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Data Across the Curriculum: Integrating Data Analysis with Narrative in Political Science

From a pedagogical standpoint, Danielle Lussier, Assistant Professor of Political Science, stresses data as a tool for helping students approach problems from multiple perspectives. Working interactively with data allows them to better compare narratives and better understand the research process in both lower-level and upper-level material.

Political science is both a quantitative and qualitative field, so students at all levels of Lussier’s political science classes delve into both data types extensively and build data analytic skills as students progress in the major. Every class taught by Lussier involves data labs that draw on both cross-national data with countries as the unit of measure and on data with individuals as the unit of measure. The labs directly relate to readings, concepts, and/or countries that students study.

At the 100-level, students gain both an introduction to fundamental data concepts such as the construction and measurement of variables and to analytical computer programs like STATA, a statistical package, and ArcGIS, which analyses spatial data. The image below is of a GIS map her introductory political science students make in a data lab.


At the 200-level, Lussier’s students delve into applied data analysis and write in-depth data reports that compare data analyses from the course readings to data analyses that students reconstruct and update from the readings.

At the 300-level, students get the opportunity to pose questions about class readings and use lab time to test their inquiries with actual data from the readings. In addition, Lussier assigns students research modules that allow them to create their own qualitative variables from cross-national data that they then transform into quantitative data, giving students the opportunity to apply the data skills they’ve accumulated in each course level.

The positive impact of incorporating data into classroom work is not lost on students. Students in all levels of her courses are widely receptive to data in coursework and have viewed working with data in her classes as an integral stepping stone to both academic and professional pursuits. Adam Lauretig ’13, the first Post-Baccalaureate Fellow for DASIL, was inspired by Lussier’s data-driven coursework to pursue more advanced courses in spatial statistics, and subsequently created visualizations like the interactive timeline map of historical coups d’etat. Additionally, many of her students have cited the research and data skills developed in her class work as marketable to employers and graduate programs.

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