What is this course about?
One-off PD days produce no durable change, and districts keep buying them. This course builds a semester-scale program with a cohort-and-coach structure that develops internal capacity rather than consultant dependency, differentiated tracks for early adopters and skeptics, a separate mandatory administrator track, and adoption measured through classroom artifacts.
Who is this course for?
- Directors of professional learning
- Instructional coaches who will facilitate
- Building administrators
- Curriculum and instruction leadership
What do I need before starting?
- Responsibility for professional learning at building or district level
- No technical background required
What will I be able to do afterwards?
- Explain why one-off PD produces no durable adoption
- Design a cohort-and-coach model that builds internal capacity
- Differentiate tracks for early adopters and genuine skeptics
- Run a separate mandatory administrator track
- Measure adoption through classroom artifacts rather than completion rates
What does each module cover?
Why do one-off PD days fail?
35 minThe evidence on professional learning transfer, and what distinguishes programs that stick.
Objectives
- Summarize the evidence on PD transfer
- Identify the features that predict durable change
- Make the case for a semester-scale investment
Topics
Activity. Audit your district's last three PD initiatives for durable adoption.
How do you build a cohort-and-coach model?
45 minStructure that develops internal capacity instead of recurring consultant spend.
Objectives
- Design cohort size and composition
- Define the coach role and select coaches
- Plan capacity growth across semesters
Topics
Activity. Design your cohort structure and name the first coach cadre.
What belongs in the four-session core?
45 minThe minimum every teacher completes, regardless of track.
Objectives
- Specify the four-session core content
- Ensure each session produces an artifact
- Keep the core achievable within contract time
Topics
Activity. Draft the four-session core with an artifact for each.
How do you differentiate for adopters and skeptics?
45 minTracks that serve both without either group derailing the other.
Objectives
- Design an advanced track for early adopters
- Design a track that takes skepticism seriously
- Prevent either group from dominating shared sessions
Topics
Activity. Design both tracks and script the response to the four most common objections.
How do you build a resource library teachers use?
40 minA shared library that gets used rather than a folder nobody opens.
Objectives
- Structure a library around real teacher tasks
- Build contribution and curation workflows
- Measure actual use
Topics
Activity. Build the library structure and seed it with ten teacher-contributed items.
Why do administrators need a separate track?
40 minThe administrator content differs, and mixing tracks suppresses honest teacher participation.
Objectives
- Specify administrator-specific content
- Explain why mixed sessions suppress teacher candor
- Make the administrator track mandatory
Topics
Activity. Design the administrator track and its evaluation-policy component.
How do you measure adoption honestly?
40 minClassroom artifacts and observation rather than completion certificates.
Objectives
- Design artifact-based adoption measurement
- Distinguish depth of use from any use
- Set a realistic adoption target
Topics
Activity. Design the measurement plan and set a defensible adoption target.
Building the semester calendar
50 minThe workshop module: a complete calendar with facilitator materials and measurement built in.
Objectives
- Build the semester calendar within contract constraints
- Assemble facilitator materials
- Schedule measurement before the program starts
Topics
Activity. Build the calendar and check it against the teacher contract and school calendar.
What is the capstone project?
District semester PD program with a measurement plan
Produce a complete semester program: cohort structure, coach cadre, four-session core with artifacts, differentiated tracks, resource library, mandatory administrator track, and an artifact-based measurement plan scheduled before launch.
Deliverable: A program plan and facilitator package ready to run next semester.
How are learners assessed?
- Calendar checked against real contract time and school calendar constraints
- Objection responses rehearsed with a genuinely skeptical colleague
- Measurement plan reviewed for whether it could detect failure
What ships with the course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Which AI agents does this course use?
The hands-on modules run against agents already deployable on the ibl.ai platform for k-12.
Where does the course material come from?
Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.
- ISTE
International Society for Technology in Education
Educator standards structuring the core session content.
- CoSN
Consortium for School Networking
District-scale implementation guidance.
- Office of Educational Technology
U.S. Department of Education
Federal guidance on educator preparation for AI.
- AI and the Future of Teaching and Learning
U.S. Department of Education
Source for the teacher-agency principles the program is built around.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Contract time is the binding constraint and most PD plans ignore it. Module 8 must check the calendar against the actual teacher contract, and if the program does not fit, cut scope rather than assuming goodwill.
- Module 4's skeptic track must treat objections as potentially correct. A track designed to overcome resistance rather than engage it produces compliance and no adoption.
- The administrator track being mandatory is load-bearing. Teachers disengage fast when they suspect administrators are evaluating a practice they do not understand.
- Measurement must be capable of returning a negative result. If the plan cannot show the program failed, it will report success regardless of what happened.
- Coordinate with HE-10 — the six-week faculty program shares structure, and the facilitator materials should be developed together rather than duplicated.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What does the Training Every Teacher on AI in One Semester course cover?
One-off PD days produce no durable change, and districts keep buying them. This course builds a semester-scale program with a cohort-and-coach structure that develops internal capacity rather than consultant dependency, differentiated tracks for early adopters and skeptics, a separate mandatory administrator track, and adoption measured through classroom artifacts. It runs One semester; 5 hours of planning content across 8 modules across 8 modules, at foundational level, and closes with a capstone: District semester PD program with a measurement plan.
Who should take Training Every Teacher on AI in One Semester?
It is written for Directors of professional learning, Instructional coaches who will facilitate, Building administrators, Curriculum and instruction leadership. Prerequisites: Responsibility for professional learning at building or district level; No technical background required.
Can we run this course on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for k-12 teams that cannot send work to a public AI tool.
How do we get access to Training Every Teacher on AI in One Semester?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.
How much does AI training for k-12 cost on ibl.ai?
There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.