Link to the Course Website
Image: A visualization my husband created based on one day of movement (including our cat and dog) in our ~800 square foot house.
I began to prepare for my Spring 2020 Introduction to Data Storytelling class immediately after starting my job at Macalester College last August. Of all the requirements of the Postdoctoral Fellowship in the Digital Liberal Arts, the task of creating a new course for a group of such talented undergraduates sounded the most daunting.
I knew the class needed to incorporate tools and methods from the digital humanities and digital liberal arts, but the structure and content was otherwise entirely up to me (I’m incredibly fortunate in this regard). In my work notes from August 5, 2019, I jotted down: “Collections as Data→ class, workshop idea?” I quickly began envisioning the ways that examining museum, library, and archival collections could provide an ideal platform for discussing such topics as invisible labor, the politics of representation, and data privacy.
The following week, I started experimenting with the Auckland Museum API, among others, and enjoyed losing myself in the data. I also scoured syllabi, benefitting particularly from the teaching materials of Rahul Bhargava, Chelsea Gunn, Lauren Klein, Alison Langmead, Kristen Mapes, Austin Mason, Miriam Posner, Annette Vee, and Roger Whitson.
Looking back now, I realize that I put myself under a lot of pressure to expose my students to each of the primary DH methods (data visualization, geospatial mapping, and network and text analysis), but also really liked the idea of centering the course around the idea of data storytelling. Thus, I almost certainly went into the course with more ideas, topics, readings, and activities than were necessary or helpful. But, in the spirit of generosity, I will extend warm thoughts to my 2019 self—oh, the things she didn’t know!
In January, I began teaching the course one week after I had my wisdom teeth removed (yes, at the age of 32!). Thankfully my jaw was fully functional by the time my class rolled around.
I had no idea, at that point, that we would end the term over Zoom, with students calling in from 5 different states and two countries outside of the US. Indeed, I was primarily concerned that my students find utility in the course, and that it meet their expectations. In my notes from that first day, I wrote: “Finished 10 min early. I guess normal for first day? Flustered.” In hindsight, I should have appreciated the in-person connections I was slowly fostering, rather than worry about whether I was filling the time fully.
During that first class, I tried to express the Frankenstein-like nature of the syllabus by showing the different disciplines and institutions represented by the authors I’d included on the reading list for the term (see below). Although the course was cross-listed between Math, Statistics, and Computer Science and Media and Cultural Studies, the readings came from the information sciences, English and comparative literature, informatics, and many other areas.
As a “hybrid” scholar myself, straddling the lines between information science and studio art (as well as other humanities disciplines, at various moments), I wanted to convey the split nature of the class. We would be discussing data in the context of the humanities, and using software mostly developed by or in collaboration with humanists. But what did that really mean?
I discovered that my students were generous and patient, and willing to have wide-ranging conversations about data in the humanities (can data ever be truly raw?), museum collections (why does every museum seem to have idiosyncratic collection management systems?), ethical data collection (does public equal consent, when it comes to data on Twitter, etc.?), and much more.
When the term abruptly shifted from in-person to remote teaching and learning, I decided to completely overhaul the syllabus: we had lost a week of class time and were all experiencing some combination of anxiety, restlessness, uncertainty, insomnia, etc.
I’d spent a lot of time preparing museum collections data for the students to use in their final group projects, but we suddenly found ourselves without access to library materials, stable internet connections, or each other (at least not to the same extent). To be honest, as we were going into Spring Break, I had no idea how I would structure the remainder of the term or the final project.
My primary concern following the transition was the well-being of the students. I graduated from college in 2009, in the midst of the last recession, but it felt very different. I was able to get a job in the food service industry to supplement my part-time job as an assistant to a curator of curricular exhibitions. Although things felt precarious, it wasn’t like this.
So, during the second week of Spring Break, I sent out an email with a link to a quick check-in survey to ask students about how they were doing. I asked about their access to technology and their feelings about doing group work remotely, but was most invested in simply making sure they were all in safe and relatively stable environments.
After reflecting a bit, I decided to structure the remainder of the term around weekly data diaries based on topics pulled from the original syllabus. Of course, each of these topics needed to be reconsidered through the lens of our current experience. For example, the week on network analysis became a week about social network analysis. For this topic, we each focused on our current networks and how we were staying in touch with friends, family, and teachers from our various locations. I was so delighted to see how one student turned this exercise into a gratitude network. For another week, we examined data privacy. Students brought up their very real concerns about conducting their studies over Zoom, a tool that has been hacked and compromised at various points over the past couple of months. During the week when we looked at text analysis, several students compared emails, texts, or other writing samples composed prior to the COVID-19 outbreak to their current communications.
At the end of the experience, I was so impressed by my students’ various displays of generosity, thoughtfulness, and creativity.
If you’re curious, here’s the syllabus for the class. I’ve removed my students blog posts and other links for privacy and copyright purposes.
So, what worked well?
- The students. They’re simply amazing, and getting to know them before and during this unprecedented time of quarantine was, in all sincerity, a great privilege and helped keep me anchored during the transition to remote learning.
- (pre-remote) The Personal Data Postcard Assignment. This project was inspired by Georgia Lupi and Stefanie Posavec’s Dear Data project. Through this project, the students seemed to learn a lot about collection bias, campus accessibility issues, and their own routines through the process of tracking their engagement with doors over the course of a week. It was so enjoyable to see their final postcards. Next time I teach this, however, I will leave more time for critique and reflection in class.
- (remote) During the transition to remote learning, I asked myself: How can I balance maintaining a real connection while also providing reasonable expectations for my students? I wanted them to work on something that would give some structure to their otherwise very unusual new circumstances. As I mentioned above, I decided to have my students start to keep data diaries, tracking their reflections on topics and prompts that I provided. I think some students found this practice to be extremely helpful, and others were probably skeptical. I certainly could empathize with both groups. Moving forward, I think data diaries may be useful to implement from early on in the term, as these could become beautiful and useful records of the progress made throughout the class, regardless of whether we are learning remotely.
- (remote) I actually created a Slack channel for the class back in December, but had decided against implementing it in January. I didn’t want my students to grapple with too many different modes of communication, and we already had a pretty robust Google Site. However, as soon as we transitioned to remote learning, I decided to open up the Slack. It ended up being incredibly useful for sharing thoughts about our weekly readings and our data diaries. Students posted photos, links, and wonderful responses. I was also able to share articles and images more spontaneously, including inspiration from a book I ordered from The Ice Plant (https://theiceplant.cc/).
What worked less well?
- Next time I teach the course, I think I will provide more scaffolding for the readings. When the readings are so numerous and arrive from so many different disciplines, I think they require more explanation. In the future, I will assign fewer readings and encourage students to consider the context within which the writer is operating (disciplinarily, culturally, etc.) more closely.
- I’d like to devote more time to the storytelling component of this class. This term revealed how personal storytelling is an important gateway to other types of data storytelling, and that I don’t need to worry as much about exposing students to quite so many scholarly DH projects. The storytelling part is more amorphous, and intimidating, but also may allow me to bring forward the critiquing skills I developed during my studio art days.
- This term has taught me that, more than anything, I need to be more adaptable. I have a tendency to prepare for things far in advance. While this is great for some things, I need to let go a bit more. Although I proved my ability to switch gears quickly in response to the pandemic, I think I could have changed other aspects of the class earlier.
I am so excited to hopefully teach this class again. I am already thinking about the many ways that the next iteration will be different, in part because of new readings and activities I’ve discovered, but also in great part because of the valuable lessons I learned from my students this term as we navigated the pandemic and all its related complexities.