Course Description
Elevate is the third certification in the Navigate AI faculty pathway and the culminating course of the Foundations Track. Where Ignite built orientation and vocabulary and Build produced a targeted course redesign, Elevate asks for something more ambitious: quality. Participants move from making AI-integrated teaching work to making it work well, with rigor, inclusion, disciplinary responsibility, and a capstone plan that points beyond their own courses toward departmental or institutional contribution.
This course is grounded in the v1.1 updates to TEACH, META, and FAFI and shaped by the 2026 higher education landscape: institutions are past the experimentation phase and into governance, and the faculty most valued in that environment are those who can design with quality, articulate their choices, and contribute to shared practice. Elevate prepares faculty to do all three.
The four modules move from design to inclusion to disciplinary ethics to leadership readiness. Each module assumes that participants can already execute the foundational skills from Ignite and Build. The new demand at Elevate is maturity of judgment: the ability to make complex design decisions and explain them, to identify where AI use creates risk for specific learners in specific contexts, and to connect individual practice to the larger institutional and professional conversation.
Who This Course Is For
Elevate is designed for faculty in the Adapting range on FAFI who have already experimented with AI-integrated teaching, redesigned at least one assignment or workflow with intentionality, and now want to improve quality and develop leadership readiness. Participants may be mentoring colleagues, presenting at teaching and learning events, serving on curriculum committees, or preparing to take on more formal roles in faculty development. They are ready for nuance, complexity, and outward-facing work.
This course is also appropriate for instructional designers and educational developers who support faculty at the Adapting level and want a course that models the quality standard they are trying to develop across their institutions. The modules are written with individual faculty practice at the center, but the frameworks and the capstone structure apply to team-based development work as well.
Elevate is not the right entry point for faculty still building basic fluency. Those faculty need Ignite and Build first. The assumption throughout Elevate is that participants know what a supervised workflow looks like, can articulate the rationale behind an AI policy, and have already redesigned something in a real course. The course asks what comes after that.
What Learners Will Produce
Participants will complete four substantial course artifacts. Module 1 produces a Co-Creation Design Draft for one real course component, accompanied by a 300 to 450 word supervision and verification note that makes the design logic explicit. Module 2 produces an Inclusive Design Improvement Plan with at least three concrete changes and a rationale grounded in UDL 3.0 and accessibility-aware AI practice. Module 3 produces a Disciplinary Ethics Case Analysis of 500 to 700 words with at least three concrete guardrails and a verification plan. Module 4 produces a Capstone Reflection and Project Plan of 700 to 900 words including scope, stakeholders, timeline, guardrails, and success indicators.
Together these artifacts document a faculty member who has moved from personal practice improvement to institutional contribution readiness. The capstone plan in Module 4 is designed to be shared, piloted, and built from. It is not the end of the certification. It is the beginning of the leadership work the next track addresses.
Learning Objectives
- Produce a capstone plan with outward-facing relevance that can be piloted and shared as part of faculty development or departmental improvement.
- Use AI as a co-creator in course design while keeping human purpose, verification, and pedagogical judgment in charge.
- Apply UDL 3.0 and inclusive design principles so AI use reduces barriers instead of creating new ones, especially for disability, language, and access differences.
- Identify and respond to discipline-specific ethical risks, including fairness, privacy, misuse, and cognitive offloading, with concrete guardrails rather than generic caution.
- Strengthen assessment quality through visible thinking, process evidence, and triangulated evidence where appropriate.
