Prioritizing STEM and coding won’t fill one of the biggest gaps in education

Teaching our kids STEM and coding won’t prepare them for the future.
Teaching our kids STEM and coding won’t prepare them for the future.
Image: AP Photo/Eric Risberg
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Like a lot of working parents, when I’m walking my daughters to school or listening to them recount their days at the dinner table, one question is often on my mind:

What should I be doing to prepare them for the world they’ll enter as adults?

When my daughters and their peers enter the workforce in 10 years, the global economy will be even more competitive, automated and technology-driven than it is today. Computing will be faster and cheaper. Artificial intelligence will be even more powerful, complemented by sensors everywhere in our environments—making it impossible to distinguish between “online” and “offline.”

Our greatest challenges, from climate change to economic inequality to privacy, will be even more acute.

Our current education systems aren’t set up to prepare kids for this reality. Schools can’t keep pace with how quickly technology is changing and they lack the resources to adapt. (Given the number of public school teachers in the US who spend their own money on basic classroom supplies, it’s safe to say that accommodating an entirely new tech-driven future will be a challenge at the very least.)

The response from schools so far has been to promote STEM—Science, Technology, Engineering, and Math—education and to teach students to code. But will these skills really equip our kids to find success in the future world of work?

Content knowledge skills are relatively easy to learn, standardize and assess. That means they’re also easy to automate. As AI and education expert Stuart Elliott has pointed out, computer literacy capabilities surpassed 30% of workers in developed countries in 2016. By 2026, this number will be 60%. As for numeracy skills, including math and data analysis, computers will outperform nearly 100% of workers.

With rapidly improving automation, lifelong learning and continuous reskilling are becoming the norm. The nature of “human work” is also changing, which means the engineers of tomorrow will need to do much more than write code. They will need to do the messy work of navigating uncertainty, solving problems collaboratively, and anticipating the implications of launching a technology product into the world.

Measuring the future

In 2016, the World Economic Forum predicted that the top three skills for 2020 are complex problem-solving, critical thinking and creativity.

With 2020 just around the corner, educators need a framework for teaching skills like these, but as yet they aren’t a part of most school curricula.

Education boards need a blueprint for a new kind of learning that will equip young people to be comfortable with ambiguity, to be self-aware, to solve problems in complex, stressful situations, to be able to make high-stakes decisions, and finally, to think creatively.

At the AI for Good Global Summit this past spring, cognitive neuroscientists, educators and social scientists discussed a first step: Setting standards for complex systems-thinking and lifelong learning, the same way many countries have done for coding.

No standards will be perfect, of course, but they can start to guide the development of relevant—and free—online curricula. They can also help to shape training and resources for educators, evolve student assessments, and build AI-powered tools that coach learners to be creative problem solvers.

Another important step is to break down complex skills into milestones that can be more easily taught and, importantly for academics, measured. For example, to tackle difficult problems, students first need to learn the skills to identify what a meaningful problem is, as well as the technical basics to solve it. At that stage, they can apply their technical knowledge to prototype solutions. Then they’ll need to learn how to work in teams, and how to think about the societal and ethical implications of launching a new technology product into the world, and so on.

While we’ve seen progress in research in this space, it’s just not happening fast enough. The Organization for Economic Cooperation and Development has created milestones for collaborative problem-solving and is researching a similar set of milestones for creativity and critical thinking skills. This work will take years at its fastest.

So, in the meantime, we—parents and professionals today—need to take action.

I’m inspired by computer scientist Seymour Papert’s belief that it’s possible to leapfrog traditional learning pathways using technology. Almost 40 years ago, Papert predicted that children could develop programming skills, such as debugging, even earlier than literacy skills, through his example of a three-year-old who couldn’t read but could verbally and logically query a computer program to learn about bears.

Today, we have an urgent need to leapfrog pathways to skill-building.

Use IRL problems to teach IRL skills

After 14 years of working in education, it’s clear to me that the best way to do this is through real-world problem-solving. 

We need to give children the tools to look about their world, find the problems they’re passionate about, and design solutions for them. This type of learning can be a vehicle for skills like systems thinking and collaboration. At the same time, real-world problem-solving can demystify technologies like AI that are becoming integral to our work and daily lives.

Real-world problem-solving is critical because it rewards kids’ desire for meaning. As they face an uncertain future, young people don’t just want to know they’ll have a job. They want to play a role in shaping the world they’ll inherit and continue to learn as part of it. By solving problems that impact their lives, children can develop skills for agency, confidence, and hopefully, a sense of optimism.

We need to change how we educate our children so they can thrive in the world we present to them in 2030.

Over the past decade, after millions of dollars of investment into coding and STEM education, the number of underrepresented communities in these fields has barely moved. We don’t have time to repeat our mistakes. We need to set much bolder goals and move beyond narrow skill-building. We need our kids today to learn to thrive in a world that may be uncomfortable, nebulous, and full of tomorrow’s hard questions, waiting for their answers.