Jo Boaler, professor of mathematics education at Stanford and Rob Gould, professor of statistics at UCLA have joined forces to propose data literacy standards for PK-12 students.

The authors begin with a 2016 Stanford study indicating that students are not able to properly evaluate online information to know what is real and what is fake. Middle, high school, and college students were fooled by sponsored content, altered images, and fake accounts. Students did not seek to verify sources of the information shared. The study presented students with digital content from Twitter, Facebook, website articles, comment sections, and online videos. Outcomes of the study included a call for both curriculum development and increased awareness of the depth of the problem.

Boaler is also the co-author of the 2021 NCTM article, Making Sense of a Data-Filled World, encouraging PK-12 teachers to integrate data literacy in their classrooms. The article recommends the use of real data, relevant to students’ lives, to develop data literacy and data science courses in the upper school. “… collecting, analyzing, and communicating about data give students opportunities to deal with uncertainty in data, to pursue their own lines of thinking, and to connect mathematics to their own lives.”

The authors return to a lack of data science standards as part of the problem. They refer to the “race to calculus” as an inequitable track beginning in middle school and suggest data science as an alternative pathway that is widely applicable to a variety of disciplines and college majors. A data cycle is proposed for each grade level that begins with investigative questions and continues through collections, analyzation, and communication. The cycle is outlined here with tasks, data talks, teacher advice, and privacy discussion prompts for each grade level.

Described as both an oversight and opportunity, data literacy skills are the new “STEM” in the world of education trends. These are the skills that should be nurtured in the youngest grades, preparing our students to employ data science competencies as they grapple with problems and develop solutions in our data-rich world.