Today I will be introducing my MA Data Journalism students to computational thinking techniques (you can read my post about why that’s important here). As part of my preparations I’ve been collecting some of my favourite examples of computational thinking being used to spot and execute data journalism stories – and I’m sharing them here…
Story 1: Which singer has the biggest vocal range?
This story, published in the UK tabloid newspaper The Mirror, is a great example of understanding how a computer might ‘see’ information and be able to help you extract a story from it. Continue reading
In this second extract from a forthcoming book chapter I look at the role that computational thinking is likely to play in the next wave of data journalism — and the need to problematise that. You can read the first part of this series here.
Computational thinking is the process of logical problem solving that allows us to break down challenges into manageable chunks. It is ‘computational’ not only because it is logical in the same way that a computer is, but also because this allows us to turn to computer power to solve it.
As Jeannette M. Wing puts it:
“To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability. Just as the printing press facilitated the spread of the three Rs, what is appropriately incestuous about this vision is that computing and computers facilitate the spread of computational thinking.”
This process is at the heart of a data journalist’s work: it is what allows the data journalist to solve the problems that make up so much of modern journalism, and to be able to do so with the speed and accuracy that news processes demand. Continue reading