Physics education research has historically evolved at the intersection of physics, rooted in neopositivism, and the social sciences, which frame knowledge as socially and contextually constructed. Our group critically investigates the ontological, epistemological, and methodological foundations of science education, examining how different paradigms—experimental, interpretive, and critical—shape what is recognised as knowledge, evidence, and learning.
In an era of technological acceleration and computational mediation of reality, it becomes imperative to question the assumptions underpinning scientific and educational knowledge. What do we consider “real” or “valid” when models, neural networks, or algorithms generate data? What forms of objectivity emerge within these new epistemic regimes?
Generative Artificial Intelligence raises radical questions: can knowledge produced by non-human systems belong to the epistemic domain of science? What kinds of agency, responsibility, and meaning remain for the teacher?
These reflections align with the “Nature of Science” strand, suggesting a redefinition of the image of science to be conveyed: not as a static corpus, but as a historically situated, transformative, and collective practice that evolves in response to the tools, contexts, and actors that enact it.