BSc Computational Social ScienceAdd to shortlist

Programme profile

Digitisation poses new questions and challenges for our societies, but it also brings new opportunities to intervene in societal issues such as inequality and climate change. Would you like to learn how to make the world a better place? Scientifically grounded in social sciences and humanities expertise, Computational Social Science students develop skills to design, create, apply and appropriate digital technology and data science to benefit society

This programme is positioned at the intersection of social sciences, humanities and computational sciences. It includes theory, research methodology and statistics as well as programming and changemaking skills. Students become specialised in sustainable digital interventions for complex societal challenges (e.g. digital surveillance and health). They do so through transdisciplinary, semester-long projects featuring student engagement and High Impact Learning that Last (HILL)

Programme content

Year 1

The first year provides students with the foundation for successful learning within a transdisciplinary programme. Students will understand the complexity of societal challenges, appreciate that these are open to multiple interpretations, and value these different interpretations. They are also introduced to the basics of data science and empirical research and the individual level of analysis and intervention.

Semesters 1 and 2 focus on the themes of climate change and digital surveillance.

Year 2

This year introduces students to the analytical level of social practices and systems as well as inviting students to turn their attention to the structural level of analysis. Students work on group assignments proposed by external partners. They are challenged to think about (systemic) digital interventions that may improve the interaction, coordination or communication between stakeholders in a digital system. Finally, they become familiar with structural cleavages and inequalities in society. Students learn how structural inequalities may translate into ‘biased’ Artificial Intelligence (AI), and they are challenged to propose interventions that result in less biased AI solutions.

Semesters 3 and 4 also consist of semester-long courses, thematically focused on health and inequality respectively

Year 3

In the fifth semester, students can opt for a minor or electives from other programmes, take an internship or study abroad. They complete their degree programme, with a graduation project, working with a real-world client organisation

Entry Requirements