This story appears as a part of Open Data PGH, a joint reporting project by Technical.ly and PublicSource on open data trends in Pittsburgh, underwritten by Heinz Endowments. Learn more here and get updates here.
The overarching goal of the Open Data PGH reporting series is to examine ways non-technologists can learn about and get involved in civic technology. One obvious way to do that: education, for the young and slightly less young.
Matthew Lavin is a clinical assistant professor of English and the director of the Digital Media Lab at the University of Pittsburgh. In Spring 2017, he taught an iteration of the English department’s Advanced Composing Digital Media course subtitled Communicating with Data, which focused on data-driven journalism and “digital humanities analysis.”
Here, we talk with Lavin about why he’d like to see humanities and computer science intersect more often in college classrooms and how to get students comfortable with the idea that non-technologists can be part of a data conversation.
Open Data PGH: Can you talk about the challenges of teaching data concepts to humanities students?
Matthew Lavin: The English department [at Pitt] is broadly seeking to build up its capacities in interrelated areas of digital media digital studies, the culture of data and digital literacy. We’ve been doing numerous sections of an intro-level course called Composing Digital Media, thinking about digital making in the context of multimodal literacy, so, some instructors do units on digital storytelling, podcasting, video editing, website design, just a broad range of digital strategies.
The course that I piloted is designed to take any one of those topic areas and zoom in and really focus heavily on it. My section was focused on communicating with data, and the students had access to Pittsburgh data, which lead to a lot of interesting project ideas.
Were your students working with datasets from the Western Pennsylvania Regional Data Center (WPRDC)?
Yes, that was the idea. During the pilot semester, I made it very flexible, so one of the project options was to really focus on Pittsburgh data. The students could choose the themes.
For the spring version, my plan is to make sure everyone is doing the same assignment. You have to be prepared because a lot of students in the class haven’t studied data-driven or code-based work at all, and sometimes having too much freedom is actually really intimidating. It’s about finding that balance of support and flexibility.
Intimidation is a big reason a lot of people without technical backgrounds don’t pursue projects where they know they’ll be using data. How do you get students comfortable with the idea that non-technologists can be part of a data conversation?
Just by way of background: I did an undergrad major English lit and I minored in philosophy and history. I took as many humanities courses as I could. Over time, I started to branch out and be interested in other things, but I definitely understand why students go there.
When I was 19, I thought there were people who had humanities brains and people who had computer brains. But this isn’t the case; maybe I do math slower than the average person, but that doesn’t bother me. As someone who leans toward humanities, it’s can be harder for me to get a concept without an example, or maybe I just don’t care as much unless there’s an example that piques my curiosity.
An instructor in a standard computer science course tends to assume some foreknowledge, and that the students expect to learn about the principles of coding and computation. A humanities mind wants to start seeing the code as something they can engage with not just a stream of letters and numbers happening in the background that they can’t touch.
During that pilot course, what did the students choose to work on? Were you surprised by the ideas they came up with?
They did some fantastic stuff. It was surprising in that they had a lot of options and did really cool things I would never have thought of. I had a student do a close analysis of the lyrics of albums of Chance the Rapper; a student who used data to look at how segregated our city is; one group of students did a group project where they tracked their own movements through Pittsburgh for the week to see where they would be found on a given day. It was a really cool range of what students were thinking about and how they were using these data-driven methods to dig deeper into the topics.
[Editor’s note: Reminds a bit of Carnegie Library of Pittsbugh librarian Tess Wilson’s work with teens and open data.]
There’s an ongoing discussion about the ways tech can be used for nefarious purposes, often unintended purposes. Do you find students are more wary of these kinds of concerns, that they’re more savvy because they’re digital natives?
I get excellent third and fourth-year students who are writers, who are in communications and marketing who are really thinking about all these things. What I hope we can do even more of is have courses that can engage with the social issues and ethics and then somewhere you can look at the programming.
So it’s not two separate classes, one focused on programming and one focused on ethics — because what I think we have a lot of right now is happening inside the brain of the student taking both courses, who can see the overlap and where problems might occur. It would be nice if that foresight about what could go wrong was happening in the classroom.
How do you help civic-minded students take that next step, to see how their data projects might have an impact or be used for greater-good kinds of things?
It really helps when they can see real-world impact. We had some fantastic guest speakers: Bob Gradeck from the WPRDC, Nora Mattern [formerly of the University of Pittsburgh] and Natasha Khan from PublicSource. The students really responded to people from the community working on these types of issues that concern everyday life, where they’re doing things that matter to the community. I think it’s easier to care about something when you can connect it to why it matters.-30-
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