Secondary school students increasingly encounter AI systems whose outputs depend on data quality, evaluation choices and modeling assumptions. To provide accessible entry points to these interconnected concepts, we developed KI-Adventskalender, a free web-based extracurricular initiative with 24 didactically curated, short, guided micro-challenges released daily in December, targeting data-centric competencies and socio-technical themes that shape how data are interpreted in practice. Drawing on two annual iterations, we report aggregate platform traces characterizing participation and task-level engagement. Participation increased substantially in 2025, but early attrition persists. Progression stabilized after midpoint: among users reaching Day 12 in 2025, more than 75% completed the calendar. Competence cluster performance shifted across years; higher revision rates co-occurred with strong pass rates, suggesting sustained engagement. We use these observations to motivate a next-step measurement agenda: tighter task instrumentation, embedded micro-assessments and mixed-method evaluation designs that can distinguish persistence from conceptual uptake, knowledge progression and durable learning outcomes.

翻译：中学生日益频繁地接触到依赖数据质量、评估选择与建模假设的AI系统。为提供这些相互关联概念的可及切入点，我们开发了KI-Adventskalender——一项免费的课外网络倡议活动，包含24个经教学设计的、每日发布的短时限导式微挑战，聚焦于塑造数据实践解读能力的数据中心能力与社会技术主题。基于两轮年度实施数据，我们报告了反映参与程度与任务层面投入度的平台聚合轨迹。2025年参与人数显著增长，但早期流失现象依然存在。进程在中期后趋于稳定：在2025年完成第12天的用户中，超过75%完成了整个日历挑战。能力集群表现呈现年度间差异；高修订率与高通过率并存，表明持续性参与。我们利用这些观察结果提出下一步测量议程：更精细的任务测量机制、嵌入式微评估以及混合方法评估设计，以区分持续性参与与概念理解、知识进阶及长效学习成果。