Articles  |  ,   |  May 13, 2021

A Differentiated Discussion About AI Education K-12

Article by Gerald Steinbauer, Martin Kandlhofer, Tara Chklovski, Fredrik Heintz and Sven Koenig.
Published in KI – K√ľnstliche Intelligenz.


AI Education for K-12 and in particular AI literacy gained huge interest recently due to the significant influence in daily life, society, and economy. In this paper we discuss this topic of early AI education along four dimensions: (1) formal versus informal education, (2) cooperation of researchers in AI and education, (3) the level of education, and (4) concepts and tools.

Introduction and Motivation

Artificial Intelligence (AI) has gained significant influence across various sectors and fields and became a major topic of discussion. The impact of AI on the working world as well as on our everyday life poses a challenge for education systems. Sound knowledge about principles and concepts of AI, the ability to understand and use AI tools, techniques and methods, together with the ability to analyze and identify long-term benefits, social and ethical aspects of AI, are becoming key skills of the twenty-first century.

Teaching these AI skills has traditionally been done at the university level. In recent years several initiatives and projects have emerged which pursue the mission of AI education at the K-12 level.

In order to provide a differentiated view on the topic of educating younger people in AI we will look at the field from four angles. The first important angle is the relation between formal and informal education. This aspect is in particular important for the scalability of approaches. In particular, informal education gained a lot of attention during the COVID-19 pandemic. The second important aspect is the cooperation between skilled researchers from the field of AI and researchers from education as well as teachers in schools. This aspect affects the quality of the education as well as the potential outreach. The third angle we need to look at is the level of the AI education. Here we see a wide range from activities for a very broad audience to elite programs for gifted students close to academic courses with a strong focus on science. The fourth axis we need to look at are adequate concepts and tools for teaching AI to youngsters. While there is a rather clear picture of how AI should be taught at the university level, it is still under debate how AI can be taught at the K-12 level. [ . . . ]