Looking into the Educational Mirror: Why Computation Is Hardly Being Taught in the Social Sciences, and What to Do About It

In the current digital era, with an increasingly complex and turbulent society, demand is rising for social scientists capable of analysing behavioural dynamics. Studying behavioural dynamics is a valuable lens, both in public policy making and community planning and in scientific projects on how human behaviour affects ecosystems. Computational social science (CSS) offers a framework for this type of studies, as it 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 programmes at bachelor and master levels in Europe. We would like to take a closer look at this discrepancy. We discuss why there is a need to develop computational education in the social sciences and why it is a challenge. We consider two perspectives. In the students’ perspective, there is the problem of mathematical anxiety and gender inequalities in STEM education. In the academic teachers’ perspective, there is the problem of a split within social sciences, inadequacy of statistical models for analysing dynamics, and insufficient educational resources at an appropriate level of difficulty. We build a case for creating a MOOC programme addressed specifically to social sciences students to fill in the existing gaps, facilitate the organisation of learning communities, and advance computational thinking within social science. Creating such a MOOC programme is the goal of our Erasmus+ project “Action for Computational Thinking in Social Sciences” (ACTISS).