I’ve been teaching my department’s class on content management systems since Fall 2019, which means that I’m coming up on my seventh(!) time with the course next August. Every time that I’ve taught it, I’ve used the Hugo static site software and the WordPress CMS as examples of content management concepts. WordPress is the more (most!) popular web CMS out there, and so it’s always been my main area of focus; I think that Hugo does a wonderful job of illustrating some CMS concepts, but it also has a higher technical learning curve, so I’ve always felt conflicted about its role in the classroom.

Me, all of December: “Next semester, I have a course release and a once-a-week evening class. I’m going to get so much research done during the day!” Me, on February 7th: “Wow, it’s great to finally be getting to research this semester.”

A few months ago, I blogged about teaching being something that’s somewhat performative, and that’s on my mind again as the local district announces “Non-Traditional Instruction” for tomorrow.

I’m stress-eating banana bread to put off grading, how’s your end of semester going?

Before writing what I want to write, I want to make a few things clear. Teaching is an important and noble profession, I love being a teacher, and it’s possible (and often easy) to distinguish between better and worse ways of teaching. With that out of the way, I want to start off this post by arguing that teaching is less of “a thing” than learning is. That is, learning is the real phenomenon here, and teaching is sort of an auxiliary practice that aims to support learning but can’t ever quite be the same thing.

Another fun bike commuting game is precipitation chicken: How much of this rain can I wait out before delaying my ride in makes me late for class?

Some switch has recently flipped in my brain so that I can hand out Bs, Cs, and worse without being anxious about it. I still have real concerns about grading as a concept, but I’ve stopped worrying about taking off points as though I’m the one being penalized.

I do not believe in using AI detection software, but I reserve the right to be annoyed by the students whom I suspect of taking advantage of that belief.

I really ought to read the original piece instead of just the Slashdot excerpt, but I tried that, and it just made me even more angry, and I don’t think it would change my response. I’m not opposed to doing away with grades, but I’m not convinced by hand-wringing about grade inflation. Grades do need to be meaningful to be useful, but the idea that As need to be reserved for an elite few speaks less to meritocracy (referenced in the full piece) than to a need for an elite.

I am, unbelievably, preparing my fourth offering of my department’s ICT/LIS 661 Intro to Data Science class, and this time around, I’ve decided to add a new section to my “about the class” page in Canvas to head off some concerns that I’ve seen over the past few years. I have a lot of students with no background in either statistics or programming who take my class, and it can be really intimidating for them.

This semester, I am encouraged to include in my syllabus links to student resources related to mental health, food insecurity, etc., but required to include instructions for how to respond to an “active aggressor.” How depressing.

This morning, I’m reviewing a manuscript while watching a “cab ride” video on YouTube and thinking about how much calmer academic work is once final grades have been submitted.

Recently, an idea has been bubbling in my head that’s the culmination of months—even years—of thinking about how I assess in my courses. I’ve typically taken the pretty-standard approach that assessment is the process of students’ proving that they’ve learned something. What if, though, assessment is itself the proof of the process of students’ learning something. That is, what if we doled out points for students’ proving that they appropriately participated in learning activities and then trusted the learning to happen on its own?

I reject surveillance culture in my teaching, which means I don’t ever make a systematic effort to check for evidence of cheating or plagiarism, which just means that the obvious evidence I find anyway just makes me all the more angry.

Catching up on grading today, and I’ve been laughing out loud at some of my students’ Hypothesis annotations of class readings. I’m so glad I use this instead of discussion board responses: It’s so much more organic and creates more social presence in online classes.

Too much truth in this.

George’s example statement is one worth bookmarking.

In the summer of 2015, New Zealander Nigel Richards won the French-language world Scrabble championships despite not speaking a word of French. I heard this story on a Radio Télévision Suisse news show repackaged as a podcast (probably Le 12h30, but I can’t remember exactly) and wrote myself a note that if I ever got a chance to teach a class on games and learning, I would use this story in it.

I mean this as a general observation and not generational handwringing, but it’s amazing how many cues my students take from YouTubers when recording video presentations for my class.

I like peer reviewing manuscripts that cite my work, and I especially like correcting manuscripts that misunderstand my work, but my favorite is reviewing a manuscript that gives my work too much credit so that I can say “hey, this guy doesn’t know as much as you think he does.”

I ended the Fall 2023 semester with a lot of anxiety and frustration about grades, and there was enough of both that I wound up making a lot of changes to a graduate class that I was sure I was going to keep mostly the same from last year. Not all of these changes were assessment-related (I replaced a lot of readings and shuffled content around some), but I also more-or-less threw out the assessment structure that I’ve been using since 2019 to replace it with something minimalist and closely tied to the course’s learning objectives.

I’m becoming more and more skeptical of “improve teaching and learning” as a motivation for education (and especially edtech) research—it’s a noble goal, but it distracts us from so many other important questions.

When my sister was in town last week, kiddo insisted on drawing her a surprisingly accurate diagram of how data gets transferred over the internet, so I brought it into the office for the next time I have to teach it.

Don’t tell my students, but half the reason I have them work with Hugo in my web content management class is because I enjoy working with it so much. Over the past week, I’ve hacked together an author taxonomy for our class site, and I’m super pleased with it.

I think academia undervalues teaching and that teaching-focused faculty deserve more status, recognition, and compensation. Yet, I’m still suspicious of the new BYU-Idaho president’s comments on the need for “a faculty free of the obligations of research.”

I’ve said it before, and I’ll say it again: Nothing reminds me as much of teaching French as does teaching programming. It takes a lot of the same metacognition to learn both, and it’s really hard to teach that metacognition.

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).

Last day of kiddo’s summer, so no matter how behind I am on course prep, we are unapologetically going to the zoo.

Every semester, I give a guest lecture on internet research methods for an undergrad class in my unit. A few days after scheduling this semester’s lecture, I’ve realized it’s the first time I’m giving it after Musk borked Twitter as a data source.

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.

I’m not the only instructor out there with an idiosyncratic but very specific mental style guide for LMS content, right? Right?

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.

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.

Slowly realizing that I have no choice but to make generative AI one of the themes of my content management class in the fall.

After five years of teaching in an LIS program, I’ve finally had the moment I’ve been dreaming of: Running into a former student during a family trip to a local library.

Just had a long conversation with a student that reminded me that we cannot (and should not try to) assess that which we do not effectively teach.