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KI-Adventskalender: An Informal Learning Intervention for Data & AI Literacy

Rahul Sharma, Lars Henrich, Larisa Ivanova, Arsalan Karimzadmotallebiazar, Annette Bieniusa, Leo Van Waveren, Sebastian Vollmer

Abstract

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.

KI-Adventskalender: An Informal Learning Intervention for Data & AI Literacy

Abstract

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.

Paper Structure

This paper contains 21 sections, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Data & Methods
  3. Platform Mechanics and Interaction Loop
  4. UI/UX and Task Design
  5. Door Content Scope
  6. Data Sources
  7. Operational Definitions
  8. Analytical Approach
  9. Ethics and Privacy
  10. Results
  11. Participation and Progression
  12. Challenge-level Performance
  13. Discussion
  14. From Behavioral Traces to Data Literacy Constructs
  15. Design Principles for Data/AI Learning Interventions
  16. ...and 6 more sections

Figures (3)

  • Figure 1: Cumulative relative active users(a) and progression (b) for both runs of KI-Adventskalender
  • Figure 2: Mean attempts (a) and rate of passing the challenge (b) across competence clusters for both runs of KI-Adventskalender
  • Figure 3: Complexity vs. Success Matrix: Comparison of weighted mean attempts and pass rates by topic category for the 2024 and 2025 curriculum designs