Teaching Journalists to Think Computationally
Given the unique brand of statistical and predictive reporting that Nate Silver’s FiveThirtyEight is known for, it’s perhaps a bit unsurprisingly to see that as they expand they’re hiring one (or more) Computational Journalists. As the thirst for new data-driven story forms swells, the demand for people that not only know data, but can also model it, abstract it, visualize it, and develop algorithms for its manipulation, will only grow.
At the crux of what the next generation of journalists need to learn are a set of concepts related to computational thinking — an approach to problem solving that incorporates decomposition, pattern recognition, abstraction, and algorithm design as components to finding generalizeable solutions to problems. Computational thinking enables scale and the re-design of workflows that make the best use of either human or computer effort in solving a problem. Want to design the next big journalism platform? — You’d better be thinking computationally.
There are a growing set of resources online for learning more about computational thinking. Google’s in it because they need more software engineers, and Microsoft is investing too, providing materials to train 160,000 primary school teachers in the UK as it incorporates computational thinking into its grade-school curriculum. At Columbia we’re developing a program called Year Zero which aims to introduce core computing and data science concepts in the context of practice.
What really kicked off the growth in educational programs teaching computational thinking was an influential article by Jeannette Wing in 2006, then a professor at Carnegie Mellon, and now a Vice President at Microsoft Research. Next Week, on Feb. 4th, we’ll be hosting Jeannette at the Tow Center, where she’ll talk about her vision for computational thinking. She’ll be joined by Mark Hansen, director of the Brown Institute for a further conversation on what computational thinking means for journalism. Join us on Feb. 4th at 6:30pm for what’s sure to be a lively event: RSVP here!
Nicholas Diakopoulos is a Tow Fellow working on the Tow Center’s Data Journalism Project at the Tow Center for Digital Journalism. The Data Journalism Project is a project made possible by generous funding from both The Tow Foundation and the John S. and James L. Knight Foundation. The Data Journalism Project includes a wide range of academic research, teaching, public engagement and development of best practices in the field of data and computational journalism. Follow Nicholas Diakopoulos @ndiakopoulos. To learn more about the Tow Center Fellowship Program, please contact the Tow Center’s Research Director Taylor Owen: firstname.lastname@example.org.