Really leaning into ethics and justice elements of data science in my fall class, and I’m wondering how much pushback I’m going to get. I’ve taught about racism, sexism, and colonization in games in another class with very few complaints, but this feels different somehow.
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This summer, I’m remixing an alternative textbook for my Fall intro to data science class, and I’m pleasantly surprised by how helpful Creative Commons-licensed journal articles are proving. Shows that “open access” is only part of license’s benefits.
One of my data science students just did a t-test to demonstrate that evil-aligned monsters in D&D 5e tend to have lower Armor Class than good-aligned monsters. This course demands a lot of effort, but moments like this make it worth it.
Teaching R for the first time, and many students are first-time programmers. I’m reminded of teaching French in terms of how easy it is to take for granted things that aren’t obvious to beginners.
Unsatisfied with the Intro to Data Science textbook I’ve inherited. Fortunately, an earlier version is Creative Commons-licensed, as are some other fantastic resources. Guess who’s going to remix himself a new textbook for next Fall!
I know I’m going to make plenty of mistakes teaching Intro to Data Science for the first time, but one thing I’m already proud of is teaching my students to use tags to format code and output in their Canvas posts.
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