What is it about?

This article showcases how to teach an interactive one-semester-long statistics and programming class. I propose a project-based seminar that also inherits elements of an inverted classroom. Thanks to this character, the seminar supports the students' learning progress and can also create engaging virtual classes. Students are guided through a typical data science workflow in R. Along the workflow, students learn data management, data wrangling, and visualization and experience presenting first research results during a simulated mini-conference.

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Why is it important?

Learning programming requires practice and this paper gives a blueprint for a teaching and learning setting.


I set up and tested the concept while teaching programming and statistics classes. It gives instructors a blueprint for teaching stats and programming in a project-based setting. It also shows how this can be applied in a virtual format or as a block seminar and how to integrate open science and peer group support practices in this teaching setting. While I use my introductory R course as a working example, the format can be applied to any course setting that requires students to learn (and most importantly practice) “hands-on” material. I also highlighted some students‘ projects in the article — and if the word limit had permitted, I would have mentioned even more to show how creative and innovative the students‘ projects were!

Cosima Meyer

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This page is a summary of: Bringing the World to the Classroom: Teaching Statistics and Programming in a Project-Based Setting, PS Political Science & Politics, September 2021, Cambridge University Press, DOI: 10.1017/s1049096521001104.
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