The frameworks behind the Navigate AI system
Navigate AI’s frameworks are not meant to sit off to the side as abstract toolkit brands. They are the operating logic inside the certification pathway, student fluency work, CourseReady review, and institutional planning offers. TEACH, FAFI, META, AI Fluency Map, and SCALE each solve a different layer of the same adoption problem, which is exactly how the rebuild guide says this page should function. fileciteturn21file1turn21file10
How the system moves
Each framework solves a different layer of the problem.
FAFI
The Faculty AI Fluency Index measures six domains of faculty AI practice across four developmental levels and supports both self-assessment and cohort reporting. The v1.1 framing is developmental, not evaluative. fileciteturn21file3turn21file4
See FAFITEACH
TEACH is the faculty-practice architecture behind the certification pathway, using the v1.1 domains for workflows, governance, pedagogy, curriculum agility, and human essentialism. fileciteturn21file10turn21file11
See TEACHMETA
META gives faculty a redesign logic for assignments and assessments in an AI world, especially inside Build, Elevate, and CourseReady. fileciteturn21file3turn21file10
See METAAI Fluency Map
The AI Fluency Map defines student capability progression across domains and levels so institutions can map outcomes, pathways, and curriculum expectations more clearly, then hand that logic into the Student AI Fluency Curriculum offer. fileciteturn21file9
See AI Fluency MapSCALE
SCALE helps institutions connect faculty development, governance, program alignment, and implementation planning into a sharper AI strategy story. fileciteturn21file8
See SCALEFrom faculty fluency to institutional execution.
The system logic is simple. FAFI identifies where faculty are. TEACH describes what stronger practice looks like. META shapes course and assessment redesign. The AI Fluency Map extends that logic to student capability. SCALE connects all of it to department- and institution-level planning. The rebuild guide specifically calls for this horizontal system story rather than a long vertical list of toolkit blurbs. fileciteturn21file1turn21file10
| Layer | Framework | Primary question it answers |
|---|---|---|
| Faculty readiness | FAFI | Where are faculty actually starting, and where are the main growth gaps? |
| Faculty practice | TEACH | What does stronger, more human-centered AI-integrated teaching practice look like? |
| Assessment redesign | META | How should assignments and evidence of learning change in an AI-enabled environment? |
| Student capability | AI Fluency Map | What should students know and be able to do across levels and programs? |
| Institutional planning | SCALE | How does all of this align into governance, support, and strategy? |
Where each framework shows up
When to buy an offer versus when to use a toolkit.
Use an offer when you need implementation.
Certifications, institutional cohorts, CourseReady review, student fluency deployment, and workshops are the right fit when you need facilitation, accountability, structured outputs, and institutional follow-through.
Use a toolkit when you need a framework lens.
The standalone framework pages and guides are useful when you need a shared language, internal planning structure, or a simpler way to orient a local conversation.
Most institutions use both.
The frameworks create the shared architecture, while the offers turn that architecture into measurable action, visible deliverables, and clearer implementation choices.
Start with the offer path, then go deeper into the framework you need.
Need help deciding which framework or offer is the right starting point?
That is exactly why Navigate AI uses a system view. The same institutional problem often needs both a framework lens and a structured implementation path.