Practical Science, Artificial Intelligence and Science Education

Practical science has been a part of international science curriculum standards for decades. Yet, its precise definition is often not clearly articulated. Scientific practices and scientific methods are often conflated in the notion of “practical science” in science education. Such ambiguity is particularly important to resolve given the current trends in how science is conducted in the age of Artificial Intelligence (AI). The definition of practical science is clarified through reflections on conceptual frameworks that focus on “scientific practices” and “scientific methods”. Subsequently the chapter focuses on the context of AI and its impact on scientific research. Currently there is much debate about how AI is influencing scientific research. 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. The following question thus emerges: What should practical science in science lessons look like in the age of AI? The question about how AI is influencing science is one that concerns not only scientists but also educators. Empirical data from Project AI-Vision conducted with professional scientists and educators in the United Kingdom are presented to illustrate the current priorities for teaching and learning of practical science given the AI context.