Complex systems simulations to develop agency and citizenship skills through science education

In the era of big data, the progressively more widespread use of computational and data-intensive approaches is leading to changes in the ways of doing science and conducting research. The new methodologies and techniques are routine for researchers and professionals who make everyday use of big data analytics or simulations tools but are mainly unknown to ordinary people. Nevertheless, the impact of computational and data-intensive approaches has gone far beyond the scientific community, reaching the entire society. Indeed, the applications of machine learning and big data analytics, as well as the results and methods of computational simulations have reached people’s life and behaviour and, even more importantly, are at the methodological core of studies on urgent issues like the climate change or the pandemic, on which policymakers and citizens have to make decisions. Hence, the educational community cannot ignore the ongoing transformation of all people’s lives, behaviors, and culture. Within the research field of education to data science and computation, this dissertation addresses the issue of introducing in teaching-learning activities one of the methods of the on-going data science revolution: the computational simulations. Addressing the conceptual, methodological, and epistemological novelty of these objects, we will show how they embed, in a very specific, disciplinary-grounded way, the paradigm shift and cultural revolution of the data science age. We do that using lenses that come from the science of complexity, with its key-ideas that, originated from the physical modelling, can be applied to the analysis of a range of different phenomena. In the dissertation, we will guide the readers to recognize how dealing with simulations not only requires technical competences of coding, but a change of mindset and ways to think about the problems and the scientific method to address them.