Alternatively, if you have access to a soldering iron and a drill, you can build your own home arcade setup. This build by SrGamer is based on a Raspberry Pi 5, and features two joysticks, loads of buttons and a gloriously chunky red power switch built into the case. The case was bought from Etsy rather than handmade, as the maker didn’t have much space to work, no woodworking experience and no access to workbenches, table saws, and other tools. We’re all standing on the shoulders of giants. All SrGamer had to do was see the potential, then bring it to life. We’re slightly worried by the choice of an MDF case, as it’s not the strongest material, and if you spill beer on it then it’ll swell up and deform, so if you use it in any of your project, be sure to finish with a coat of paint.
At times, it can seem like everything is being automated with AI. However, there are some parts of learning to program that cannot (and probably should not) be automated, such as understanding errors in code and how to fix them. Manually typing code might not be necessary in the future, but it will still be crucial to understand the code that is being generated and how to improve and develop it.
As important as debugging might be for the future of programming, it’s still often the task most disliked by novice programmers. Even if program error messages can be explained in the future or tools like LitterBox can flag bugs in an engaging way, actually fixing the issues involves time, effort, and resilience — which can be hard to come by at the end of a computing lesson in the late afternoon with 30 students crammed into an IT room.
Debugging can be challenging in many different ways and it is important to understand why students struggle to be able to support them better.
But what is it about debugging that young people find so hard, even when they’re given enough time to do it? And how can we make debugging a more motivating experience for young people? These are two of the questions that Laurie Gale, a PhD student at the Raspberry Pi Computing Education Research Centre, focused on in our July seminar.
Laurie has spent the past two years talking to teachers and students and developing tools (a visualiser of students’ programming behaviour and PRIMMDebug, a teaching process and tool for debugging) to understand why many secondary school students struggle with debugging. It has quickly become clear through his research that most issues are due to problematic debugging strategies and students’ negative experiences and attitudes.
When Laurie Gale started looking into debugging research for his PhD, he noticed that the majority of studies had been with college students, so he decided to change that and find out what would make debugging easier for novice programmers at secondary school.
When students first start learning how to program, they have to remember a vast amount of new information, such as different variables, concepts, and program designs. Utilising this knowledge is often challenging because they’re already busy juggling all the content they’ve previously learnt and the challenges of the programming task at hand. When error messages inevitably appear that are confusing or misunderstood, it can become extremely difficult to debug effectively.
Program error messages are usually not tailored to the age of the programmers and can be hard to understand and overwhelming for novices.
Given this information overload, students often don’t develop efficient strategies for debugging. When Laurie analysed the debugging efforts of 12- to 14-year-old secondary school students, he noticed some interesting differences between students who were more and less successful at debugging. While successful students generally seemed to make less frequent and more intentional changes, less successful students tinkered frequently with their broken programs, making one- or two-character edits before running the program again. In addition, the less successful students often ran the program soon after beginning the debugging exercise without allowing enough time to actually read the code and understand what it was meant to do.
The issue with these behaviours was that they often resulted in students adding errors when changing the program, which then compounded and made debugging increasingly difficult with each run. 74% of students also resorted to spamming, pressing ‘run’ again and again without changing anything. This strategy resonated with many of our seminar attendees, who reported doing the same thing after becoming frustrated.
Educators need to be aware of the negative consequences of students’ exasperating and often overwhelming experiences with debugging, especially if students are less confident in their programming skills to begin with. Even though spending 15 minutes on an exercise shows a remarkable level of tenaciousness and resilience, students’ attitudes to programming — and computing as a whole — can quickly go downhill if their strategies for identifying errors prove ineffective. Debugging becomes a vicious circle: if a student has negative experiences, they are less confident when having to bug-fix again in the future, which can lead to another set of unsuccessful attempts, which can further damage their confidence, and so on. Avoiding this downward spiral is essential.
Laurie stresses the importance of understanding the cognitive challenges of debugging and using the right tools and techniques to empower students and support them in developing effective strategies.
To make debugging a less cognitively demanding activity, Laurie recommends using a range of tools and strategies in the classroom.
Some ideas of how to improve debugging skills that were mentioned by Laurie and our attendees included:
Using frame-based editing tools for novice programmers because such tools encourage students to focus on logical errors rather than accidental syntax errors, which can distract them from understanding the issues with the program. Teaching debugging should also go hand in hand with understanding programming syntax and using simple language. As one of our attendees put it, “You wouldn’t give novice readers a huge essay and ask them to find errors.”
Teaching systematic debugging processes. There are several different approaches to doing this. One of our participants suggested using the scientific method (forming a hypothesis about what is going wrong, devising an experiment that will provide information to see whether the hypothesis is right, and iterating this process) to methodically understand the program and its bugs.
Most importantly, debugging should not be a daunting or stressful experience. Everyone in the seminar agreed that creating a positive error culture is essential.
Teachers in Laurie’s study have stressed the importance of positive debugging experiences.
Some ideas you could explore in your classroom include:
Normalising errors: Stress how normal and important program errors are. Everyone encounters them — a professional software developer in our audience said that they spend about half of their time debugging.
Rewarding perseverance: Celebrate the effort, not just the outcome.
Modelling how to fix errors: Let your students write buggy programs and attempt to debug them in front of the class.
In a welcoming classroom where students are given support and encouragement, debugging can be a rewarding experience. What may at first appear to be a failure — even a spectacular one — can be embraced as a valuable opportunity for learning. As a teacher in Laurie’s study said, “If something should have gone right and went badly wrong but somebody found something interesting on the way… you celebrate it. Take the fear out of it.”
In our current seminar series, we are exploring how to teach programming with and without AI.
Join us at our next seminar on Tuesday, 12 November at 17:00–18:30 GMT to hear Nicholas Gardella (University of Virginia) discuss the effects of using tools like GitHub Copilot on the motivation, workload, emotion, and self-efficacy of novice programmers. To sign up and take part in the seminar, click the button below — we’ll then send you information about joining. We hope to see you there.
If you’ve ever tried to specialise in any field of making, you’ll find that at some point you’ll have stopped – or at least delayed – creating things, in order to make things that help you make things. If you’re at the start of your journey into woodworking, for example, you’ll very sensibly want to start with a bench hook, to hold workpieces steady while you’re sawing them. Then, of course, you’ll need a bench, otherwise the bench hook is useless. A few weeks pass, and at every turn, you’re spending more time making jigs than you are making the thing you wanted to make – what even was that again?
I was working part time alongside job hunting after uni, and came across the application for a graphic design role at Raspberry Pi. I then got invited for an interview where I got to meet my lovely team, and speak through a few of my projects. After a couple of weeks I received an email saying I didn’t get the graphic design position advertised…however I was offered an internship for six months as a graphic designer! After two months of my internship I was offered a full time position.
What did you know about Raspberry Pi before joining?
I’ve known about Raspberry Pi for many years through my dad. On one of his birthdays we got him a Raspberry Pi 4B from the store in Cambridge!
What Raspberry Pi design stuff have you worked on?
I have worked on a variety of projects ranging from packaging to web assets to magazines to events. My first packaging project was reskinning the PoE HAT.
I also designed the tote bags you may have seen at any of the pop-up stores we’ve had, as well as on past magazines, like a feature page I had the pleasure of working on in Wireframe.
Have you made anything with a Raspberry Pi, or have any plans to?
I currently have a Raspberry Pi 5 at home that is in desperate need of a project for it! My dad and I are constantly looking for inspiration, so plans are pending…
What other hobbies do you have?
Over lockdown I taught myself to crochet: cardigans, plushies etc. I even made some cutesy leaf coasters for some of my colleagues. I have also completed two half marathons so far. Unfortunately – or thankfully – I didn’t get a ballot place in the London marathon next year.
It’s refreshing that newer doesn’t always have to mean bigger and better. I’ve been using a Raspberry Pi 4 for the last few years as a desktop Linux machine, and although it could be faster, then thing that holds me back from upgrading it is nothing to do with the Pi itself. It’s the peripherals: if I moved to a Raspberry Pi 5 I’d have to get new headphones, as the Raspberry Pi 5 moved away from a 3.5mm headphone jack. I’d have to spend money on headphones that use Bluetooth, and forever be losing them or running out of charge. I realise this makes me unusual in the world of the tech enthusiast, but once I get something that works, I just don’t want to go to the effort of changing it.
That may make me an outlier in terms of individuals, but there’s another consumer sector that really wants to be able to get the bare minimum and stick with it: businesses. Upgrading is a cost. Buying new cables because the new version of a device uses USB-C instead of Micro USB is a cost. Any change at all imposes a cost, and if you can avoid that, you’re winning.
We all know that things like connectivity and processing speed are features. But price is also a feature, and a really big one. So too is backward compatibility. If I don’t want to buy a new thing because it messes with my minimal setup of screen, keyboard, mouse and headphones, then it’s vanishingly unlikely that I’d invest in a new device if it meant I would have to build a whole new factory to accommodate it.
It’s great there are new devices to play with. But it’s even greater knowing that you can buy one, and build it into your project, or your product, or even your manufacturing setup, in confidence that it won’t be rendered obsolete by the next new model. It sounds counter-intuitive, but that’s how you keep customers coming back: not by locking them in, but by making it clear that they don’t have to upgrade if they don’t want to.
With the new academic year fully under way in many parts of the world, it’s the perfect time to reflect on the growth and innovations we’ve achieved with the Ada Computer Science platform. Your feedback has helped us make improvements to better support teachers and students — here’s a look back at some of the key developments for Ada from the past 12 months.
Teachers in discussion at a Raspberry Pi Foundation teacher training event.
Supporting students through personalised learning, new resources, and new questions
We made significant improvements throughout the year to support students with exam preparation and personalised learning. We introduced over 145 new self-marking questions and updated 50 existing ones, bringing the total to more than 1000. A new type of question was also launched to help students practise writing longer responses: they label parts of a sample answer and apply a mark scheme, simulating a peer review process. You can read more about this work in the AI section below.
We updated the question finder tool with an intuitive new design. Instead of seeing ten questions at random, students can now see all the questions we have on any given topic, and can use the filters to refine their searches by qualification and difficulty level. This enables students to better personalise their revision and progress tracking
“Ada Computer Science has been very effective for my revision. I like how it provides hints and pointers if you answer a question incorrectly.”
– Ada Computer Science student
The ‘Representation of sound’ topic received a major update, with clearer explanations, new diagrams, and improved feedback to support students as they tackle common misconceptions in sound physics. We also refreshed the ‘Representation of numbers’ topic, adding new content and interactive quizzes to support teachers in assessing students’ understanding more effectively.
We introduced a new database scenario titled ‘Repair & Reform’, offering an entity relationship diagram, a data dictionary, and a new SQL editor and question set to help students prepare for project-based assessments. We’ve further expanded this scenario into a full project covering all stages of development, including requirements analysis and evaluation.
April was dedicated to gearing up for the exam season, with the introduction of revision flashcards and ready-made quizzes on key topics like bitmapped graphics and sorting algorithms. We also launched a student revision challenge, which ran from April to June and attracted over 600 participants.
“Ada Computer Science is an excellent resource to help support teachers and students. The explanations are clear and relevant, and the questions help students test their knowledge and understanding in a structured way, providing links to help them reconcile any discrepancies or misunderstandings.”
– Patrick Kennedy, Computer Science teacher
Supporting teachers
We expanded our efforts to support new computer science teachers with the launch of a teacher mentoring programme that offers free online drop-in sessions. We also hosted a teacher training event at the Raspberry Pi Foundation office in Cambridge (as seen in the picture below), where educators saw previews of upcoming content on AI and machine learning and contributed their own questions to the platform.
AI content and AI features
We continued our focus on AI and machine learning, releasing new learning resources that explore the ethical and social implications of AI alongside the practical applications of AI and machine learning models.
To expand the Ada platform’s features, we also made considerable progress in integrating a large language model (LLM) to mark free-text responses. Our research showed that, as of June, LLM marks matched real teachers’ marks 82% of the time. In July, we received ethics approval from the University of Cambridge to add LLM-marked questions to the Ada platform.
Computer science education in Scotland
We made significant strides towards supporting Scottish teachers and students with resources tailored to the SQA Computing Science curriculum. From September to November last year, we piloted a new set of materials specifically designed for Scottish teachers, receiving valuable feedback that we’ve used in 2024 to develop new content. More than half of the theory content for the National 5 and Higher specifications is now available on the platform.
Our ‘Reform & Repair’ database scenario and project align with both SQA Higher and A level standards, providing a comprehensive resource for students preparing for project-based assessments.
Looking ahead: New resources for September and beyond
We have big plans for Ada for the next 12 months. Our focus will remain on continuously improving our resources and supporting the needs of both educators and students.
After the positive response to our ‘Repair & Reform’ database project, our content experts are planning additional practical projects to support students and teachers. The next one will be a web project that covers HTML, CSS, JavaScript, and PHP, supporting students taking SQA qualifications in Scotland or undertaking the non-examined assessment (NEA) at A level.
We’ll be working on a number of teacher-focused improvements to the platform, which you’ll also see on Ada’s sibling site, Isaac Physics. These will include an overhaul of the markbook to make it more user-friendly, and updates to the ‘Assignments’ tool so assignments better meet the needs of teachers in schools.
We’ll be welcoming the next cohort of computer science students to the STEM SMART programme in January 2025 where, in partnership with the University of Cambridge, we’ll offer free, complementary teaching and support to UK students at state schools. Applications are now open.
Thank you to every teacher and student who has given their time in the last year to share feedback about Ada Computer Science — your insights are invaluable as we work to make high-quality computer science materials easily accessible. Here’s to another fantastic year of learning and growth!
When you walk into a vibrant Code Club, it is easy to see that the young creators are having fun with digital making. But are they actually learning anything? Our recent evaluation has shown that not only are they developing their coding skills, but there are many other benefits.
Code Club is a network of free coding clubs where young people learn how to create with technology. The Raspberry Pi Foundation supports Code Clubs through training and guidance for mentors, and by providing learning resources that lead to meaningful and lasting learning outcomes for the young people attending the clubs.
Founded in the UK in 2012, Code Club has grown into a global movement and has already inspired more than 2 million young people to learn how to build their own apps, games, animations, websites, and so much more. We are incredibly proud of the impact Code Club has already achieved and we want many more young people to benefit. Our ambitious goal for the next decade is to reach 10 million more young people through Code Club.
New impact insights about Code Club
We’re ambitious about Code Club because we know it works. Over the last year, the Durham University Evidence Centre for Education (DECE) conducted an independent evaluation of the programme that confirmed earlier evidence: attending Code Club leads to positive outcomes for young people.
The DECE evaluation showed that young people who attend Code Club build their coding skills. They also become more confident in learning coding, grow their interest in it, and develop a sense of belonging. Researchers observed how each young person has their individual projects to work on, which promote a sense of ownership and personalised learning, but that there are also opportunities for collaboration and celebrating their achievements with other creators in the club.
Young people also develop positive attitudes to coding and a range of life skills such as problem solving and communication. These skills and mindsets prepare young people to confidently engage with emerging technologies and with learning in a broader context.
“Coding is really fun when I know what to do, but sometimes it is hard. But I always keep trying.”
– Code Club creator.
Another finding was that Code Clubs are a place where young people who experience difficulties in formal classroom settings can thrive. This suggests Code Clubs can help educators engage a more diverse group of young people in creating with technology than formal education alone could.
“We see pupils in completely different roles when they are doing these Code Club activities. They enjoy more, and you can see they have skills to do things that we otherwise don’t notice.”
– Code Club mentor.
None of the benefits for young people would be possible without the volunteers who give their time and make Code Clubs the positive learning environments they are. Their support is crucial to young people’s engagement and skill development. The evaluation showed that mentors find the experience of volunteering rewarding, and pointed us towards areas where we can offer further support to help them run engaging, impactful Code Clubs.
“…volunteering with Code Club has helped me feel I’m a useful member of society in my old age, so the benefits have been good for me too.”
– Code Club mentor.
How we’re building on our support for clubs
With AI already transforming so many parts of our lives, learning how to create with technology has never been more important. Generative AI is changing how humans give instructions to computers, and at Code Club, young people can experiment with new technologies such as AI in a safe environment. New projects that support young people to learn about AI technologies will be added to the Code Club Projects site later this month, alongside support for club leaders and mentors on this topic.
The evaluation methods used by the DECE will help us hone our ongoing impact measurement work for Code Clubs running in communities all over the world. As we continue to support Code Clubs, we are taking into account that the independent evaluation ran in school-based Code Clubs in the UK only. In our work to grow the Code Club network across the globe, we are adapting our support and resources for local contexts in collaboration with partners who share their expertise.
This will ensure that Code Clubs can provide a fun, welcoming space for all young people. And while they’re having fun, they will also gain relevant learning experiences that empower them to engage confidently with a world that is being transformed by digital technologies.
If you’re interested in the DECE evaluation’s results, we’ve put together a summary for you to download.
Thomas Killus has created such a brolly using a Raspberry Pi Pico microcontroller board. It sends instructions to strips of standard WS2812b addressable RGB LEDs that run along the ribs of an umbrella, and this in turn brightly disperses light across the adjoining panels. The umbrella would certainly shine bright in a crowd and maybe even prevent it being left behind on the bus. But it’s also, curiously, the first step towards something bigger.
“I have always been fascinated with beautiful light installations,” Thomas says. “My dream is to someday build a complete LED suit that can either be pre-programmed or made to interact with the environment through sensors. It would be nothing practical, but I hope to bring a smile to the people around me and myself. I thought an umbrella would be a small step into this direction.”
Brolly good
Planning the umbrella was straightforward enough. “Get an umbrella, get LEDs and put them together,” Thomas explains. In the past he had tended to use an ESP32 microcontroller for his hardware projects and Python for his pure software projects. “But one day I saw a Raspberry Pi Pico microcontroller in a store and I recognised the great potential of finally using Python in my hardware projects, so I knew I had to give it a try,” he explains.
The idea was to create a set of pre-programmed animations that could be easily skipped through by simply pressing a button. These animations were created on a PC using a simulator Thomas had developed in Pygame. They were then saved to an SD card which plugged into the umbrella. “Raspberry Pi Pico can read the animation data and control the LEDs accordingly,” he explains. “I thought this way, I wouldn’t have to limit the animations by the computer power or memory limitations of Raspberry Pi Pico.”
Development went reasonably well. “It didn’t cause me major headaches,” Thomas says. “But in the beginning, I had some issues with reading the animation commands fast enough from the SD card while displaying them live but I eventually figured it out using byte files.”
Shine a light
There are some features he would like to implement, though. Thomas originally planned to also add an MPU9250 nine-axis motion tracking sensor to measure acceleration, rotation and orientation. “I wanted to add features which will make the umbrella change its lights when you spin it, jump or turn into a different direction and I hoped it would give the user more interactions with the umbrella,” he says.
Thomas also wants to reduce the number of visible cables and make the underneath “sparkle with the same joy,” as he puts it. “LED light isn’t diffused on this side and it takes away a lot of the effect,” he laments. Even so, the umbrella has gone down well among the Raspberry Pi community even though many say it has no practical use. “I guess they are right,” he says. “But I enjoyed building it, I learned some things and it made me smile when it lit up for the first time.”
You don’t have to use this little dock mechanism – we can definitely imagine 3D-printing an enclosure that sticks to the back of the lid with a few cables between the laptop and Raspberry Pi. However you choose to connect your Raspberry Pi though, it doesn’t require any extra software setup and is immediately good to go, which is very nice.
Take it with you
As there are no computer parts inside the shell, the whole thing is very light, even with a Raspberry Pi attached to it (although it does throw off the balance a little). The heaviest part of the assembly is probably the 5,000mAh battery, which charges nice and quickly, although only with the included DC barrel jack. With a Raspberry Pi plugged in the battery lasts for a couple of hours just fine with fairly normal use, and you can also check the battery with a touch of a button.
Perhaps due to either how light it is, or the materials used in construction, but the Note does feel a little bit flimsy while using it. The mousepad is fine, however the physical clicks for right and left click feel clunky and only work near the bottom of the touchpad. Compared to other normal laptops the keyboard is actually pretty good though, and is nice to type on – it has an extra bit of resistance that makes the keys satisfying to use.
Multi-purpose
We didn’t find much use for it with our other PCs – although we don’t have any mini PCs like a Mac Mini or such around, which seems like a good fit for the CrowView. It’s quite nice for watching videos from a phone though, especially if you’re travelling and don’t want to lug a regular, heavier laptop around with you.
However, it’s as a Raspberry Pi dock that it really shines for us, and despite our concerns with the build quality and awkwardness of the provided dock system, it works more than well enough that we’re definitely going to be using it in the future instead of juggling cables on monitors and PSUs. We might use a Bluetooth mouse though.
Verdict
9/10
There are some minor build quality issues but the product itself is fantastic and does exactly what you’d want it do.
Specs
Display: 14-inch IPS, 1920×1080
Battery: 5000mAh
I/O: Keyboard, touchpad, mouse, webcam, USB A, USB-C, speakers, 3.5mm headphone jack, mini HDMI in
Since we first launched the Code Editor, a free online tool designed to support young people as they learn text-based programming, we’ve been excited to hear how educators have been trying it out in their classrooms.
“I used the Code Editor with my computer science students yesterday and it worked a dream! Students were able to write and run code without any issues.”
– Head of Computer Science
The Code Editor is designed for learning, rather than for professional use, and is informed by our understanding of pedagogy and computing education. It can be accessed from a web browser without installing any additional software.
Earlier this year, we announced that we’d be introducing classroom management features and we’re now pleased to confirm that we’ve launched the beta version of Code Editor for Education with school accounts.You can be the first to try out the new features, together with the many schools who have chosen to pre-register their school accounts.
Simple and easy classroom management
We’ve kept the educator interface clean, simple, and easy to use. School owners can invite other teachers to join, add students, organise students into classes, and help students reset their passwords quickly. Educators can create coding projects to share with students and view their work.
All features, totally free
We’ve added these classroom management features because one of the key problems we’ve seen educators face over the past months has been the lack of an affordable tool to teach text-based coding in the classroom. We will always provide the Code Editor and all of its features to educators and students for free.
Safe and private by design
We take safeguarding seriously, providing visibility of student work at all times, as well as features such as the ability to report a concern. In line with best practices protecting children online, we minimise data capture so that we have just enough to keep students safe.
Future developments
As the platform is currently in beta, we’d love to hear what you think of the new classroom management features — please send us your feedback.
We’ll be actively looking to develop new features over the coming months. Such features are set to include an extended set of Python libraries,custom instructions that sit alongside starter code projects and teacher-to-student feedback capabilities. All new developments will be informed by ongoing educator feedback.
This little device includes a mechanical keyboard that, Michael says: was his primary motivation for making his retro marvel. Having first cut his teeth learning BASIC on a Sharp PC-1260, he quickly became a fan of portable computers and snapped up many more. But when, in recent years, he sought to revive his interest in such machines, he said he’s been left disappointed.
“I have tried Raspberry Pi and Linux-compatible portables and laptops but I’ve never been really satisfied with their keyboards,” he says, name-checking the Pocket C.H.I.P, Devterm and uConsole projects. “Even at work I used a mechanical keyboard with the company laptop so I started to search for smaller keyboards and portable Raspberry Pi projects. I then found ZeroWriter.”
Key to success
ZeroWriter is an open e-ink typewriter with a Raspberry Pi Zero 2 W board at its heart. Michael decided to create one for himself, and ordered the Vortex Core 40% keyboard while swapping out the WaveShare 4.2-inch e-paper display with a Waveshare five-inch monitor. “As there was still space, I added a speaker to the side,” he adds. “But the project was limited in terms of the Python audio effects development I wanted to pursue.”
Michael decided to take the project to another level, hence the use of Raspberry Pi 4. “With the experience of my first build, it was clear that I should go bigger and I also searched for another keyboard,” he says. Looking on pcbway.com, he found the Happy Keyboard, a 47-key, 40% ortholinear mechanical keyboard that uses a Raspberry Pi Pico development board running KMK firmware. It formed the basis of the design for the entire project.
“I started with the keyboard because it was the single largest part of the build,” he explains, adding that the next step was to find a display. “I searched for a screen with vertical resolution bigger than 400 or 480, and found a 9.3-inch display by Waveshare with a funky resolution of 1600×600 which fitted perfectly to the 40% keyboard.” This setup dictated the design of the project’s case, and it helped that every Waveshare screen comes with a CAD file and audio amplifier.
“It was all natural and fell into place because of the size of the components and the requirement that the keyboard should be as low as possible,” Michael says. “Somehow I loved the wide display more than a normal 16:9 display, so this may be the reason for the centred screen.”
A great case
Other design considerations needed to be considered. “It was clear in the beginning that the Raspberry Pi 4 and the battery would have to sit behind the keyboard,” Michael says, having decided to place them in a sizable rear compartment. The Raspberry Pi Pico development board also needed to be moved because there wasn’t sufficient room on the main keyboard PCB.
In extending the back section by up to two centimetres and increasing its height to match that of the screen and keyboard, Michael found space to fit audio speakers. He worked on ways of being able to use the USB ports, too, by creating insert panels on the back of the case for flexibility. “Instead of having to print an entire case, taking tens of hours, every time I decided I’d want to reconfigure the ports, I could just print new panels, which takes about an hour,” he explains.
Even so, there were other issues to contend with. Michael had trouble with the HDMI connection being on top of the screen. “I had to rotate it, and it took me some time to figure out how to flip the screen,” he says. “The display’s on-screen menu is still the wrong way around and this can’t be fixed, but I think that’s a Waveshare issue.”
The biggest headache, however, was power – the system draws juice from a pair of 21700 batteries connected to a UPS HAT. “I tried several battery boards but I was getting random reboots and other issues,” he says. “I then recognised that the cables I used to connect to the Raspberry Pi 4 computer were too thin. After I used better cables it worked fine. There were still some power warnings after two hours but it’s not bad.”
Powering up
Battery issues are why he decided against using a Raspberry Pi 5 board, for now at least. “If I could find a battery able to power it, I’d use Raspberry Pi 5,” he says. Michael also wants to be able to move the Raspberry Pi computer away from the side and make a side panel. “This would make it possible to use more single-board computers in the future, and help to connect the screen and keyboard to Raspberry Pi internally,” he says.
But he’s more than happy with the result so far and he says it’s a build that has fulfilled his requirements. “It’s also been a good way to learn FreeCAD which was fun most of the time – there was a lot of cursing before understanding, though.” He uses the device for programming and watching streams and finds it to be very convenient. “It’s easy to fetch and can be placed on the couch or kitchen table without taking up much room,” he says. And that, in a nutshell, is what a portable computer should be like.
Coolest Projects celebrates young digital creators and the amazing things they make with technology. Today, we’re sharing the impact that taking part in Coolest Projects showcases has on young people’s motivation and confidence, as well as announcing dates for Coolest Projects 2025.
Coolest Projects in 2024
This year, 7197 young people across 4678 projects took part in our global Coolest Projects online showcase, with participants from 43 countries. All of these projects were shared in our online showcase gallery, and we hosted a live-streamed event celebrating the judges’ favourites watched by over 1000 people.
At the 2024 in-person Coolest Projects events in Ireland and the UK, 192 young people shared 120 projects. At these events, the young creators presented their projects to other attendees and our team of judges. They also took part in other activities, including a digital escape room.
We wanted to understand how Coolest Projects impacts young people, and so we collected the following data:
For the online showcase, mentors and tech creators filled in a survey when they completed their project registration, and we ran focus groups with mentors, who are adults that support the tech creators
At the UK and Ireland in-person events, creators completed a survey, other event attendees completed feedback cards, and we also interviewed creators.
Online showcase: Impact on skills and confidence
In the survey, mentors and young people told us that taking part in the Coolest Projects online showcase had a positive impact:
91% of young people and 87% of mentors agreed or strongly agreed that taking part in Coolest Projects online inspired them or their team to continue to participate in computing and technology
89% of young people and 86% of mentors agreed or strongly agreed that taking part in Coolest Projects online increased their or their team’s confidence in coding and digital making
Mentors told us that the community built by the online showcase gallery played an important role in making young people want to participate, and improving their confidence. One mentor said that “[being part of the online showcase] motivates them actually to do something innovative and… [the] global community motivates them to think out of the box.”
They also reported that the online community inspired young people to solve real-world problems. One mentor said, “the wonderful thing is the kids create so many things which are solutions to world problems.” Others told us that young people feel a great deal of pride that their solutions are available for others to see online and that they get ideas from other projects on how to solve problems. One mentor from India told us about a young person who created a boat to clean rivers and then was inspired to learn to program micro:bit devices, having seen similar projects in the gallery.
Focus on ‘growth, not competition’
The phrase ‘growth, not competition’ came from the mentors in the focus group, and we love this description.
“[With] Coolest Projects… the only agenda is to grow. Grow with the coding, nurture your skills, creativity.” – Focus group attendee.
In he focus group, mentors told us they really valued the way the Coolest Projects online showcase allows all young people to participate, including those who were less experienced tech creators. One mentor told us that because everyone’s project is displayed in the gallery the “beauty is that everybody is encouraged individually… regarding the experience. … They can start with very small things. And they have [the] opportunity to upload it on the platform.”
One mentor who supports young people in remote locations in India spoke about the way Coolest Projects offers a level playing field where his students can be included and participate to the same extent as less remote places: “students never feel left behind.”
The in-person events also reflected the diversity of young people’s experience of digital making. Of those creators who answered surveys, 35% said it was their first time making this kind of project, while 37% said they had made similar projects before. This mix of experience was also reflected in the interviews, with some young people creating something for the first time and having only started learning coding recently, while others had been developing their projects for a long time. Many creators told us they felt inspired by the opportunity to show their projects to others, regardless of their experience level.
In-person events: Building a community of digital creators
Attendees at both Coolest Projects UK and Ireland commented on the sense of community and the excitement that was generated by being around other young people. One young person spoke about how much they enjoyed being “surrounded by people who like coding too”. They really valued seeing other creators’ projects and speaking with their peers.
The young people we spoke to reflected on the positive impact of this sense of community and belonging. They told us that seeing others’ projects inspired them to develop their ideas and learn new skills. One young person described how the in-person event allowed them to “get inspired and socialise.” A second said, “that’s why I’m here — to get inspired.”
Another clear theme was how much young people valued the opportunity to show their projects to others. This gave them confidence in their own ability to build things. One creator at Coolest Projects UK spoke about the sense of achievement they felt after building something themselves and then being able to present it to others.
Young people at both events spoke about their plans for what they wanted to do next, talking about trying new technology such as building games, learning Python, and creating mobile apps. At both events, creators described how they wanted to continue to develop and build on their existing ideas with the possibility of showcasing them again.
What we want to learn next
We are continuing to look for ways to improve the Coolest Projects experience for young people and their mentors. As part of this, we are conducting user experience research to understand how we can improve the registration process for the online Coolest Projects showcase.
We were delighted to hear from mentors in this year’s focus group how much they valued the online showcase gallery, and we want to understand the impact of this resource better as part of Coolest Projects 2025. If you want to find out more about Coolest Projects, we highly recommend taking a look at the amazing projects made by young people around the world.
Dates for Coolest Projects 2025
We’re so pleased that so many young people around the world loved taking part in Coolest Projects this year. And we’re very excited that Coolest Projects will be back and bigger than ever before in 2025!
The Coolest Projects online showcase is open to any young person up to age 18, based anywhere in the world. Registration opens 14 January, and we’ll host a celebratory livestream on 25 June.
Coolest Projects in-person events will also be popping up around the world. In-person events are open to everyone up to age 18 in the host country. Family and friends are very welcome to come along too.
Save the date for:
Coolest Projects Ireland, 1 March 2025
Coolest Projects USA, 5 April 2025
Coolest Projects Belgium, 20 April 2025
Coolest Projects UK, 17 May 2025
Coolest Projects Belgium, date to be confirmed (TBC)
Coolest Projects Ghana, date TBC
Coolest Projects India, date TBC
Coolest Projects Malaysia, date TBC
Coolest Projects South Africa, date TBC
Keep an eye on the Coolest Projects website for more event dates and details coming soon.
It’s never too early to start making and saving digital projects to showcase next year. We can’t wait to see what the world’s young tech creators will make!
You can buy the Plasma 2350 board on its own or in a Starter Kit (£34.50 / $38) with a USB-A to USB-C cable and 10m string of 66 individually addressable frosted LED stars. These look superb when lit up, and are a great way of showcasing the capabilities of the Plasma 2350. We also tried out a long 300-LED strip and there was easily enough current (up to 3A) from the USB-C power connection to light them all.
Wired for light
Connecting your LED string or strip to the board is simple. As on the Plasma 2040, there are four screw terminals on one end: for 5V power, data, clock, and ground. While WS2812/NeoPixel LED strips have only three wires, omitting the clock connection, the latter is needed for DotStar LEDs. A little care needs to be taken to make sure each wire is in the correct terminal and that they’re screwed securely.
Despite coming in a slimmer ‘gum stick’ form factor than the Plasma RP2040, the board manages to cram in many useful features. There’s an unpopulated header down one long edge to break out selected GPIO pins, offering access to UART and I2C interfaces, along with analogue inputs, PWM outputs, and PIO state machines. There’s also a Qwiic/STEMMA QT connector for breakout boards, as well as Pimoroni’s new proprietary SP/CE (Serial Peripheral / Connector Evolution) port – an eight-pin JST-PH connector including four pins for SPI.
Buttons for everything
One slight downside of the SP/CE’s inclusion is that there’s no room for a B user button next to the A one (as on the Plasma 2040), although the Boot button doubles as a user input. There’s also a handy Reset button, to save repeatedly disconnecting and connecting the USB-C power. An on-board RGB LED is a nice touch, too.
Before you can start programming some light patterns, you’ll need to install MicroPython. In its RP2350 GitHub repo, Pimoroni provides a custom UF2 file for the Plasma 2350. To install it, connect the board to your computer via USB while holding the Boot button, to mount it as a drive, then drag the file over to it. Alternatively, if you prefer CircuitPython, with which you can utilise Adafruit’s excellent LED Animation library, there’s also a UF2 image for that.
Using MicroPython in the Thonny IDE, we tried out some code examples from Pimoroni’s GitHub repo, altering the constant for the number of LEDs to match our string. While there are only a few examples there – including a nice ‘rainbow’ colour-cycling effect – we found that most of the ones for the Plasma 2040 and Plasma Stick 2040 W still work. Impressive lighting effects include alternating/random blinkies, sparkles, snowfall, fire, pulsing and a lovely rainbow sweeping across the string of LEDs.
Since the Plasma 2350 lacks on-board Wi-Fi, you can’t get your LEDs to react to data from the network, but you could always connect a breakout input such as a temperature sensor.
Verdict
9/10
An easy way to control NeoPixel/DotStar LED strings with programmable effects, with extra processing power if you need it.
Features
Features: RP2350A processor; Boot, Reset, and user buttons; on-board RGB LED
LED compatibility: 5V WS2812/NeoPixel, APA102/DotStar
Connections: 4 × screw terminals, USB-C port for power/programming, Qwiic/STEMMA QT, SP/CE, unpopulated 15-pin GPIO header
Across continents and cultural contexts, our free Computing Curriculum serves as a common thread that connects educators. Read the stories of 3 educators who share their thoughts on the curriculum’s application, adaptability, and the impact it’s had on their educational settings.
I’m Freda, and I co-founded a non-profit organisation called Waloyo in South Africa.
Coming from a background of technology consulting, I know the value of computing education. I have a real drive to teach young kids coding so they can get ahead and find jobs in our digital economy.
Our role at Waloyo is to work with non-profit organisations that work with young people and want to expand their services to include computing skills training. Waloyo trains non-profit facilitators, who in turn teach computing skills to youth between the ages of 6 and 18. A unique challenge is that the majority of facilitators we train don’t have any previous computing experience. The resources we use need to be clear and easy to follow.
What I really love about The Computing Curriculum resources is the facilitator guides.
Our initial plan was to run the training programmes after school and outside the school curriculum, but we were getting requests from schools to support them too. South Africa doesn’t have a national computing curriculum, so there aren’t many subject specialist teachers. So we looked for curriculum resources from other countries to support our work and that’s how we found The Computing Curriculum.
In rural Africa where we work, students have low levels of exposure to computers and computing. So whether they are 6 or 18 years old, we usually start with Scratch. The younger kids then continue with Scratch and the older kids move quickly on to Python as they build confidence.
What I really love about The Computing Curriculum resources is the facilitator guides. They fit in well with our process of training NGO facilitators to work directly with the kids. I love the comprehensiveness and flexibility of what your curriculum provides to enable this method of delivery.
So far we’ve launched 3 programmes in communities in South Africa, impacting around 150 young people, and it’s worked beautifully. It’s phenomenal to see how excited the kids get when the computer does what they want it to do!
I’m Al, and I’ve been a secondary science teacher since 1991.
For the past 13 years, I’ve taught in international schools. Two years ago, I decided to retrain in teaching computing. My wife and I are currently teaching in Kazakhstan. I now teach at primary level but still handle some secondary classes. For primary, there’s significant time pressure, especially with extra lessons for the local language, making it challenging to fit computing into the schedule.
The private schools where I work are starting to implement the UK computer science curriculum. At one of the schools, they have a robotics course which has given rise to a misconception that everything in computing is about robotics! My role, therefore, involves expanding the concept of robotics to include a broader range of computing activities and finding efficient ways to integrate these new materials into the curriculum with minimal effort from the staff. I focus on selecting appropriate units to fit into what the schools are already doing rather than implementing a comprehensive new program.
The Raspberry Pi Foundation’s curriculum resources are valuable because they provide comprehensive lists of programs and ideas that I can adapt for my colleagues. I adapt resources to make them more accessible for primary teachers, simplifying and customising them for ease of use.
The Raspberry Pi Foundation’s curriculum resources are valuable because they provide comprehensive lists of programs and ideas that I can adapt for my colleagues.
Once students understand that computing is a tool for developing skills rather than just passive consumption, they take ownership of their learning which boosts their confidence. Culturally relevant materials are particularly effective, especially in diverse international classrooms. Adapting resources to be culturally relevant and incorporating students’ examples enhances their usefulness and impact. The resources are excellent, but by tailoring them, they can be even more effective, particularly in an international context with diverse nationalities and learning concepts.
Head of ICT at an international school in Egypt
As Head of Department, I am responsible for what all the different age groups learn, from year 1 to year 12. We use the Cambridge International (CIE) curriculum, so I was looking for supplementary resources that build from the basics, have a clear progression map, and complement the resources we already had.
With The Computing Curriculum, it is easy to pick out individual lesson resources to use. I love that it doesn’t need a licence and that the students don’t face any problems when they download it to practise at home. I’m covering curriculums for both computing and digital literacy, so I use resources that are relevant to my curriculum maps.
With The Computing Curriculum, it is easy to pick out individual lesson resources to use.
In some schools, their idea of an ICT lesson is getting students to play games, use Word documents, make PowerPoint presentations, and that’s it. But this generation of students love coding and making their own games. So instead of playing the game, we teach them how to develop a game and how to add the characters themselves.
From year 1 to year 2, students take part in a wide range of computing activities and develop a lot of new skills. They find these skills amazing. It makes them feel engaged, excited, and that they are doing something valuable.
Using The Computing Curriculum
These educators’ stories show how easy it is to adapt our Computing Curriculum to your unique context, enhancing students’ technical skills and inspiring creativity, critical thinking, and a passion for problem-solving. We look forward to continuing this journey with these and other educators as they transform computing education for their learners.
KG revisits the classics from gaming horror’s great 1990s golden age this month. Spattered with gore, and overcome by a desperate urge to prove that computer games weren’t just for families. Discover how to hook up a modern Blu-ray drive to Raspberry Pi 5 and play Halloween classics like Alone in the Dark, Phantasmagoria, and Viel of Darkness.
10 amazing Halloween projects
Get spooky this October with Rob’s malign makes. This month you’ll unearth a Doll of Doom, remote-controlled Saw dolls, possessed portraits, animated pumpkins, and much more. Take your haunted house up to another level with these devilishly good makes.
Real-time ML audio noise suppression
Arm’s Sandeep Mistry has used machine learning on Pico 2 to create a noise-cancelling audio device. This detailed tutorial explains how machine learning technology can be rained and deployed on Pico 2.
Bringing Junked Joysticks back to life
HackSpace’s David Miles has brought a heavy pair of flight joysticks and brought them back to life with Raspberry Pi Pico. These look like they belonged originally in a professional flight simulator, and have been reverse-engineered into fully-fledged flight simulator controllers that are recognised as USB joysticks.
Incredible Projects
This month’s magazine is packed with projects to discover and build, coding and making techniques to explore and learn, and the very best of the Raspberry Pi community. Pick up a copy in-store today [you can’t miss it; we splashed out on some fluorescent orange paint for the cover – Ed] or get a copy from The Raspberry Pi Press online store.
We love Raspberry Pi robots, and Raspberry Pi Pico has become a fantastic addition to the world of hobby robotics. With the release of Pico 2 and RP2350, their ability to pilot automatons has only grown. Scroll down below to win one of the brand new robotics controllers that makes use of RP2350, the MOTION 2350 Pro
Today we’re unveiling a fresh look and feel for Code Club, along with a new ambition to inspire 10 million more young people to get creative with technology over the next decade.
Code Club is a network of free coding clubs where young people learn how to create with technology. Founded in the UK in 2012, it has grown to be a global movement that has already inspired more than 2 million young people to learn how to build their own apps, games, animations, websites, and so much more.
We know that Code Club works. Independent evaluations have demonstrated that attending a Code Club helps young people develop their programming skills as well as wider life skills like confidence, resilience, and skills in problem-solving and communication. This impact is a result of the positive learning environment created by the teachers and volunteers that run Code Clubs, with young people enjoying the activities and developing skills independently and collaboratively — including young people who sometimes struggle in a formal classroom setting.
Just as important, we know that Code Clubs inspire young people from all backgrounds, including girls and young people from communities that are underrepresented in the technology sector.
What’s changing and why
While we are incredibly proud of the impact that Code Club has already achieved, we want to see many more young people benefiting, and that led us to set the ambitious goal to reach 10 million more young people over the next decade.
To help us figure out how to reach that ambition, we spent a lot of time this year listening to the community as well as engaging with parents, teachers, and young people who aren’t yet involved in Code Club. All of the changes we’ve made have been informed by those conversations and are designed to make it easier for educators and volunteers all over the world to set up and run Code Clubs.
The biggest change is that we are making Code Club a more flexible model that can be adapted to reflect your local context and culture to ensure that it is as meaningful as possible for the young people in your community.
That means you can host a Code Club in a school or a community venue, like a library or makerspace; you can choose the age range and rhythm of meetings that make sense for your setting; and you can tailor the activities that you offer to the interests and skills of the young people you are serving. In order for the movement to be as inclusive as possible, you don’t even need to be called ‘Code Club’ to be an ‘Official Raspberry Pi Foundation Code Club’ and benefit from all the support we offer.
To support this change, we have developed a Code Club Charter that we ask all club leaders and mentors to sign up to. This sets out the principles that are shared by all Code Clubs, along with the commitments that the Raspberry Pi Foundation is making about our support to you.
We have launched a new website that makes it easier for you to find the information you need to set up and run your Code Club, along with an updated and simplified club leader guide. In a few weeks time, we are launching a new online course with guidance on how to run a successful club, and we will be adding to our programme of online community calls, webinars, and training to support a growing community of club leaders and mentors.
One of the most important parts of our support for Code Clubs is the projects that help young people learn how to bring their ideas to life using a wide range of hardware and software. As they are created by experienced educators, based on research, rigorously tested, and translated into dozens of languages, you can have confidence that these projects lead to meaningful and lasting learning outcomes for the young people attending your club. Code Club projects enable young people to learn independently, meaning that mentors don’t need technical skills.
What this means for CoderDojos
Alongside Code Club, the Foundation supports CoderDojo, a network of coding clubs that started life in Cork, Ireland in 2011 and merged with the Raspberry Pi Foundation in 2017.
In order to reduce duplication and make it easier for anyone to set up and run a coding club, we have decided to bring together the resources and support for all club leaders and mentors under one website, which is the new Code Club website.
There is no need for existing CoderDojos to change their name or anything about the way they operate. All registered CoderDojos will be able to manage their club in exactly the same way through the new website, and to access all of the support and resources that we offer to all coding clubs. New clubs will be able to register as CoderDojos.
The ethos, experiences, and lessons from the CoderDojo community have been a vital part of the development of the new Code Club. We have worked hard to make sure that all existing CoderDojos feel that their values are reflected in the Charter, and that the guidance and resources we offer address their circumstances.
CoderDojos will very much remain part of this community, and the Raspberry Pi Foundation will continue to celebrate and learn from the amazing work of CoderDojos all over the world.
Code Club in the age of artificial intelligence
With AI already transforming so many parts of our lives, it’s not surprising that some people are starting to ask whether young people even need to learn to code anymore.
We’ve got a lot to say on this subject — so watch this space — but the short version is that learning how to create with technology has never been more important. The way that humans give instructions to computers is changing, and Code Club provides a way for young people to experiment with new technologies like AI in a safe environment. Over the next couple of weeks, we’ll be launching new Code Club projects that support young people to learn about AI technologies, including generative AI, and we’ll be providing support for club leaders and mentors on the topic too.
Thank you and get involved
I want to end by saying a huge thank you to everyone who has been part of the Code Club journey so far, and particularly to everyone who has worked so hard on this project over the past year — far too many people to name here, but you know who you are. I also want to thank all of the parents, teachers, mentors, and partners who have provided the feedback and ideas that have shaped these changes.
Code Club and CoderDojo were both founded in the early 2010s by individuals who wanted to give more young people the opportunity to be digital creators, not just consumers. From that first Dojo in Cork, Ireland, and the first Code Clubs in London, UK, we’ve built a global movement that has empowered millions of young people to engage confidently with a world that is being transformed by digital technologies.
It’s never been a better time to get involved with Code Club, so please take a look and get in touch if you need any help or support to get started.
Since they became publicly available at the end of 2022, generative AI tools have been hotly discussed by educators: what role should these tools for generating human-seeming text, images, and other media play in teaching and learning?
Two years later, the one thing most people agree on is that, like it or not, generative AI is here to stay. And as a computing educator, you probably have your learners and colleagues looking to you for guidance about this technology. We’re sharing how educators like you are approaching generative AI in issue 25 of Hello World, out today for free.
Generative AI and teaching
Since our ‘Teaching and AI’ issue a year ago, educators have been making strides grappling with generative AI’s place in their classroom, and with the potential risks to young people. In this issue, you’ll hear from a wide range of educators who are approaching this technology in different ways.
For example:
Laura Ventura from Gwinnett County Public Schools (GCPS) in Georgia, USA shares how the GCPS team has integrated AI throughout their K–12 curriculum
Mark Calleja from our team guides you through using the OCEAN prompt process to reliably get the results you want from an LLM
Kip Glazer, principal at Mountain View High School in California, USA shares a framework for AI implementation aimed at school leaders
Stefan Seegerer, a researcher and educator in Germany, discusses why unplugged activities help us focus on what’s really important in teaching about AI
This issue also includes practical solutions to problems that are unique to computer science educators:
Graham Hastings in the UK shares his solution to tricky crocodile clips when working with micro:bits
Riyad Dhuny shares his case study of home-hosting a learning management system with his students in Mauritius
And there is lots more for you to discover in issue 25.
Whether or not you use generative AI as part of your teaching practice, it’s important for you to be aware of AI technologies and how your young people may be interacting with it. In his article “A problem-first approach to the development of AI systems”, Ben Garside from our team affirms that:
“A big part of our job as educators is to help young people navigate the changing world and prepare them for their futures, and education has an essential role to play in helping people understand AI technologies so that they can avoid the dangers.
Our approach at the Raspberry Pi Foundation is not to focus purely on the threats and dangers, but to teach young people to be critical users of technologies and not passive consumers. […]
Our call to action to educators, carers, and parents is to have conversations with your young people about generative AI. Get to know their opinions on it and how they view its role in their lives, and help them to become critical thinkers when interacting with technology.”
Share your thoughts & subscribe to Hello World
Computing teachers are being asked again to teach something that they didn’t study. With generative AI as with all things computing, we want to support your teaching and share your successes. We hope you enjoy this issue of Hello World, and please get in touch with your article ideas or what you would like to see in the magazine.
We’d like to thank Oracle for supporting this issue.
Signing up for Tindie is pretty trivial. You need a basic account to be able to buy from Tindie, and every account has all the options to start selling. Your need to give your store a name, then set up a verified PayPal account, and then you are ready to list your first product. A couple of things to note about Tindie is that you must have an image of your actual product on the product page, you can’t have a render of a product that you will make if you get an order. Neither can you list a product that you plan to make, so you can’t use Tindie to act as a pre-order system.
Listing a product is pretty straightforward: you fill in some details about the product, then supply links to any documentation and any source files you are sharing. Brilliantly, Tindie is also set up to promote open-source hardware projects well, so there are dialogue options to add OSHWA certification numbers, see Figure 1. You can add multiple images and also links to videos which automatically embed in the bottom of the project page. Save your product listing as a draft, and you can preview the page and check your work; it’s very similar to creating a blog post. When you are ready to launch the product you submit the product for approval and the Tindie team will take a look before setting it live on the site.
When someone orders your product you get a notification in your store menu and an email to your registered email address. You have two weeks from the time of order to ship the item and mark it as such. If you don’t ship it in that time then Tindie will refund the buyer and cancel the order. On Tindie you can add shipping options for different regions and services and then assign them to different products. This makes for a very flexible system. For example, many of my products can ship within the UK as a large letter weighing under 100 grams so can set up that postal option and then assign it to numerous products as in Figure 2.
Each shipping option has an “additional item cost,” so you can add an extra charge for additional packaging. You can use this functionality to push a postage option into a different service, so for example if someone buys one item they pay for a 100g large letter, but the additional item costs mean that if they buy three items which would weigh over 100g then the additional item cost has raised the postage price so that it covers the 250g large letter option. It takes a little thinking about, and trial and error, but it becomes pretty straightforward after a few sales. I tend to use tracked services so that items are insured and that delivery to the person is somewhat guaranteed; this perhaps loses me some sales as my shipping rates are higher, but keeps the stress levels lower! The majority of my sales are to the UK or the US but occasionally I will get a notification that someone has requested a shipping option for a product to a new region. This doesn’t guarantee a sale, but you can research shipping options to the destination and set up an option in response and the potential customer will be notified.
Yet another consideration around postage, which may be a little less obvious, is packaging and the storage of packaging. Often this can be tricky and you may well need to allocate more space than you need to store your product packaging. Many of the products I sell are small electronics, and as such the actual kit is packed into small anti-static packaging which can be shipped in a very small padded envelope. Some of the larger products require a bigger envelope, and sometimes products require a range of padded mailer envelopes to accommodate the range of options.
As an example I can send a basic PCB and header kit of the StoRPer robot PCB in a size 000 small padded mailer, but if I need to add 3D-printed motor mounts and a laser cut ‘deck’ as add-on options then I often need to jump to a larger envelope. If I packed the items in the smaller mailer it becomes too wide for the ‘large letter’ service, see Figure 3. It also makes sense to bulk buy your shipping packaging, and for my range of products this means the shipping packaging takes up at least as much storage space as the actual stock items, as in Figure 4.
StoRPer: Genesis Within the stock subject there are a couple of things worth considering. The first is how much stock are you capable of making and storing. I live in a pretty small and packed old Welsh mining cottage and I have physical limitations on how much space I can give to stock. When I first started and just had some of the early products like my rocketry screw switches and centre of pressure and gravity stickers, everything could fit in a shoe box. As I added products and product options this has grown somewhat. Stock storage and also stock value have affected how products and designs are sold. An example of mine is the Laser Cut Fin Jig Short Kit. The Fin Jig product is a tool that once assembled allows rocket builders to position fins onto rocket body tubes incredibly accurately. Getting fins on straight and vertical and well aligned is a key concept in getting a rocket to perform well. The jig has numerous laser cut parts and also quite a bit of metalwork in the form of longish 90° angle aluminium sections and 5mm threaded rod sections plus lots of nuts and bolts. A full kit with all the metalwork included would be heavy and costly to post, and would require me to stock and warehouse lots of long metal sections. The threaded rods and angle sections are the type of thing that can be found in most parts of the world but perhaps not everyone has access to a laser cutter. The solution therefore was the ‘short kit’ in Figure 5, which just offers the laser-cut MDF parts from which you can build the whole tool. I am sure this approach has lost me some customers, but it means that I can at least do something with the design and it has become a reasonably well sold item. I can keep around a year’s worth of stock in a shoe box and the postage is pretty affordable.
Aside from developing an item to the point you feel confident it is a quality product, documentation is a key bit of work that you need to do. Documentation has a couple of roles in a maker business. First and foremost it needs to explain the product and give the technical information that a customer might need. It also though is crucial in terms of making a sale. If there are parts of a product that seem unclear and unexplained and the potential customer can’t find an answer quickly then it is much less likely they will purchase the product. The level of documentation a product needs is hugely variable. For example I haven’t felt the need to document things like my centre of pressure and centre of gravity stickers, but the recently launched HEXA model rocket kit has a 14-page PDF about the assembly of the kit and usage, as in Figure 6.
One thing I have noticed is that you need to repeatedly make content about items that you sell to keep bringing them to the attention of potential customers. I am not particularly good at this, as I tend to really immerse myself in creating projects and products and then move on to the next idea. The people who excel at building business in this sector are those who can create content that regularly shows new features or applications of products. Wonderfully, sometimes people talk about their build of your product online, and this can serve to generate interest in your designs. This is one reason why considering open-source approaches may help, as others may be more inclined to use your project and share it.
In the Night market
While this article has predominantly looked at Tindie and online sales, you can of course find places and events where you can sell directly to customers. If your products are less specific than mine and appeal to a general population then, of course, craft fairs and markets are a great potential source of sales. I recently applied for and was allocated space at EMF Camp’s excellent solar-punk themed night market in the Null Sector area of the festival. Even at a festival full of hacker types it’s unlikely I would do that well selling niche high-power rocketry parts, so I opted to just take StoRPer, my modular, open-source, Raspberry Pi Pico-powered robot platform. Getting into the theme, I even modified a vintage travel case to contain stock, be branded and lit: it’s in Figure 7.
I felt it was important to have a few examples of the robot built up, and you have to be prepared to talk a lot about your product and the design choices you have made. You also need to work out how you can receive money from sales – a small amount of customers will carry and use cash, but it’s far more common for people to use contactless payment. There are a few contactless reader options available for small businesses and it’s worth looking around them all. You may even find that you can manage contactless payments using a smartphone. I opted for a common solution from Sumup, where I bought a Sumup Air card reader for £40 as a one-off expense.
Sumup, and other similar services, set you up with an account and charge a small transaction fee. Contactless payments are first transferred into the Sumup account and you can then transfer the money out to whatever bank account you prefer. The card reader device connects to the Sumup application on my phone via Bluetooth, and you can quickly set up a charge/transaction in-app. This works excellently. As a side note, if you have less than perfect data coverage or Wi-Fi at an event it isn’t totally critical, so long as the contactless transaction has completed it will be logged in the application and everything will pass through when connectivity is re-established. Similarly, this means that, perhaps with the help of a USB powerbank, you can be totally off-grid!
I hope this article has inspired you to have a go at selling some of your creations. It can be challenging but also rewarding, sometimes financially, but often it’s the fact that people enjoy using your designs and product that really motivates you to make and sell more. It’s also a great way to connect and communicate with like-minded makers who are interested in similar projects to yourself.
To empower every educator to confidently bring AI into their classroom, we’ve created a new online training course called ‘Understanding AI for educators’ in collaboration with Google DeepMind. By taking this course, you will gain a practical understanding of the crossover between AI tools and education. The course includes a conceptual look at what AI is, how AI systems are built, different approaches to problem-solving with AI, and how to use current AI tools effectively and ethically.
In this post, I will share our approach to designing the course and some of the key considerations behind it — all of which you can apply today to teach your learners about AI systems.
Design decisions: Nurturing knowledge and confidence
We know educators have different levels of confidence with AI tools — we designed this course to help create a level playing field. Our goal is to uplift every educator, regardless of their prior experience, to a point where they feel comfortable discussing AI in the classroom.
AI literacy is key to understanding the implications and opportunities of AI in education. The course provides educators with a solid conceptual foundation, enabling them to ask the right questions and form their own perspectives.
As with all our AI learning materials that are part of Experience AI, we’ve used specific design principles for the course:
Choosing language carefully: We never anthropomorphise AI systems, replacing phrases like “The model understands” with “The model analyses”. We do this to make it clear that AI is just a computer system, not a sentient being with thoughts or feelings.
Accurate terminology: We avoid using AI as a singular noun, opting instead for the more accurate ‘AI tool’ when talking about applications or ‘AI system’ when talking about underlying component parts.
Ethics: The social and ethical impacts of AI are not an afterthought but highlighted throughout the learning materials.
Three main takeaways
The course offers three main takeaways any educator can apply to their teaching about AI systems.
1. Communicating effectively about AI systems
Deciding the level of detail to use when talking about AI systems can be difficult — especially if you’re not very confident about the topic. The SEAME framework offers a solution by breaking down AI into 4 levels: social and ethical, application, model, and engine. Educators can focus on the level most relevant to their lessons and also use the framework as a useful structure for classroom discussions.
You might discuss the impact a particular AI system is having on society, without the need to explain to your learners how the model itself has been trained or tested. Equally, you might focus on a specific machine learning model to look at where the data used to create it came from and consider the effect the data source has on the output.
2. Problem-solving approaches: Predictive vs. generative AI
AI applications can be broadly separated into two categories: predictive and generative. These two types of AI model represent two vastly different approaches to problem-solving.
People create predictive AI models to make predictions about the future. For example, you might create a model to make weather forecasts based on previously recorded weather data, or to recommend new movies to you based on your previous viewing history. In developing predictive AI models, the problem is defined first — then a specific dataset is assembled to help solve it. Therefore, each predictive AI model usually is only useful for a small number of applications.
Rick Payne and team / Better Images of AI / Ai is… Banner / CC-BY 4.0
Generative AI models are used to generate media (such as text, code, images, or audio). The possible applications of these models are much more varied because people can use media in many different kinds of ways. You might say that the outputs of generative AI models could be used to solve — or at least to partially solve — any number of problems, without these problems needing to be defined before the model is created.
3. Using generative AI tools: The OCEAN process
Generative AI systems rely on user prompts to generate outputs. The OCEAN process, outlined in the course, offers a simple yet powerful framework for prompting AI tools like Gemini, Stable Diffusion or ChatGPT.
Yasmine Boudiaf & LOTI / Better Images of AI / Data Processing / CC-BY 4.0
The first three steps of the process help you write better prompts that will result in an output that is as close as possible to what you are looking for, while the last two steps outline how to improve the output:
Objective: Clearly state what you want the model to generate
Context: Provide necessary background information
Examples: Offer specific examples to fine-tune the model’s output
Assess: Evaluate the output
Negotiate: Refine the prompt to correct any errors in the output
The final step in using any generative AI tool should be to closely review or edit the output yourself. These tools will very quickly get you started but you’ll always have to rely on your own human effort to ensure the quality of your work.
Helping educators to be critical users
We believe the knowledge and skills our ‘Understanding AI for educators’ course teaches will help any educator determine the right AI tools and concepts to bring into their classroom, regardless of their specialisation. Here’s what one course participant had to say:
“From my inexperienced viewpoint, I kind of viewed AI as a cheat code. I believed that AI in the classroom could possibly be a real detriment to students and eliminate critical thinking skills.
After learning more about AI [on the course] and getting some hands-on experience with it, my viewpoint has certainly taken a 180-degree turn. AI definitely belongs in schools and in the workplace. It will take time to properly integrate it and know how to ethically use it. Our role as educators is to stay ahead of this trend as opposed to denying AI’s benefits and falling behind.” – ‘Understanding AI for educators’ course participant
All our Experience AI resources — including this online course and the teaching materials — are designed to foster a generation of AI-literate educators who can confidently and ethically guide their students in navigating the world of AI.
You can sign up to the course for free here:
A version of this article also appears in Hello World issue 25, which will be published on Monday 23 September and will focus on all things generative AI and education.
As discussions of how artificial intelligence (AI) will impact teaching, learning, and assessment proliferate, I was thrilled to be able to add one of my own research projects to the mix. As a research scientist at the Raspberry Pi Foundation, I’ve been working on a pilot research study in collaboration with Jane Waite to explore the topic of program error messages (PEMs).
PEMs can be a significant barrier to learning for novice coders, as they are often confusing and difficult to understand. This can hinder troubleshooting and progress in coding, and lead to frustration.
Recently, various teams have been exploring how generative AI, specifically large language models (LLMs), can be used to help learners understand PEMs. My research in this area specifically explores secondary teachers’ views of the explanations of PEMs generated by a LLM, as an aid for learning and teaching programming, and I presented some of my results in our ongoing seminar series.
Understanding program error messages is hard at the start
I started the seminar by setting the scene and describing the current background of research on novices’ difficulty in using PEMs to fix their code, and the efforts made to date to improve these. The three main points I made were that:
PEMs are often difficult to decipher, especially by novices, and there’s a whole research area dedicated to identifying ways to improve them.
Recent studies have employed LLMs as a way of enhancing PEMs. However, the evidence on what makes an ‘effective’ PEM for learning is limited, variable, and contradictory.
There is limited research in the context of K–12 programming education, as well as research conducted in collaboration with teachers to better understand the practical and pedagogical implications of integrating LLMs into the classroom more generally.
My pilot study aims to fill this gap directly, by reporting K–12 teachers’ views of the potential use of LLM-generated explanations of PEMs in the classroom, and how their views fit into the wider theoretical paradigm of feedback literacy.
What did the teachers say?
To conduct the study, I interviewed eight expert secondary computing educators. The interviews were semi-structured activity-based interviews, where the educators got to experiment with a prototype version of the Foundation’s publicly available Code Editor. This version of the Code Editor was adapted to generate LLM explanations when the question mark next to the standard error message is clicked (see Figure 1 for an example of a LLM-generated explanation). The Code Editor version called the OpenAI GPT-3.5 interface to generate explanations based on the following prompt: “You are a teacher talking to a 12-year-old child. Explain the error {error} in the following Python code: {code}”.
Figure 1: The Foundation’s Code Editor with LLM feedback prototype.
Fifteen themes were derived from the educators’ responses and these were split into five groups (Figure 2). Overall, the educators’ views of the LLM feedback were that, for the most part, a sensible explanation of the error messages was produced. However, all educators experienced at least one example of invalid content (LLM “hallucination”). Also, despite not being explicitly requested in the LLM prompt, a possible code solution was always included in the explanation.
Figure 2: Themes and groups derived from teachers’ responses.
Matching the themes to PEM guidelines
Next, I investigated how the teachers’ views correlated to the research conducted to date on enhanced PEMs. I used the guidelines proposed by Brett Becker and colleagues, which consolidate a lot of the research done in this area into ten design guidelines. The guidelines offer best practices on how to enhance PEMs based on cognitive science and educational theory empirical research. For example, they outline that enhanced PEMs should provide scaffolding for the user, increase readability, reduce cognitive load, use a positive tone, and provide context to the error.
Out of the 15 themes identified in my study, 10 of these correlated closely to the guidelines. However, the 10 themes that correlated well were, for the most part, the themes related to the content of the explanations, presentation, and validity (Figure 3). On the other hand, the themes concerning the teaching and learning process did not fit as well to the guidelines.
Figure 3: Correlation between teachers’ responses and enhanced PEM design guidelines.
Does feedback literacy theory fit better?
However, when I looked at feedback literacy theory, I was able to correlate all fifteen themes — the theory fits.
Feedback literacy theory positions the feedback process (which includes explanations) as a social interaction, and accounts for the actors involved in the interaction — the student and the teacher — as well as the relationships between the student, the teacher, and the feedback. We can explain feedback literacy theory using three constructs: feedback types, student feedback literacy, and teacher feedback literacy (Figure 4).
Figure 4: Feedback literacy at the intersection between feedback types, student feedback literacy, and teacher feedback literacy.
From the feedback literacy perspective, feedback can be grouped into four types: telling, guiding, developing understanding, and opening up new perspectives. The feedback type depends on the role of the student and teacher when engaging with the feedback (Figure 5).
From the student perspective, the competencies and dispositions students need in order to use feedback effectively can be stated as: appreciating the feedback processes, making judgements, taking action, and managing affect. Finally, from a teacher perspective, teachers apply their feedback literacy skills across three dimensions: design, relational, and pragmatic.
In short, according to feedback literacy theory, effective feedback processes entail well-designed feedback with a clear pedagogical purpose, as well as the competencies students and teachers need in order to make sense of the feedback and use it effectively.
This theory therefore provided a promising lens for analysing the educators’ perspectives in my study. When the educators’ views were correlated to feedback literacy theory, I found that:
Educators prefer the LLM explanations to fulfil a guiding and developing understanding role, rather than telling. For example, educators prefer to either remove or delay the code solution from the explanation, and they like the explanations to include keywords based on concepts they are teaching in the classroom to guide and develop students’ understanding rather than tell.
Related to students’ feedback literacy, educators talked about the ways in which the LLM explanations help or hinder students to make judgements and action the feedback in the explanations. For example, they talked about how detailed, jargon-free explanations can help students make judgments about the feedback, but invalid explanations can hinder this process. Therefore, teachers talked about the need for ways to manage such invalid instances. However, for the most part, the educators didn’t talk about eradicating them altogether. They talked about ways of flagging them, using them as counter-examples, and having visibility of them to be able to address them with students.
Finally, from a teacher feedback literacy perspective, educators discussed the need for professional development to manage feedback processes inclusive of LLM feedback (design) and address issues resulting from reduced opportunities to interact with students (relational and pragmatic). For example, if using LLM explanations results in a reduction in the time teachers spend helping students debug syntax errors from a pragmatic time-saving perspective, then what does that mean for the relationship they have with their students?
Conclusion from the study
By correlating educators’ views to feedback literacy theory as well as enhanced PEM guidelines, we can take a broader perspective on how LLMs might not only shape the content of the explanations, but the whole social interaction around giving and receiving feedback. Investigating ways of supporting students and teachers to practise their feedback literacy skills matters just as much, if not more, than focusing on the content of PEM explanations.
This study was a first-step exploration of eight educators’ views on the potential impact of using LLM explanations of PEMs in the classroom. Exactly what the findings of this study mean for classroom practice remains to be investigated, and we also need to examine students’ views on the feedback and its impact on their journey of learning to program.
If you want to hear more, you can watch my seminar:
If any of these ideas resonated with you as an educator, student, or researcher, do reach out — we’d love to hear from you. You can contact me directly at veronica.cucuiat@raspberrypi.org or drop us a line in the comments below.
Join our next seminar
The focus of our ongoing seminar series is on teaching programming with or without AI. Check out the schedule of our upcoming seminars.
To take part in the next seminar, click the button below to sign up, and we will send you information about how to join. We hope to see you there.
The Poetry Camera began life as an ‘AI classifier’ and was partly inspired by Kelin’s friend Susi Fu’s Artist and Machine performances examining how artists and computers can learn from each other. “Susie would draw sketches of the person standing in front of her, while a machine – using Raspberry Pi – printed out AI-drawn sketches of the same subject.”
An MIT computer science graduate turned digital product designer, Kelin took charge of the Raspberry Pi prototyping, learning how to solder, plus some basic electronics, while designing her first PCB (a HAT for Raspberry Pi). The initial cardboard design took only a few days to complete.
Industrial designer Ryan, meanwhile, has worked as a toy designer and in a creative technologist-type design role at Google where he learned “Javascript and a bit of Python,” and was introduced to Raspberry Pi for prototyping, which he’d “definitely recommend” for anyone who wants to build hardware prototypes that need a logic layer.
He was “ecstatic to create something from scratch, and prototype it on his home 3D printer”. Having started out as pen and paper sketches, Poetry Camera’s form was created and iterated on in Rhino.
Power play
As “the brain of the whole device,” Raspberry Pi Zero 2 W connects to a Camera Module 3 and a thermal printer via UART. It calls on remote AI models via an API for pointers on poem writing. The idea was that they’d get faster responses this way, but this approach necessitates connecting to Wi-Fi hotspots, which could be challenging depending on where they took Poetry Camera out and about. “In ideal conditions, it works like a well-oiled machine but Wi-Fi networks can be very spotty, especially at crowded events where there’s a lot of signal interference”. Six AA batteries keep everything powered (the thermal printer can drain batteries fast) with a buck converter to step down the voltage for Raspberry Pi. Kelin and Ryan chose Raspberry Pi for its wireless connectivity and the volume of tutorials on how to interface with cameras and thermal printers, starting with Raspberry Pi 3B+ before switching to Zero 2 W “since it hits a sweet spot in terms of small size and fast processing power”. They made use of Adafruit’s Python Thermal Printer library and found ChatGPT “very well versed” – pun hopefully intended – for creating code. “We were able to ask a question in our own naive way and get a custom tailored response that often works right out of the box, instantly.”
The pair are constantly tweaking and updating Poetry Camera. It’s already on version 4, and its creators have been delighted by how well it’s been received. “In the future, we’re looking forward to letting people customise their cameras’ outputs – by updating the poem prompts, or adding images, or using their own servers.”
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