Use cases - Learning Commons Docs

These are several common ways that edtech teams use Knowledge Graph data in product development and instructional workflows.

Use case	Description	Examples
Align content to standards	Create content rooted in Academic Standards and learner competencies across subjects.	Replace fragmented infrastructure with a single, trusted source of standards data: Populate a standards menu (i.e., 50 states across subjects) Use standards as context when generating AI outputs Integrate standards data with your CMS
Plan instructional content	Use dependencies (Learning Progressions) and granular skills (Learning Components) to inform instructional content and plans.	Group students more effectively by looking at the skills they’ve mastered Give each student their own instance of a knowledge model graph, with a score for each node (Learning Component) Build a teachers dashboard that gives grounded AI recommendations on lesson plans and identifies gaps in prerequisite skills Give more precise feedback
Compare standards across states	Use Standards Crosswalks to adapt content aligned to one state standard to other states’.	Outsource the burden of managing standards across states: Align content across all states you serve Reduce maintenance burden on internal systems Share content across state lines with automatic remapping to local standards
Align content to curriculum	Create or use educational materials that are aligned to official curricula Contact us ↗ to get access to this gated functionality.	Feed lesson narratives, instructional routines, and Learning Components into LLM prompts to generate parent-facing activities Map student performance data to standards Use IM misconceptions to generate differentiated lesson plans and support RTI workflows
Deliver personalized assessments	Build adaptive experiences that go beyond content delivery into diagnostic assessment.	Combine curricular data with student data to help teachers plan targeted weekly interventions Combine Academic Standards and Learning Components with student data to prepare teachers for observation and coaching

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