This paper compares secondary computer science curricula and examination frameworks across 15 countries. It identifies two structural barriers to universal AI literacy: in several systems, many students finish secondary education without formal programming exposure; among students who do receive computer science education, a “Syntax Ceiling” separates broad Python access from the deeper algorithmic training associated with C++, which remains concentrated in elite STEM tracks. The paper argues that governance structures, high-stakes examinations, and shared teacher pipelines jointly shape these inequalities.
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