Mind the Gap. Barriers in Computational Social Sciences Education and How to Deal with Them

In the current digital era, with an increasingly complex and turbulent society, demand is rising for social scientists capable of analysing behavioural dynamics. Studying behavioral dynamics is a valuable lense, both in public policy making and community planning, as in scientific projects on how human behaviour affects ecosystems. Computational Social Science (CSS) answers this need for skills by offering a framework that connects a complex networked systems perspective with a suite of computational tools and methodologies. Despite its potential and fast growth, CSS is still hardly found in programs at bachelor and master levels in Europe. It seems that teaching social sciences students computational thinking seems to be lagging a bit behind. In the presentation we would like to look at this discrepancy from the perspective of sociology of education and higher education researches. At the beginning, we will discuss why there is a need to develop computational education in the social sciences and why we have not been so successful in developing this kind of education. Our aim is to address the perception of CSS, students’ barriers in this field (e.g. mathematical and statistical anxiety, transition of gender inequalities in STEM education into differences in social sciences) and the perspective of academic teachers. Afterwards, we would like to present some ideas for tackling these challenges in frames of our Erasmus+ project “Action for Computational Thinking in Social Sciences” (ACTISS).