Readers Believe Data Visualizations

The mere inclusion of a simple data visualization, like a chart or map, has shown to significantly increase a story’s believability, whether true or not. Researchers from Cornell University tested readers with two articles on a scientific claim, both identical except in one regard. One included a graph and the other did not. While only 68 percent of readers believed the claim in the article without a graph, nearly all –97 percent– of readers believed the same claim with the graph included. Similar effects were seen when a chemical formula was included, suggesting that the persuasive effects are based on the association of a graph with what the researchers call the “prestige of science.” The researchers conclude that “graphs signal a scientific basis for claims, which grants them greater credibility.” While their conclusions pertain to science stories in particular, it’s just one step to the applicability to news in general to infuse them with an aura of scientific backing.

Researchers have also demonstrated that graphs can have a measurable impact on attitude changes. In a study from the New York University School of Law, participants were shown data visualizations to bolster arguments on different topics. For those who already held strong beliefs about the selected topics, the graphs had little effect. However, for those who were on the fence about an issue, data visualizations were effective in swaying opinion–a frightening implication for increasing the effectiveness of propaganda and misinformation to reach and to influence the important undecided population.

Data Visualizations and Social Media

In addition to the scholarly studies that support the unique power of visual evidence, we know that social media favors the simplicity of the single image. A graph, like a meme, is far more accessible and shareable on Facebook or Twitter than a link to an article. A tweet with an embedded image gets 150 percent more retweets, according to data from Buffer. Sharing an eye-catching data visualization that has an air of credibility (because it’s scientific!) is hard to resist, especially with the low-friction tap of a retweet. A Breitbart story with a bogus map supposedly showing how Trump won the popular vote “in the heartland” was shared widely on Facebook and Twitter. The map itself gives “proof” to those already inclined to believe the headline. A different map purportedly showing how the country would have voted if only millennials participated in the Presidential election went viral and was retweeted hundreds of thousands of times before readers pointed out that the map was based on a survey before the election. The key to spotting the error? The data source, which was cropped out in some versions of the map, pointed to the online poll SurveyMonkey.

That the data source was easily missed and shared despite its absence hints at how readers are more willing to accept a data visualization without a source than they would a quote without an attribution. But even if a chart clearly cites a credible data source, the methodology, visualization, or framing around the data could be completely off. There is a long trail that leads from the raw data to the final visualization, with many opportunities along the way to introduce bogus information, making the accuracy of graphs more difficult to assess.

A selection of some of the most shared fake news stories, according to Buzzfeed.

Fighting Fake News

As a media arms race emerges between fake news purveyors attempting to deceive and to disseminate doubt, and platforms enabling better ways to detect and debunk, I join with many others to push for better education in media literacy as the best long-term bulwark against misinformation, even more so than any technological measure. While it’s been provocatively suggested that media literacy could actually be the problem and not the solution to fake news, I’m not convinced that the same argument can be applied to visual and data literacy, specifically.

Having training in numeracy allows us to have a quick “gut check” – the intuitive moment that Malcolm Gladwell describes for decision-making that happens in a “blink,” but relies on early, sustained, and internalized experience. Visual and data literacy should be part of an overall media literacy effort in education. Understanding how graphs and charts are generated from data can dispel much of the mystery that fuels the notion that charts are from experts and hence, more authoritative than other media. Knowing basic chart design helps us not only identify outright lies, but recognize when visual tricks distort the underlying facts.

Of course, data and visual literacy are valuable beyond recognizing fake news that use graphs and maps. In our increasingly data- and image-saturated environment, those skills become necessities to live, work, and play in an informed manner. We all need to level up our ability to “call bullshit” as two educators from the University of Washington bluntly put it. And we’ll need it more than ever. Recent signals from the Trump administration troublingly suggests that misinformation may become a regular part of the government. The new administration lies and then casually claims “alternative facts” to backup those lies. The president appoints officials with views antithetical to the mission of the agencies they would lead, which should raise red flags about data suppression or distortion. The White House credentialed fake-news purveyor the Gateway Pundit and by doing so validates the site as a legitimate news organization. What all this means is that the reliability of our government-sponsored information and datasets could come into question. Statistics from the government on crime, demographics, employment, and other vital measures have always been the gold-standard, but a Trump administration now forces us to be extra vigilant with federal source data and any visualizations that come from them.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

The post The Dangers of Fake News Spread to Data Visualization appeared first on MediaShift.

Students at the Hofstra University School of Communication. Photo by Hofstra University.

I supported Hillary Clinton, but refrained from egregious displays of post-election disappointment other than ones aimed at the media as we examined their coverage of the candidates. My colleagues adopted various stances in their classrooms. Students told me that one of their professors avoided discussing politics entirely. A different professor unabashedly ridiculed Trump’s win with the foreknowledge that he was safe in the political unison of Clinton student supporters. While I did not think it was appropriate to outright denounce Trump — unlike the professor at Orange Coast College in California who is now facing a backlash for voicing dismay to her students — I wonder if my diplomacy was akin to the media’s own hesitation for fear of accusations of bias. Could I have done more, and should I have done more, to engage students to expose Trump’s hypocrisy, lies and unfitness for the Presidency?

Evaluating the candidates

I fell back on my role as a facilitator and had my students challenge themselves. Early in the semester, for example, they prepared for the first debate by comparing the candidates on one narrow issue of their choice, with sourcing such as campaign statements, sponsored legislation or published interviews. It forced them, or so I had hoped, to be critical not just about differences in policy, but in detail, nuance and record. It made them look for what each candidate actually said or put forth, and not what might be a talking point from a surrogate or from the opposition (or from their friends and relatives). We would also discuss the media’s role and their ongoing self-flagellation, missteps and attempted course corrections. This was an introductory journalism course, after all, and my goal was not to have my students evaluate the candidates directly, but to evaluate the media’s analysis of the candidates for evaluation by the public.

The distance I kept from my political preference wasn’t so difficult to see. In one discussion, one of my students reflexively prefaced his comment, “I didn’t vote for Trump, but…,” as if he had to make that disclaimer to me or to the class in general. Whether he felt it necessary to say that to inoculate himself from a perceived negative disposition from me or from his classmates was worrisome. Had I not fostered an atmosphere where a diversity of ideas could be exchanged? Or was he afraid of being pounced upon if he were, in fact, a Trump supporter? I had two minds about the anonymity of an individual’s choice of candidate. On one hand, I had no business discussing or judging anybody’s political leanings. On the other, where else but in a classroom should you be challenged and expected to defend your views?

I never did a public accounting of who would vote for whom, but I did conduct an anonymous poll after the first debate. My students were evenly split, 39% leaned Democratic and 39% leaned Republican, with the remaining 13% claiming Libertarian and the rest marking the “other” category. The distribution wasn’t surprising, given the conservative history of the region. Hofstra University, where I teach, is located on Long Island, just outside New York City, where Nassau County went for Clinton and Suffolk County farther east went for Trump. The split in the student political views were an unfamiliar situation for me, as my previous teaching appointments were at the very urban (read: “liberal”) City University of New York Graduate School of Journalism and at the Ivy league (“liberal elite”) Columbia University Graduate School of Journalism. At both my previous posts, I could reliably count on a uniformity of progressive politics that matched my own.

Forging relationships across ideologies

In the end, I’m less concerned about what I, as an individual in front of a classroom, can do, or could have done, to influence my students’ choices in the election. Certainly I am concerned that they walk away with a mindset and toolset for critical analysis of the news. But the election was, in my estimation, decided more along emotional and cultural lines than on facts or policy. Moreover, as I witnessed friendships grow between the freshmen in my classroom, I realize that there is more power in peer relationships to influence attitudinal changes than there is from my position as their professor. Students whom I knew to be Trump supporters had, from what I could see, active and genuine friendships with others who were publicly Clinton supporters or who identified as LGBT or of color. The hateful rhetoric from the campaign was lost or just ignored in these relationships. That a peer network has more potential to win over hearts and minds than any top-down approach is a lesson we can apply outside the classroom as well. A case in point, Facebook’s success hinges on the value we place on the information and stories shared by our friends.

New friendships begin in the classroom. Photo by Hofstra University.

I’m hopeful that the bonds of individual friendships formed in my classroom are indicative of natural, ongoing contact that forms new communities that eventually erode the divisions we’ve seen heightened during the election season. Those friendships also underscore the importance of a diverse student body to enable the passive, experiential learning that is just as important as the storytelling tools on my syllabus.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

The post Politics in the Classroom: Reflections on Teaching in a Divisive Election appeared first on MediaShift.

There are both curricular challenges for faculty, as well as reporting difficulties for students. First, the Commission on Presidential Debates announced only in late summer that Hofstra would host the debate after Wright State University in Ohio pulled out, citing security and cost concerns. That left only weeks before the start of the semester for instructors to revamp syllabi and come up with debate-related assignments.

Second, admission to the event is tightly controlled. All students are subject to a university-wide lottery just for a seat in the debate hall. Moreover, the actual debate will see wall-to-wall coverage from mainstream media, which will flood the campus. How could Hofstra students report on the event in a way that could add value to what will already be reported? How could faculty best leverage the debate as a journalistic learning moment? In particular, how could new media tools or approaches provide alternative ways to tell stories about the debate?

Hofstra University prepares for the first Presidential debate. (Photo by Russell Chun)

Exposure and Partnerships

For Professor Kelly Fincham, an expert in new media spaces and social media, having the debates on campus was an opportunity to get her students to observe and partner with professional news organizations. The simple fact that media would be setting up meant that students could learn from watching the process. “Students will get to see the world of media in action,” she told me. “They’ll be immersed in a massive global event.” But they would also be busy reporting. Fincham created an independent study course specifically for the Presidential debate. With six student reporters, she’s coordinating her team with Newsday, the local Long Island news outlet, and WABC, the local ABC affiliate, to file stories before, during and after the debate.

Professor Mario Gonzalez, a television and multimedia news veteran, agrees with the value of having media outlets surround campus and the kind of learning that environment affords. “I want them to experience what it’s like to be out there,” he said. “They can learn a lot just by seeing how other news organizations do things, and to listen to the kind of questions that they’re asking.” Like Fincham, Gonzalez also plans on getting students to report on and around the debates. As the faculty co-advisor for the weekly student-run newscast Hofstra Today, he’s sending his students to fan out over campus the day of the debate to capture interviews and b-roll of the activity.

Many more students will take part working as student reporters or working alongside professional organizations. In all, approximately 100 students received credentials as student journalists or volunteers for the media on campus, according to Colin Sullivan, the director of communications for the Division of Student Affairs. Even without official media credentials, students are informally partnering with media outlets. The social media team at Newsday, for example, plans to aggregate student social media accounts, retweeting student-driven stories on and around the debate.

Planning for the Unexpected

Gonzalez covered the previous two Presidential debates at Hofstra, so he has somewhat of an idea of what to expect. “The campus will be an area full of activity,” he said. “Part of the excitement is that we don’t know what’s going to happen. You could plan all day, but you really don’t know until that day.” He’s urging his students to trust in what they’ve learned in the classroom and to simply explore and “feel it out” for good stories. “There are so many story angles, and it’s hard for us to say, ‘this is what’s going to happen,'” he said.

He anticipates that along with the national and international media, local residents will want to be on campus so they can boast about being there for the historic event, and protesters of all stripes and colors will make their presence known. He has a sense of where protesters would likely be and where security checkpoints will funnel the crowds, but constant communication and a willingness to “fly by the seat of your pants” is a core message for his students.

New Media Tools

For her class on journalism tools, Fincham plans to have her students explore the brave new world of live video streaming via Twitter’s Periscope. For my part, I’m encouraging the use of another alternative, Facebook Live. We see both tools as a natural fit to provide coverage for what Fincham calls “millennials on the street.” Students will broadcast their raw, unfiltered and unedited interviews with fellow students on social media, revealing their in-the-moment thoughts, opinions and emotions on what will be a remarkable day for them. The mobile reporting will hopefully yield some surprising moments and, more importantly, give students a chance to discover what works and doesn’t work with mobile live video streaming.

Other faculty intend to use social media and crowdsourcing tools to take advantage of the excitement and more engaged student body. Professor Peter Goodman is coordinating Google-powered polls to take the temperature of student opinions, and to measure any substantial shift after each debate. Several professors are requiring not only live tweeting of the debate, but also specific tweets that incorporate likely participants on campus on the day of the debate — students, professors, protesters and supporters. The “Twitter scavenger hunt,” adapted from fellow educators Carrie Brown, Mindy McAdams and Cindy Royal, forces students to be on the lookout for a variety of voices to include in addition to broadcasting their own.

Students will rely heavily on mobile reporting for class assignments on the Presidential debates at Hofstra. (Photo courtesy of Denis Labrecque, Flickr Creative Commons)

The live video feeds and other social media reporting will be shared and organized with the official hashtag #hofdebate16 across classes to contribute to the ongoing conversation about the debate, on and off campus.

Reporting on the Reporters

With so much critical attention paid to the performance of the media and on debate moderators this campaign, it was important for Fincham to also have students evaluate the media itself. Her special topics class on the presidential debate aims to keep tabs on what the national campaign reporters are (and aren’t) saying on Twitter in the days leading up to the debate and on the night of the debate. Fincham leans on two commercial subscription services to help her students gather and analyze the social media output. Cision, a public relations software company, will identify and build a reputable list of political reporters in all outlets, and DiscoverText, a text analytics company, will help track the Twitter accounts and gather one week’s worth of tweets. The analyses have the potential to reveal patterns in how, or if, the reporters do live fact-checking, how they engage on Twitter, and how and if they share their own opinions.

Whether or not the debate at Hofstra changes the dynamics or course of the Presidential race remain to be seen, but for the journalism students and faculty, the debate and anticipated media feeding frenzy constitute a unique occasion to learn to report with new tools and learn from the media environment itself.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

The post Teachable Moments at the Presidential Debate at Hofstra appeared first on MediaShift.

As many news organizations are diving head-first (pun intended) into exploring VR as a potential storytelling medium, so too are journalism schools. The Newhouse School of Public Communications at Syracuse and the City University of New York are just a few of the many schools offering workshops, courses or collaborations to see what’s possible in this new medium. If VR is a challenge for content producers, it’s even more so for educators, who are already balancing a full plate of core coursework and new tools.

The challenges of VR as a new storytelling vehicle and curricular elective have also been a focus of recent professional and academic conferences, panels and discussions. At one such symposium this past spring that I co-chaired with Aashish Kumar, hosted by the Herbert School of Communication at Hofstra University, we engaged VR leaders from a variety of organizations, including Frontline, the AP, Emblematic Group, Empathetic Media and the CUNY Graduate School of Journalism. More questions than answers surfaced, as is the case with most forums, but what follows are four key takeaways from the Hofstra event, drawn from the panelists’ presentations, subsequent discussions and observations from student explorations of the new technology.

Participants at the Hofstra VR symposium get a hands-on demonstration of the storytelling technology. Photo credit: Hofstra University

A directorless shot means more direction, not less

One the most vexing challenges for VR directors is how to develop a narrative when the traditional techniques from film are no longer available. Without a frame or conventional edits, and with more agency endowed to the viewer, we asked our panelists how the absence of the omniscient director’s hand forces a redefinition of their traditional role. Carla Borras, a producer for Frontline, asserted that the assumption that VR removes the director’s hand is false, and in fact, VR demands more directorial influence, not less.

Moreover, VR direction must be informed not from film or video, but from other media, such as theatre or gaming. Viewers, unable to rely on cuts and framing, will depend more on movement, lighting and auditory cues. Borras gave an example of a plane flying overhead, which provides a natural cue for the reader to instinctively follow across the sky. As the plane departs in the distance, directors have a point in space to transition to a new scene or add textual information because they know where the viewer is likely looking.

Interactive cues will become more important, as well. Dan Archer of Empathetic Media elaborated on clever uses of interactive (and time-based) cues to ensure that viewers look where you want them to look. He cites the direction in Story Studio’s “Lost” as a good example of interactive cuing. If a viewer gazes too long in the “wrong” direction, a computer-generated firefly will buzz into the viewer’s field of view to urge them to follow and to turn their head in another direction.

Carla Borras, producer at Frontline, and Russell Chun, assistant professor at Hofstra, discuss virtual reality challenges. Photo credit: Hofstra University

Other VR storytellers have likened the new director’s role as an “influencer,” much like a matador who delicately guides the movements of a bull, or even a dungeon master, who weaves a story in tandem with the players in the role-playing game Dungeons and Dragons. But whatever the new role, it’s clear that the VR director is someone who will be drawing upon approaches from a multitude of interdisciplinary media and communication forms.

The future of VR is potentially in abstract, new experiences

Many of our experiences in VR comes to us from one of two approaches. VR can be computer-generated, recreating scenes like Nonny de La Pena’s groundbreaking VR project “Hunger in Los Angeles,” which allows us to empathize with someone having a diabetic seizure while in line at a food bank, or like Dan Archer’s reconstruction of the crime scene of Michael Brown’s death in Ferguson based on eyewitness accounts.

We can also experience VR with 360-degree video, which, as VR cinematographer Evan Wexler told ArsTechnica, makes place as important as character. As he puts it, “the place is the story.” But both approaches struggle with existing storytelling techniques from traditional documentary filmmaking and gaming. We have yet to see new content, unique to VR, unbound by the legacies of our current visual vocabulary. Nathan Griffiths at the Associated Press argued that the future of VR is in abstract experiences not necessarily grounded in reality. “As soon as we break from reality-based VR … I think that’s where we may see, in the long term, we will see the form really, really start to take off,” he said.

Nathan Griffiths, interactive editor at the Associated Press. Photo credit: Hofstra University

VR documentarian Marcelle Hopkins underscored the idea, saying at one point, “I think and I hope actually that we haven’t figured out yet what VR is capable of because I think in 5 years it’s going to look very different from the way that we’re making it now.”

Marcelle Hopkins, VR director, and Jamie Pallot, executive producer, Emblematic Group. Photo credit: Hofstra University

Partnerships are essential

Since VR is such a multidisciplinary effort, partnerships are critical, which is an important lesson for teaching virtual reality. Media outlets are partnering to extend their reach in this particularly technical realm. For example, the Associated Press teamed up with Ryot, a Los Angeles-based media company, and Vrse.works has been distributing content with the New York Times. Organizations represented by panelists at the Hofstra event, Frontline and the Emblematic Group, will join together to create best practices for VR production with a grant from the Knight Foundation.

In academia, while it’s not unusual to collaborate across departments or schools, it’s often the exception rather than the norm. But bureaucratic hurdles like sharing teaching loads have to give way to foster easier cooperation between departments that should have natural interests in VR storytelling such as journalism, media studies, film and video, engineering, computer science, or art and design. We’ve already seen how the rise of data journalism has led schools to integrate computer sciences into journalism curricula, and enabling cross-departmental efforts to teach virtual reality storytelling should be no different.

Widespread adoption of VR depends on friction-free playback

During the time between panel discussions at the Hofstra event, students and faculty mingled freely with a variety of VR headsets and viewers. Students had access to several Google Cardboard viewers, a Samsung Gear VR, an HTC Vive and other desktop computers demonstrating 360 video in the browser. While the students were awestruck at the immersion and interactivity, I was struck at their general lack of facility with the technology.

We often talk of the newer generation as digital natives, but with VR they may have well been your grandmother on Facebook. Many didn’t know how or where to access VR content or even understand how a Cardboard viewer worked. The confusion speaks to the challenges of multiple, competing players in the runtime environment. While innovative content may be available, widespread adoption depends on a more seamless way for the audience to access it. Facebook recognizes this and is already embedding 360 content right inside the news feed, but its “magic window” is only a partial, and unsatisfying, VR experience.

We gave away free Cardboard viewers, in part to encourage attendance at the event, but also to provide greater access, just as the New York Times had to do for their subscribers. But the question remains whether these students, and the public in general, will use the viewers regularly. Participants in a 2015 usability study conducted by Gannett noted that the VR experience is isolating and all-absorbing, which doesn’t align with modern news consumption habits and our multitasking daily activities.

Nobody knows if VR, in the long run, will become a staple story form and an integral part of journalism education. But because we’re still at the very early stages of VR, the exciting reality of virtual reality is that the current flourishing of immersive experiments will continue to grow and diversify.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

The post 4 Takeaways for Virtual Reality in Journalism and Education appeared first on MediaShift.

Screenshot of Time Labs Oscar diversity data visualization, “See the Entire History of the Oscar Diversity Problem in One Chart”

Time’s data visualization showing the small scattering of nominations for actors of color, and its even smaller subset for winners, reaffirms the validity of the #OscarsSoWhite hashtag not just for this year, but for many years past. According to Time, “the full 92-year history of the Academy Awards shows that Hollywood’s highest honors have lagged the population on issues of race and representation.”

Fast Company uses similar data in a video infographic that turns the homogeneity of the Oscar gold into a damning indictment on its lack of diversity. Mother Jones, the Economist, and others have weighed in with similar presentations of their own, often with comparisons to the general audience as a whole. A new study out by the University of Southern California Annenberg School for Communication and Journalism also confirms what Hollywood critics have been saying all along: that the Oscars are just the tip of the iceberg. Annenberg’s comprehensive data reveals the lack of inclusion for women, persons of color, and LGBT representations both in front of and behind the camera.

Missing in all this data, however, is a consideration of the actual roles that actors of color are getting nominated for, and occasionally winning. The data and data visualizations merely count the yes’s and the no’s, bean-counting when the question of “how” is as important as “how many.” The issue of minority representation is nothing new. The gangster, the nerd, the exotic vixen, the terrorist, and the noble savage are just some examples of familiar and tired racial tropes that are too common in the media. Indeed, apart from historical roles, recent Oscar wins simply reinforce stereotypes.

In the entire history of the Oscars, there have been only eight lead actors of color who have won. Of those, half of them were in historical dramas which demanded ethnic and non-white identities for casting accuracy: Forest Whitaker as Idi Amin, Jamie Foxx as Ray Charles, Ben Kingsley as Gandhi, and Yul Brynner as the King of Siam. The only recent wins have been Denzel Washington for his riveting 2001 Academy award performance in Training Day, where he played the thug, and Halle Berry in Monster’s Ball, a film exploring race and racism.

Oscar award winners Denzel Washington in Training Day and Halle Berry in Monster’s Ball

The data and the visualizations hide the fact that, without historical figures, the Academy is left to award strong performances in movies that are about race itself or to stereotypes. But even films about historical figures aren’t immune from exclusionary casting. Ridley Scott made questionable choices in Exodus: Gods and Kings by whitewashing the roles in ancient Egypt, with Moses and the Pharaoh’s court played by mostly white actors, and the thieves and slaves played by non-white actors. But Scott’s misfire aside, there’s value in the histories of communities of color played by actors of those communities. It just seems that we need more than that.

Whether or not the #OscarsSoWhite spotlight on Hollywood marks a tipping point remains to be seen. But journalists and audiences alike should recognize that data and visualizations chronicling the (hopefully) more diverse casting for future Oscars don’t reflect the more important measures of progress if they are simply counting wins and losses. They could, in fact, lull us into a false sense of forward movement if we are satisfied with tracking dots. We should be demanding data points that are better and not just more numerous.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

The post The #OscarsSoWhite Controversy is More than Numbers appeared first on MediaShift.

Other data journalism educators have written about what works for them, from summarizing the essential data tools, to ways to prepare and approach a dataset, to narrowing classes to focus on just a few datasets. Here, I chronicle where we started and how we ended, and the rationale for the decisions. While the goals of the course remained unchanged, much of the course structure, assignments and toolset evolved. These are the lessons I learned.

1. Report stories not requirements

The first iteration of the course required three team assignments, which I had categorized as: a “numbers” assignment, a “crowd-sourced” assignment, and a “media-based” assignment. The numbers story had students reporting and finding stories in newly released published data. The crowd-sourced story required students to gather their own data from surveys or to collect data themselves from scraping the Web. The media-based story was an ambitious attempt to get students to quantify other media sources such as text, sound, video or images.

We quickly ditched efforts to constrain the stories either by the kind of data-gathering or data source, and our latest syllabi required only three stories — two in a team and one as a solo effort. It seems obvious now, but we had much stronger, more coherent packages when students pitched stories that were inherently interesting with news value, rather than stories which satisfied requirements of form — say a “map” story or a “chart” story. Students still had to reckon with the fact that we were telling data-driven narratives, but starting with the story allowed them to explore the data approaches and visualizations that would effectively carry their story. Tempting as it might be to teach mapping techniques, and then have the students go out and report a “map” story to practice those skills, that approach deprioritizes basic storytelling by putting form over content.

Visualization from a student story on campaign bundling in the 2014 New York City mayoral race. Courtesy of Nick Wells and Jessica Glazer.

2. Prepare students in numeracy prior to a course in data journalism

Our course covered basic numeracy (means, medians, percentage change) and an introduction to spreadsheets. But as others have advocated, those essential concepts shouldn’t be reserved for data journalists. Those essential concepts should be taught to all journalists. We made data literacy a part of the core curriculum. Moving basic numeracy to the introductory craft courses meant that we could delve deeper in the data journalism course and spend more time on storytelling with data. As my co-instructor Amanda Hickman put it, “It takes a certain level of skill just to get the hood up.”

3. Set clear parameters for what constitutes a “data story”

For many students (and some news outlets), using data for a story is entirely new. So understanding what a data-driven story looks like and knowing what our expectations were was new territory. We had no word count requirements, and in fact, some of the weakest stories were ones with too much text. We didn’t want long posts with an accompanying graph, but instead, stand-alone visualizations that drove a narrative. We also learned to be very specific on the deliverables required at each stage of the development process: the pitch, storyboard, rough draft and final.

Having a clear definition of what a rough draft entailed (minimum number of hyperlinks, sources, clear captions, etc.) translated to a more refined final submission. Hickman noted that, especially when students are working in a new medium, they need to be pushed to get things done soon enough so they know they can recover. It became our version of the Silicon Valley mantra “fail fast.”

4. There’s no perfect tool

For any tool, we balanced the learning opportunities, ease of use for non-coders and its professional results.  We started by favoring the learning opportunities too heavily. In our first semester, we used Tumult Hype, a relatively new HTML5 authoring application, to integrate multimedia. Although it was easy to pick up, we quickly realized its limitations. As one student criticized in the course evaluation, “The school’s not doing us students any favors by teaching Hype. It is not a professional‐level tool and being able to use Hype is not an in‐demand skill.”

We turned to open-source and popular libraries like JQuery UI and Bootstrap for interfaces, relied on flexible JavaScript frameworks like HighCharts for visualizations, and moved from Google Fusion Tables to CartoDB. We also encouraged students to use Quartz’s Chartbuilder for simple charts and Raw for more obscure types. These tools allowed a range of skills, and especially in the case of CartoDB and HighCharts (in conjunction with JSFiddle), students could examine the code that powered the visuals. “It was a nice interim step to programming,” Hickman told me. In addition, the API was well-documented. “It meant that students could solve their own problems.” That’s a thought that any instructor would embrace.

Mapping accessibility in New York City’s subways, a student visualization made with CartoDB. Courtesy of Ben Brody.

5. Don’t forget about pencil and paper

The one problem with a tool like HighCharts is that it encourages students to simply pick an existing graphical form like choosing an item off a menu without a thoughtful approach to visual encoding. There’s value in not restricting a student’s thinking to conventional forms and getting them to spend time with pencil and paper. “One of the things we lost when we went to Highcharts is getting the students to assemble the visuals,” Hickman said. “It was hard to be truly creative or innovative in that context. There was a level of creativity that we stopped seeing when we started doing heavier-handed programming.” One option to offset that tendency is to invest some attention in Adobe Illustrator to develop what Hickman refers to as “the flat and well-annotated cousin.”

6. Keep their eyes outward

One of our successes that has been part of the course since the beginning was what we called a Festival of Data. At the start of each class, a different student critiqued a data visualization that they brought in. It served as an ice-breaker to get the class warmed up and talking about data, but it also forced them to be constantly on the lookout for successful (and not so successful) examples in the wild. The exercise helped hone their judgements and at the conclusion of the course, we had a nice collection of data-driven stories and commentary.

7. Inspire students

A key takeaway from our experience is realizing the need to inspire students about data and data visualization. For our own course enrollment requirements, we had to motivate students who wouldn’t ordinarily think about taking a data course. Sandeep Junnarkar, the director of Interactive Journalism at CUNY, noted that many students are more naturally drawn to other types of storytelling, like visual or audio, despite the hype about data. “I just don’t think most students are aware of the power and the capability of data and data visualization, “ he said. “It’s a far more complex storytelling.” Educators can address the issue, Junnarkar suggests, by creating smaller venues and more intimate approaches such as setting up individual data mentors and informal clubs for more casual and personal interactions with data reporting.

Like all instructors, each year I learn how to teach the course better, and the latest syllabus reflects these improvements.

Russell Chun is an assistant professor of journalism at Hofstra University School of Communication, where he teaches multimedia storytelling and data journalism. Twitter @russellchun.

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