Table of contents for Computational thinking in journalism
- As we change journalism education, we need to study journalism learners
- A foundational concept for the new news economy
- What Would WEB Du Bois Tell Henry Jenkins and Soulja Boy?
- Building the bridge between journalism and computer science
- Can VIBE magazine be saved? And should we care?
- Scratch as a Tool for Teaching Computational Journalism
- Crafting Literary Journalism
- How stories and network science could improve educational equity and diversity
- What computing and informatics tools will help Haiti?
- Why I fear I’ll never master SEO
- You’re gonna need to read this, but it won’t be on Amazon
- Scholastic Journalism Education as a Tool for Teaching Computational Thinking
- How should journalism educators teach and study social media?
- What is a computational journalist?
- The Food Stamp Game: a test case for teaching computational journalism, part 1
- On teaching game design in a journalism course, part 2
- On teaching game design in a journalism class, part 3
- On teaching game design in a journalism class, Part 4: Newsgames as literary journalism
After years of exhortation and industry convulsions, journalism education is changing. The argument for infusing digital media education – even programming — into the journalism curriculum is over. The questions are mostly logistical – what type, in what sequence, how much and to what ends? Driven largely by business needs, college newspapers are becoming sites of experimentation with new business and management models. Professional news organizations are expanding their relationships with journalism schools beyond their traditional roles as providers of internships and first employers. In some cases, they are collaborating on beat coverage and special investigations. In at least one instance, the local professional news outlets have physically moved on campus.
At the graduate level, Medill’s Innovation program helped spawn Narrative Science, a company that programs robots to generate stories. We faculty at small programs, who have thinking through what these changes mean for institutions like ours, finally have our own journal, Teaching Journalism and Mass Communications. The 2013 edition of Georgia Tech’s groundbreaking Computation + Journalism Symposium will likely drive the conversation even further.
All signs of progress, but something important is being lost amid the frenzy.
As former President George W. Bush famously put it, “Rarely is the question asked, ‘Is our children learning?’” Mindy McAdams speaks for many of us who have spent years looking for ways to infuse digital skills into the journalism curriculum:
“Moreover, they won’t practice what they learned, and very soon, they will forget all of it.
“We can offer a course about scraping and doing stuff with large data sets. We can teach students how to find stories in data. Students who like this, who learn how to do it and want to continue doing it, are probably among those most likely to get a journalism job. Like the Web technologies course, though, this is a class that many students will either avoid like the plague or take and then count the minutes until it’s over.”
Please, please read the whole post. She points to a real challenge that we haven’t yet cracked: how to engage students who think that journalism is about writing, not math or technology. Students who have convinced themselves that writing is something they are inherently “good” at, while math and tech are something they are inherently “bad” at. Students who don’t see why they need to understand html when they can just use a wysiwyg platform to build a website.
And my colleague and friend Michelle Johnson adds another layer: too often, the students who are least successful in adapting to journalism’s digital evolution are students of color, apparently another manifestation of the racial achievement gap. She writes:
“[F]or the past 20 years, I’ve read literally hundreds of applications for journalism training programs and scholarships, as well as for admission to journalism school. And sadly, I’m seeing some troubling signs.
“This isn’t just hand-wringing about a decline in writing skills among young people with short attention spans who communicate via texting abbreviations — I’ve noticed that among all the students.
“Simply put, I’m seeing that many of the students of color lack experience with the tools and technologies that will be fundamental to journalism innovation going forward. And this comes at a time when funding for training programs for students of color has shrunk, along with the bottom lines of the news industry and professional associations.”
These are exactly the concerns that keep me awake at night, even as I champion interactive journalism as a way of bringing members of under-represented groups into computing fields. (I’d also add working-class students to Michelle’s list, by the way.)
I would submit that amid our frenzy to learn and then incorporate all the skills that our graduates need into our curricula, we need a better understanding of what students absorb, and what affects their sense of self-efficacy as they confront the unexpected skills and content we are asking them to learn. That’s part of what I’m hoping to better understand with the new research project that I’ve embarked upon with Dr. S. Monisha Pulimood, of TCNJ’s Computer Science Department. The formal title is TUES: Collaborating Across Boundaries to Engage Undergraduates in Computational Thinking.(NSF Award #1141170). As we state in our abstract:
“To adequately prepare a workforce for the changing economic and global landscape, the project is developing a model that enables students with diverse perspectives and disciplinary backgrounds to learn how to collaborate and integrate concepts from their respective fields to develop technology-based solutions for complex real-world problems.”
It’s a tall order that we’ve set ourselves, and we are grateful to have Diane Bates, our independent evaluator, on board to help us assess what we are doing.
I’ll share more specific information about our project as it develops, but for now, I want to share some specific questions that I’m working through about integrating computational thinking and integrate it into journalism classes.
What’s the right learning environment to support computational thinking in journalism? One of the posts that I wrote for a 2010 series about my own early exposure to skills that are currently classed as computational thinking began with this prologue:
“There are, at least, two approaches to education: the mimetic approach and the mathetic approach. The mimetic approach emphasizes memorization and drill exercises and is most efficient in inculcating facts and developing basic skills [Gar89, p. 6]. The mathetic approach stresses learning by doing and self exploration; it encourages independent and creative thinking [Pap80, p. 120]. In the mimetic framework, creativity comes after the mastery of basic skills. On the other hand, proponents of the mathetic school believe that self discovery is the best, if not the only, way to learn…”
Sugih Jamin, Associate Professor, EECS, University of Michigan
Whether taught in a classroom or newsroom, journalism education tends to be mimetic, while approaches to engaging novices in computing tend to be mathetic. We introduce students to specific routines and rigors of reporting, emphasizing adherence to rules of attribution, AP style, divisions of genre and structure (hard news, features, inverted pyramids, nut grafs, and so on.) We stress the importance of getting the story right the first time, and then admit that there will likely be corrections and emendations as a breaking news story develops. We do these things for good reason: flubbing the fundamentals can not only get a reporter fired, it can lead to lawsuits, or in extreme cases, endanger innocent lives and reputations. Consequently, journalism students and professionals learn to think of every thing they do in highly instrumental terms, especially when it comes to learning what they need to know to ensure that they will get or keep a job.
By contrast, programming environments for novices such as Scratch or Alice are very successful at making introductory programming concepts more accessible. However, their strategy for engaging learners emphasizes play in ways that can be off-putting to journalism students who feel a need to quickly learn how to assemble a professional product. In the past, I’ve used Scratch in two ways – as a first step in learning Flash (something I’ve abandoned since Adobe made Mindy McAdams’ Flash Journalism text obsolete, and experts such as Mark Luckie began pooh-poohing it as an important skill for journalists.) I’ve had some success teaching Scratch in game design courses, and I may think about using Alice for this purpose in the future, since its most recent iteration is specifically designed to give students a leg up Java, and that can be useful to aspiring app developers.
Do we need a journalism-specific programming environment to engage novice journalism students?
There are other, more mimetic, web-based learning environments for learning to code, such as Udacity.com’s CS `101 course, which focuses on Python and teaches students how to build a web scraper. There is an appeal to that approach because it has students build something that has obvious practical use in journalism. However, that course is arguably vulnerable to the criticism made by Bret Victor of platforms such as Khan Academy and CodeAcademy – that is, that they emphasize rote skills, while programming is “a way of thinking.”
Might it make sense to create a hybrid learning environment that combines the low barriers to entry of Scratch or Alice, with the goal orientation of something like Udacity? Will we begin to succeed at teaching programming as a way of thinking if we can more closely articulate between these learning environments and our broader journalism education curricula? (Here I am speaking of curricula not only for the classroom, but also for professional training.) Will novice programmer journalists be more motivated to learn in an environment where they can see direct connections between what their growing computing knowledge, the specific journalism artifacts they are learning to create, and the marketable skills they are developing? If so, what is the best way to create these linkages?
Is learning scripting really a gateway to computational thinking? The notion that journalism students should learn to “code” has gained increasing acceptance, but what that means and how one learns to do it are not universally understood. For several years, I’ve taken a position similar to the one that Miranda Mulligan took in a September 5, 2012 essay for NiemanLab:
- More significant conversations about digital presentation, ultimately leading to better, more meaningful, online storytelling. Understanding your medium makes you better at your craft.
- Deeper thought and understanding of data. Learning more about what goes into writing and programming software teaches you to think in terms of abstractions, functions, parameters, components, frameworks, object classes, templates, and more.
But there may be an additional unexamined assumption here, that learning scripting leads to the kind of computational fluency that, as Mulligan puts it, “teaches you to think in terms of abstractions, functions, parameters, components…” I would submit that we need data to support this hypothesis. I certainly agree with her intuitively, but we need to know. These are some of the things we hope to learn in our research project, but there is lots of good work to be done to understand what, if any correlations exist between learning to script and learning to think computationally about the creation of journalism artifacts.
What do we know about the success of CAR courses that teach Excel, SPSS, Access and SQL? The one place in the journalism curriculum that has come closest to teaching something like computational thinking has been in Computer Assisted Reporting classes (which these days, of course, is arguably a redundant term.) A syllabus repository for some of these courses is here. We’ve had a required CAR course at TCNJ for 10 years. Many of these classes required that students minimally learn to use Microsoft Excel and Access (something I required when I taught it in the early 2000s). Some also incorporated SPSS and SQL. I don’t know of anyone who has studied these courses to assess the degree to which they affect students’ computing efficacy, programming skill, or acquisition of computational thinking concepts such as abstraction, decomposition, data structures, etc.
We could also use some research on the viability of such classes as points of articulation with emerging computational journalism curricula in computer science. One hopeful example is the work done by my TCNJ colleagues Donna Shaw and Emilie Lounsberry on the development of a database manager, GUMSHOE, that tracked the disposition of gun-related arrests through the Philadelphia courts, ultimately contributing to an award winning story package on endemic problems in the Philadelphia court system.
These are just some of the questions that I think could lead to fruitful education research. I have others, such as questions about the possible role of stereotype threat on the achievement gap issues that Michelle Johnson cited, and whether learning science might help us better illuminate the real gaps in understanding and engagement that have many of us classroom teachers worried. As I’ve learned from talking to learning scientist Deborah Tatar, making assumptions about why whole groups of people aren’t grasping particular concepts is often a big mistake.
Much, much more to be learned. I’m hoping that what has been, until now, an understandably ad hoc and organic effort develops into an area of systematic study.