Summary: Shawn and Troy talk about Parent Conferences, and more. Dave examines data science in Part 2. Jokes: If you want a job in the moisturizer industry, the best advice I can give is to apply daily. I was fired from the keyboard factory yesterday.  I wasn’t putting in enough shifts. Helen Waite is in charge of my complaint department… if you have an issue with my jokes, you can go to Helen Waite. Just got a birthday card, opened it up, and a load of rice fell out. It was from Uncle Ben. Did you hear about the incredibly average philosopher? His name was Mediocrates. If I were a rapper, I’d be MC Spice. Then I could say, STOP! Hammer Thyme! Why are robots never afraid? Because they have nerves of steel. My wife texted me she saw a wolf on the way to work. My question is how she knew it was on its way to work?… Who can shave 25 times a day and still have a beard? A barber! I just got a new job as a street cleaner! Turns out there’s not much training involved, you just pick stuff up as you go along. This morning, I accidentally ran into the man who once sold me an antique globe. It’s a small world. Did you hear about the guy who tied his spaghetti together?  He ended up skipping dinner. I tried taking some high-resolution photos of local farmland, but they all turned out a bit grainy. Middle School Science Minute   by Dave Bydlowski (k12science or davidbydlowski@mac.com) K12Science Podcast: Data Science Education, Part 2 I was recently reading the November-December 2025 issue of “The Science Teacher”, a publication of the National Science Teaching Association. In this issue, I read a featured article written by Matthias Fisher, Cody Pritchard, Zhen Xu, and Joshua Rosenberg. They wrote an article entitled, “Finding Your Way into Data Science Education as a Science Teacher.” This is the second podcast in a series of three podcasts on the topics of Data, Data Science, and Data Science Education. In this article, the authors aimed to support science teachers without backgrounds in data science. by addressing three major challenges:  1. The lack of training to teach data science.   2. The difficulty of designing relevant and engaging data science lessons.   3. The challenge of teaching data science with limited technological resources.   In this podcast I address challenge #2 – the difficulty of designing relevant and engaging data science lessons