I’m happy to share that the Fall 2023 edition of my remixed Introduction to Data Science textbook is now available on my website. This book adapts material from the “ModernDive” Statistical Inference via Data Science course, Catherine D’Ignazio and Lauren Klein’s excellent Data Feminism, a number of other Creative Commons-licensed works, and some of my own contributions to put together a no-cost, openly-licensed textbook for my data science students. I put together the first edition of this book for last Fall’s version of this course, but the first run through taught me a lot, and I’m very happy about this edition (though I do have a small laundry list of errors to fix, and I’d like to eventually get into some fiddlier bits like removing social media icons from the header).
I love hearing from former students about the great and interesting things that they’re up to—and especially when something they learned in one of my classes helped them along the way. In my experience, former students who are up to great and interesting things would often be doing those things whether or not they had taken one of my classes, but I still appreciate feeling like my teaching contributed in some small way.
🔗 linkblog: my thoughts on 'Why AI detectors think the US Constitution was written by AI | Ars Technica'
I don’t like generative AI, and I get grumpy about advice to accept it and work it into classes (even though I probably agree with that approach at the end of the day). For all that dislike and grumpiness, though, I feel even more strongly that AI detectors are not the way to go. This is a really interesting article. link to ‘Why AI detectors think the US Constitution was written by AI | Ars Technica’
Fall 2023 will mark my fifth time teaching my department’s class on Content Management Systems. I have really loved taking on this class and making it my own over the past several years. It’s also been fun to see how teaching the class has seeped into the rest of my life: It’s a “cannot unsee” situation (in a good way!) where the concepts I teach work themselves into everyday encounters with the news, my own websites, and other things around the internet.
Somewhat meandering read, but I think there are interesting implications for both teaching and research. link to ‘The End of Grading | WIRED’
When I was still an undergraduate student at BYU, I took a job as a student instructor for FREN 102, the second half of a two-course sequence in first-year French. I had a lot of weird experiences as an undergraduate student teaching and grading other undergraduate students, but the one that I remember this morning is the time that I held a student’s scholarship in my hand. I don’t remember the student’s name or much about her, except a vague recollection of her face and a couple of conversations with her.
Today, I heard from a student that I had a couple of semesters ago asking for a letter of recommendation for a master’s program. I only had the student in one class, his attendance was spotty, and I didn’t have a lot of sustained interactions with him, so I am questioning whether I would be the best letter writer for him. However, while I said as much to the student in my reply, I also told him that despite all of that, I would still be willing to write him a letter.
One of the most interesting parts of teaching information communication technology classes despite not being formally trained in that field is picking up terms and concepts that I never learned as part of my degrees. One of the most interesting concepts I’ve picked up along the way is the formal distinction between digital and analog phenomena. I often use clocks or thermometers as examples of this in class: Analog phenomena can take on any number of values within certain bounds, whereas digital phenomena are limited to discrete values within those bounds.