AAAI-25
AI Education
K-12 Computing
Machine Learning
In Press

What Can Youth Learn About Artificial Intelligence and Machine Learning in One Hour? Examining How Hour of Code Activities Address the Five Big Ideas of AI

2025
Philadelphia, PA
Peer Reviewed
Authors: Luis Morales-Navarro, Yasmin B. Kafai, Eric Yang, Asep Suryana
Conference: The Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25)
Abstract

As artificial intelligence (AI) becomes increasingly prevalent in society, there is a growing need to introduce AI concepts to K-12 students. Hour of Code, a global initiative that provides one-hour programming activities, has emerged as a popular platform for introducing computing concepts to youth. This research examines how Hour of Code activities engage with the five big ideas of AI education: perception, representation and reasoning, machine learning, natural interaction, and societal impact.

Through content analysis of 47 AI-related Hour of Code activities, we found that most activities focus on perception (83%) and machine learning (75%), with increased attention to societal impact (42%) compared to previous years (<2%). However, representation and reasoning received limited coverage (14%). Our findings reveal that while Hour of Code activities have evolved to address critical aspects of AI education, there remains room for improvement in providing hands-on, collaborative learning experiences that engage students with all five big ideas of AI.

Key Findings

Coverage of AI Big Ideas

  • 83% addressed perception
  • 75% addressed machine learning
  • 42% included societal impact
  • 14% covered representation & reasoning

Learning Approaches

  • • Most activities used "telling" rather than hands-on approaches
  • • Limited opportunities for collaborative learning
  • • Need for more unplugged activities
  • • Insufficient tools for hands-on model building
Research Impact & Implications

For Educators

Guidance on selecting Hour of Code activities that comprehensively address AI education goals, balancing technical concepts with societal considerations.

For Activity Designers

Evidence-based recommendations for better introductory AI/ML activities, including hands-on model building tools and collaborative learning.

For Policy Makers

Highlights evolution of AI education resources and areas needing investment to ensure comprehensive AI literacy for all students.

Citation

Morales-Navarro, L., Kafai, Y. B., Yang, E., & Suryana, A. (2025). What Can Youth Learn About Artificial Intelligence and Machine Learning in One Hour? Examining How Hour of Code Activities Address the Five Big Ideas of AI.Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25).

About the Authors

Research Team

Luis Morales-Navarro

University of Pennsylvania

Yasmin B. Kafai

University of Pennsylvania

Eric Yang

University of Pennsylvania

Asep Suryana

University of Pennsylvania

Research Context

Conducted at Penn GSE as part of ongoing efforts to improve AI education for K‑12. Contributes to research on computational thinking and AI literacy in educational settings.

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