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

TL;DR

This paper reviews Hour of Code activities to assess how effectively they introduce K-12 students to AI concepts, highlighting gaps and suggesting improvements for broader AI literacy.

Contribution

It provides an analysis of current activities' focus areas and offers recommendations for designing more comprehensive and engaging AI educational tools.

Findings

Most activities focus on perception and machine learning

Limited engagement with representation and other AI topics

Increased attention to critical computing aspects

Abstract

The prominence of artificial intelligence and machine learning in everyday life has led to efforts to foster AI literacy for all K-12 students. In this paper, we review how Hour of Code activities engage with the five big ideas of AI, in particular with machine learning and societal impact. We found that a large majority of activities focus on perception and machine learning, with little attention paid to representation and other topics. A surprising finding was the increased attention paid to critical aspects of computing. However, we also observed a limited engagement with hands-on activities. In the discussion, we address how future introductory activities could be designed to offer a broader array of topics, including the development of tools to introduce novices to artificial intelligence and machine learning and the design of more unplugged and collaborative activities.