CS0 and CS1 courses are becoming an essential part of many social science programs, including sociology and political science. This particular assignment was designed as part of the ‘Basics of Programming in Python’ course for undergraduate political science students. The course aims not only to prepare students for the unified programming exam, but also to apply concepts of computational thinking in the context of political science problems. By linking these fields, students learn to overcome inner barriers in coding and explore the potential of computational social science methods for both academic path and career.

This project seeks such a connection between subjects of political science major as Comparative Electoral Systems and Quantitative Methods of Political Research, and concepts of computer science. Students process the generated votes, applying critical thinking to identify spoilt ballots, and then formulate rules for counting votes (First-past-the-post, Borda count, Condorcet winner criterion) in algorithmic form. Optionally, a short essay can be added in which students are asked to speculate about political leanings, the transitivity of preferences and the advantages/disadvantages of particular electoral systems based on analyses of the data in the assignment. As the result, students not only develop hard skills in programming, but most importantly conceptualize complicated topics through the prism of their specialization, fostering the ability to see the connections between these fields and understand how they can work together to address complex real-world scenarios.