What Knowledge Graph does
Knowledge Graph provides a structured collection of enriched educational datasets that connects academic standards, curricula, and learning science data. It standardizes high-quality datasets with a unified schema, allowing edtech developers to focus on building AI-powered educational tools.| Dataset category | Description | Examples |
|---|---|---|
| Curriculum | Lessons, activities, materials, and assessments from publishers. | Illustrative Mathematics 360 ↗ |
| Academic Standards | Hierarchical structures of state or national learning goals. | State standards from CASE Network 2 ↗ |
| Learning Progressions | Logical and usually sequential ordering of learning targets. | Student Achievement Partners’ Coherence map ↗ |
| Learning Components | Academic Standards broken down into concrete skills or concepts. | ANet’s learning component for K12 math ↗ |
When to use Knowledge Graph
| Use case | Description |
|---|---|
| Standards alignment | Identify how your content supports specific academic standards and create content rooted in learner competencies across all key subjects. |
| Instructional planning | Create dependencies, learning progressions, and content coverage, starting with math in the Common Core State Standards. |
| Compare state standards | Adapt content aligned to one state standard to other states, initially in math across the Common Core State Standards and 15+ additional states. |
| Curriculum alignment | Align your content or create additional materials aligned to the curriculum. To support these use cases, Knowledge Graph organizes educational information into a small set of structured datasets. Contact support@learningcommons.org ↗ for information about access to gated functionality like this. |
How to access Knowledge Graph
Knowledge Graph is accessible in a variety of ways and is designed to be database-neutral, lightweight, and interoperable. The local files in particular can be used across graph databases, relational systems, in-memory tools, and AI pipelines without requiring any specialized infrastructure.| Access method | Link | When to use |
|---|---|---|
| Local files | nodes.jsonl ↗, relationships.jsonl ↗ | For offline access, custom processing, or complex queries across graph databases, relational systems, in-memory tools, and AI pipelines. Preserves the structure of entities and relationships, and supports both deterministic joins and AI workflows like embeddings or RAG. |
| REST API | REST API docs | For real-time programmatic access to data in an application |
| MCP server | MCP server docs | For using natively with an LLM |
| Claude connector | Claude connector docs | For using Knowledge Graph directly with the Claude app |