| ID | 186718 |
| Title Proper | Teaching Computational Social Science for All |
| Language | ENG |
| Author | Kim, Jae Yeon ; Yee Man Margaret Ng ; Ng, Yee Man Margaret |
| Summary / Abstract (Note) | 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. |
| `In' analytical Note | Political Science and Politics Vol. 55, No.3; Jul 2022: p.605 - 609 |
| Journal Source | Political Science and Politics 2022-09 55, 3 |
| Key Words | l ; Teaching Computational Social Science |