As technology and data literacy become increasingly important, we examine how statistical software is taught in political methodology courses. This paper also highlights  current teaching practices and the role of statistical software in political methodology.

This research aimed to address two questions: (1) how is statistical software incorporated into undergraduate political methodology courses, and (2) how are these courses structured and taught? 

Myself along with a  team of research assistants collected and coded course information from 93 syllabi across 78 institutions, drawn from a cross-section of schools ranked by US News & World Report. Of the 93 syllabi, 25 came from the South, 24 from the North, 9 from the East, and 35 from the West.

Second, we ran an anonymous survey in January 2021  of instructors who had taught an undergraduate political methodology course. We received more than 140 responses, spanning R1 (53%), R2 (11%), and R3 (9%) institutions, as well as liberal arts colleges (26%) and community colleges (0.7%).

Across both the syllabi analysis and survey, we found wide variation in how these courses are structured and which software they use.

Assessment: Courses relied heavily on individual problem sets, labs, and homework (used in 84% of syllabi and reported by 77% of survey respondents), followed by exams (81% and 69%, respectively). Papers were also common (45% of syllabi, 66% of survey respondents), while group problem sets and presentations were used far less often.

Institutional support varies widely: Many survey respondents reported access to teaching assistants and dedicated lab sessions, but the majority of syllabi we analyzed showed no evidence of these same resources. 

I worked as a research assistant for this paper under Prof David S Brown (Drexel University), Prof Andrew Phillips (University of Colorado),  and Prof Katherine Bryant (Westmont)