The AIKI Method
The scientific method applied to Artificial Intelligence. This is how we teach your child to think with AI — and how we measure their progress from A1 to C2.
The cycle: 5 steps, one continuous loop
Every AIKI activity follows the same cycle that scientists and engineers use to solve problems.
1 · Think
= HypothesisBefore writing anything, the child thinks about what they want to achieve and forms their hypothesis. It's the step most people skip: going to the AI without knowing what they're looking for. AIKI trains intention up front.
2 · Ask
= ExperimentThey turn the idea into a clear question (their prompt), with context and detail. They design their experiment: a good question says exactly what you want to know.
3 · Analyze
= ObservationThey observe the AI's answer: identifying which part is useful, correct or incomplete. This is where critical thinking is born: not accepting the first answer as truth.
4 · Improve
= DataWith the data obtained, they reframe and refine their question to get closer to their goal.
5 · Learn
= IterationThey repeat the cycle with intention and consolidate what they've learned. Iterating with intention is the key competency of the future.
What we assess: 4 competencies
When a report is generated, the pedagogical AI analyzes the child's real conversations and scores these four competencies. We don't measure whether they get a fact right: we measure how they think. Each competency is scored from 0 to 100 and carries a different weight in the final mark.
Quality of questions (Q)
Do they add context, set goals and give clear instructions when asking?
Iteration & improvement (I)
Do they reframe, ask for examples and adjust when the answer doesn't help?
Critical thinking (C)
Do they cross-check and spot errors instead of accepting the first answer?
Problem solving (R)
Do they break things into steps, propose solutions and apply what they learn?
How the level is calculated (A1 → C2)
The weighted average of the 4 competencies gives an AIKI score from 0 to 100. That score translates into an A1–C2 level, just like the common framework of reference for languages. It's what parents see in the report — and it's independent from how the child's AIKI grows.
La fórmula
Score = Q·30% + I·25% + C·30% + R·15%
Balance rule: the final level can't be more than one step above the weakest competency. That way nobody levels up just for being strong at a single thing.
| Level | Classification | Score | What they master |
|---|---|---|---|
| A1 | Initial | 0 – 19 | Starts to think before asking. |
| A2 | Basic | 20 – 39 | Asks better questions and tells important ideas apart. |
| B1 | Intermediate | 40 – 59 | Researches with AI: concrete goals and precise questions. |
| B2 | Upper intermediate | 60 – 74 | Thinks in a structured way and develops judgment. |
| C1 | Advanced | 75 – 89 | Iterates and improves: reframes for better results. |
| C2 | Expert | 90 – 100 | Masters thinking with AI: questions and creates. |
Scores are indicative and the AI calibrates by age: a 60 from a 6-year-old doesn't demand the same as a 60 from a 12-year-old. The goal isn't to compete, but to see progress.
And separately: how your AIKI grows 🌱
The child's AIKI evolves based on how much they use the app. It's the visual, fun part — their game, which motivates them to come back. It doesn't measure learning: a child can have an AIKI Mentor (played a lot) and still be at A2, or an AIKI Apprentice already at B1. Growth belongs to the child; the A1–C2 level, to the parents.