Identifying What to Teach

“Data journalism isn’t easy to define or to teach. It is constantly changing and best practices are evolving. One needs to learn a lot by doing, too.” – Jonah Newman of the Chicago Reporter

Our interviews echoed many of the findings in our quantitative data, so rather than repeat those findings, this chapter focuses on how the professors put the concepts into practice in the classroom. It is intended to provide a roadmap of existing pedagogical work in data journalism and offer insights into common challenges.

We interviewed nearly 50 teachers and practitioners, and while there is a diversity of thought, there also is a consensus when it comes to the foundations of data journalism curricula: critical thinking, mastery of key data skills, and teaching programming concepts so that students will be able to learn new tools as needed.

David Boardman, dean of Temple University’s School of Media and Communication, suggested that data journalism is about learning higher and more complex levels of analysis. This includes learning more sophisticated tools and software and almost certainly some level of programming.

In a data journalism class, having that critical thinking skill means that the students learn to treat data in an ethical way, so that rather than bending the data to represent a particular view, the goal is toward truth and accuracy.

“I would always err on the [teaching of] critical thinking skills,” said LaFleur of the Center for Investigative Reporting. “That is the harder skill to ingrain in people. You can learn how to click things and write a line of code.”

In general, those who teach data journalism focus on hands-on methods. In the beginning, the professors will provide data to students to analyze. LaFleur, for example, uses hands-on training with one data set and then will introduce a similar data set and assign the students to ask the same types of questions, but on their own.

By the middle of a course, students often have to obtain their own data, submitting public records requests. The students then move on to data that require more complex analysis. By doing this, the professors are doing two key things: teaching the critical thinking that goes with negotiating for information and understanding the bounds of that information. At the same time, the students are using basic tools to accomplish their goals, be they spreadsheets or a relational database. In some classes, the focus is on writing a memo by the end of the course on a possible story. In other courses, the professors expect the students to report and write a story. This last step—either a memo or a story—once again helps the student use critical thinking, this time pairing that with the skills of storytelling.

The key is learning how to obtain mastery, said Ira Chinoy, an associate professor at the University of Maryland who previously led the data journalism efforts at the Washington Post.

Chinoy relates this to the 2009 “Miracle on the Hudson” and how the pilot used reflexive mastery to land the US Airways plane on the river after bird strikes caused both engines to fail. In class, when students get discouraged about bad interactions or conversations in pursuit of their databases, Chinoy brings up “Sully” Sullenberger’s actions and says, “Do you think he could have done that on his first day of pilot school?”

Chinoy emphasized that the information should not always be presented to the students up front. He likes to give them a chance to come up against obstacles. They also need to develop a sense of when data could be problematic, what are signs of that, and what is each student’s best practice for examining the data.

results matching ""

    No results matching ""