The impact of artificial intelligence on scientific practices: an emergent area of research for science education

Abstract

Artificial intelligence (AI) is now a major driver of societal acceleration making a significant impact on science and science education. AI is used by scientists to generate hypotheses, design experiments, collect and interpret data in ways that were not previously possible with traditional methods alone. Science education research is increasingly paying attention to the role of AI in teaching and learning. However, a significant gap in the emerging science education literature on AI concerns the impact of AI on scientific practices themselves, and implications such impact for science education. The article uses the NRC (2012. A framework for K-12 science education: practices, crosscutting concepts, and core ideas. National Academies Press.) framework of ‘scientific practices’ to trace example uses of AI in scientific practices and raises questions for science education. The questions relate to the relevance of AI-informed scientific practices for science curriculum, teaching and teacher education at the secondary level. The ultimate purpose of the article is to highlight that the sooner the role of AI on scientific practices are researched and applied in science education policy and practice, the less likely that education will become outdated in helping students thrive in the fast changing landscape of scientific research.