Artificial-Intelligence Literacy for Upper-Secondary School · Icelandic
You Write First.The Machine Speaks Second.
- what
- 21 modules on four competency lines
- who for
- upper-secondary students and their teachers
- how long
- about 20 min per module · 6 project packs
The Curriculum · 21 Modules on Four Competency Lines
substrate judgment
direction-holding
collaborative action
edge literacy
From Module 21 · Video Games · The Human Anchor
„Choose a video game you know well. Write about flow, community, difficulty, frustration, the feeling of victory, unfairness, and what keeps you coming back.“
Start here
Pick one that grabs you. About 20 minutes.
Brand new to the computer? Start here.
Get the basic gestures down first, copy, paste, sending a picture, taking a screenshot, in Handtökin (Hands On): a small, calm practice game with no account and no wrong answers. Then Tækniseigla is easy.
How it fits together
Four surfaces, one path. You can start anywhere, but this is the through-line.
The three-step method
The human anchor
The student writes a personal, situated summary without machine help. This sets a baseline that machine output must not swallow.
The algorithmic pivot
The student uses a structured prompt to push artificial intelligence into systematic analysis that would be hard to do by hand.
The fiduciary anchor
The student verifies the output, finds errors, records sources, rejects what does not hold, and takes personal responsibility for the result.
For teachers and students
Teachers get a predictable, reusable module with teaching notes and assessment criteria. Anyone who has taught one unit knows at once how the next one is built.
Students practice judgment, not the polishing of a final artifact. The work shows how it was done, where the machine failed, and what responsibility the person took back.
Why practice
Every task here demands practice, whether it is a physics or a maths problem you want to wrestle with, a poem or a swing. The skill does not come from the finished product, it comes from doing the thing yourself, again and again.
Letting the chat sort it out for you is about as smart as turning up to a treadmill on rollerblades, standing still on it, and expecting to get fit. The machine can move the belt, but the legs are yours.
The future will call loudly for amplified people, the ones who have trained their imagination and creativity to put the machines to work. Large language models are buckets, not boxes: every generation has to add to them. Practice is how you become the one who amplifies the machine, instead of being replaced by it.
Listen: large language models are buckets, not boxes → (opens in a new tab)