Kategorie: Linux

  • Integrating generative AI into introductory programming classes

    Integrating generative AI into introductory programming classes

    Reading Time: 6 minutes

    Generative AI (GenAI) tools like GitHub Copilot and ChatGPT are rapidly changing how programming is taught and learnt. These tools can solve assignments with remarkable accuracy. GPT-4, for example, scored an impressive 99.5% on an undergraduate computer science exam, compared to Codex’s 78% just two years earlier. With such capabilities, researchers are shifting from asking, “Should we teach with AI?” to “How do we teach with AI?”

    Photo of Leo Porter (UC San Diego)
    Leo Porter from UC San Diego
    Photo of Daniel Zingaro (University of Toronto)
    Daniel Zingaro from the University of Toronto

    Leo Porter and Daniel Zingaro have spearheaded this transformation through their groundbreaking undergraduate programming course. Their innovative curriculum integrates GenAI tools to help students tackle complex programming tasks while developing critical thinking and problem-solving skills.

    Leo and Daniel presented their work at the Raspberry Pi Foundation research seminar in December 2024. During the seminar, it became clear that much could be learnt from their work, with their insights having particular relevance for teachers in secondary education thinking about using GenAI in their programming classes

    Practical applications in the classroom

    In 2023, Leo and Daniel introduced GitHub Copilot in their introductory programming  CS1-LLM course at UC San Diego with 550 students. The course included creative, open-ended projects that allowed students to explore their interests while applying the skills they’d learnt. The projects covered the following areas:

    • Data science: Students used Kaggle datasets to explore questions related to their fields of study — for example, neuroscience majors analysed stroke data. The projects encouraged interdisciplinary thinking and practical applications of programming.
    • Image manipulation: Students worked with the Python Imaging Library (PIL) to create collages and apply filters to images, showcasing their creativity and technical skills.
    • Game development: A project focused on designing text-based games encouraged students to break down problems into manageable components while using AI tools to generate and debug code.

    Students consistently reported that these projects were not only enjoyable but also responsible for deepening their understanding of programming concepts. A majority (74%) found the projects helpful or extremely helpful for their learning. One student noted that.

    Programming projects were fun and the amount of freedom that was given added to that. The projects also helped me understand how to put everything that we have learned so far into a project that I could be proud of.

    Core skills for programming with Generative AI

    Leo and Daniel emphasised that teaching programming with GenAI involves fostering a mix of traditional and AI-specific skills.

    Infographic highlighting a workflow when writing software with Copilot.
    Writing software with GenAI applications, such as Copilot, needs to be approached differently to traditional programming tasks

    Their approach centres on six core competencies:

    • Prompting and function design: Students learn to articulate precise prompts for AI tools, honing their ability to describe a function’s purpose, inputs, and outputs, for instance. This clarity improves the output from the AI tool and reinforces students’ understanding of task requirements.
    • Code reading and selection: AI tools can produce any number of solutions, and each will be different, requiring students to evaluate the options critically. Students are taught to identify which solution is most likely to solve their problem effectively.
    • Code testing and debugging: Students practise open- and closed-box testing, learning to identify edge cases and debug code using tools like doctest and the VS Code debugger.
    • Problem decomposition: Breaking down large projects into smaller functions is essential. For instance, when designing a text-based game, students might separate tasks into input handling, game state updates, and rendering functions.
    • Leveraging modules: Students explore new programming domains and identify useful libraries through interactions with Copilot. This prepares them to solve problems efficiently and creatively.

    Ethical and metacognitive skills: Students engage in discussions about responsible AI use and reflect on the decisions they make when collaborating with AI tools.

    Graphic depicting students' confidence levels regarding their programming skills and their use of Generative AI tools.

    Adapting assessments for the AI era

    The rise of GenAI has prompted educators to rethink how they assess programming skills. In the CS1-LLM course, traditional take-home assignments were de-emphasised in favour of assessments that focused on process and understanding.

    Table highlighting the different types of assessments involved in Leo and Daniel's course.
    Leo and Daniel chose several types of assessments — some involved having to complete programming tasks with the help of GenAI tools, while others had to be completed without.
    • Quizzes and exams: Students were evaluated on their ability to read, test, and debug code — skills critical for working effectively with AI tools. Final exams included both tasks that required independent coding and tasks that required use of Copilot.
    • Creative projects: Students submitted projects alongside a video explanation of their process, emphasising problem decomposition and testing. This approach highlighted the importance of critical thinking over rote memorisation.

    Challenges and lessons learnt

    While Leo and Daniel reported that the integration of AI tools into their course has been largely successful, it has also introduced challenges. Surveys revealed that some students felt overly dependent on AI tools, expressing concerns about their ability to code independently. Addressing this will require striking a balance between leveraging AI tools and reinforcing foundational skills.

    Additionally, ethical concerns around AI use, such as plagiarism and intellectual property, must be addressed. Leo and Daniel incorporated discussions about these issues into their curriculum to ensure students understand the broader implications of working with AI technologies.

    A future-oriented approach

    Leo and Daniel’s work demonstrates that GenAI can transform programming education, making it more inclusive, engaging, and relevant. Their course attracted a diverse cohort of students, as well as students traditionally underrepresented in computer science — 52% of the students were female and 66% were not majoring in computer science — highlighting the potential of AI-powered learning to broaden participation in computer science.

    A girl in a university computing classroom.

    By embracing this shift, educators can prepare students not just to write code but to also think critically, solve real-world problems, and effectively harness the AI innovations shaping the future of technology.

    If you’re an educator interested in using GenAI in your teaching, we recommend checking out Leo and Daniel’s book, Learn AI-Assisted Python Programming, as well as their course resources on GitHub. You may also be interested in our own Experience AI resources, which are designed to help educators navigate the fast-moving world of AI and machine learning technologies.

    Join us at our next online seminar on 11 March

    Our 2025 seminar series is exploring how we can teach young people about AI technologies and data science. At our next seminar on Tuesday, 11 March at 17:00–18:00 GMT, we’ll hear from Lukas Höper and Carsten Schulte from Paderborn University. They’ll be discussing how to teach school students about data-driven technologies and how to increase students’ awareness of how data is used in their daily lives.

    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.

    The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

    Website: LINK

  • A lightweight file server running entirely on an Arduino Nano ESP32

    A lightweight file server running entirely on an Arduino Nano ESP32

    Reading Time: 2 minutes

    Home file servers can be very useful for people who work across multiple devices and want easy access to their documents. And there are a lot of DIY build guides out there. But most of them are full-fledged NAS (network-attached storage) devices and they tend to rely on single-board computers. Those take a long time to boot and consume quite a lot of power. This lightweight file server by Zombieschannel is different, because it runs entirely on an Arduino.

    An ESP32 is a microcontroller with built-in connectivity (Wi-Fi and Bluetooth). Like all MCUs, it can “boot” and start running its firmware almost instantly. And while it runs, it will consume much less power than a conventional PC or a single-board computer. Zombieschannel’s project proves that the Arduino Nano ESP32 is suitable for a file server — if your expectations are modest.

    The hardware for this project consists of a Nano ESP32, an SD card reader module, and a small monochrome OLED screen. The SD card provides file storage and the OLED shows status information.

    Most of the work went into writing the firmware, which Zombieschannel did with assistance from ChatGPT. That has the Arduino hosting a basic web interface that local users can access to upload or download files. Zombieschannel also created a command line interface that provides more comprehensive access via a serial connection. 

    This does have limitations and the transfer speeds are quite slow by modern standards. But the file server seems useful for small files, like text documents. Zombieschannel plans to design an enclosure for the device and it should tuck unobtrusively into a corner, where it can run without drawing much power.

    [youtube https://www.youtube.com/watch?v=RzPNge3pa38?feature=oembed&w=500&h=281]

    The post A lightweight file server running entirely on an Arduino Nano ESP32 appeared first on Arduino Blog.

    Website: LINK

  • This vending machine draws generative art for just a euro

    This vending machine draws generative art for just a euro

    Reading Time: 2 minutes

    If you hear the term “generative art” today, you probably subconsciously add “AI” to the beginning without even thinking about it. But generative art techniques existed long before modern AI came along — they even predate digital computing altogether. Despite that long history, generative art remains interesting as consumers attempt to identify patterns in the underlying algorithms. And thanks to the “Generative Art 1€” vending machine built by Niklas Roy, you can experience that for yourself by spending a single euro.

    Roy built this vending machine to display at the “Intelligence, it’s automatic” exhibit, hosted at Zebrastraat in Belgium. Rather than AI, Roy gave the machine more traditional algorithms to generate abstract pieces of line art. Each piece uses the current time as the “seed” for the algorithms, so it will be unique and an identical piece will never appear again. And the current piece, shown on a screen in the machine, always evolves as time passes. If a viewer sees something they like, they’ll need to insert a euro coin immediately or risk losing the opportunity to secure the art.

    Once paid, the machine will use a built-in pen plotter to draw the line on a piece of paper. It will also label the art with a unique identifier: the seed number. Then, it will stamp the paper for authenticity. Finally, it will cut that piece from the roll of paper and dispense the art through a chute at the bottom.

    That all happens under the direction of an Arduino Mega 2560 board. It controls the pen plotter, which is a repurposed model called Artima Colorgraf. The coin-op mechanism is an off-the-shelf unit and a Python script, running on a connected laptop, performs the art generation. What message is this vending machine meant to convey? Maybe that art is ethereal or that it has little value — just a euro — to modern society. Whatever the case, it is a work of art in its own right.

    [youtube https://www.youtube.com/watch?v=g9BWODjYZBY?feature=oembed&w=500&h=281]

    The post This vending machine draws generative art for just a euro appeared first on Arduino Blog.

    Website: LINK

  • This three-fingered robot hand makes use of serial bus servos

    This three-fingered robot hand makes use of serial bus servos

    Reading Time: 2 minutes

    A small startup called K-Scale Labs is in the process of developing an affordable, open-source humanoid robot and Mike Rigsby wanted to build a compatible hand. This three-fingered robot hand is the result, and it makes use of serial bus servos from Waveshare.

    Most Arduino users are familiar with full-duplex serial communication, which requires two data lines. The first carries data in one direction, while the second carries data in the other. As such, devices can send and receive data at the same time — they don’t have to wait to until the line is “free” to send data.

    But half-duplex serial communication is also possible. Each device just has to wait its turn to send data. That is less common, but it does have some benefits. In this case, Rigsby used Waveshare servo motors that communicate via a half-duplex serial bus. The benefit is that users can daisy-chain multiple servos together, connecting to a single serial pin on the host device. These particular servo motors also have magnetic encoders instead of potentiometers, which are more reliable.

    Five of those servos actuate the 3D-printed fingers on Rigsby’s robot hand (the top two fingers have two joints each). He used an Arduino UNO Rev3 board to control them, but couldn’t use the typical RX and TX (0 and 1) pins for communication over the serial bus. For that reason, he included a serial bus module meant specifically for driving servos like these.

    This seems to work pretty well and the motors move smoothly — though they currently lack sensors that would enable force/pressure control.

    [youtube https://www.youtube.com/watch?v=O0obGqlXZ9o?feature=oembed&w=500&h=281]

    The post This three-fingered robot hand makes use of serial bus servos appeared first on Arduino Blog.

    Website: LINK

  • Arduino and System Electronics partner for industrial vision and AI-powered inventory and logistics

    Arduino and System Electronics partner for industrial vision and AI-powered inventory and logistics

    Reading Time: 3 minutes

    Arduino and System Electronics are joining forces to create cutting-edge solutions for industrial and building automation, focusing specifically on edge computing to deliver real-time processing, predictive analytics, and seamless integration for AI-driven inventory management and logistics. 

    System Electronics – as an “Innovation accelerators for over 50 years” – brings to the table the electronics and mechatronics expertise to facilitate innovation and make a decisive contribution to their clients’ competitive edge. “Our collaboration with System Electronics merges their deep industrial expertise with Arduino’s focus on edge computing, enabling businesses to deploy intelligent, scalable automation solutions faster than ever. From AI-driven inventory management to predictive maintenance and real-time quality control, this partnership empowers industrial players to optimize operations, reduce downtime, and drive efficiency with cutting-edge technology,” our CEO Fabio Violante announced. “This is another step toward making advanced AI and automation accessible to industries of all sizes, accelerating the transformation of smart manufacturing and logistics.

    Andrea Gozzi, General Manager of System Electronics added, “At System Electronics, we believe in developing solutions that bring real value to industrial automation. By partnering with Arduino, we’ll create powerful and flexible AI-driven solutions that meet the needs of modern manufacturing, robotics, and smart infrastructure: innovations built for reliability, scalability, and performance.” 

    The benefits of a partnership for innovation

    AI-driven inventory and warehouse management leverage computer vision and automation to make predictive maintenance and autonomous decision-making faster and more efficient than ever.

    To fully explore these opportunities, Arduino and System Electronics are integrating acceleration technology from Hailo, a leader in Edge AI processors. By combining Hailo’s AI acceleration, Arduino’s open ecosystem, and System Electronics’ industrial-grade expertise, this collaboration aims to deliver real-time, high-performance automation solutions with enhanced precision and speed – bringing intelligence directly to where it’s needed most.

    Why explore smart inventory and logistics

    Smart factories and connected warehouses leverage powerful, real-time AI computing at the edge to improve efficiency and quality standards. 

    For example, computer vision can be employed at the edge to detect defects and irregularities, as well as to automate warehouse logistics with precise item tracking and storage optimization; sensor data can be analyzed to implement predictive maintenance and tackle anomalies before failures occur, reducing downtime; motion planning and obstacle avoidance can be optimized for AGVs and robotic arms thanks to intelligent control based on data and AI. 

    See the demo in action at Embedded World

    Within their collaboration, Arduino and System Electronics have developed an innovative solution for Modula, leaders in warehouse automation: “We are committed to revolutionizing intralogistics through automation and smart technology that make processes easier. Harnessing the power of AI-driven intelligence allows us to enhance efficiency, optimize workflows, and deliver even greater value to our customers without adding complexities for them,” said Franco Stefani, founder of Modula.

    This demo for a smart inventory solution will debut at Embedded World 2025 (Nuremberg, March 11th-13th): visit Arduino in Hall 3A, Booth #313, to see it in action and connect with the experts behind its development.

    The post Arduino and System Electronics partner for industrial vision and AI-powered inventory and logistics appeared first on Arduino Blog.

    Website: LINK

  • Experience AI: The story so far

    Experience AI: The story so far

    Reading Time: 5 minutes

    In April 2023, we launched our first Experience AI resources, developed in partnership with Google DeepMind to support educators to engage their students in learning about the topic of AI. Since then, the Experience AI programme has grown rapidly, reaching thousands of educators all over the world. Read on to find out more about the impact of our resources, and what we are learning.

    The Experience AI resources

    The Experience AI resources are designed to help educators introduce AI and AI safety to 11- to 14-year-olds. They consist of:

    • Foundations of AI: a comprehensive unit of six lessons including lesson plans, slide decks, activities, videos, and more to support educators to introduce AI and machine learning to young people
    • Two standalone lessons:
      • Large language models (LLMs): a lesson designed to help young people discover how large language models work, their benefits, and why their outputs are not always reliable
      • Ecosystems and AI — Biology: a lesson providing an opportunity for young people to explore how AI applications are supporting animal conservation
    • AI safety: a set of resources with a flexible design to support educators in a range of settings to equip young people with the knowledge and skills to responsibly and safely navigate the challenges associated with AI

    We also offer a free online course, Understanding AI for educators, to help educators prepare to teach about AI.

    International expansion

    The launch of Experience AI came at an important time: AI technologies are playing an ever-growing role in our everyday lives, so it is crucial for young people to gain the understanding and skills they need to critically engage with these technologies. While the resources were initially designed for use by educators in the UK, they immediately attracted interest from educators across the world, as well as individuals wanting to learn about AI. The resources have now been downloaded over 325,000 times by people from over 160 countries. This includes downloads from over 7000 educators worldwide, who will collectively reach an estimated 1.2 million young people.

    Photo of an educator teaching an Experience AI lesson.

    Thanks to funding from Google DeepMind and Google.org, we have also been working with partners from across the globe to localise and translate the resources for learners and educators in their countries, and provide training to support local educators to deliver the lessons. The educational resources are now available in up to 15 languages, and to date, we have trained over 100 representatives from 20 international partner organisations, who will go on to train local educators. Five of these organisations have begun onward training already, collectively training over 1500 local educators so far.

    The impact of Experience AI

    The Experience AI resources have been well received by students and educators. Based on responses to our follow-up surveys, in countries where we have partners

    • 95% of educators agreed that the Experience AI sessions have increased their students’ knowledge of AI concepts 
    • 90% of young people (including young people in formal and non-formal education settings and learning independently) indicated that they better understand what AI and machine learning are
    Photo of a young person learning about AI on a laptop.

    This is backed up by qualitative feedback from surveys and interviews.

    “Students’ perception and understanding of AI has improved and corrected. They realised they can contribute and be a part of the [development], instead of only users.” – Noorlaila, educator, SMK Cyberjaya, Malaysia

    “[Students] found it interesting in the sense that it’s relevant information and they didn’t know what information was used for training models.” – Teacher, Liceul Tehnologic “Crisan” Criscior, Romania

    “Based on my knowledge and learning about AI, I now appreciate the definition of AI as well as its implementation.” – Student, Changamwe JSS, Kenya

    Photo of a group of educators participating in an Experience AI teacher training event in Kenya.

    The training and resources also support educators to feel more confident to teach about AI:

    • 93% of international partner representatives who participated in our training agreed that the training increased their knowledge of AI concepts
    • 88% of educators receiving onward training by our international partners agreed that the training increased their confidence to teach AI concepts
    • 87% of educator respondents from our ‘Understanding AI for educators’ online course agreed that the course was useful for supporting young people

    “It was a wonderful experience for me to join this workshop. Truly I was able to learn a lot about AI and I feel more confident now to teach the kids back at school about this new knowledge.” – Nur, educator, SMK Bandar Tasek Mutiara, trained by our partner Penang Science Cluster, Malaysia

    “This was one of the best information sessions I’ve been to! So, so helpful!” – Meagan, educator, University of Alberta, trained by our partner Digital Moment, Canada

    “The layout of the course in terms of content structuring is amazing. I love the discussion forum and the insightful yet empathetic responses by the course moderators on the discussion board. Honestly, I am really glad I started my AI in education journey with you.” – Priyanka, head teacher (primary level), United Arab Emirates, online course participant

    What are we learning?

    We are committed to continually improving our resources based on feedback from users. A recent review of feedback from educators highlighted key aspects of the resources that educators value most, as well as some challenges educators are facing and possible areas for improvement. For example, educators particularly like the interactive aspects, the clear structure and explanations, and the videos featuring professionals from the AI industry. We are continuing to look for ways we can better support educators to adapt the content and language to better support students in their context, fit Experience AI into their school timetables, and overcome technical barriers. 

    We value feedback on our resources and will continue to highlight the importance of AI education in schools and work with partners across the globe to adapt our resources for different contexts.

    Get involved

    If you would like to try out our Experience AI resources, head to experience-ai.org, where you can find our free resources and online course, as well as information about local partners in your area.

    Website: LINK

  • Discover the all-new Raspberry Pi Official Magazine

    Discover the all-new Raspberry Pi Official Magazine

    Reading Time: 3 minutes

    We’re hugely proud of the new magazine. It’s got all the amazing features that made The MagPi such a success, but with a new design that’s easier to read, better at displaying code, and more in sync with Raspberry Pi’s amazing documentation and tutorials.

    Thank you again to everybody who supports us by subscribing to the magazine or contributing to our endeavour. We really can’t do it without you.

    We’ve worked incredibly hard to make this issue one to remember. Inside the inaugural Raspberry Pi Official Magazine, you will discover…

    Level up your tech skills with our guide to Raspberry Pi troubleshooting

    Raspberry Pi problem solving

    Our lead feature this month is a huge analysis of Raspberry Pi troubleshooting. We’ve gathered a vast amount of documentation on power requirements, SD card performance, Raspberry Pi OS customisation, boot problems, audio and video fixes, and hardware enhancements.

    Discover tools for every kind of maker

    The maker toolset

    It’s incredibly important to make things. Making is rewarding, fun, and practical. In this month’s magazine, you’ll discover everything you need to set up your makerspace. Our maker toolset has the full range from simple circuits and humble sewing up to 3D printing and metalwork.

    A unique musical instrument built with Raspberry Pi RP2040

    HexBoard

    Raspberry Pi Official Magazine is packed with all the best projects from around the globe. Jared DeCook shares his incredible HexBoard musical instrument with us. Instead of piano-style keys, it features hexagonal buttons and RGB LEDs, all controlled by Raspberry Pi RP2040.

    How one maker is using stepper motors and magnets to build a robotic chess set

    Raspberry Pi Chess Board

    Imagine playing chess against a robot. That’s what high school student Tamerlan Goglichidze has created. With a stepper motor and magnets it moves the chess pieces around.

    Your guide to attaching a Sense HAT V2 to Raspberry Pi and controlling its input/output

    Sense HAT V2

    Sense HAT is a great way to discover coding and data gathering. In this tutorial we’ll show you how to attach a Sense HAT to your Raspberry Pi and start controlling the LED display. 

    Build a CNC filament winder

    Custom CNC Machine

    Jo Hinchliffe brings together various parts for a custom CNC machine that acts as a carbon filament winding machine for making custom carbon-fibre tubes.

    10 amazing Raspberry Pi 5 accessories

    10 Amazing Accessories

    Power up your Raspberry Pi 5 with these incredible add-ons that enable extra functionality. We’ve got everything from USB sound cards to overpowered cooling systems.

    You’ll find all this and much more in the latest edition of Raspberry Pi Official Magazine. Pick up your copy today from our store, or subscribe to get every issue delivered to your door.

  • Win one of five PiFi kits

    Win one of five PiFi kits

    Reading Time: < 1 minute

    Ever been in a hotel or AirBnB with rubbish WiFi? Make it better by using a Raspberry Pi with PiFi, a powerful dongle that let’s you create a secure wireless router with a Raspberry Pi – including VPN capabilities. We have five to give away, and you can enter below…

  • Teaching about AI – Teacher symposium

    Teaching about AI – Teacher symposium

    Reading Time: 5 minutes

    AI has become a pervasive term that is heard with trepidation, excitement, and often a furrowed brow in school staffrooms. For educators, there is pressure to use AI applications for productivity — to save time, to help create lesson plans, to write reports, to answer emails, etc. There is also a lot of interest in using AI tools in the classroom, for example, to personalise or augment teaching and learning. However, without understanding AI technology, neither productivity nor personalisation are likely to be successful as teachers and students alike must be critical consumers of these new ways of working to be able to use them productively. 

    Fifty teachers and researchers posing for a photo at the AI Symposium, held at the Raspberry Pi Foundation office.
    Fifty teachers and researchers share knowledge about teaching about AI.

    In both England and globally, there are few new AI-based curricula being introduced and the drive for teachers and students to learn about AI in schools is lagging, with limited initiatives supporting teachers in what to teach and how to teach it. At the Raspberry Pi Foundation and Raspberry Pi Computing Education Research Centre, we decided it was time to investigate this missing link of teaching about AI, and specifically to discover what the teachers who are leading the way in this topic are doing in their classrooms.  

    A day of sharing and activities in Cambridge

    We organised a day-long, face-to-face symposium with educators who have already started to think deeply about teaching about AI, have started to create teaching resources, and are starting to teach about AI in their classrooms. The event was held in Cambridge, England, on 1 February 2025, at the head office of the Raspberry Pi Foundation. 

    Photo of educators and researchers collaborating at the AI symposium.
    Teachers collaborated and shared their knowledge about teaching about AI.

    Over 150 educators and researchers applied to take part in the symposium. With only 50 places available, we followed a detailed protocol, whereby those who had the most experience teaching about AI in schools were selected. We also made sure that educators and researchers from different teaching contexts were selected so that there was a good mix of primary to further education phases represented. Educators and researchers from England, Scotland, and the Republic of Ireland were invited and gathered to share about their experiences. One of our main aims was to build a community of early adopters who have started along the road of classroom-based AI curriculum design and delivery.

    Inspiration, examples, and expertise

    To inspire the attendees with an international perspective of the topics being discussed, Professor Matti Tedre, a visiting academic from Finland, gave a brief overview of the approach to teaching about AI and resources that his research team have developed. In Finland, there is no compulsory distinct computing topic taught, so AI is taught about in other subjects, such as history. Matti showcased tools and approaches developed from the Generation AI research programme in Finland. You can read about the Finnish research programme and Matti’s two month visit to the Raspberry Pi Computing Education Research Centre in our blog

    Photo of a researcher presenting at the AI Symposium.
    A Finnish perspective to teaching about AI.

    Attendees were asked to talk about, share, and analyse their teaching materials. To model how to analyse resources, Ben Garside from the Raspberry Pi Foundation modelled how to complete the activities using the Experience AI resources as an example. The Experience AI materials have been co-created with Google DeepMind and are a suite of free classroom resources, teacher professional development, and hands-on activities designed to help teachers confidently deliver AI lessons. Aimed at learners aged 11 to 14, the materials are informed by the AI education framework developed at the Raspberry Pi Computing Education Research Centre and are grounded in real-world contexts. We’ve recently released new lessons on AI safety, and we’ve localised the resources for use in many countries including Africa, Asia, Europe, and North America.

    In the morning session, Ben exemplified how to talk about and share learning objectives, concepts, and research underpinning materials using the Experience AI resources and in the afternoon he discussed how he had mapped the Experience AI materials to the UNESCO AI competency framework for students.

    Photo of an adult presenting at the AI Symposium.
    UNESCO provide important expertise.

    Kelly Shiohira, from UNESCO, kindly attended our session, and gave an invaluable insight into the UNESCO AI competency framework for students. Kelly is one of the framework’s authors and her presentation helped teachers understand how the materials had been developed. The attendees then used the framework to analyse their resources, to identify gaps and to explore what progression might look like in the teaching of AI.

    Photo of a whiteboard featuring different coloured post-it notes displayed featuring teachers' and researchers' ideas.
    Teachers shared their knowledge about teaching about AI.

    Throughout the day, the teachers worked together to share their experience of teaching about AI. They considered the concepts and learning objectives taught, what progression might look like, what the challenges and opportunities were of teaching about AI, what research informed the resources and what research needs to be done to help improve the teaching and learning of AI.

    What next?

    We are now analysing the vast amount of data that we gathered from the day and we will share this with the symposium participants before we share it with a wider audience. What is clear from our symposium is that teachers have crucial insights into what should be taught to students about AI, and how, and we are greatly looking forward to continuing this journey with them.

    As well as the symposium, we are also conducting academic research in this area, you can read more about this in our Annual Report and on our research webpages. We will also be consulting with teachers and AI experts. If you’d like to ensure you are sent links to these blog posts, then sign up to our newsletter. If you’d like to take part in our research and potentially be interviewed about your perspectives on curriculum in AI, then contact us at: rpcerc-enquiries@cst.cam.ac.uk 

    We also are sharing the research being done by ourselves and other researchers in the field at our research seminars. This year, our seminar series is on teaching about AI and data science in schools. Please do sign up and come along, or watch some of the presentations that have already been delivered by the amazing research teams who are endeavouring to discover what we should be teaching about AI and how in schools

    Website: LINK

  • DIY micro lab analyzes ammonia levels in blood and urine

    DIY micro lab analyzes ammonia levels in blood and urine

    Reading Time: 2 minutes

    Cirrhosis of the liver is an extremely serious condition that requires extensive medical monitoring and often intervention. Progression of the condition can be fatal, so even if caught early it must be monitored closely. But, like most things in medicine, that gets expensive. That’s why Marb built his own DIY “micro lab” to analyze ammonia levels in blood and urine.

    Disclaimer: Don’t rely on YouTube videos for your medical needs!

    The severity of Marb’s condition correlates with increased ammonia production, which is common for cirrhosis of the liver. More ammonia in the blood and urine indicates progression of the disease and a need for immediate medical intervention. Marb’s micro lab lets him monitor his own ammonia levels at home.

    The central detection mechanism of this micro lab relies on Berthelot’s reagent, which becomes a blue-green color in the presence of ammonia. To make use of that, the micro lab needs to properly expose the sample to Berthelot’s reagent and look at the resulting color change.

    An Arduino Nano board controls the whole process through a custom PCB. That starts with heating the sample in a vial to release the ammonia vapor. The vapor travels via a tube through a gas diffuser into another vial containing Berthelot’s reagent. A magnetic stirrer beneath mixes the gas into the reagent. A 660nm (deep red) laser shines through that vial into a photo diode on the other side, and the Arduino monitors that through a pre-amp.

    If a lot of the red light passes through, then the Berthelot’s reagent didn’t turn very blue and there is little to no ammonia present. If hardly any red light passes through, then reagent is very blue and that indicates a high level of ammonia.

    The amount of light detected, between those two extremes, provides a reasonably accurate measure of Marb’s ammonia levels, so he can keep track of his condition’s progression.

    [youtube https://www.youtube.com/watch?v=AdfZKD2SkI0?start=24&feature=oembed&w=500&h=281]

    The post DIY micro lab analyzes ammonia levels in blood and urine appeared first on Arduino Blog.

    Website: LINK

  • The 2024 Arduino Open Source Report is here!

    The 2024 Arduino Open Source Report is here!

    Reading Time: 2 minutes

    Every year, we take a moment to reflect on the contributions we made to the open source movement, and the many ways our community has made a huge difference. As we publish the latest Open Source Report, we are proud to say 2024 was another year of remarkable progress and achievements.

    A year of growth and collaboration

    At Arduino, we continued pushing the boundaries of open hardware and software

    In 2024, we:

    These updates ensure a more flexible and robust ecosystem for developers, educators, and makers worldwide.

    But what truly makes open source thrive is the community behind it! Over the past year, Arduino users contributed 1,198 new libraries to the Library Manager (+18% YoY growth!), shared hundreds of open-source tutorials, and actively engaged in thousands of discussions and collaborations on GitHub and Project Hub. These collective efforts fuel innovation, making the Arduino ecosystem more dynamic, inclusive, and powerful than ever.

    How can you contribute to open source?

    We believe open-source success is built on collaboration. Every original Arduino purchase, Arduino Cloud subscription, and community contribution helps support and expand this shared ecosystem. Donations of course are also welcome, and play a great part in everything we do! 

    Download the 2024 Open Source Report to explore the milestones we’ve achieved together. Here’s to another year of openness, creativity, and progress!

    (Want to catch up on previous editions? Here are the Open Source Reports for 2023, 2022, and 2021.)

    The post The 2024 Arduino Open Source Report is here! appeared first on Arduino Blog.

    Website: LINK

  • Code Club: Empowering the Next Generation of Digital Creators

    Code Club: Empowering the Next Generation of Digital Creators

    Reading Time: 4 minutes

    Code Club is more than just a place to learn coding — it’s a thriving global community where young minds discover, create, and grow with technology. With a refreshed look and ambitious goals for 2025, Code Club is set to connect an even larger network of mentors and reach millions more young people worldwide.

    Code Club at RPF HQ, Cambridge
    Code Club at RPF HQ, Cambridge

    Since it was founded in the UK in 2012, Code Club has grown into a global movement, inspiring over two million young people to build apps, games, animations, websites, and more. Supported by the Raspberry Pi Foundation, Code Club provides free training and resources to mentors, ensuring creators achieve meaningful and lasting skills. Our vision for the next decade? To empower ten million more young people to have confidence in their coding.

    A proven impact

    A recent independent evaluation by the Durham University Evidence Centre for Education (DECE) confirmed what we’ve always believed: Code Club makes a real difference. Young people who attend gain valuable coding skills, grow in confidence, develop a strong interest in technology, and find a sense of belonging in the digital world.

    Mentor Rajan at his Code Club in India
    Mentor Rajan at his Code Club in India

    The power of mentorship

    At the heart of Code Club are passionate volunteers who bring coding to life. Whether it’s the thrill of overcoming a challenge or the excitement of seeing an idea come to life on screen, mentors make a lasting impact while learning coding skills alongside their club’s creators.

    Bob Bilsland, a dedicated volunteer since 2012, runs one of the world’s longest-running Code Clubs at Malvern CofE Primary School, Worcestershire, England. His motivation?

    “What brings me back week after week is the sharing of what I enjoy doing. It’s so much fun to help others explore this space themselves, to see what they can personally create. I see that giving others the opportunity to explore and familiarise themselves with computing as something that could open up a world of possibilities for them in the future.” 

    For Yang, a mentor at the EY office clubs, representation in tech is key:

    “If there are some female role models, I think for a little girl growing up, that means so much. Because if they can see somebody thrive in this industry, they will see themselves there one day. And that’s the inspiration.” 

    Mentor Yang at her Code Club in London
    Mentor Yang at her Code Club in London

    Across the world, volunteers like Nadia in Iraq and Solomon in The Gambia are using Code Club to bridge the digital divide, create opportunities, and empower communities.

    “[Code Club] added to my skills. And at the same time, I was able to share my expertise with the young children and to learn from them as well.” – Nadia Al-Aboody, Iraq.

    “We strongly believe in the transformative power of digital skills and their potential to create opportunities for young people. Witnessing the lack of access to computer knowledge among high school graduates in The Gambia and other sub-Saharan African countries inspired us to take action. By bridging the digital skills gap, we aim to empower young individuals to thrive in the 21st century.” – Solomon, Gambia 

    A community that inspires

    Code Club isn’t just loved by mentors; it’s so important to the young people who participate.

    Eoghan, a young creator from Ireland, values the collaboration and support he receives:

    “It’s really fun to meet and talk about ideas with other creators, and the mentors are very helpful in fixing any coding problems.” 

    Mentor Jayantika at her Code Club in Pune, India
    Mentor Jayantika at her Code Club in Pune, India

    Jayantika, a 15-year-old from rural Pune, India, started as a creator and is now a peer mentor. For her, Code Club is about giving back:

    “I believe coding opens doors and helps young children express their creativity. By mentoring, I hope to prepare them for a future that is increasingly driven by AI and technology.” 

    Join the movement

    Along with the incredible community, Code Club is supported by sponsors and funders who share our mission. We would like to extend a thank you to Cognizant, who have committed their support to the Code Club mission in the UK and Ireland for 2025.

    Mentors gathering at Clubs Con 2024
    Mentors gathering at Clubs Con 2024

    Code Club is more than just learning to code; it’s about creating opportunities, encouraging confidence, and building a global network of digital creators. Whether you’re a mentor, educator, or young digital maker, there’s a place for you in our community. Start your Code Club journey today and join a global community of digital creators.

    Website: LINK

  • This mod simplifies single-point threading on mini lathes

    This mod simplifies single-point threading on mini lathes

    Reading Time: 2 minutes

    “Single-point threading” on a lathe is the process of cutting threads, such as for a bolt, into the material through turning. The spindle/workpiece spin and the carriage moves linearly at a precise amount per turn of the spindle. That linear movement is the thread pitch. But this process usually requires several passes to reach the final depth, which presents a problem: how do you start each thread at the exact same point each time? Daniel Engel’s Arduino-based mod solves that problem on mini lathes.

    To facilitate single-point threading, most lathes have a lead screw that can engage with the carriage in order to move the tool at a constant rate. That lead screw connects to the spindle through “change gears” or a transmission system, letting the machinist adjust the linear travel of the carriage relative to each spindle turn in order to achieve a desired pitch. 

    But what happens when you finish the first pass and need to go back for a second? How do you keep the leadscrew (and therefore carriage) in sync with the spindle? One method is to run the lathe in reverse, but that has problems of its own. Some lathes have half-nuts designed to sync engagement, but many mini lathes lack that feature.

    Engel’s modification does two things to help: first, it provides a gear reduction to the spindle. That lets him perform single-point threading a much lower RPM, increasing torque and making it easier to stop at the right time (such as meeting a shoulder). Second, it lets an Arduino UNO Rev3 board monitor the spindle position via Hall effect sensors that detect four permanent magnets mounted on the spindle from the factory.

    The Arduino records the stop and start positions, displaying them on an LCD screen along with the spindle RPM and current position. After finishing a pass, Engel can use that information to return to the exact same starting position in order to perform the next pass.

    This is a clever solution to a common problem and Engel’s tutorial has all the information you need to perform the same modification on your own mini lathe. 

    [youtube https://www.youtube.com/watch?v=iHXrOEHyonw?feature=oembed&w=500&h=281]

    The post This mod simplifies single-point threading on mini lathes appeared first on Arduino Blog.

    Website: LINK

  • This robotic piano has solenoids for all 88 keys

    This robotic piano has solenoids for all 88 keys

    Reading Time: 2 minutes

    Pianos famously have a lot of keys. A standard full-size piano has 52 white keys and 36 black keys, for a total of 88. Therefore, people need to get clever when they build self-playing pianos. However, the brute force approach works, too. Paul Junkin’s brute force strategy was to add a solenoid for every one of those 88 keys on his piano-playing robot.

    Junkin built this robot to play an old piano that had been in his family’s home since his childhood. For that reason, he didn’t want to do any permanent modifications to the piano itself and instead designed the robot to sit over the keys. It has a frame made of aluminum extrusion to support all of those solenoids.

    They are 12V solenoids that can push with 25 newtons of force. An Arduino UNO Rev3 drives those solenoids through PWM modules and power MOSFETs. The PWM control lets the Arduino output something effectively approximating analog voltage in order to adjust the velocity of each key strike.

    To tell the Arduino which keys to strike and with what velocity, Junkin used a USB-to-MIDI adapter going from his laptop to a MIDI-to-serial converter that connects to the Arduino. Software on the computer sends MIDI note commands through those adapters to the Arduino, which then actuates the solenoids accordingly.

    This turned out well and the robot is able to play songs perfectly. And, best of all, it would be possible to put this robot on any other piano of a similar size.

    [youtube https://www.youtube.com/watch?v=LBCMGGnA6GU?feature=oembed&w=500&h=281]

    The post This robotic piano has solenoids for all 88 keys appeared first on Arduino Blog.

    Website: LINK

  • MKR Keylock is an open-source IoT keypad for your front door

    MKR Keylock is an open-source IoT keypad for your front door

    Reading Time: 2 minutes

    The age-old combination of physical locks and keys, although reliable, also comes with a few drawbacks, such as when you lose the key or you want to share access with someone else remotely. Davide Gomba has recognized this and built the MKR Keylock project as a way to address some of these shortcomings.

    Starting with an existing electronic lock module, Gomba installed it in his door before identifying the circuit responsible for triggering it to open. Once found, he connected the line to a relay that, when triggered by a GPIO signal, will unlock the bolt. An Arduino MKR WiFi 1010 was then attached to a 4×4 keypad, a small buzzer for signaling an incorrect code, and another relay that runs to the doorbell for remote ringing. Thanks to the MKR board’s Wi-Fi connectivity, the firmware configures an MQTT client that listens to a few topics: “/code” to set the keypad code, “/open” to override the locking mechanism, and “/alive/status” that reflects the real-time status of the lock.

    Over on the web side, Gomba made a new Home Assistant integration that operates on the same topics as a controller. From a webpage, users can then toggle the lock or provide a new code for the lock to check against.

    Want to bring your own door into the IoT era? More information about this IoT lock can be found here on Hackster.io.

    The post MKR Keylock is an open-source IoT keypad for your front door appeared first on Arduino Blog.

    Website: LINK

  • Social battery badge

    Social battery badge

    Reading Time: < 1 minute

    Introverts aren’t shy, quiet creatures that need to stay at home all day – it’s more complicated than that. Where extroverts thrive on social interaction, introverts find it takes a bit of energy to be around other people. When they’re feeling full of social energy it’s fun to socialise; when that social battery is drained, they need to read a book, go for a walk, or conduct some other solitary activity in order to recharge. That’s something that a lot of people don’t understand, but the next time you’re at a conference and you need a break from people, you can spell it out with the aid of this Social Battery (£14.99) by David Capper.

  • Teaching about AI in K–12 education: Thoughts from the USA

    Teaching about AI in K–12 education: Thoughts from the USA

    Reading Time: 5 minutes

    As artificial intelligence continues to shape our world, understanding how to teach about AI has never been more important. Our new research seminar series brings together educators and researchers to explore approaches to AI and data science education. In the first seminar, we welcomed Shuchi Grover, Director of AI and Education Research at Looking Glass Ventures. Shuchi began by exploring the theme of teaching using AI, then moved on to discussing teaching about AI in K–12 (primary and secondary) education. She emphasised that it is crucial to teach about AI before using it in the classroom, and this blog post will focus on her insights in this area.

    Shuchi Grover gave an insightful talk discussing how to teach about AI in K–12 education.
    Shuchi Grover gave an insightful talk discussing how to teach about AI in K–12 education.

    An AI literacy framework

    From her research, Shuchi has developed a framework for teaching about AI that is structured as four interlocking components, each representing a key area of understanding:

    • Basic understanding of AI, which refers to foundational knowledge such as what AI is, types of AI systems, and the capabilities of AI technologies
    • Ethics and human–AI relationship, which includes the role of humans in regard to AI, ethical considerations, and public perceptions of AI
    • Computational thinking/literacy, which relates to how AI works, including building AI applications and training machine learning models
    • Data literacy, which addresses the importance of data, including examining data features, data visualisation, and biases

    This framework shows the multifaceted nature of AI literacy, which involves an understanding of both technical aspects and ethical and societal considerations. 

    Shuchi’s framework for teaching about AI includes four broad areas.
    Shuchi’s framework for teaching about AI includes four broad areas.

    Shuchi emphasised the importance of learning about AI ethics, highlighting the topic of bias. There are many ways that bias can be embedded in applications of AI and machine learning, including through the data sets that are used and the design of machine learning models. Shuchi discussed supporting learners to engage with the topic through exploring bias in facial recognition software, sharing activities and resources to use in the classroom that can prompt meaningful discussion, such as this talk by Joy Buolamwini. She also highlighted the Kapor Foundation’s Responsible AI and Tech Justice: A Guide for K–12 Education, which contains questions that educators can use with learners to help them to carefully consider the ethical implications of AI for themselves and for society. 

    Computational thinking and AI

    In computer science education, computational thinking is generally associated with traditional rule-based programming — it has often been used to describe the problem-solving approaches and processes associated with writing computer programs following rule-based principles in a structured and logical way. However, with the emergence of machine learning, Shuchi described a need for computational thinking frameworks to be expanded to also encompass data-driven, probabilistic approaches, which are foundational for machine learning. This would support learners’ understanding and ability to work with the models that increasingly influence modern technology.

    A group of young people and educators smiling while engaging with a computer.

    Example activities from research studies

    Shuchi shared that a variety of pedagogies have been used in recent research projects on AI education, ranging from hands-on experiences, such as using APIs for classification, to discussions focusing on ethical aspects. You can find out more about these pedagogies in her award-winning paper Teaching AI to K-12 Learners: Lessons, Issues and Guidance. This plurality of approaches ensures that learners can engage with AI and machine learning in ways that are both accessible and meaningful to them.

    Research projects exploring teaching about AI and machine learning have involved a range of different approaches.
    Research projects exploring teaching about AI and machine learning have involved a range of different approaches.

    Shuchi shared examples of activities from two research projects that she has led:

    • CS Frontiers engaged high school students in a number of activities involving using NetsBlox and accessing real-world data sets. For example, in one activity, students participated in data science activities such as creating data visualisations to answer questions about climate change. 
    • AI & Cybersecurity for Teens explored approaches to teaching AI and machine learning to 13- to 15-year-olds through the use of cybersecurity scenarios. The project aimed to provide learners with insights into how machine learning models are designed, how they work, and how human decisions influence their development. An example activity guided students through building a classification model to analyse social media accounts to determine whether they may be bot accounts or accounts run by a human.
    A screenshot from an activity to classify social media accounts 
    A screenshot from an activity to classify social media accounts 

    Closing thoughts

    At the end of her talk, Shuchi shared some final thoughts addressing teaching about AI to K–12 learners: 

    • AI learning requires contextualisation: Think about the data sets, ethical issues, and examples of AI tools and systems you use to ensure that they are relatable to learners in your context.
    • AI should not be a solution in search of a problem: Both teachers and learners need to be educated about AI before they start to use it in the classroom, so that they are informed consumers.

    Join our next seminar

    In our current seminar series, we are exploring teaching about AI and data science. Join us at our next seminar on Tuesday 11 March at 17:00–18:30 GMT to hear Lukas Höper and Carsten Schulte from Paderborn University discuss supporting middle school students to develop their data awareness. 

    To sign up and take part in the seminar, click the button below — we will then send you information about joining. We hope to see you there.

    I want to join the next seminarThe schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

    Website: LINK

  • Pi Terminal review

    Pi Terminal review

    Reading Time: 2 minutes

    It also has the equally important connectivity requirements of modern industrial automation. From your classic terminal pins, serial connector, Ethernet, etc., there’s also access to the built-in Wi-Fi and Bluetooth of CM4, along with a GPS antenna add-on, and you can expand it with LoRa or LTE for more radio connections.

    Ready to go

    There’s no construction required for the device – unless you want to add LoRa, LTE, or an SSD module, but that’s exceptionally easy – and there’s even a little demo to help you get to grips with how the interface could work. It’s powered by a 12 V~36 V barrel jack which is a more old-school standard than USB-C, but does allow for a lot more taxing components to be attached to the various ports littered around the side.

    Extra antennas are included to help increase range, which is always very handy. Fortunately, every port is also well labelled, so it is unlikely that you’ll accidentally plug an antenna into the wrong radio port.

    The demo shows that the screen is sharp, colourful, and very responsive as well. It’s programmed in Node-RED, which may not be everyone’s cup of tea, but the whole system is built upon Raspberry Pi OS, so you can create an interface in any language that Raspberry Pi/Linux can support. So, all of them.

    Biggest fan

    It’s a very nice piece of kit and very flexible thanks to its wide array of connectivity and Raspberry Pi base. Unlike other similar devices, it does lack physical buttons as standard, so everything will have to be touchscreen unless some switches are added by the user. The fan is also very loud when it gets up to speed, which may not matter for some noisy industrial environments, but was very distracting in a quieter setting. Still, it’s a robust and very capable device. The acrylic plates are incredibly strong and everything else is very sturdily constructed too. You also could easily create a 3D-printed case for it, if the need arose.

    Verdict

    8/10

    A great piece of kit at a good price that is stronger than it looks, although it does have its own minor quirks.

    Price

    £148/$180

    Specs

    SoC: Raspberry Pi Compute Module 4 with 4GB RAM

    Display: 7˝ IPS LCD, 1024 × 600, 5-point capacitive touch

    Wireless connectivity: Wi-Fi, BLE 5.0, GPS, LoRa (with expansion), LTE (with expansion)

    Wired connectivity: GPIO, Relay, DO, DI, CAN, RS485, ADC, RS232, USB-C, USB 2.0, Gigabit Ethernet, HDMI, 3.5 mm headphone jack, TF card, SIM card, CSI (for camera)

  • Wired for success: Inspiring the next generation of women in science

    Wired for success: Inspiring the next generation of women in science

    Reading Time: 3 minutes

    Did you know that it’s International Day of Women and Girls in Science on February 11th, 2025? To celebrate this global event, we’re shining a light on the efforts to make STEM more accessible, inclusive, and inspiring for future generations. Let’s dive in!

    Mind the gap: gender representation in STEM 

    Science and technology have made huge leaps forward in recent years. Yet, according to UNESCO, women still make up just 35% of STEM graduates – a figure that has remained unchanged for the past decade.

    According to Dr. Erica Colón, founder of Nitty Gritty Science, one major issue is the lack of visible female role models. “If you were to ask children to draw a scientist, many would draw a man,” she told Arduino. From textbooks to posters, Erica says STEM careers are often portrayed as male-dominated, making it harder for young girls to see themselves in these roles. 

    Additionally, many students don’t even know about the exciting opportunities available in tech because these careers aren’t widely discussed in schools. But we can change that narrative.

    At Arduino, we’re committed to making STEM education accessible to everyone – regardless of their gender, race, background, or experience. And we’re not alone…

    Breaking down barriers: how educators and organizations are driving change

    Educators and organizations worldwide are working hard to reshape STEM education and make it more inclusive.

    One champion of this movement is Nathalie Duponsel, a doctoral candidate in Educational Technology at Concordia University in Montreal, Canada, and a certified primary school teacher. In this video, Natalie explains why Arduino’s open-source platform is key to lowering cost barriers and improving access to technology. “It also gives students real-world examples to work on, which is great for improving their skill sets and brings them around to this maker mindset,” she notes.

    Another initiative making a real impact is Arduino4Her, a training project for girls in Ghana hosted by MakerSpaceGH. This popular project equips young women with hands-on skills in Arduino technology, electronics, and programming through interactive workshops and inspiring presentations. The energy is always electric and it’s incredible to see so many young women embracing tech, creating bold new ideas, and challenging STEM stereotypes.

    How you can make a difference

    Want to inspire more girls to pursue a career in STEM? Whether you’re an educator, parent, or someone who wants to be part of the change, here’s how you can help:

    • Ignite a love of STEM early on – STEM skills should be nurtured from a young age. It’s never too early to encourage hands-on play and learning activities that spark curiosity, problem-solving, and creativity. For example, block-based coding with the Arduino Alvik robot (currently on sale until February 19th, 2025!) provides a fun route into coding and robotics for kids as young as seven.
    • Integrate hands-on tech projects – Integrating hands-on and interactive tools like the Plug and Make Kit, the Alvik robot or the Student Kit is a great way to introduce all students to key STEM areas. Who knows, you might even spark a lifelong passion or inspire the next Rosalind Franklin!
    • Highlight female role models – Share the stories of women in STEM – past and present – to help girls see what’s possible. Need inspiration? Check out this blog post, where we honor six trailblazing women whose contributions to science were overlooked.
    • Create supportive learning environments – Building an encouraging community is key. Whether through clubs, mentorship programs, or events like Arduino Days or Arduino4Her, girls need safe spaces where they can explore and excel in STEM.
    • Advocate for inclusive STEM education – Push for curriculum changes that showcase the contributions of women and minorities in science and technology. “As a teacher, all you can do is put that information out there and make your students aware that they can do anything,” says Dr. Erica Colón. “We have to keep encouraging and showing different roles that they can do.”

    On this International Day of Women and Girls in Science, let’s take action to empower, inspire, and break barriers. The future of STEM belongs to everyone!

    The post Wired for success: Inspiring the next generation of women in science appeared first on Arduino Blog.

    Website: LINK

  • Teaching AI safety: Lessons from Romanian educators

    Teaching AI safety: Lessons from Romanian educators

    Reading Time: 6 minutes

    This blog post has been written by our Experience AI partners in Romania, Asociatia Techsoup, who piloted our new AI safety resources with Romanian teachers at the end of 2024.

    Last year, we had the opportunity to pedagogically test the new three resources on AI safety and see first-hand the transformative effect they have on teachers and students. Here’s what we found.

    Students in class.

    Romania struggles with the digital skills gap

    To say the internet is ubiquitous in Romania is an understatement: Romania has one of the fastest internets in the world (11th place), an impressive mobile internet penetration (86% of the population), and Romania is leading Central and Eastern Europe in terms of percentage of population that is online (89% of the entire population). Unsurprisingly, most of Romania’s internet users are also social media users. 

    When you combine that with recent national initiatives, such as

    • The introduction of Information Technology and Informatics in the middle-school curriculum in 2017 as a compulsory subject
    • A Digital Agenda as a national strategy since 2015 
    • Allocation of over 20% of its most recent National Recovery and Resilience Fund for digital transition

    one might expect a similar lead in digital skills, both basic and advanced.

    But only 28% of the population, well below the 56% EU average, and just 47% of young people between 16 and 24 have basic digital skills — the lowest percentage in the European Union. 

    Findings from the latest International Computer and Information Literacy Study (ICILS, 2023)  underscore the urgent need to improve young people’s digital skills. Just 4% of students in Romania were scored at level 3 of 4, meaning they can demonstrate the capacity to work independently when using computers as information gathering and management tools, and are able, for example, to recognise that the credibility of web‐based information can be influenced by the identity, expertise, and motives of the people who create, publish, and share it.

    Students use a computer in class.

    Furthermore, 33% of students were assessed as level 1, while a further 40% of students did not even reach the minimum level set out in the ICILS, which means that they are unable to demonstrate even basic operational skills with computers or an understanding of computers as tools for completing simple tasks. For example, they can’t use computers to perform routine research and communication tasks under explicit instruction, and can’t manage simple content creation, such as entering text or images into pre‐existing templates.

    Why we wanted to pilot the Experience AI safety resources

    Add AI — and particularly generative AI — to this mix, and it spells huge trouble for educational systems unprepared for the fast rate of AI adoption by their students. Teachers need to be given the right pedagogical tools and support to address these new disruptions and the AI-related challenges that are adding to the existing post-pandemic ones.

    This is why we at Asociația Techsoup have been enthusiastically supporting Romanian teachers to deliver the Experience AI curriculum created by the Raspberry Pi Foundation and Google DeepMind. We have found it to be the best pedagogical support that prepares students to fully understand AI and to learn how to use machine learning to solve real-world problems.

    Testing the resources

    Last year, we had the opportunity to pedagogically test the new three resources on AI Safety and see first-hand the transformative effect they have on teachers and students.

    Students in class.

    We worked closely with 8 computer science teachers in 8 Romanian schools from rural and small urban areas, reaching approximately 340 students between the ages of 13 and 18.

    Before the teachers used the resources in the classroom, we worked with them in online community meetings and one-to-one phone conversations to help them review the available lesson plans, videos, and activity guides, to familiarise themselves with the structure, and to plan how to adapt the sessions to their classroom context. 

    In December 2024, the teachers delivered the resources to their students. They guided students through key topics in AI safety, including understanding how to protect their data, critically evaluating data to spot fake news, and how to use AI tools responsibly. Each session incorporated a dynamic mix of teaching methods, including short videos and presentations delivering core messages, unplugged activities to reinforce understanding, and structured discussions to encourage critical thinking and reflection. 

    Gathering feedback from users

    We then interviewed all the teachers to understand their challenges in delivering such a new curriculum and we also observed two of the lessons. We took time to discuss with students and gather in-depth feedback on their learning experiences, perspectives on AI safety, and their overall engagement with the activities, in focus groups and surveys.

    Feedback gathered in this pilot was then incorporated into the resources and recommendations given to teachers as part of the AI safety materials.

    Teachers’ perspectives on the resources

    It became obvious quite fast for both us and our teachers that the AI safety resources cover a growing and unaddressed need: to prepare our students for the ubiquitous presence of AI tools, which are on the road to becoming as ubiquitous as the internet itself.

    A teacher and students in class.

    Teachers evaluated the resources as very effective, giving them the opportunity to have authentic and meaningful conversations with their students about the world we live in. The format of the lessons was engaging — one of the teachers was so enthusiastic that she actually managed to keep students away from their phones for the whole lesson. 

    They also appreciated the pedagogical quality of the resources, especially the fact that everything is ready to use in class and that they could access them for free. In interviews, they also appreciated that they themselves also learnt a lot from the lessons:

    “For me it was a wake-up call. I was living in my bubble, in which I don’t really use these tools that much. But the world we live in is no longer the world I knew. … So such a lesson also helps us to learn and to discover the children in another context, – Carmen Melinte, a computer science teacher at the Colegiul Național Grigore Moisil in the small city of Onești, in north-east Romania, one of the EU regions with the greatest poverty risk.

    What our students think about the resources

    Students enjoyed discussing real-world scenarios and admitted that they don’t really have adults around whom they can talk to about the AI tools they use. They appreciated the interactive activities where they worked in pairs or groups and the games where they pretended to be creators of AI apps, thinking about safety features they could implement:

    “I had never questioned AI, as long as it did my homework,” said one student in our focus groups, where the majority of students admitted that they are already using large language models (LLMs) for most of their homework.

    “I really liked that I found out what is behind that ‘Accept all’ and now I think twice before giving my data,” – Student at the end of the ‘Your data and AI’ activities.

    “Activities put me in a situation where I had to think from the other person’s shoes and think twice before sharing my personal data,” commented another student.

    Good starting point

    This is a good first step: there is an acute need for conversations between young people and adults around AI tools, how to think about them critically, and how to use them safely. School is the right place to start these conversations and activities, as teachers are still trusted by most Romanian students to help them understand the world.

    Students use a computer in class.

    But to be able to do that, we need to be serious about equipping teachers with pedagogically sound resources that they can use in class, as well as training them, supporting them, and making sure that most of their time is dedicated to teaching, and not administration. It might seem a slow process, but it is the best way to help our students become responsible, ethical and accountable digital citizens.

    We are deeply grateful to the brave, passionate teachers in our community who gave the AI safety resources a try and of course to our partners at the Raspberry Pi Foundation for giving us the opportunity to lead this pilot.

    If you are a teacher anywhere in the world, give them a try today to celebrate Safer Internet Day: rpf.io/aisafetyromania

    Website: LINK

  • Gustavo Reynaga: Inspiring the next generation of makers with MicroPython

    Gustavo Reynaga: Inspiring the next generation of makers with MicroPython

    Reading Time: 3 minutes

    If you’re a fan of open-source technology, Gustavo Salvador Reynaga Aguilar is a name to know. An experienced educator with a passion for technology, Gustavo has spent nearly three decades teaching and inspiring students at CECATI 132 in Mexico. He’s worked with platforms like Arduino, Raspberry Pi, and BeagleBone, and is renowned for projects such as the OSHWi Octopus Badge, a creative electronic badge shared openly on GitHub.

    At the core of his work is a commitment to making technology accessible and empowering others to innovate – a philosophy that aligns perfectly with Arduino’s mission!

    Making connections at Pycon Latam

    At Pycon Latam 2024, held in Mazatlán, Sinaloa, Gustavo led the workshop “Primer Contacto con MicroPython” (which can be loosely translated as “MicroPython: First Contact”), introducing attendees to the power of MicroPython for programming microcontrollers. The session demonstrated how hardware and software can come together seamlessly with tools like the Arduino Nano RP2040 Connect (on sale for our Saint Valentine’s special until February 19th, 2025!) and Arduino Lab for MicroPython.

    The workshop was a hit among software developers, many of whom were impressed by the ease of implementing IoT and embedded solutions using Arduino and MicroPython. Gustavo’s approachable style and passion for teaching left a lasting impression, making the complex world of microcontrollers accessible to all.

    For those who missed his workshop, Gustavo is sharing the MicroPython manual he distributed at Pycon Latam on his GitHub account! This free resource is perfect for anyone looking to dive into MicroPython and start building their own projects. You can find it here.

    Why MicroPython matters

    MicroPython, a lightweight version of Python 3, has become increasingly popular in recent years, particularly for IoT applications. Its simplicity and efficiency make it an ideal choice for embedded systems, which combine hardware and software to perform specific tasks. 

    For makers and developers, MicroPython offers:

    • Ease of use: A simple syntax that’s perfect for anyone – beginners or not!
    • Versatility: Compatibility with various microcontrollers and IoT platforms.
    • Community-driven innovation: As an open-source language, it benefits from continuous development and shared resources.

    Gustavo’s workshop underscored these advantages, showing attendees how to program microcontrollers, manage GPIO pins, and connect to IoT platforms – all while using accessible, open-source tools. 

    And to make your life even easier, we’ve recently streamlined the entire process of installing libraries and managing MicroPython code on your Arduino boards by releasing the MicroPython Package Installer!

    Stay inspired by Gustavo’s open-source expertise

    Gustavo is not only a talented educator but also a powerful advocate for the open-source community. With more workshops planned for 2025 and beyond, his work continues to inspire makers and developers around the world.

    Follow him on X, GitHub, LinkedIn, and YouTube, or explore his projects on gustavoreynaga.com. Whether you’re just starting out or looking to deepen your expertise, Gustavo is a fantastic resource and an inspiring example of how open-source technology can transform education and innovation.

    The post Gustavo Reynaga: Inspiring the next generation of makers with MicroPython appeared first on Arduino Blog.

    Website: LINK

  • WOPR

    WOPR

    Reading Time: 2 minutes

    What’s inside?

    Raspberry Pi 4

    Raspberry Pi Touch Display 2

    • 5 V / 30 A power supply

    • 615 Adafruit NeoPixels

    • Bluetooth speaker

    A script runs on boot, which twinkles the NeoPixels in the traditional 1980s supercomputer colours: yellow and red.

    Another script can be run to play a short clip from the film WarGames on the Touch Display 2 screen, explaining the WOPR. At the press of a button on the Touch Display, our faux WOPR also parrots famous lines from the film, such as: “Shall we play a game?” and “How about a nice game of chess?”

    For those who wish to linger a little longer in the Maker Lab, Toby devised a game in which clips from 1980s films and music videos flash (a little too fast, in our opinion) up on the screen, with your job being to enthusiastically shout out where each clip is from.

    Authentic enclosure

    The body of the WOPR is a combination of 3D-printed plastics and laser-cut MDF painted in industrial grey, with Cricut silver lettering on the side. Everything is glued together, and a great deal of sanding was required to make it appear as though it is a sleek and very fancy contraption from the future.