in the world, you’ll need to understand these things and how they can be used, even if you’re not the programmer writing the code who makes them leave.
Students from all walks of life need to acquire basics in computer science.
It is particularly important to increase socio-economic, racial and gender diversity on the ground.
“Research shows that teams with different backgrounds are better problem solvers because they think about problems in different ways,” DeLyser said. “When everyone comes with the same point of view, you tend to miss some of the big ideas or challenges that come up along the way. … We [want to] provide equal access, regardless of postal code [students] growing up, to those well-paying careers and opportunities later in life.
There are already good models for teaching 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. “Often we frame [computer science access] as a deficient narrative. Nothing happens in education, or education fails.
But that’s not the case, she added. For example, the large school district in 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 with the company are getting first-hand insight into how the retail giant is using AI to configure store layouts, aiming to to maximize profits.
It’s never too early to start teaching artificial intelligence.
Believe it or not, kids as young as kindergarten or even preschool can learn the basics of AI, DeLyser said.
“AI is pattern recognition. One of the most important prerequisite skills for developing algebra and math for kindergartners, and even kindergartners, is pattern recognition.” It’s a circle, it’s a square,” DeLyser said. Teaching AI is “getting them to go further in learning than they do for pattern recognition. It’s like, OK, ‘I’m going to teach you, you’re going to teach a friend. Now I’m going to teach a computer. It’s not that far off from the work they already do.’