Following on the heels of Eric’s talk, I (Paulina) got to guest lecture with the super cool students of the Archaeological Research Facility (ARF) Peralta Hacienda Historical Park field school. I approached my topic like a workshop because the Field Director (the awesome Dr. Meredith Reifschneider) allotted me three hours to talk about Data Literacy (Data Lit) and Data Visualization (Data Viz).
Few people can talk (or listen) for three hours straight, so I broke the workshop into three parts with copious breaks. Stretching, socializing, and snacking keep people engaged. As does providing activities that support different kinds of learning. So during my lecture combined some get up and move around activities, some analytical activities, some visual activities, and some writing activities into one multi-hour session.
Although we had lots of breaks, I created continuity by keeping a rotating notes sheet active throughout the class. On that, I encouraged students to answer specific questions I had for them during the lecture. Then, after they answered each question, I had them pass down the notes to another student. That way, by the end, everyone had contributed something to everyone else’s notes sheet (including me!).
Me (Paulina) explaining what the white pieces of paper are for
My favorite piece of that collaborative work was the inclusion of everyone’s response to our narrative activity. I got a delightful piece of meta-narrative that will always remind me of getting to hang out and work with the ARF field school students.
Beyond that, we covered the basics of data lit, what it is and how we learn to be data literate. We also looked at some pros and cons of different kinds of data visualizations with a focus on the visual dynamics that humans are good at (like comparing straight lines). And more than anything, I encouraged them to play with their data.
After spending so many hours excavating and cataloging, it was time for them to turn those data into a narrative of some kind. This meant that they needed to be able to summarize the information about their observations in some way. We did this by walking through Cow-culating your data with spreadsheets and R – Part I Spreadsheets in real time, adapting it on the fly.
Me responding to a student’s question while clutching my own cup of caffeine during the workshop
They even got to watch me make mistakes when leading them (I hadn’t worked in google sheets for a while). This was really cool because that’s part of data literacy too! Just like how we don’t read everything correctly every time (or even look at all the words), data literacy is about being comfortable making mistakes and adapting to new situations. Or being able, like some of the students, to not quite know what is wrong but identify that something is “off” about what they produced.
Like all literacies, archaeological data literacy is about practice more than just “knowing” how to do it. And it was great to introduce these students to some of the ways we can all practice these skills on our own or collaboratively.
