This whitepaper distills the K-12 explainable AI literacy framework—covering pedagogy, curriculum design, resource ecosystems, and implementation pathways for schools.
A four-step explainable model (Context · Core Concept · Collaborative Practice · Assessment) plus curriculum maps that help educators build AI literacy lessons fast.
Sample lesson decks, project tasks, rubric templates, and student work to create a full teacher–student resource loop.
Policy alignment, school governance, and teacher development roadmaps with milestones for responsible deployment.
Three chapters: Vision (core concepts), Design (curriculum and resource methods), and Governance (long-term operations and policy).
Downloadable assets stay in sync with the site, ready for sharing or remixing inside schools.
Quarterly releases with additional drops around key semester checkpoints. Summaries appear on the site for quick tracking.
Use the links above or contact our curriculum team for print copies and co-development opportunities.
We iterate with classroom evidence and policy updates. Share cases, tools, or data to help grow an open K-12 explainable AI ecosystem.