Teaching Computational Social Science for All

Jae Yeon Kim, Yee Man Margaret Ng

Research output: Contribution to journalArticlepeer-review

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 challenging and more exciting. First, it discusses two approaches for making computational methods accessible: showing the big picture and walking through the workflow. Second, a step-by-step guide for a typical course is provided using three examples: learning programming fundamentals, wrangling messy data, and communicating data analysis.

Original languageEnglish (US)
JournalPS - Political Science and Politics
DOIs
StateAccepted/In press - 2022

ASJC Scopus subject areas

  • Sociology and Political Science

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