On Sunday morning I came across a tweet by NPR’s Lulu Garcia-Navarro morning asking people when they knew things were going to be different due to COVID. Whenever I read replies to a tweet like this I’m always tempted to scrape all the replies and take a look at the data to see if anything interesting emerges.
Over the past few years I’ve been working on moving from a mindset of end-of-semester project to semester-long project. Inevitably students end up doing lots of work as the deadline approaches at the end of the semester (and I can’t blame them, that’s how I work around deadlines too, and how just about anyone I know works), but creating opportunities for them to get started on their projects earlier in the semester is very important.
Over the university summer break, we (Zeno and Lee) were busy making preparations for moving more of our Introduction to Data Science course from being human-graded to computer-graded. We both took this course in the Fall of 2019, as part of our first-year studies at the University of Edinburgh, and this is where we first learned R.
Colin Rundel and I will be teaching a series of three virtual workshops in July 2020 on teaching statistics and data science online.
On May 15th and 20th the third Preparing for Careers in Teaching Statistics and Data Science Workshop was held. 37 graduate students and recent PhDs gathered (remotely of course) to learn from Allan Rossman (Cal Poly), Mine Çetinkaya-Rundel (University of Edinburgh, Duke, RStudio), Jo Hardin (Pomona), Beth Chance (Cal Poly), Lucy D’Agostino McGowan (Wake Forest), and Ulrike Genschel (Iowa State).
As recent, current, and future chairs of the American Statistical Association (ASA) Section on Statistics and Data Science Education, we have sent the following letter to Ron Wasserstein (Executive Director of ASA) and Bhramar Mukherjee (COPSS Chair) and requested that they share it with the COPSS Executive Committee.
Story of my first attempt at learning how to make generative art in R.