Why Data & AI Literacy are Important Skills for K-12 Students

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Every day, 402.74 trillion bytes of data are added to the internet, presenting a daunting challenge to K-12 students. The new information provides vast new troves of knowledge, but it’s also a breeding ground of disinformation, intrusion, and scams. How can children navigate their education amidst this overwhelming influx of data?

Education experts say the answer lies in acquiring data and AI literacy skills. Such skills, they argue, lead to improved critical thinking, academic gains, and career prospects.

Unfortunately, U.S. schools lag behind other nations in teaching data literacy. A 2022 report by DataScience 4 Everyone, a coalition seeking to expand access to data science education, shows how other countries are implementing data and AI literacy education for children throughout the K-12 grades. From Canadian fourth graders learning about the importance of data in science class to Chinese middle and high school students getting new textbooks dedicated to AI, a range of countries have already embraced new curricula, standards, and teaching strategies to help their students master these hugely important skills.

So, what is data literacy anyway?

Data literacy is a deceptively simple concept. On the one hand, it means exactly what it sounds like. On the other hand, it includes such a vast array of academic and critical thinking skills, that it’s helpful to break it down.

• Data refers to information in any form: words, images, numbers, statistics, charts and graphs, audio, video, etc.
• Literacy is the ability to read, understand, analyze, question, and communicate new information.
• Data literacy is the ability to explore, analyze, comprehend, and communicate with data in a productive way.

Data literacy involves both a collection of technical skills as well as all the thinking and communication skills needed to make data useful in the real world.

Kristin Hunter-Thomson is a former teacher and researcher who now works to help educators understand and incorporate data literacy into their classrooms through her company, Dataspire. “I approach data literacy from the perspective that every citizen in the 21st century should be data literate, in the same way we are able to read, write, and have numeracy skills,” she explains. “Many people think of data literacy as large datasets driving corporate decision-making, but I think about it in terms of what data visualizations show up on your electricity bill or through your smartwatch or in the news. Teaching students data literacy is teaching them the language of data so that they can be successful going about their lives in our data-filled 21st century.”

In other words, data literacy can’t be taught in a vacuum. It’s a skill set that can only be learned after many other skills are in place, including:

• Research. Students need to understand how to find information not just by googling or ChatGPTing a query, but by pinpointing their searches.
• Being savvy consumers of information. Once presented with information, students need to learn how to evaluate different sources: Are they valid? What’s their point of view? Where is the information coming from? Answering these questions requires domain knowledge (including academic subjects like history or science and current events like the news or technological trends).
• Critical thinking. When analyzing information, students need to know how to question assumptions and employ logic as they evaluate the information they find.
• Technical fluency. Students need a range of technical skills to understand and manipulate data, including managing data sets, mining existing data, warehousing, and organizing data. To extract meaning from the data they need to be adept at using a variety of data-related tech tools (e.g. Excel, sheets, Tableau, Mixpanel) and may require programming, statistics, algebra, or calculus.
• Communication is essential. To be truly data literate, students need to be able to communicate with others about their work, findings, and thought processes. This requires strong communication skills, including active listening, writing, public speaking, and presentation design — including visualization — skills.

With these skills in place, students can interact with data in smart and meaningful ways. Are these skills enough for your child to be ready for a world of fast-changing jobs and technology? Not quite. With the advent of Artificial Intelligence (AI), experts are arguing that students also need AI literacy to help them navigate the technology that is expected to upend everything from office work and truck driving to medicine and manufacturing.

What is AI literacy?

Artificial Intelligence (AI), the transformative technology that enables computers to perform human-like tasks by organizing huge quantities of data, has already changed many students’ lives. According to a 2023 ACT survey, about 46 percent of high school students have used an AI tool (most commonly ChatGPT) with school work as their primary reason. Since so many high school students are already using AI it stands to reason they should also acquire AI literacy skills.

AI literacy involves both the ability to:

• understand how artificial intelligence works; and
• use AI technologies competently.

Many underlying critical thinking skills needed for AI literacy are similar to those needed for data literacy, but students need additional technical skills and knowledge of Artificial Intelligence to use AI effectively and ethically.

As an example of an AI-focused curriculum, Inspirit, an online program taught by students and graduates of Stanford, Harvard, and MIT, offers fifth to seventh graders an AI education that starts with learning block-based programming tools and advances to machine learning models for chatbots and self-driving cars. For seventh and eighth graders, the Inspirit curriculum includes programming in Python and RunDexter, training AI to fight disease or understand human language, and applying algorithms to real-world data sets. Classes for high school students offer small mentor-led groups that use AI to design socially useful projects that are presented to parents and guests on the last day of the class.

Hunter-Thomson, founder of Dataspire, believes teachers need to help students understand how AI is trained by previous human input and how to think critically about AI tools and outputs. In the era of AI, when there can be less transparency about information sources, she says it’s essential that students understand “where information shared online comes from, how it is created, and how to vet the source” since AI can both generate falsehoods unintentionally and can easily be used to deceive.

The benefits of data literacy and AI literacy

• Academic gains. The Thinking With Data Project in 2012 conducted a quasi-experimental study where seventh graders in two different schools in Ohio learned data literacy skills in math, science, English language arts, and social studies while students in the control group did not learn data literacy skills. The students who learned data literacy skills ended up earning higher test scores in both math and social studies than the control group.
• Ethical thinking skills. Some research suggests data literacy also helps K-12 students’ ethical understanding. For instance, in a 2022 study, researchers from the Massachusetts Institute of Technology and Boston College found that AI literacy in middle school helped students identify bias and understand ethical and societal concerns.
• Future prospects. Data literacy may also ensure students have a crucial set of skills for their careers. The Data Literacy 2023 Report surveyed 558 business leaders in the U.S. and the U.K. about the need for data literacy skills when hiring new employees. According to the report, 66 percent of business leaders “would be willing to pay a higher salary to candidates with strong data literacy skills.” Seventy-seven percent of the business leaders suggested a salary increase of 10 to 15 percent for data-literate candidates, and approximately 25 percent said they would offer a 30 percent hiring bonus. Additionally, the U.S. Bureau of Labor Statistics shows the current median salary for the occupation Data Scientist is $108,000 and projects that the occupation will grow 35 percent between 2022 and 2032 — with related fields also being in high demand and earning high pay.

Where does the U.S. stand compared to other countries in teaching data literacy?

In countries around the world, schools are rushing to teach data and AI literacy. In Germany, starting in fifth grade all students do a year-long data science project focused on machine learning and data exploration. In U.K. secondary schools, students learn to use Geographic Information Systems (GIS) to collect, map, analyze, edit, and visualize geographic data. In grade nine, students in India study ethics in data science.

Other nations stand out as leaders in the field of data and AI education. China published AI textbooks for middle and high school students in 2018, while downgrading geometry, algebra, and calculus from mandatory courses to optional. Questions related to these downgraded math classes were also removed from the college entrance exam and replaced, in part, by questions related to data analysis.

Equally sweeping is Singapore’s “Smart Nation” strategy. The initiative helps teachers use AI to customize education for every student, especially those with special needs. AI “companions” provide individualized feedback to motivate every pupil after identifying how they respond to classroom activities and materials. Similarly, South Korea plans to provide every student with an AI tutor that understands their specific learning behaviors and guides them toward personalized homework assignments. In addition, they have pledged to implement AI as a subject in the K-12 curriculum nationwide by 2025.

In New Zealand, each year 30,000 primary and secondary students participate in the Census at School project that teaches data science, probability, and statistics using data they collect. New Zealand also has early learning centers that embrace data literacy as a form of language for kids as young as 4 and 5. “The work that folks are doing in New Zealand … is really exciting and pushing the field forward,” shares Kristin Hunter-Thomson of Dataspire.

Slower progress in the U.S.

American schools trail behind the nations listed above, but efforts are being made to catch up. A “data literacy crisis” was announced in the U.S. after math scores for 15-year-olds plummeted 13 points during the Covid-19 pandemic. To combat this, a bipartisan group of legislators have supported the passage of H.R. 1050, the Data Science and Literacy Act. The bill would provide funding to develop curricula in data literacy, purchase high-quality learning materials, and hire and train data science educators. The bill is expected to be introduced in the U.S. Senate in September 2024.

In the meantime, data literacy is gradually taking hold at the state and federal levels. Data Science for Everyone’s map indicates that as of March 2024, a dozen states have added data science to their course catalogs, nine more have added pilot courses or professional development training for teachers in data literacy, and six others are working on adopting standards. Zarek Drozda, Director of Data Science for Everyone, also noted in a recent interview with Ed Week that 19 states have a subject code that allows them to offer data literacy and data science programs to their students.

AI literacy lags farther behind. In November 2023, the National Artificial Intelligence Advisory Committee (NAIAC) published a report that recommends education in AI Literacy. Unfortunately, the NAIAC proposal prioritizes college and university students, all but ignoring K-12 students.

What’s the future of data and AI literacy in our children’s classrooms? To paraphrase an old cliche: AI is the limit. Just as AI itself is transforming our economy, workplaces, and everyday tools, it’s inevitable that it will ultimately change how our children learn as well. The question remains: how fast will America’s schools and families adapt?

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