AI in the classroom, without exposing your students’ data
Prepare lessons, differentiate, write to parents faster, yes, but never by pasting a pupil’s name or file into an AI with no guarantees.
Compulsory school, vocational school, adult education: what you write is about identifiable pupils and apprentices, their difficulties, sometimes their health or family. Pasted into consumer AI without a data processing agreement, it exposes precisely what your duty requires you to protect.
The point is not to ban AI from school: your students already use it, so do some of your colleagues. The point is to frame it: decide what enters a tool, what never does, and win back time for the classroom.
- Evenings and weekends spent on lesson sequences, assessment rubrics and feedback to students
- Delicate messages to parents rewritten again and again, with no proven template
- Student data pasted into public AI, outside any school framework
- Reports pushed back: class council minutes, visits to host companies, apprentice follow-up
See for yourself
A prompt structured in 5 blocks: Instruction · Role and audience · Data · Constraints · Format. An unframed AI invents; the frame stops it.
In a workshop, we adapt these prompts to your school, each with its safeguards: no student name, no follow-up file ever enters a public AI.
Séquence d’enseignement alignée sur le Plan d’études romand
A structured lesson sequence, objectives and progression included, ready to adjust to your class instead of a blank page.
See it in Chaptal →Communication à un parent sur son enfant
A fair, measured message on a delicate situation, built without ever naming the child in the tool.
See it in Chaptal →Évaluation d’un·e apprenti·e alignée sur le plan de formation du métier
A structured assessment based on the trade’s training plan, ready for the meeting with the apprentice and the host company.
See it in Chaptal →30 use cases cover your line of work in the Chaptal catalog, out of 750 in the corpus · each one states what it produces, what it expects from you, and what it refuses to do.
« Le Collaborateur, augmenté »
Teachers and trainers learn to frame AI on their real tasks, lesson plans, assessments, parent messages, without exposing a student.
See the training →A clear framework for your school
A survey of actual usage, a register of tools, simple rules: what enters an AI, what never does.
See audit & advisory →Foire aux questions
Can I mark student work with AI?
Not as it is. A paper carries a name, a handwriting, sometimes a personal situation; it does not enter a public AI without anonymization. The framed prompt works on criteria and anonymous excerpts, and the grade remains your judgment.
What does the nLPD say about my students’ data?
Student data is personal data, often sensitive, and Swiss law together with cantonal directives places its protection with the school. The simple rule: no identifiable student in any tool without a framework validated by your institution.
My students already use AI for their work. How should I respond?
A ban alone does not hold; what holds is an explicit framework. A class charter built together, instructions stating when the tool is allowed, and assessments designed accordingly work better than hunting for generated text.
Does the training also cover apprentice trainers?
Yes. The card covers compulsory school and vocational training: apprentice assessment, communication with the host company, preparation for the qualification procedure. Workshops start from your actual tasks.
Do I need to be comfortable with technology?
No. The catalog prompts work as they are, with no setup; the training is jargon-free and runs on your own classroom examples.