Generally, I discourage my intro to data science students from tackling questions they can’t answer at their level of programming, but sometimes I get so interested in the question that I end up writing the code for them so I can see what they do with it.
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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.
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!
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