Robots and Physical Computing

Activity Sheet: Detecting and Logging Magnetism with a micro:bit (Python) Overview In this activity, you turn a BBC micro:bit into a magnetism data logger using Python. The micro:bit's built-in compass sensor measures magnetic force; your program sends the readings down the USB cable so the computer can draw live graphs of them. Based on the blog post Detecting and Logging Magnetism with a micro:bit . Time: about 45–60 minutes Learning objectives By the end of this activity, you will be able to: •        Explain that the micro:bit's compass is a sensor that measures magnetic fields. •        Write a Python loop that reads a sensor over and over. •        Send labelled data from the micro:bit to a computer using serial . •        Read a live graph and describe how a moving magnet changes the readings. What you need Item ...

In a recent post ( First play with a SPOKE capacitive touch MIDI board ), I shared some first impressions of getting the SPOKE board connected, trying the web-based examples, and using it as drums in GarageBand. At the end of that post, I mentioned that the next thing I wanted to try was looking at the coding side of things., image taken from https://www.spokeboard.com/ Because the SPOKE board acts as a MIDI controller, my mind immediately went back to Sonic Pi . As I mentioned in an earlier post ( Spooky Hot-Cross Buns - Sonic Pi ), I have no musical ability at all, but I really enjoy creating with Sonic Pi—it is free, fun, and a brilliant bit of software. Putting the two together seemed like an obvious next step. For this experiment, I connected the SPOKE board as before, but instead of using an installed desktop app, I ran the web version of Sonic Pi ( https://sonic-pi.net/code.html ) straight in Chrome with no special set-up. This is a really useful option when you are working on a...

The National Teaching Repository (NTR) has just won a prestigious national award for teaching and learning — the Collaborative Award for Teaching Excellence 2026 . Good timing, then, to bring together two things I've been enjoying lately: being part of the NTR board, and playing with AI to solve problems. I wanted to see what happened if I pointed some vibe-coding and some AI-assisted analysis at the repository itself. Could I surface patterns in the NTR that aren't obvious just from browsing it — the invisible web of who has worked with whom, and what the collective body of work is actually about ? Two small activities, one feeding into the other. Activity 1: Mapping co-author connections The first idea was simple: go through the NTR's FigShare listing and map the links between authors, to see the inter-connectedness that has organically built up over the years. The prompt I used was: I would like to go through the https://figshare.edgehill.ac.uk/The_National_T...

I have been having a first play with a SPOKE capacitive touch controller board. At the time of writing, it is available from Pimoroni at: https://shop.pimoroni.com/products/spoke-capacitive-touch-controller-board?variant=56217676382587 This is not a full review, more a first-impressions note after getting it connected and trying a few of the web-based examples. The short version is: it worked, it was fun, and there was one small setup detail that was worth noting if you are using a mac neo. The SPOKE board is a capacitive touch controller. In practice, that means you can touch parts of the board and use those touches as inputs. One of the interesting things about it is that it can act as a MIDI controller, so immediately my mind went to sound, music, GarageBand, and possibly coding experiments later on. image taken from  https://www.spokeboard.com/ The place to start is the SPOKE website: https://www.spokeboard.com/ On the site, there is a very useful route labelled “Have your SPOK...

20-minute primary activity: Seeing the physical world as data with microbit This is a short classroom or STEM-club activity for primary children using a pre-prepared BBC micro. The aim is not to spend the session building the whole data logger, but to let children quickly see that a small device can measure the physical world and show those measurements changing on a screen. This activity builds on two earlier posts: DIY Data Science with microbits , especially Method 1, the “Direct Link” approach, and Detecting and logging magnetism with a microbit . These have a lot more detail on what is going on and why. This activity has been used and refined with 12 groups of up to 15 children at a time. I would suggest getting them into groups of 2-3 around a computer and a microbit. What you need 1 micro, already programmed in MakeCode blocks USB cable connected to a computer MakeCode open in a Chrome-based browser A small magnet or set of magnets A torch, phone light, or simply a way of coveri...