Pandemic data journalism

Welcome to the COVID data journalism course-in-a-box from the COVID Tracking Project archive, housed at the University of California, San Francisco. This course contains five modules aimed at using content from the COVID Tracking Project to teach and learn the conceptual foundations of data journalism.

Although the content of this course is targeted primarily toward data journalism educators on the undergraduate level, all the materials here are open for use to anyone interested in learning or teaching data journalism.

If you use any components of this course, please consider taking our survey to help us refine the content.

Course material

The course itself is split into five modules, each containing a series of submodules. Each module is briefly described below, but links to each module and its content can be found at the top of this page.

Data as a system: Before working with data, data journalists need to develop an ability to think critically about its strengths and weaknesses. And thinking of data as one part of a larger system can help.
Spreadsheets: Spreadsheets are a foundation of data journalism, and much of what you’ll learn in this module will look familiar when working with data in other formats and in other platforms.
Liberating data: Data doesn’t always arrive ready to analyze. A data journalist’s job often involves collecting data from multiple sources or transforming it from unwieldy formats to something more structured.
Intro to R: The statistical programming language R is quickly becoming one of the standard tools for data journalists around the world. Its use can help us expand our understanding of data and how to analyze it.
The weight of data: Data is more than just numbers – it’s an attempt to quantify often emotional aspects of humanity, like loss and illness. Data journalists should be prepared for the implications of working with and presenting these numbers, both on themselves and their audiences.

Course structure

Modules are designed to take one to two weeks, assuming about two hours of class meetings each week.

The content in this course is designed to be used either:

From start to finish in a full, standalone course
As individual modules integrated into an existing course.

Each of this course’s five modules contains a mix of submodules that include:

lectures
solo work
group work
walkthroughs
class exercises
class discussions

Each module also includes a setup page for instructors and tips/further reading for students.

Notes and tips

Within many of the modules, different “alert” boxes will offer tips to instructors and students.

FOR INSTRUCTORS: This message for instructors offers pedagogical guidance and tips on presenting the lesson.

PRO TIP: This message for students offers reminders or best practices during walkthroughs and other aspects of the course.

REMINDER: Specific instructions involving troubleshooting or avoiding errors and pitfalls.

Want to contribute?

This course and its materials are open-source and currently hosted via GitHub.

If you’re interested in contributing to this course, consider making a pull request to the GitHub repository.

You can also contact the course creator, Tyler Dukes, directly with questions about the content or how to help.