Two half-day workshops over two weeks
Plan AB Global Holding / Education program
AI in Education
Help educators and institutions use AI thoughtfully for planning, learning and assessment while protecting professional judgment.
Discuss this engagement →View a sample output ↓A focused first engagementIndicative duration Starting scope Working format
Start with Educator Practice Lab.
One educator team and one lesson, assessment or administrative workflow.
Guided practice, peer review and a classroom-ready design session.
Leave with: A reviewed learning activity, teacher checklist and a responsible-use routine.
What we need from you: A learning objective, a sample lesson or assessment and your institution’s current AI-use expectations.
This is a suggested starting format. Scope, schedule, availability and fees are confirmed in a written proposal before kickoff.
Request a starter proposal →The challenge
Where the work begins.
Teachers face new tools and expectations, but also concerns about accuracy, privacy, fairness and student agency. A useful program must work in real teaching conditions.
Who it is for: Teachers, school leaders, universities and learning institutions in any market.
How we work01 / Context 02 / Practice 03 / Safeguard 04 / Transfer
A focused path from question to action.
Context
Identify classroom realities, institutional guidance and educator confidence levels.
Practice
Try bounded AI uses for planning, resources, feedback and administrative work.
Safeguard
Apply privacy, verification, assessment and age-appropriate use principles.
Transfer
Create reusable teaching workflows and a plan for peer learning.
What you receive
Tangible outputs.
Scope and timing are agreed with you; these are the core deliverables we would shape around your context.
- Role-specific AI literacy sessions
- Teaching workflow examples
- Responsible-use checklist
- Adaptation plan for the institution
In practice
What educators take away
Participants build a lesson-planning workflow, critique an AI-produced resource, and decide when student learning is helped—or weakened—by automation. The program is adapted to the institution and is not limited to one country.
See the work
What a working output looks like.
Illustrative sample · fictional scenario · no client dataA classroom-ready AI activity brief
| Stage | Teacher action | Learner evidence |
|---|---|---|
| Prepare | Define the learning goal and remove learner-identifying data from examples. | A task aligned with the curriculum and clear AI-use boundaries. |
| Practise | Compare an AI draft with a trusted source; ask learners to identify gaps. | Annotated errors, source checks and an explanation in the learner’s own words. |
| Assess | Use a rubric for reasoning, verification and reflection. | A process record and a reviewed final response, rather than output quality alone. |
Open the working brief
- Activity example
- Learners critique an AI-generated explanation and improve it with sources.
- Professional judgment
- The teacher chooses the task, checks suitability and makes the assessment decision.
- Safe inputs
- Use fictional or anonymized examples; avoid uploading identifiable learner records.
- Adaptation
- The format is adapted to age group, curriculum, teaching language and institutional policy.
This sample shows the structure and level of specificity of a deliverable. The final output is built around your workflows, people and agreed scope.
Next step
Start a conversation →Bring us the real challenge.
We will frame the right starting engagement around your context and decision.