Provost
Drive innovation in teaching and learning
What You Do Today
Champion pedagogical innovation — online learning, experiential education, competency-based programs, interdisciplinary initiatives. Push the institution to evolve while respecting faculty autonomy over pedagogy.
AI That Applies
AI identifies effective pedagogical innovations from across higher education, models implementation feasibility, and measures outcome improvements from pilot programs.
Technologies
How It Works
The system ingests across higher education as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Evidence about what works in teaching innovation becomes more accessible. You can advocate for changes with better data.
What Stays
Inspiring faculty to innovate — when they're already overloaded and change feels risky — requires creating a culture of experimentation and trust.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for drive innovation in teaching and learning, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long drive innovation in teaching and learning takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your department chair or principal
“Which training programs have the highest completion rates, and which have the lowest — what's different?”
They influence which ed-tech tools get approved and funded
your instructional technologist
“How do we currently assess whether training actually changed behavior on the job?”
They support the tech stack and can show you capabilities you don't know exist
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.