Corrected: A previous version of this article should have said that more states are adding data-science education into their K-12 curriculum, but not data-science requirements.
It’s almost impossible to go anywhere or do anything in today’s world without experiencing the impact of data science: from streaming apps’ recommendations to product placements in stores to election predictions.
And the rise of generative artificial intelligence—technology that’s reliant on the data it’s trained on—will only make data-science skills more relevant and important for all jobs, experts say.
“This is not at all relegated to Silicon Valley or traditional technology jobs,” said Zarek Drozda, the director of Data Science for Everyone, a national initiative advocating data-science education to be included in K-12. “It’s hard to name a sector without data science today, and every job—whether it’s the top of the corporate ladder or it’s an entry-level position—will need to be using data more intensively to make decisions on a daily basis.”
In fact, a majority of senior business leaders from the biggest global companies predict that “big-data analytics” will be the No. 1 job creator in the next five years, according to the World Economic Forum’s 2023 Future of Jobs report.
“It is increasingly obvious that every student needs the basic fundamentals of digital skills, data analysis, and ability to navigate new and emerging technology tools,” Drozda said.
Yet students’ basic data-science skills have been in decline. Over the last decade, scores in data analysis, statistics, and probability on the National Assessment of Educational Progress in mathematics dropped 10 points for 4th grade students and 17 points for 8th grade students.
To address those shortcomings, more states are adding data-science education in their K-12 curriculum. The number of states with K-12 data science programs increased from one to 17 over the past three years, according to Data Science for Everyone.
In some school districts, data science is an elective course for high school students; in other places, it’s incorporated into the math curriculum; and in others, it is integrated throughout the K-12 curriculum.
We need to find opportunities to update and modernize state standards that are aligned to the skill sets that students need today and will definitely need five or 10 years from now. It's a challenge that state standards update every 10 years and ChatGPT updates every two to three weeks.
So what do schools need to do to prepare students for jobs and careers that will rely heavily on data-science skills? Here are five steps educators and data-science advocates say schools should take:
1. Invest in professional learning
The most-mentioned action step is for schools and districts to invest in professional learning for educators. Many teachers—sometimes even those who focus on math—are uncomfortable teaching data-science concepts because they don’t have the background for it and weren’t properly prepared in college, according to educators and data-science education experts.
“To my knowledge, nobody is graduating with a degree in data-science education,” said Kevin Dykema, the president of the National Council of Teachers of Mathematics and an 8th grade math teacher in Michigan. “So it’s people who are teaching other content areas that are being told, ‘Hey, you’re now going to teach a data-science course.’ But that wasn’t their background and that wasn’t necessarily their knowledge set, so there’s a need for some professional development.”
Virginia, which is in its second year of piloting its new data-science standards, provided a three-day professional learning event for teachers who are part of the pilot program, said Deb Crawford, the lead for the state’s data-science course-development and pilot team. During those three days, secondary math or computer science teachers were immersed in learning the standards and the tools they can use to teach the content. Teachers also received vetted resources, as well as ongoing support throughout the school year.
2. Focus on real-world applications
Educators and advocates underscore the importance of using curricular resources that give students the opportunity to apply what they’re learning to real-world situations.
Students will be more engaged in the learning if the curriculum uses data that are relevant to their interests, said Maud Abeel, a director for Jobs for the Future, a national nonprofit that develops programs and public policies to increase college and career readiness.
Teachers who let students choose the topics of their data-science projects, whether it’s Spotify trends or March Madness or mental health, find that “students work through the data-science courses faster than anticipated,” Drozda said.
Joy Straub, who taught a dedicated data-science high school course at the Vista Unified school district in California for six years, said the best practice is to make the class “exploratory.” Teachers should give the students the skills to analyze data, “but let them ask the questions. Let the students dig and dig deeper and deeper.”
3. Partner with higher education institutions
School districts can’t do this work alone, educators and advocates say. Colleges and universities have a part to play.
For instance, colleges and universities could partner with their local K-12 schools to help train teachers in data science and develop locally relevant curriculum. Higher education institutions could also ensure that students receive college credit for data-science courses they take in high school, experts suggest.
“This could be one of those areas where the higher ed. community already has probably a pretty strong understanding of what’s important to teach in data science,” Abeel said. “Those partners could help bring data science into the K-12 world.”
Colleges of education and other teacher-preparation programs also need to better prepare future educators to teach data-science skills, experts say.
Tyler Haslam, who is one of 60 high school math teachers across Utah who are piloting a new data-science course and pathway, said that when he was studying to be a teacher, data science and statistics weren’t “heavily focused on for a math teacher.” It wasn’t until he got his master’s degree that he took more advanced statistics courses, which made him feel better prepared for teaching AP Statistics, and now, data science, too.
4. Look for industry partners, too
Businesses and organizations should work with K-12 schools “to create better alignment” between what students are learning and what employers are looking for, Drozda said.
Dykema, the president of the National Council of Teachers of Mathematics, said companies should continue “to beat the drum, saying, ‘We need this. Here’s what schools need to better prepare our current students for the future world.’” Businesses should push lawmakers to fund teacher professional development for data science or create data-science standards for K-12, he added.
Business partners, in turn, can provide resources: internships and credentials for students, curricular materials, and technology tools. For instance, in Virginia, Amazon and NASA are among the partners helping to provide training and materials to data-science teachers, Crawford said.
5. Seek support from policymakers
A lot of the aforementioned steps are difficult to do without funding and without the backing of state standards, according to educators and advocates. Most states don’t have K-12 data-science standards, so educators can’t put much emphasis on the subject, even if they think it’s important.
“We need to find opportunities to update and modernize state standards that are aligned to the skill sets that students need today and will definitely need five or 10 years from now,” Drozda said. “It’s a challenge that state standards update every 10 years and ChatGPT updates every two to three weeks.”