Teaching Computational Social Science for All

Abstract

Computational methods have become an integral part of political science research. However, helping students to acquire these new skills is challenging because programming proficiency is necessary, and most political science students have little coding experience. This article presents pedagogical strategies to make transitioning from Excel, SPSS, or Stata to R or Python for data analytics less painful and more exciting. First, it discusses two approaches for making computational methods accessible: showing the big picture and walking through the workflow. Next, a step-by-step guide for a typical course is provided through three examples: learning programming fundamentals, wrangling messy data, and communicating data analysis.