The UAICS knowledge map contains a computational thinking family; at the same time, the standard has never assessed programming. The two decisions look contradictory. They come from a single judgement, worth setting out in full. First, why computational thinking is in. Decomposition, pattern recognition, abstraction — these are not coding; they are methods for making a problem explicit. And that is precisely the substrate of working with AI: breaking a task into ordered steps

Claiming to be "based on international frameworks" is easy. The hard part is answering: based on what, exactly? What was adopted, what redesigned, what added? This article publishes the full methodology, open to examination. Begin with each framework’s coverage and gaps. UNESCO’s AI Competency Framework for Students (2024) — four dimensions by three levels — goes deepest on the human-centred and ethical, but deliberately avoids age banding, so it cannot say what a nine-year-o

Competency-based education carries a long-standing dilemma: the most important capacities are the hardest to examine. Reflection, values, self-awareness — every curriculum declares them essential, and so they become rating scales, reflection essays, checklists, and marks. What students usually learn is not reflection, but how to produce writing that resembles it. Measurement theory explains why. Examinations reliably assess knowledge with right answers and performance with qu