Teaching and Learning AI in K-12 Informatics Education

Abstract

With the diffuse and very rapidly evolving presence of Artificial Intelligence (AI) in so many aspects of our everyday life, the question of at what age and how to start preparing citizens for the AI revolution has become urgent. Moreover, AI in general, and the recent and easy availability for everyone of generative AI in particular, are raising pressing issues regarding education in terms of both opportunities and challenges.

This working group research is an international and collective effort to reach deep but scalable insights into current trends, developments, and perspectives regarding AI in K-12 education. The focus is on AI as content matter as opposed to AI as enabler of digital technology for teaching and learning.

This work complements earlier reviews of scientific literature on AI in education by sketching the bigger picture by putting progress in scientific research in the context of developments in educational practice. Drawing on a scoping literature review, interviews with educators, AI experts, and policymakers, and an analysis of institutional documents, we provide an overview of the current trends and gaps.

The analyses revealed several gaps and opportunities. First, maintaining a conceptual distinction between teaching with AI, with AI as enabler of digital tools for education, and teaching about AI, with AI as content matter, is crucial. Second, in spite of the abundance of interventions and tools in literature and documents, there is a lack of fundamental pedagogical knowledge about the underlying mechanisms informing teaching and learning of AI. Third, research and design efforts are required to find a proper balance between technical and socio-ethical aspects of AI in curricula. Fourth, there is a need for research-informed initiatives to support K-12 teachers’ preparation and continuous professional development on teaching and learning of AI.

These findings give rise to the formulation of four grand challenges as inspiration for future research and policy developments