Technical data

Data science is the future. Let’s start teaching it (Reviews)


As the coronavirus infected millions of Americans, the media became saturated with numbers: new cases of infection, hospitalization rates, death toll and vaccine test results. Many Americans have been overwhelmed, and in part because too few of us are comfortable with data, we’ve been exposed to a plague of misinformation.

Most Americans lack the skills and knowledge to work with data, despite its critical importance to understand our world and make informed decisions. This data illiteracy must change and our education system must prioritize teaching data science to all students.

Technically speaking, data science is nothing new. Scientists, businesses and governments have a long history of collecting and interpreting data and using it as the basis for decision-making. But two recent changes have made data science much more relevant to all of us. The first is an explosion in data availability, powered by smartphones and the internet. The second is a dramatic improvement in the quality of software tools for analyzing this data.

Although it is generally misunderstood as a skill relevant only for technical roles, the rise of data science has had huge impacts in almost everything from soccer to the history of art. This radical change presents many opportunities, and data analysis and interpretation skills can give young people access to new career opportunities. The employment information website Glassdoor, for example, classified as “data scientist” as the second best job for 2021 based on openings, pay and job satisfaction. Even for those not pursuing a career in data science, huge numbers of working adults (nurses, salespeople, journalists) need data skills.

Most importantly, using data is a practical skill that makes education more relevant. When i wrote Freakonomics, I have used the data to explore topics as diverse as sumo wrestling, real estate, and drug trafficking. Likewise, educators can engage students by having them analyze data on topics of interest to them such as crime., the border crisis, global development, or climate change.

In many ways, this is a plea for pedagogical pragmatism. Our world has been revolutionized by information technology, but our K-12 program is still trapped in the industrial age. Instead of teaching our young people obscure trigonometric techniques, let’s help them learn to interpret the enormous amounts of data produced every day in our hyperconnected world.

Instead of teaching our young people obscure trigonometric techniques, let’s help them learn to interpret the enormous amounts of data produced every day in our hyperconnected world.

So what should be done? Reforms should continue along several lines. First, education policy makers at state and district levels can modernize the curriculum in mathematics and other disciplines, especially in secondary schools, to emphasize data science and mastery of calculus; a dozen states are already starting this work. Second, universities need to change their admission policies to accept data science courses as evidence of rigorous math preparation. Third, federal and state policymakers should increase funding to equip educators with the tools and training necessary to effectively teach this material.

There are already signs of progress. Some organizations, like CourseKata and Bootstrap, expose students to powerful data analysis tools and equip them with the skills to perform real-world analysis and report their findings. CourseKata has developed a comprehensive data science course curriculum and Bootstrap offers flexible modules that can be integrated across disciplines. The US Department of Education’s Institute for Educational Sciences is helping spur change by including data science efforts in its grants.

But there is still a long way to go, which is why my team at the Center for Radical Innovation for Social Change at the University of Chicago launched the Data Science for Everyone Coalition mobilize and bring together an active community, trigger policy reform, and expand access to resources that will catalyze the expansion of data science education in K-12 schools. Over the next two years, the coalition hopes to reach 3,000 members, including teachers, parents, administrators and policy makers.

Basically, this is a popular campaign. This means engaging parents at the local level on the importance of learning data science and connecting with educators in schools across the country, who need more support to teach data science. So far, members of the coalition have achieved important victories.

Coalition members are already improving access to high-quality data science education. For example, the San Diego School District has pledged to roll out data science education across P-12 by 2023, which will impact 120,000 students in 168 schools. The District of Columbia school system is partnering with American University to provide teacher education at the undergraduate and graduate levels. The Stanford Graduate School of Education (known as STEP) teacher education program is launching a new pre-service teacher education course on teaching data science in high school that caters to multiple disciplines. And companies like DataCamp, which offers online data science courses, and Tableau, an analytics platform, offer their software for free to teachers and students.

These organizations are courageously pioneering a new mathematical data-driven future, and we all need to fully commit the resources necessary to make it happen. Let’s build a math curriculum together that further engages students, prepares them for successful careers, and prepares them to become good citizens.