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.
@article{arxiv.2603.26906,
title = {KI-Adventskalender: An Informal Learning Intervention for Data & AI Literacy},
author = {Rahul Sharma and Lars Henrich and Larisa Ivanova and Arsalan Karimzadmotallebiazar and Annette Bieniusa and Leo Van Waveren and Sebastian Vollmer},
journal= {arXiv preprint arXiv:2603.26906},
year = {2026}
}
Comments
Accepted at ACM CHI 2026 Workshop on Data Literacy for the 21st Century