Frequently asked
questions

Learning Commons is Mark Zuckerberg and Priscilla Chan’s education initiative, which aims to scale proven teaching and learning practices to benefit every learner. Learning Commons became the name of our education efforts in 2025 to build on the Chan Zuckerberg Initiative’s work over the past decade to advance learning science and help translate that research into classroom practice. Through our partners and our products, we have developed tools and resources that are now reaching more than 5 million students.

Led by Sandra Liu Huang, a product and philanthropy leader, Learning Commons brings together a world-class engineering team, deep knowledge of learning science, and strong connections to researchers, educators, and developers. With our partners, our mission is to build the AI infrastructure that better connects the ways students learn with the tools they learn with.

Our vision is to scale proven teaching and learning practices to benefit every learner.

For far too long, educators have had to stitch disconnected curricula, tools, and technologies together, often at the expense of time, differentiation, and instructional coherence. In turn, students experience inconsistent activities or support that doesn’t fully meet their individual learning needs.

As AI expands the possibilities to better support students and teachers, it also introduces complexity when products aren’t connected or grounded in pedagogy. By collaborating early and often with educators on the development of our products, we’re working to ensure that the evolution of edtech reflects real classroom priorities, aligns to core curriculum, and enables interoperability across tools.

Technology products play a critical role in supporting educators and learners. With our vision to scale proven learning practices to benefit every learner, it is essential that the tools used in every classroom are more consistent and aligned with high-quality curricula, academic standards, and learning science, and rigorously evaluated against expert rubrics and research.

By developing open, machine-readable educational datasets and evaluation methods for AI, we aim to improve the rigor of education technology used by educators to create truly impactful learning experiences.

As a result, we partner with both for-profit and non-profit edtech developers to scale learning science building blocks into their products.

We’re actively partnering with school districts, education technology companies, curriculum providers, researchers, and other education experts to develop high-quality, openly available resources to help integrate trusted instructional content directly into AI-powered edtech tools.

Our partners include 1EdTech, Instructure, Illustrative Mathematics, The Achievement Network (ANet), ISTE, Playlab, Carnegie Learning, EduAide, and The Teaching Lab.

Learning Commons aims to scale proven teaching and learning practices to benefit every learner. Our current products are Knowledge Graph, Evaluators, Curriculum Sync, and Along.

Learning Commons aims to translate what learning science tells us about how students learn best into classroom practice. With the advent of generative AI, that translation work can be accelerated and scaled to have a greater impact. We are building infrastructure for AI tools to make it easier for edtech developers to access pedagogy and research to help create more effective learning experiences for all students.

Our advisory board brings together experts from a range of fields to help guide our efforts to scale proven teaching and learning practices to benefit every learner.

The Advisory Board members are:

Dan Carroll
Former Chief Product Officer and co-founder of Clever

Richard Culatta
CEO of ISTE+ASCD

Bethanie Drake-Maples
Founder and CEO of Atypical AI

Louis Gomez
Professor of Education at UCLA and a member of the National Academy of Education

Babak Mostaghimi
Founding Partner of LearnerStudio

Amelia Vance
Founder and President of the Public Interest Privacy Center (PIPC)

At Learning Commons, we build our tools with care, and a deep sense of responsibility — grounded in safety, transparency, and responsible design. Learn more about our commitment by reading our Responsible AI Principles.

If you have found a bug or have a feature suggestion, please reach out to us at support@learningcommons.org.