Use case: If your product generates content for students in a specific state or district, and you need it grounded in that state’s standards.
Your product generates AI content for end users. Without structured standards data, that content gets generated in a vacuum. For example, a prompt can ask for “a 3rd grade fractions lesson,” but a language model has no reliable way to know that Ohio’s third grade fraction standard is worded differently from California’s, or that the Common Core code your team hardcoded doesn’t match what a given state actually adopted.
That gap shows up the moment you start to scale. A single-state implementation can get away with hardcoding one framework’s code and wording directly into a prompt. Expand to a second state, and that logic breaks, since each state can adopt its own numbering, phrasing, and grade placement for what is otherwise the same underlying skill. Rebuilding alignment logic for every new framework is a structural problem that gets worse with every state you add.
How Learning Commons helps
A standard isn’t just a code. It sits inside a structure: an adopted statement in the exact wording your state uses, a place in a progression of what comes before and after it, and a set of finer-grained skills underneath it. Send in a code and jurisdiction, and Knowledge Graph resolves all three, so your AI has a real structure to generate against.
Datasets in Knowledge Graph include:
- Academic Standards map a standard to its authoritative statement, sourced through Common Good Learning Tools‘s CASE data across all 50 U.S. states and core subjects
- Learning Components break a standard into the granular skills and concepts underneath it, currently available for mathematics across all grades, and for ELA in grades K-2 so far
- Learning Progressions sequence academic standards into what comes before and after a given skill, currently available for math
- Standards Crosswalks map an academic standard to its equivalent in another state’s framework, currently available for math
- Curriculum aligns your content to real classroom materials like Illustrative Mathematics, available on a gated basis
How it works
What you can do with this
- See how different parts of a curriculum maps to the standard it’s building toward, so new material stays consistent with both the standard and what that lesson has already taught.
- Pull a standard’s progression to find the prerequisite or next skill, without hardcoding your own sequence per state.
- Break a broad standard into its learning components when you need finer-grained content.
- Flag when a piece of generated content introduces a term the academic standard hasn’t taught yet.