K-12 Data Literacy and Data Science Learning Progressions

A roadmap for teaching K-12 data science

New to data science? Start here About these progressions

Explore the Learning Progressions

The progressions form a cycle, beginning with core ideas in Strand A and building deeper skills through Strands B to E.

Dispositions & Responsibility

Knowing what data is, where it comes from, and how people shape it

Essential core habits

Strand A

Creation & Curation

Taking messy, real-world information and organizing it

Methods & techniques

Strand B

Analysis & Modeling Techniques

Making sense of data by exploring patterns and using the right tools to draw meaningful insights

Methods & techniques

Strand C

Interpreting Problems & Results

Using data to ask strong questions and make evidence-based claims

Methods & techniques

Strand D

Visualization & Communication

Communicating with data through clear visuals and messages tailored to your audience

Methods & techniques

Strand E

Explore the Learning Progressions

What's Next

5 min read

What’s next for these learning progressions

See how data science connects to your subject, with subject-specific progressions coming in 2026.

Getting Started

5 min read

Five basic concepts for teachers new to data science

Not sure where to start with data science? Good news – you’re probably already practicing more data science than you realize.

Background

8 min read

How to Prioritize the Learning Progressions

Think of this as your onboarding ramp to the learning progressions — start with the most critical ideas and build your data science toolkit over time.

Explore the Learning Progressions

Dispositions & Responsibility

Creation & Curation

Analysis & Modeling Techniques

Interpreting Problems & Results

Visualization & Communication

Explore the Learning Progressions

What’s next for these learning progressions

Five basic concepts for teachers new to data science

How to Prioritize the Learning Progressions

Developed by our coalition

Coalition organizers