Curriculum
An AI-literacy map you can inspect
A good curriculum should be legible to parents and teachers, and explainable by children. Here are our competencies and assessment by age.
The through-line is: see AI in the world → understand AI through body and data → ask whether AI is trustworthy → make meaningful work with AI → take responsibility to people, community, and the future.
We place a human-centred mindset, AI ethics, AI techniques and applications, and AI system design into one competency system that deepens with age, rather than bolting them on after the features.
Aligned to an international framework
Competencies by age reference the dimensions of an international AI-literacy framework, combined with children's-rights design principles to ensure age-appropriateness, transparency, and inclusion.
Competency structure adapted from UNESCO's AI Competency Framework for Students (2024), licensed CC BY-SA 3.0 IGO; derived content on this page is released under the same license and marked as modified.
Goals & tools by age
See & distinguish
- Tell a 'rule-based' system from one that 'learns from data'
- Say that AI makes mistakes, and raise observations in a group
- Do simple sorting and embodied games to understand data
Collect & test
- Explain rule-based vs. data-driven
- Begin discussing bias, privacy, and fairness; make a model card
- Take part in collecting, labelling, and simple image/sound classifying
Model & critique
- Describe the AI project lifecycle; compare model vs. result quality
- Run model tests; judge the reliability of content
- Plan a community-project prototype with design thinking
Design & take responsibility
- Treat AI as an object of research, design, and critique
- Assess performance, bias, feasibility, and social impact together
- Complete a showcase prototype and an impact brief
Three tracks, not one test
We use three streams of evidence together, valuing the thinking process and reflection over feature completion alone.
Observation record
Teamwork, question quality, and debugging attitude, recorded continuously by teachers in class.
Work evidence
Data cards, model cards, prototypes, and display boards showing how work was designed and tested.
Learner self-review
What did I change my mind about, what do I trust less now, and what do I want to test next.