发表机构
University of Bucharest, Faculty of Mathematics and Computer Science（布加勒斯大学数学与计算机科学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究对 15 国课程与考试框架比较分析，指出人工智能素养普及面临学生编程经历缺失和‘语法天花板’问题，发现治理结构和考试是驱动因素，专业与通用课程语言选择相关，全民人工智能素养实现需多方面考量。
AI 中文摘要
人工智能素养普及面临国家组织中等计算机科学教育方式的结构性挑战。多数系统中通用课程承载普及人工智能素养重任，专业信息学课程服务 STEM 路径。本文对 15 国课程与考试框架进行比较分析，发现两大挑战：部分学生无编程学习经历；接受计算机科学教育的学生存在‘语法天花板’。通过多案例表明治理结构和高风险考试是主要驱动因素，且专业与通用课程语言选择相关，实现全民人工智能素养需应对多方面问题。
英文摘要
The promise of AI literacy ``for all'' confronts a structural challenge embedded in how nations organise secondary computer science education. In most systems, a general-track subject -- Digital Literacy, ICT, TIC, or SNT -- bears the weight of universal AI literacy, while a specialist Informatics course serves STEM pathways separately. Yet the content and depth of the general track are shaped by governance decisions made largely with reference to the specialist one. This paper presents a comparative analysis of curricula and examination frameworks across fifteen countries, identifying two structural challenges. First, in several systems a significant portion of students completes secondary education without any formal programming exposure. Second, among those who do receive CS education, a \emph{Syntax Ceiling} emerges: Python-based instruction reaches most students, while the algorithmic depth associated with C++ remains concentrated in elite STEM tracks. Drawing on reform cases spanning centralised mandates (France, China, Japan), assessment-driven systems (Poland, Romania, South Korea), and recent universal reforms (Switzerland, Kazakhstan), we show that governance structures and high-stakes examinations are the primary drivers of both challenges -- and that specialist and general-track language choices are rarely independent, linked through shared teacher pipelines that curriculum policy seldom acknowledges. Achieving genuine AI literacy for all requires confronting not just curriculum content, but the access architectures and resource constraints that determine who receives it -- and at what depth.
CommentsPresented at 2nd International Workshop on AI Literacy Education For All (CEUR proceedings)
