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October 17, 2019
MULTIMEDIA

#GIJC19: Advice on Teaching Data Journalism

In September, I got a chance to attend the Global Investigative Journalism Conference in Hamburg, Germany. This was the 11th edition of the biggest investigative journalism conference in the world, with over 250 sessions and more than 1,500 media professionals in attendance.

The GIJC19 also had an amazing feature this year. The data journalism track was designed by investigative reporting guru Brant Houston, the co-founder of the Global Investigative Journalism Network and the former executive director of the US-based IRE (Investigative Reporters and Editors, Inc.).

We have used Brant and IRE’s Investigative Reporter’s Handbook to design our investigative reporting training sessions. It’s one of the best guides available, and you should check it out if you get a chance.

In a session on the first day of the conference, Brant Houston, Paul Bradshaw, and Kuang Keng Kuek Ser talked about best practices in teaching data journalism.

Paul Bradshaw, as readers of this website will know, is one of our inspirations and we have used his books and work on several occasions. Kuang, a data journalism trainer from Malaysia, is the founder of DataN and is a competition officer of the global Data Journalism Awards. He was kind enough to reach out to us earlier this year to seek entries from Pakistani data journalists for the global awards contest. During his presentation at the GIJC19, Kuang also mentioned the Pakistan Data Journalism Awards as an example to encourage data journalists. We’re grateful for this recognition of our national awards contest.

The experts provided some neat tips about teaching data journalism. I’ve highlighted some of the points that struck me as important.

1. Check with trainees about their needs: Paul said if trainers can find out what data sets the trainee journalists are interested in, they can use these to drive engagement during the training. Kuang said an online survey or talking to journalists directly before the training can help identify their pain points and the stories for which they are most likely to use data. Trainers should ask the trainees why they are there and spend time on things that are most relevant to the trainee journalists because that will help them actually put to use the data skills they have learned.

2. Overcoming the fear of numbers: Share examples of everyday data journalism rather than just the spectacular stuff, which can be intimidating. Paul recommended that trainers could perhaps start with data visualisation exercises and then get the participating journalists to track their way back to cleaning dirty data — to bring the learning full-circle. Brant said that journalists either think numbers are sacred or they don’t believe a thing about the numbers so we have to bring them to a middle ground. About innumeracy, Brant said journalists need to be told that we just want to count well. He suggested to start instruction with clean data so “everyone can see the power and glory of data”.

3. Derive motivation from publishing: Kuang said that journalists are usually excited about data training when they see they can get a story out of it. His advice was to use real-world data sets that are relevant to the journalists and that they can turn into news stories during the workshop. Brant said trainers should keep in mind that “it’s all about the story.” He said good learning is about discovery and trainers should build components in the training that lead the participants “to have epiphanies”. Kuang said he grabs the attention of journalists during a training by showing them examples of data stories produced by their competitors.

4. What next? There was a consensus about taking a before-during-after approach for the workshops where the before stage is covered in point #1 above and the during part is the workshop itself. Brant said trainees should be made to come up with a plan that they will follow for their data stories after the workshop. He said trainers also need to think about how they are going to stay connected with the trainees afterwards. Kuang said one strategy could be to ask the trainees what kind of newsroom support they need from their editors on data-driven stories. Then, he said, this feedback can be used to have a discussion with editors so they also know and understand how they can assist their reporters.

The experts also shared two important resources for data journalism educators:

Teaching Data and Computational Journalism by Charles Barret and Cheryl Phillips. Fortunately The Columbia Journalism School has made this book freely available online at this link.

The Investigative Journalism Education Consortium: Check out the consortium’s website for syllabi on investigative and data journalism as well as a data book and links to open data sets.

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