Below are posts associated with the “ICT 661” tag.
draft advice for intro to data science students
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. I’m not convinced that the advice I give below is everything that I ought to say (or exactly how I ought to say it), but this semester, I want to get out ahead of a lot of the one-on-one pep talks I give throughout the semester.
new edition of my remixed data science textbook
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).
🔗 linkblog: A jargon-free explanation of how AI large language models work | Ars Technica'
Haven’t read this yet, but I’m bookmarking for my classes.
🔗 linkblog: Pluralistic: The surprising truth about data-driven dictatorships (26 July 2023) – Pluralistic: Daily links from Cory Doctorow'
Interesting stuff from Doctorow. If I can, I want to work it into my data science textbook for next semester.
draft syllabus statement on code, plagiarism, and generative AI
I’m spending a chunk of today starting on revisions to my Intro to Data Science course for my unit’s LIS and ICT graduate prograrms. I’d expected to spend most of the time shuffling around the content and assessment for particular weeks, but I quickly realized that I was going to need to update what I had to say in the syllabus about plagiarism and academic offenses. Last year’s offering of the course involved a case of potential plagiarism, so I wanted to include more explicit instruction that encourages students to borrow code while making it clear that there are right and wrong ways of doing so. Likewise, my colleague Josh Rosenberg posted earlier today about ChatGPT’s Code Interpreter, and while I don’t know that my students will even know that’s an option, I wanted to get out ahead of that possibility, too.
🔗 linkblog: Too much trust in machine translation could have deadly consequences.'
This article provides good examples of how the efficacy and efficiency of a given technology is often less important than deeper questions of reliance and roles.
ClassDojo and 'data as oil'
The new semester at the University of Kentucky starts on Monday, and I am flailing to try to get my data science course ready to go—including putting together an open, alternative textbook for my students. I’ve been borrowing heavily from Catherine D’Ignazio and Lauren Klein’s Data Feminism for my textbook: It’s a fantastic resource, and I’m hoping my students take a lot from it.
Of course, my kid’s semester has already started, and I’ve already blogged a bunch about my frustrations with her new school’s use of ClassDojo this year. It turns out that Data Feminism is also a helpful resource here. Riffing on the common “data is the new oil” metaphor, D’Ignazio and Klein argue that:
why 'open access' isn't enough
I just barely microblogged something about what I want to say here, but over the past hour, it’s been nagging at me more and more, and I want to write some more about it.
I was introduced to academia through educational technology, and I was introduced to educational technology through a class at BYU taught by David Wiley. This class was not about educational technology, but David’s passion for Web 2.0, Open Educational Resources, and remix culture were so strong that I got hooked. OER and Creative Commons licensing both got firmly planted deep in my thinking, and even though they never became a focus of my own edtech work, they’ve also never left my brain.