You aren't a proper stats nerd if you have not scrolled for an hour through all of The Pudding's content.
Thank goodness for The Pudding, which helped me spice up the discussion boards in my online stats class.
For a long time, I emphasized rigor over wonder. In my stats class, I had functionally reasonable but not terribly engaging topics for class discussion. That changed last semester. I spiced up my discussion board with some of my favorite data visualizations, like this one about using a fast food app to track power outages after a natural disaster and this one that illustrates data on the efficacy of nutritional supplements in a beautiful and functional way. Here is another that lets students look at trends in art and wonder about how this may reflect on cultural shifts in courting and romantic relationships.
TL;DR
The Pudding recently shared a post about trends in love songs from 1958 through 2023. The whole interactive is very engaging and lets you play clips from different songs. Super interactive. The interface walks you through the data, so your students aren't just stuck with a whole bunch of data to try to make sense of in one go. It illustrates how data visualizations can be used to illustrate changes over time. It is up-to-date data (for now!) that your students have heard. In a discussion board format, you can ask your students what trends they see in the data, why these trends might exist, etc.
Deep Dive:
1. Methodology! Where the data came from and how they cleaned it with ChatGPT:
And they used qualitative methodology to create song categories:
2. Data to ponder and play with: The Pudding shares their data, via .CSV and through his cool, interactive image:
Anyway, in my class, I just ask my students to wonder about the data. Why are Heartache songs so popular right now? Do they think that reflects the mood of the nation or pop culture trends? Are Brittany and Christina responsible for the sexual confidence surge of the early 2000s? What is it about modern times that has popularized the "It's Complicated" song?
Is this the most rigorous, science-y discussion board topic? No. Does it show, painlessly, how researchers can find archival data, code that data, read a data viz, and use it to contemplate trends in art and pop culture? Can students speculate on how trends in art are influenced by trends in culture? I believe it does.
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