What students and teachers in England want from a computing curriculum
The UK Government is undertaking the first major review of England’s curriculum and qualifications system since the current national curriculum was introduced in 2014. We believe that this is an excellent opportunity not simply to update the computing curriculum content, but to reconsider what computing education is for, who it serves, and how it prepares… The post What students and teachers in England want from a computing curriculum appeared first on Raspberry Pi Foundation.
The UK Government is undertaking the first major review of England’s curriculum and qualifications system since the current national curriculum was introduced in 2014. We believe that this is an excellent opportunity not simply to update the computing curriculum content, but to reconsider what computing education is for, who it serves, and how it prepares young people for life in a digital society. Today, we are launching a report featuring 6 key priorities for curriculum reform based on discussions we have had with students and teachers. <img fetchpriority="high" decoding="async" width="800" height="450" src="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-800x450.png" alt="Students and educators sit at a table discussing England's curriculum review and The Future of England's Computing Curriculum." class="wp-image-93234" srcset="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-800x450.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-300x169.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-500x281.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-768x432.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-450x253.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3-900x506.png 900w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-3.png 1344w" sizes="(max-width: 800px) 100vw, 800px" /> Putting students and teachers at the heart of the conversation Too often, curriculum reform happens around students and teachers rather than with them. Yet these are the people who experience computing education every day, and they have valuable insights into what is working, what is not, and what needs to change. Our new report is based on a series of student focus groups and teacher workshops held by us and the University of Cambridge in Manchester, London, and Cambridge during spring 2026. <img decoding="async" width="800" height="533" src="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-800x533.jpg" alt="Teachers sit at a table discussing England's curriculum review and The Future of England's Computing Curriculum." class="wp-image-93233" srcset="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2-900x600.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-2.jpg 2000w" sizes="(max-width: 800px) 100vw, 800px" /> The student discussions included young people currently studying computer science at GCSE and A level (ages 14–18), as well as young people who had decided to not continue with the subject. We also brought together 18 computing teachers from secondary schools across England to explore curriculum priorities and challenges for implementation. Although participants in our workshops had differing perspectives, they consistently pointed to the same underlying challenge: the current curriculum no longer reflects the realities of technology, work, or young people’s lives. “AI is everywhere now, we need to understand how it works, not just be told not to use it.” – Student, London In particular, many students highlighted a lack of confidence in their practical digital skills despite using technology constantly in everyday life. “I can code a bit, but I don’t know how to use Excel properly, that’s what I’ll actually need.” – Student, London Calls for a practical, relevant, inclusive, and future-facing curriculum Students and teachers are not calling for a less rigorous curriculum. Nor are they arguing that computing should lose its technical foundations, with teachers consistently emphasising the value of understanding computational thinking, programming, algorithms, data, and computer systems and networks. Instead, students and teachers want to make computing education more practical, relevant, inclusive, and future-facing. <img loading="lazy" decoding="async" width="800" height="533" src="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-800x533.jpg" alt="Teachers sit at a table discussing England's curriculum review and The Future of England's Computing Curriculum." class="wp-image-93236" srcset="https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-2048x1365.jpg 2048w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/06/The-Future-of-Englands-Computing-Curriculum-1-900x600.jpg 900w" sizes="auto, (max-width: 800px) 100vw, 800px" /> Teachers particularly emphasised the importance of helping students understand how AI systems function, including issues such as bias, training data, limitations, and ethical implications. Participants argued that computing education should help young people understand the technologies shaping their lives, not simply prepare them for examinations. Perhaps the strongest area of agreement was that curriculum reform will only succeed if it is matched by investment in teaching. Six key priorities for curriculum reform Based on our discussions with students and teachers, we have identified several priorities for curriculum reform. 1. Guarantee a core digital education for every young person All students should leave school with a strong foundation in digital literacy, online safety, data awareness, and AI literacy. These should be treated as essential components of modern education, not optional extras. 2. Modernise curriculum content The curriculum should focus on contemporary technologies and concepts, including AI, cybersecurity, and data, while trimming content that is overly specific, outdated, or disconnected from modern practice. Foundations such as programming, algorithms, and computational thinking should remain central. 3. Prioritise practical and applied learning Computing should be taught through making, experimentation, and problem solving. Project-based learning, physical computing, and relevant, real-world applications should become central approaches across all ages. 4. Introduce greater flexibility and specialisation The revised curriculum should balance a shared foundation with opportunities for students to specialise in areas aligned with their interests and aspirations. 5. Embed inclusion throughout the curriculum Any reforms should actively address barriers to participation by ensuring inclusive teaching approaches, diverse, relatable role models, and accessible learning experiences. 6. Invest in teachers and implementation Curriculum reform must be accompanied by sustained investment in teacher recruitment, professional development, and classroom resources. Without this, reforming the curriculum risks widening existing inequalities in provision. Read our full report We believe listening to students and teachers should be central to curriculum reform. You can read the full report now: Download the report PDF The post What students and teachers in England want from a computing curriculum appeared first on Raspberry Pi Foundation.
Young people’s computer programs get data from space
An amazing 25,707 participants had their code run on the International Space Station (ISS) this year, marking the European Astro Pi Challenge’s 10th anniversary in style. Yesterday, Astro Pi teams and their mentors received their official certificates and data — the final stage of this year’s challenge. On each certificate, participants can see the exact… The post Young people’s computer programs get data from space appeared first on Raspberry Pi Foundation.
An amazing 25,707 participants had their code run on the International Space Station (ISS) this year, marking the European Astro Pi Challenge’s 10th anniversary in style. Yesterday, Astro Pi teams and their mentors received their official certificates and data — the final stage of this year’s challenge. On each certificate, participants can see the exact time and the location of the ISS when their program was run. Congratulations to every student, teacher, volunteer, and parent involved. Your support made this historic year possible. We are also thrilled to share a special message from our 2025/26 Astro Pi Ambassador, ESA Astronaut Sophie Adenot. The European Astro Pi Challenge is an ESA Education project run in collaboration with the Raspberry Pi Foundation, implemented by ESEROs at a national level. It offers young people the amazing opportunity to conduct scientific investigations in space by writing computer programs that run on Raspberry Pi computers on board the International Space Station. Mission Zero: Art in orbit Mission Zero invites young people to create nature-inspired pixel art to display for the astronauts aboard the ISS. This year, we ran a total of 17,170 programs created by 24,408 participants. By using the Astro Pi’s colour sensor to set their background colours, these programs combined live data from the station with each team’s unique artwork. The results brought a vibrant reminder of nature and Earth to the crew. You can explore these creations on our interactive mosaic — can you find your team’s pixel art on the mosaic? <img loading="lazy" decoding="async" width="500" height="250" src="https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-500x250.png" alt="Pixel art creations made by young people who participated in Mission Zero." class="wp-image-93189" srcset="https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-500x250.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-300x150.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-768x384.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-1536x768.png 1536w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-800x400.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-450x225.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection-900x450.png 900w, https://www.raspberrypi.org/app/uploads/2026/06/MZ-selection.png 1600w" sizes="auto, (max-width: 500px) 100vw, 500px" /> A selection of Mission Zero pixel art submissions Mission Space Lab: The speed of light (and cameras) In Mission Space Lab, teams wrote Python programs to calculate the speed of the ISS. Using the Astro Pi sensors and Raspberry Pi High Quality cameras, 387 teams (representing 1,299 young people) achieved the prestigious ‘flight status’ and had their programs run in space. These teams are now receiving their raw data sets, which include images of Earth’s surface captured from 400km above. <img loading="lazy" decoding="async" width="500" height="375" src="https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-500x375.png" alt="Photos of the Earth’s surface that Mission Space Lab teams captured with their programs" class="wp-image-93192" srcset="https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-500x375.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-300x225.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-768x576.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-800x600.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-450x338.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-900x675.png 900w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design.png 1236w" sizes="auto, (max-width: 500px) 100vw, 500px" /> Earth observation images captured from the ISS by Mission Space Lab teams Doing science in space: The ‘blue shift’ mystery Science in orbit often brings surprises. This year, we noticed the colour balance in some ocean images was shifting toward a bright blue. After investigating, we found the camera’s white balance algorithm was reacting to ‘blue shift’. This occurs when the spectrum of light compresses as the Earth turns toward the camera at dawn. It’s a fantastic example of the real-world physics our participants encounter when dealing with orbital data! <img loading="lazy" decoding="async" width="500" height="281" src="https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-500x281.png" alt="Photos of the ocean with varying range of blue brightness." class="wp-image-93247" srcset="https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-500x281.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-300x169.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-768x432.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-800x450.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-450x253.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4-900x507.png 900w, https://www.raspberrypi.org/app/uploads/2026/06/Untitled-design-4.png 1400w" sizes="auto, (max-width: 500px) 100vw, 500px" /> A selection of images showing the ‘blue shift’ effect Inspiring even more young people and communities We know what a great opportunity Astro Pi is and how much of an impact it can have on participants and their communities. So we constantly challenge ourselves to widen our reach and bring the challenge to communities around the UK and Ireland, especially those that don’t normally get the chance to send code to space. This year, we visited schools, clubs, and science events. We also trained teachers and volunteers to help us share the challenge. <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-500x333.jpg" alt="A young person colouring a pixel art design." class="wp-image-93204" srcset="https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-2048x1365.jpg 2048w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/06/AstroPi-Norwich-2026-3-900x600.jpg 900w" sizes="auto, (max-width: 500px) 100vw, 500px" /> A young person designing Mission Zero pixel art What’s next? That’s a wrap for the 2025/26 challenge, but the journey doesn’t end here. On Friday 12 June, ESA astronaut Pablo Álvarez Fernández will answer questions submitted by the Mission Space Lab teams. You can watch the livestreamed event on YouTube. Save the date: Astro Pi 2026/27 launches Monday 14 September 2026 Mission Zero: We’ll be selecting new code examples from this year’s Mission Zero submissions for our next project guide Mission Space Lab: We have some exciting technical updates coming for the next cohort of Space Lab teams In the meantime, stay curious, space travelers. The journey has only just begun! The post Young people’s computer programs get data from space appeared first on Raspberry Pi Foundation.
Support your young people with our AI literacy resources
At the Raspberry Pi Foundation, we believe that alongside learning to code, a crucial part of computing education is building AI literacy skills. Amidst the rapid pace of development and the growing impact of AI tools, it is increasingly important for educators everywhere to feel equipped to address the topic of AI with their learners,… The post Support your young people with our AI literacy resources appeared first on Raspberry Pi Foundation.
At the Raspberry Pi Foundation, we believe that alongside learning to code, a crucial part of computing education is building AI literacy skills. Amidst the rapid pace of development and the growing impact of AI tools, it is increasingly important for educators everywhere to feel equipped to address the topic of AI with their learners, to help young people understand their world, be responsible users of AI technologies, and prepare to become the future creators of these technologies. We work at the leading edge of AI education, combining research and industry expertise with practical classroom experience to define what AI means for computing education, and how to best support teachers and learners to understand these technologies. Whether you are a teacher, a Code Club mentor, or a parent, we have a wide range of free resources to help you teach your young people about AI, and learn more about it yourself. Explore our teaching resources We offer a variety of teaching materials to help you bring AI into your setting. You do not need to be a professional educator or have a background in computer science to use these resources, and we provide everything you need to guide your learners with confidence. Experience AI is our free AI literacy programme, developed in collaboration with Google DeepMind. Through ready-to-use classroom resources, including lesson plans, presentations, and hands-on activities, the programme helps educators all over the world teach their learners about how AI works, as well as its wider social and ethical implications. You and your learners will investigate AI tools, explore real-world uses of AI, and engage with critical issues such as bias, fairness, and transparency, helping learners to understand AI and use it responsibly. The lessons currently available are designed for learners aged 11–14, and we are releasing resources for other age groups this year. To help bring Experience AI to more educators and learners around the world, we work with a global network of partner organisations, who help us provide tailored and translated resources and offer localised, high-quality training and support for educators in their regions. Experience AI resources are currently available in 19 languages, and have already been downloaded in more than 180 countries. In recognition of its impact, in 2025 Experience AI was named a laureate of the UNESCO King Hamad Bin Isa Al-Khalifa Prize for the Use of ICT in Education. “[Experience AI] has definitely changed my outlook on AI. I went from knowing nothing about it to understanding how it works, why it acts in certain ways, and how to actually create my own AI models and what data I would need for that. I would 100% recommend others who don’t know much about AI to try it out.” – Student, Arthur Mellows Village College, UK If you are looking to introduce school-aged young people to AI with short, beginner-friendly coding and digital making projects, take a look at our collection of Code Club projects about AI and machine learning. These projects are a great way to spark curiosity and investigate how AI and machine learning works. In the projects, learners get hands-on with a range of AI tools and platforms, and explore different applications of AI, such as image recognition, voice recognition, and (for learners aged 13 and over) generative AI. For example, in Doodle detector, learners use Machine Learning for Kids with Scratch to create a machine learning application that can identify what they have drawn. The projects feature clear step-by-step instructions, and many include video tutorials, to help learners work at their own pace and in a style that suits them. We also provide mentor guidance to help you prepare. <img loading="lazy" decoding="async" width="1999" height="1050" src="https://www.raspberrypi.org/app/uploads/2026/06/image1.png" alt="An illustration of an image classification application correctly identifying a drawing of an apple. " class="wp-image-93155" style="aspect-ratio:1.9038175508180466;width:708px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/06/image1.png 1999w, https://www.raspberrypi.org/app/uploads/2026/06/image1-300x158.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/image1-500x263.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/image1-768x403.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/image1-1536x807.png 1536w, https://www.raspberrypi.org/app/uploads/2026/06/image1-800x420.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/image1-450x236.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/image1-900x473.png 900w" sizes="auto, (max-width: 1999px) 100vw, 1999px" /> Learners can explore topics such as image classification through our collection of Code Club projects about AI and machine learning For resources to support older learners to build their understanding of AI, head to Ada Computer Science. Ada Computer Science is our free online platform for computer science students and teachers, developed in partnership with the University of Cambridge. It provides comprehensive resources for learners aged 14–19 across the breadth of computer science, including detailed learning materials about AI and machine learning. The materials include helpful definitions, clear explanations, and carefully designed self-marking questions to support young people’s learning. <img loading="lazy" decoding="async" width="1300" height="731" src="https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event.png" alt="Learners aged 14–19 can build their knowledge of AI and machine learning on our Ada Computer Science platform" class="wp-image-93156" style="aspect-ratio:1.7784246915213868;width:804px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event.png 1300w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-300x169.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-500x281.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-768x432.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-800x450.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-450x253.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/Ada-CS-event-900x506.png 900w" sizes="auto, (max-width: 1300px) 100vw, 1300px" /> Learners aged 14–19 can build their knowledge of AI and machine learning on our Ada Computer Science platform Explore our learning and training opportunities for educators To help you build your knowledge around AI technologies and grow your confidence to teach your young people about this important topic, we offer a range of learning resources and professional development opportunities, all for free. They are open to everyone, so we invite you to dive into any that interest you. For flexible, self-paced learning options, take a look at the following free online courses, which cover a range of topics within AI: Introducing AI: Investigate how AI systems work and how to evaluate them, and explore the benefits, risks, and ethical issues related to them. This course is made up of 2 modules, and takes around 2–4 hours to complete. AI literacy for teachers and school leaders: Learn how to support your students and staff to understand, use, and critically assess AI technologies. This course takes around 1–2 hours to complete. Machine learning and AI: Discover machine learning and how it works, and train your own AI models using free online tools. This course is made up of 4 modules, and takes around 4–8 hours to complete. <img loading="lazy" decoding="async" width="2560" height="1440" src="https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-scaled.png" alt="Learn more about AI through our free online courses for educators " class="wp-image-93159" style="width:694px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-scaled.png 2560w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-300x169.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-500x281.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-768x432.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-1536x864.png 1536w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-2048x1152.png 2048w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-800x450.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-450x253.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/introducing-ai-course-card-2-900x506.png 900w" sizes="auto, (max-width: 2560px) 100vw, 2560px" /> Learn more about AI through our free online courses for educators You might also be interested in Hello World, our free magazine and podcast for educators teaching computing and AI. Each magazine is packed with resources, discussions, news, and ideas, and you can subscribe to receive each issue as soon as it is released. The next issue, coming in July, will focus on critical thinking in the age of AI. You can download our previous issues to explore articles about a variety of topics within AI too. What’s more, you can continue your learning with the Hello World podcast, which accompanies the magazine and features discussions with educators and researchers from around the world. Visit the podcast page to discover previous episodes exploring vibe coding and programming education, AI education around the world, and more. <img loading="lazy" decoding="async" width="1200" height="628" src="https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner.jpg" alt="Hello World Issue 29 - Safety & security" class="wp-image-93160" style="aspect-ratio:1.9108551930049051;width:790px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner.jpg 1200w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-300x157.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-500x262.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-768x402.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-800x419.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-450x236.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/06/11452_HW_29_LinkedIn_Banner-900x471.jpg 900w" sizes="auto, (max-width: 1200px) 100vw, 1200px" /> Hello World Issue 29 – Safety & security To learn about research-informed teaching strategies to help you as you explore AI with your learners, you can read these short Pedagogy Quick Reads: Anthropomorphism: Explore how to help learners avoid thinking of AI systems as human-like, to support their understanding. Computational Thinking 2.0: Consider how computational thinking is evolving and how to help learners develop the computational thinking skills they need to understand modern digital systems involving AI. Feedback literacy: Explore how feedback literacy can help teachers and learners interact effectively with feedback generated by AI tools. <img loading="lazy" decoding="async" width="1600" height="1281" src="https://www.raspberrypi.org/app/uploads/2026/06/image2.png" alt="A Pedagogy Quick Read entitled ‘The effects of anthropomorphisation on students’ mental models of AI’." class="wp-image-93161" style="aspect-ratio:1.249041611486722;width:574px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/06/image2.png 1600w, https://www.raspberrypi.org/app/uploads/2026/06/image2-300x240.png 300w, https://www.raspberrypi.org/app/uploads/2026/06/image2-500x400.png 500w, https://www.raspberrypi.org/app/uploads/2026/06/image2-768x615.png 768w, https://www.raspberrypi.org/app/uploads/2026/06/image2-1536x1230.png 1536w, https://www.raspberrypi.org/app/uploads/2026/06/image2-800x641.png 800w, https://www.raspberrypi.org/app/uploads/2026/06/image2-450x360.png 450w, https://www.raspberrypi.org/app/uploads/2026/06/image2-900x721.png 900w" sizes="auto, (max-width: 1600px) 100vw, 1600px" /> For more insights from computing education research, you can join our monthly online research seminars. Our 2026 research seminar series focuses on teaching about AI across the curriculum, delving into research on teaching and learning about AI from disciplines beyond computer science, including the arts, sciences, and humanities. Our next seminar takes place on 16 June, and you can catch up on previous seminars from our current series here. You can also explore our archive of recordings from previous seminar series, with themes including teaching about AI and data science, teaching programming (with or without AI), and more. Bring AI into your classroom today All of these resources and learning opportunities are available to anyone interested in educating young people about AI, anywhere in the world. We hope they help you gain understanding, confidence, and inspiration to guide your young learners to engage with AI safely and responsibly, and to learn valuable skills that will help them navigate their world. “Let the students explore, advance, and grow. And who knows — maybe one of our students will go on to become a mentor or leader in this field someday.” – Ana Judith Zavaleta, computer science teacher, Mexico, speaking about Experience AI If you are in the UK, you can also use these resources to get involved with the first-ever AI Awareness Day, a new nationwide campaign designed to build AI literacy across UK schools, which is taking place on 4 June. The post Support your young people with our AI literacy resources appeared first on Raspberry Pi Foundation.
Building confidence to teach AI in the classroom
Hayley McKechnie is a computing lead at a primary school in the East of England, who shares in this blog how she supports her students and her fellow teachers to build confidence around artificial intelligence (AI). She developed her skills through training delivered by Parent Zone, our partner for Experience AI in the UK. Artificial… The post Building confidence to teach AI in the classroom appeared first on Raspberry Pi Foundation.
Hayley McKechnie is a computing lead at a primary school in the East of England, who shares in this blog how she supports her students and her fellow teachers to build confidence around artificial intelligence (AI). She developed her skills through training delivered by Parent Zone, our partner for Experience AI in the UK. Artificial intelligence is part of everyday life for young people, but teaching students what AI is, how it works, and why it should be used responsibly can still be a challenge. As a computing lead at a school in the East of England, the Experience AI programme has played a central role in building my confidence, as well as that of my colleagues, when it comes to teaching AI in the classroom. Through professional development, practical classroom materials, and a strong focus on ethics, the programme has helped me bring AI to life in a way that feels accessible, age-appropriate, and responsible. Building confidence through training I began my AI education journey by attending training sessions hosted by Parent Zone to strengthen my own understanding of artificial intelligence. This felt like an important first step, because many teachers are learning about AI alongside their students. <img loading="lazy" decoding="async" width="1999" height="1333" src="https://www.raspberrypi.org/app/uploads/2026/05/image1-2.jpg" alt="Educator in the classroom with Experience AI" class="wp-image-93142" style="aspect-ratio:1.4996652532916759;width:742px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image1-2.jpg 1999w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/image1-2-900x600.jpg 900w" sizes="auto, (max-width: 1999px) 100vw, 1999px" /> The training really helped me understand how AI actually works. That’s so important, because if you’re not confident in your own understanding, it’s very difficult to explain it clearly to children. At first, I trialled one or two lessons with my students, introducing concepts gradually as AI tools became more visible in everyday life. As my confidence grew, I started using more of the materials, and this year I plan to deliver the full six-week unit as a dedicated part of our computing curriculum. What I particularly like is how clear and straightforward the programme is. The training makes it easy for teachers to pick up, while still giving students a solid foundation in how AI works. Before starting AI lessons, I always ground learning in familiar examples, such as voice assistants, search engines, and design tools. This helps students see that AI isn’t abstract; it’s already part of their everyday lives. Making ethics central One of the biggest strengths of the Experience AI training, in my view, is its strong emphasis on ethics and critical thinking. Rather than presenting AI as something to trust automatically, it encourages students to question and evaluate the technology they use. <img loading="lazy" decoding="async" width="1999" height="1500" src="https://www.raspberrypi.org/app/uploads/2026/05/image2.jpg" alt="Young learners in the classroom using Experience AI resoruces " class="wp-image-93144" style="aspect-ratio:1.3326722855726327;width:704px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image2.jpg 1999w, https://www.raspberrypi.org/app/uploads/2026/05/image2-300x225.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/image2-500x375.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/image2-768x576.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/image2-1536x1153.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image2-800x600.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/image2-450x338.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/image2-900x675.jpg 900w" sizes="auto, (max-width: 1999px) 100vw, 1999px" /> I want my students to understand that AI can be helpful, but it isn’t infallible and shouldn’t be relied on blindly. For example, I’ve shown students how AI-generated search results can sometimes be inaccurate. It’s a simple but effective way to demonstrate why human judgement still matters. These kinds of discussions help students understand both the potential and the limitations of AI, reinforcing the idea that technology should support thinking rather than replace it. Learning alongside colleagues Beyond my own classroom, I’ve also used Experience AI training to support other teachers. As part of my role coordinating computing across schools in my region, I organised a cluster meeting for 20 computing leads from across Essex, Suffolk, and Norfolk. <img loading="lazy" decoding="async" width="1080" height="566" src="https://www.raspberrypi.org/app/uploads/2026/05/image3-4.png" alt="" class="wp-image-93145" style="aspect-ratio:1.9081422588201888;width:712px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image3-4.png 1080w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-300x157.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-500x262.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-768x402.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-800x419.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-450x236.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image3-4-900x472.png 900w" sizes="auto, (max-width: 1080px) 100vw, 1080px" /> The session gave teachers the opportunity to share experiences, explore how AI could be introduced in age-appropriate ways, and discuss how to embed ethical considerations across the curriculum. A Parent Zone trainer led the session and helped deepen our understanding. Many computing teachers are still getting to grips with AI themselves. The training helped me feel more confident, and that’s something I’ve been keen to pass on to others. Feeling inspired? You can access all of our AI literacy and safety resources for free via the Experience AI website. Start exploring today and discover classroom-ready lesson plans, slide decks, and activities. Interested in joining the next group of teachers to be trained on Experience AI? If you’re a UK teacher, visit Parent Zone’s website to enrol in the next cohort of educators. Or if you’re outside the UK, visit our Partners page to find out about teacher training sessions in your country. The post Building confidence to teach AI in the classroom appeared first on Raspberry Pi Foundation.
Can AI support creativity? What educators can learn from creative machine learning
Can AI support creativity? The technology is often framed as threatening creative work either by automating it or by encouraging imitation. But Professor Rebecca Fiebrink’s work in creative machine learning suggests a more useful way to think about this relationship. In our March research seminar, she showed how machine learning can help people work with… The post Can AI support creativity? What educators can learn from creative machine learning appeared first on Raspberry Pi Foundation.
Can AI support creativity? The technology is often framed as threatening creative work either by automating it or by encouraging imitation. But Professor Rebecca Fiebrink’s work in creative machine learning suggests a more useful way to think about this relationship. In our March research seminar, she showed how machine learning can help people work with meaningful data, communicate ideas through examples, and build new kinds of creative projects. <img loading="lazy" decoding="async" width="1999" height="1333" src="https://www.raspberrypi.org/app/uploads/2026/05/image7.jpg" alt="Rebecca Fiebrink." class="wp-image-93096" style="aspect-ratio:1.4996652532916759;width:710px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image7.jpg 1999w, https://www.raspberrypi.org/app/uploads/2026/05/image7-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/image7-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/image7-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/image7-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image7-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/image7-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/image7-900x600.jpg 900w" sizes="auto, (max-width: 1999px) 100vw, 1999px" /> Rebecca Fiebrink is Professor of Creative Computing at the Creative Computing Institute, University of the Arts London. Our current seminar series focuses on teaching applied AI and how educators of subjects beyond computing can make AI and machine learning relevant in their classroom. We were delighted to have Rebecca join us to share insights about the place of machine learning in artistic creation. In her talk, Rebecca explored three connected questions: How machine learning can be valuable to musicians, artists, and other creators What machine learning tools for creators should look like What creators need to know about machine learning in order to use it effectively Using movement, sound, and image data to teach about machine learning One of the seminar’s key ideas was that machine learning can help creators work with forms of data that already matter to them. Rebecca showed that useful data can come from many sources, including microphones, webcams, phones, wearables, sensors, and body movement. She argued that collecting data is often relatively easy, while interpreting and using it is much harder. This suggests a different starting point for AI education. Instead of beginning with a large dataset prepared by somebody else, learners can start with data that is meaningful in their own context. For instance, data about hand gestures can be linked to different musical rhythms, colours, or game actions. <img loading="lazy" decoding="async" width="2220" height="1478" src="https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01.png" alt="Visual examples of how hand gestures can be associated with rhythm, video game actions, or visuals using machine learning." class="wp-image-93099" style="aspect-ratio:1.502053588891062;width:802px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01.png 2220w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-300x200.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-500x333.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-768x511.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-1536x1023.png 1536w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-2048x1363.png 2048w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-800x533.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-450x300.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/Screenshot-2026-05-28-at-10.50.01-900x599.png 900w" sizes="auto, (max-width: 2220px) 100vw, 2220px" /> From hand gestures to rhythms and game actions. Images from the speaker’s presentation. What counts as input? The seminar also points to a broader shift in how we think about input if we consider creative work. Traditional computing often treats input as something abstract and controlled: a click, a typed command, or a button press. But many creative practices do not work like that. They depend on timing, gesture, rhythm, touch, sound, and movement. Instead of asking learners to translate everything into words or code first, Fiebrink suggested that educators can use machine learning to allow learners to begin with movement, demonstration, or sound. This is especially relevant in art forms shaped by flow and physical expression, such as music, dance, performance, and interactive media. Educators can use machine learning to allow learners to begin with movement, demonstration, or sound [instead of with code]. That creates interesting possibilities for teaching. AI does not have to be explored only through screens, prompts, and abstract models. It can also be approached through embodied activities, where learners use gestures, performance, and experimentation to see how an AI system responds. This can make machine learning feel more connected to forms of making that young people already understand. Teaching machine learning through examples A second important theme in the seminar was that machine learning allows people to instruct computers through data and examples. Rebecca suggested that this can be especially valuable in creative and embodied work, where what a person wants to express may be difficult to describe in words, maths, or code alone. <img loading="lazy" decoding="async" width="1753" height="1240" src="https://www.raspberrypi.org/app/uploads/2026/05/image1-1.png" alt="Contrasting pictures of painting and violin playing compared to a snapshot of code." class="wp-image-93100" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image1-1.png 1753w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-300x212.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-500x354.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-768x543.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-1536x1087.png 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-800x566.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-450x318.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image1-1-900x637.png 900w" sizes="auto, (max-width: 1753px) 100vw, 1753px" /> The seminar suggested that data and examples can communicate creative intent in ways that code or language cannot always capture. One of the strongest examples in the seminar was ‘Wekinator‘, a tool Rebecca has been developing since 2008. She described the tool’s approach as ‘interactive machine learning’: users demonstrate training examples, train a model, test it in real time, then modify their examples and repeat the process. This is a useful example for the classroom because it shows that training a machine learning model is not a single event, after which the model is trained and finished. Instead it is an iterative process. With Wekinator, learners can try something out, observe the result, and improve the system by changing the examples they provide. That makes ideas such as testing, evaluation, and bias much easier to discuss. Supporting creativity and learner agency Rebecca also argued that machine learning can help more people become creators. She contrasted large, one-size-fits-all systems that encourage users to imitate existing styles with smaller, more personal systems that can be trained on new data for specific purposes. She captured this contrast clearly, from prompts such as ‘Write music like Bach!’ to examples of personalised tools and interfaces. <img loading="lazy" decoding="async" width="1753" height="1240" src="https://www.raspberrypi.org/app/uploads/2026/05/image2-2.png" alt="Examples from the seminar showing how large models can make it easier for novices to conform to familiar creative styles like those of Bach or Monet." class="wp-image-93104" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image2-2.png 1753w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-300x212.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-500x354.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-768x543.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-1536x1087.png 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-800x566.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-450x318.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image2-2-900x637.png 900w" sizes="auto, (max-width: 1753px) 100vw, 1753px" /> Examples from the seminar showing how large models can make it easier for novices to conform to familiar creative styles. This is an important distinction in teaching and learning. If learners only use AI tools to reproduce familiar outputs, then creative work can become narrow and formulaic. But if they can build or train systems around their own interests, intentions, and materials, then machine learning can support experimentation and authorship. If [learners] can build or train systems around their own interests, intentions, and materials, then machine learning can support experimentation and authorship. Teaching AI without turning it into a black box In the final part of the seminar, Rebecca moved from examples to teaching principles. One of the clearest was that machine learning should be taught at a high level with minimal maths, but not as a black box. Learners do not need advanced mathematics to start exploring machine learning meaningfully, but they do need to understand that: Machine learning models are built from data Models make predictions based on patterns People can inspect, test, and improve models Rebecca also argued that small data and interactive machine learning can be highly effective. She highlighted quick experimentation, creative usefulness, and the opportunity to build intuition about ideas such as outliers, features, regularisation, and bias in data. Small-scale activities can make technical ideas more visible and manageable for learners. <img loading="lazy" decoding="async" width="1753" height="1240" src="https://www.raspberrypi.org/app/uploads/2026/05/image4.png" alt="""" class="wp-image-93108" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image4.png 1753w, https://www.raspberrypi.org/app/uploads/2026/05/image4-300x212.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image4-500x354.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image4-768x543.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1536x1087.png 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image4-800x566.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image4-450x318.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image4-900x637.png 900w" sizes="auto, (max-width: 1753px) 100vw, 1753px" /> Small-data, interactive machine learning can support experimentation and build understanding of how models work. Why this matters for teaching Rebecca ended on an inspiring note: she argued that learning and teaching creative machine learning is both worth doing and possible. She pointed to a growing set of tools that support experimentation and original creative work without much maths or coding, including Wekinator, Teachable Machine, Micro:bit CreateAI, and more. The seminar also addressed some important limitations. Rebecca warned that commercial tools are not always good at supporting learning or genuine creative work. She also discussed the difficulty of making generative AI tools safe for children, noting the need for built-in filters, moderation, prompt design, and extensive testing. Therefore, what’s important is to think about what learners are actually learning, and to make space for experimentation without losing sight of safety and critical thinking. Join our next seminar Our research seminars brings together educators and researchers to explore key questions in computing education. Next in our series on applied AI, Prof. Gianfranco Polizzi (University of Birmingham, UK) will talk about media literacy in the age of AI. Sign up now to join the seminar on 16 June, 17:00 BST: I want to sign up The post Can AI support creativity? What educators can learn from creative machine learning appeared first on Raspberry Pi Foundation.
Celebrating young tech creators at Coolest Projects Ireland 2026
In April, young tech creators gathered at Explorium in Dublin for Coolest Projects Ireland 2026, a lively, creative celebration of young makers and their digital projects. This year’s event was held as part of Kinia’s Creative Technology Week, and welcomed over 100 young people, showcasing more than 80 incredible tech projects. Participants included young people… The post Celebrating young tech creators at Coolest Projects Ireland 2026 appeared first on Raspberry Pi Foundation.
In April, young tech creators gathered at Explorium in Dublin for Coolest Projects Ireland 2026, a lively, creative celebration of young makers and their digital projects. This year’s event was held as part of Kinia’s Creative Technology Week, and welcomed over 100 young people, showcasing more than 80 incredible tech projects. Participants included young people from Code Clubs, CoderDojos, and schools across Ireland, as well as young creators taking part individually. <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-500x333.jpg" alt="Young people sat in an auditorium wearing Coolest Projects t-shirts." class="wp-image-93082" srcset="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16-900x600.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-16.jpg 2000w" sizes="auto, (max-width: 500px) 100vw, 500px" /> With creations ranging from coding projects to hardware builds to AI systems, the event provided a wonderful opportunity to celebrate the creativity and passion of young tech creators across Ireland. Here are some project highlights from the day. Jake | Enter the Kindergarten, Scratch Jake’s project, Enter the Kindergarten, is a Scratch game where the player has to dodge babies and obstacles in a childcare setting. Jake was inspired to create the game after overcoming his own fear of babies. Here is what he shared with us about his project: “Well, I used to be afraid of babies. So one Saturday morning, me and my dad came up with the idea to make a kindergarten game where you have to get to the end of the kindergarten.” Aarabhi | Mystical Waterfall, Hardware To build her hardware project, Mystical Waterfall, Aarabhi used a Raspberry Pi Pico to create a nature scene, featuring running water and LED lights. Aarabhi spoke to us about why she wanted to enter Coolest Projects: <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-500x333.jpg" alt="A young person standing next to their project." class="wp-image-93084" srcset="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi-900x600.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Aarabhi.jpg 2000w" sizes="auto, (max-width: 500px) 100vw, 500px" /> “I watched a Netflix series, The InBESTigators, where children showcase their science projects. After watching it, it was my dream to do the same!” Arittra | Cara, AI Arittra’s project, Cara, was chosen as the judges’ favourite in the AI category this year. Cara, which means ‘friend’ in Irish, is a large language model (LLM) that provides information on the Irish legal, housing, and administrative systems, aimed at supporting people who have emigrated to Ireland. Arittra told us more about the challenges he faced whilst building his project: <img loading="lazy" decoding="async" width="500" height="375" src="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-500x375.png" alt="A young person working at a computer at a Coolest Projects event." class="wp-image-93086" srcset="https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-500x375.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-300x225.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-768x576.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-1536x1152.png 1536w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-800x600.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-450x338.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra-900x675.png 900w, https://www.raspberrypi.org/app/uploads/2026/05/Coolest-Projects-Ireland-Arittra.png 1800w" sizes="auto, (max-width: 500px) 100vw, 500px" /> “One of the key problems with artificial intelligence is that they hallucinate, but I found a countermeasure to it. I trained it on search variety and gave it backup data, so if one part of the server starts hallucinating, another part automatically steps into its place to find maximum accuracy.” Get involved Congratulations and thank you to each and every young creator who joined us for Coolest Projects Ireland 2026. Sharing your projects, celebrating your achievements, and inspiring others is what Coolest Projects is all about. Missed the fun in Dublin, or want to take your projects to a global stage? Take part in the Coolest Projects 2026 online showcase, which is open for entries from young creators anywhere in the world until 27 May. Look out for more in-person Coolest Projects events taking place around the world over the rest of the year, too! Find out more at coolestprojects.org. The post Celebrating young tech creators at Coolest Projects Ireland 2026 appeared first on Raspberry Pi Foundation.
Beyond content: Helping teachers feel ready to teach AI
We are working with partner organisations around the world to support teachers in building confidence with AI in the classroom through our Experience AI programme. In this guest post, Catarina Marques from our partner TUMO Portugal shares what the organisation is learning from delivering training to educators. Whenever we run Experience AI training sessions, we… The post Beyond content: Helping teachers feel ready to teach AI appeared first on Raspberry Pi Foundation.
We are working with partner organisations around the world to support teachers in building confidence with AI in the classroom through our Experience AI programme. In this guest post, Catarina Marques from our partner TUMO Portugal shares what the organisation is learning from delivering training to educators. Whenever we run Experience AI training sessions, we keep coming back to the same thing: teachers are not lacking interest in AI, what they are lacking is time. Time to explore the technology and tools, time to talk about them with colleagues, and time to work out what they really mean for their classrooms. <img loading="lazy" decoding="async" width="467" height="700" src="https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-467x700.jpg" alt="A group of people sat around a table with laptops." class="wp-image-93035" srcset="https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-467x700.jpg 467w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-167x250.jpg 167w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-768x1152.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-1024x1536.jpg 1024w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-800x1200.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-450x675.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1-900x1350.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-1.jpg 1365w" sizes="auto, (max-width: 467px) 100vw, 467px" /> And that matters, because AI is not something schools can just put off until later. It is already here. Students are hearing about it, using it, and forming opinions about it. Teachers are being asked to respond to it now, often while still trying to make sense of it themselves. More than delivering content The Experience AI teacher training is about more than educators to a set of resources. It is about helping them feel truly ready to take the Experience AI resources into the classroom and use them effectively with their students. <img loading="lazy" decoding="async" width="467" height="700" src="https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-467x700.jpg" alt="A group of people sat around a table with laptops." class="wp-image-93041" srcset="https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-467x700.jpg 467w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-167x250.jpg 167w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-768x1152.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-1024x1536.jpg 1024w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-800x1200.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-450x675.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5-900x1350.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-5.jpg 1365w" sizes="auto, (max-width: 467px) 100vw, 467px" /> What we see again and again is that teachers need space to stop and think. AI is moving quickly, and schools do not always have the time or support to keep pace. New tools are developed all the time. Expectations keep shifting. There is a lot of noise, and not always much room to pause and ask: what is actually useful here? What do we need to understand better? In our experience, that is where real learning starts: not in rushing through information, but in discussing it, debating it, and testing ideas together. Listening matters One of the most valuable parts of these training sessions is the part where teachers start talking to each other. They bring real questions into the room. Which AI tools can actually help with their work? How should they think about ethics? How do they talk about AI safety with students? How do they respond to something that may feel both useful and worrying at the same time? <img loading="lazy" decoding="async" width="467" height="700" src="https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-467x700.jpg" alt="A group of people sat around a table with laptops." class="wp-image-93036" srcset="https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-467x700.jpg 467w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-167x250.jpg 167w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-768x1152.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-1024x1536.jpg 1024w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-800x1200.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-450x675.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2-900x1350.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-2.jpg 1365w" sizes="auto, (max-width: 467px) 100vw, 467px" /> There is often confusion, and sometimes there is resistance too. That makes sense; this is still new territory for many schools. But there is also a real appetite to learn, especially because support in this area can still feel limited. That is why listening is such an important part of our training. Teachers need space to reflect, compare experiences, and hear how others are approaching the same challenges. Very often, understanding grows through that process. Play helps Another thing we feel strongly about is that the training has to be engaging. AI can feel intimidating. If the atmosphere is too heavy, it can be easy for people to step back from it. That is why the hands-on and playful side of Experience AI is so important. Team activities, discussion, and even a bit of healthy competition change the energy in the room. People get involved. They relax. They start exploring instead of worrying about getting everything right. <img loading="lazy" decoding="async" width="467" height="700" src="https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-467x700.jpg" alt="A group of people sat around a table with laptops." class="wp-image-93038" srcset="https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-467x700.jpg 467w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-167x250.jpg 167w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-768x1152.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-1024x1536.jpg 1024w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-800x1200.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-450x675.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3-900x1350.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-3.jpg 1365w" sizes="auto, (max-width: 467px) 100vw, 467px" /> That matters for teachers, and it matters for students too. When teachers experience this kind of learning for themselves, it becomes easier for them to imagine creating it in their own classrooms. Play is not separate from the learning here — it is part of what makes it stick. Preparing schools for now For us, this work feels urgent. Schools need the language, confidence, and literacy to engage with AI now, not in a few years’ time. <img loading="lazy" decoding="async" width="467" height="700" src="https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-467x700.jpg" alt="A group of people standing with laptops." class="wp-image-93040" srcset="https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-467x700.jpg 467w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-167x250.jpg 167w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-768x1152.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-1024x1536.jpg 1024w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-800x1200.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-450x675.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4-900x1350.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/tumo-4.jpg 1365w" sizes="auto, (max-width: 467px) 100vw, 467px" /> What teachers need most is not endless hype or more pressure. They need time to explore, time to discuss, time to understand, and time to build confidence. Experience AI has offered a way to begin that process. If we want young people to engage critically and confidently with AI, we have to start by giving teachers the chance to do the same. If you want to find out more about Experience AI, visit our website experience-ai.org The post Beyond content: Helping teachers feel ready to teach AI appeared first on Raspberry Pi Foundation.
Start small, dream big with Code Club: Become an Incubator Partner
Imagine places for young people to not just learn to use technology but to understand it, shape it, and build with it. That’s what you can create by partnering with the Raspberry Pi Foundation on Code Club, the global movement of computing clubs where school-age young people develop the confidence to create with digital technologies.… The post Start small, dream big with Code Club: Become an Incubator Partner appeared first on Raspberry Pi Foundation.
Imagine places for young people to not just learn to use technology but to understand it, shape it, and build with it. That’s what you can create by partnering with the Raspberry Pi Foundation on Code Club, the global movement of computing clubs where school-age young people develop the confidence to create with digital technologies. We’re looking for organisations worldwide to join us as new Incubator Partners and bring Code Club to young people in their regions. <img loading="lazy" decoding="async" width="500" height="293" src="https://www.raspberrypi.org/app/uploads/2026/05/image2-1-500x293.png" alt="" class="wp-image-93051" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image2-1-500x293.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image2-1-300x176.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image2-1-450x263.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image2-1.png 600w" sizes="auto, (max-width: 500px) 100vw, 500px" /> What is the Incubator programme about? Through our non-funded 12-month global Incubator programme, we support a diverse network of organisations to establish and grow free Code Clubs in their communities. By combining your local knowledge and community connections with our tried and tested projects, training, and support, you can build something that lasts and grows. <img loading="lazy" decoding="async" width="500" height="375" src="https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-500x375.jpg" alt="A group of educators at a conference." class="wp-image-91620" srcset="https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-500x375.jpg 500w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-300x225.jpg 300w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-768x576.jpg 768w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-800x600.jpg 800w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-450x338.jpg 450w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526-900x675.jpg 900w, https://www.raspberrypi.org/app/uploads/2025/10/IMG_1526.jpg 1000w" sizes="auto, (max-width: 500px) 100vw, 500px" /> Attendees at our Code Club Partner meetup in Sri Lanka in 2025 As a partner, you’ll join a global network of organisations all working toward the same goal: giving young people access to free, inclusive, and inspiring opportunities to learn coding and digital making. “Many of our partners are non-profit and volunteer-led, driven by a real commitment to their communities. It’s incredibly inspiring — and we’re excited to keep growing this global network of partners so even more young people can benefit.” – Sonja Bienert, Senior Global Partnerships Manager By joining, you’ll get partner-specific access to events like global meetups, online workshops, and Coolest Projects, as well as materials to support your fundraising. Your Code Clubs will be able to use our wide range of free, creative projects for young people, including activities about AI, and activities that support clubs with limited devices. And you’ll be able to build collaborations with other partners in the network. Real stories from our partners Across the world, our partners are already transforming lives. Full Stack Vision Foundation, Aruba In Aruba, Full Stack Vision Foundation has grown Code Club from a single library session into a thriving network of ten clubs: “Giving young people the ability to make, create, and sustain technological solutions is what the Caribbean wants.” – Bruce Harms, Founder and President of Full Stack Vision Foundation <img loading="lazy" decoding="async" width="500" height="334" src="https://www.raspberrypi.org/app/uploads/2026/05/image1-500x334.jpg" alt="Three smiling young tech creators at a computer screen during a Code Club session in Aruba." class="wp-image-93052" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image1-500x334.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/image1-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/image1-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/image1-800x534.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/image1-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/image1-900x600.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/image1.jpg 1280w" sizes="auto, (max-width: 500px) 100vw, 500px" /> By adapting projects to reflect local culture — like reimagining a Scratch project around aloe vera instead of sugar — the team at Full Stack Vision ensures young people see themselves in what they’re creating. Orientations Training Centre, Sudan & Egypt In Sudan and Egypt, Orientations Training Centre has reached over 450 active members through a mix of in-person and online clubs: “I learned that coding is not just about computers — it’s about solving problems and helping people.” – Yasmin, Code Club attendee <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/image4-1-500x333.jpg" alt="A young tech creator and a mentor look at a laptop screen during a Code Club session in Egypt." class="wp-image-93050" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image4-1-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-1536x1024.jpg 1536w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-800x533.jpg 800w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1-900x600.jpg 900w, https://www.raspberrypi.org/app/uploads/2026/05/image4-1.jpg 1999w" sizes="auto, (max-width: 500px) 100vw, 500px" /> “Start small but dream big. A Code Club can change lives — not just by teaching coding but by nurturing problem-solvers, innovators, and leaders for the future.” – Abdelmoneim Mohammed, CEO of Orientations Training Centre Their work shows how getting creative with digital technology can unlock confidence, leadership, and ambition. STEMUP Educational Foundation, Sri Lanka In Sri Lanka, STEMUP Educational Foundation started with a single Code Club in a public library and has grown into a nationwide movement supported by more than 1,500 volunteers, reaching young people across both urban and rural communities. <img loading="lazy" decoding="async" width="500" height="282" src="https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-500x282.png" alt="Young people showcase their tech creations at Coolest Projects." class="wp-image-88957" srcset="https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-500x282.png 500w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-300x169.png 300w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-768x432.png 768w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-800x450.png 800w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-450x253.png 450w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07-900x507.png 900w, https://www.raspberrypi.org/app/uploads/2024/11/Shot-07.png 1000w" sizes="auto, (max-width: 500px) 100vw, 500px" /> After attending a Coolest Projects event for young tech creators during the partner meetup we held in Malaysia, STEMUP brought the tech showcase to Sri Lanka for the first time in 2024, giving young people the chance to share their creations and connect with others. The event sparked huge excitement, with schools even organising transport so students could take part. “That kind of energy… because they don’t have these opportunities to showcase what they have built, connect with like-minded people, connect with industry… I think that’s a really unique opportunity kids are having.” – Prabhath, founder of STEMUP Educational Foundation A global movement powered by local leaders Every partner brings something unique: local insight, cultural context, and a deep understanding of their community. Together, we’re building a global movement that is inclusive, creative, and full of possibility. “I feel part of something bigger — a worldwide movement where kids everywhere are learning to create with technology, not just consume it. Being a global partner means we can learn from what’s working in other countries, adapt those ideas to Bangladesh, and also contribute our own innovations back to the network. The global connection gives Code Club Bangladesh more recognition locally — it reassures schools, volunteers, and funders that we’re part of a trusted, established initiative.” – Code Club Bangladesh partner Are you ready to get started? You can register today to start your Code Club Incubator Partner application. If you’re passionate about empowering young people and ready to grow a network of computing clubs in your community, we’d love to hear from you. Fill in the registration form to take the first step towards becoming an Incubator Partner: I want to register We can’t wait to welcome the next group of Code Club Partners. The post Start small, dream big with Code Club: Become an Incubator Partner appeared first on Raspberry Pi Foundation.
AI is not neutral: What recent research says about bias, identity, and power
Artificial intelligence (AI) systems are often presented as objective. But plenty of evidence shows that AI systems can reflect and reinforce existing inequalities, from healthcare and education to scientific research itself. In the first seminar of our new research seminar series on applied AI, Thema Monroe-White from George Mason University explored how we can better… The post AI is not neutral: What recent research says about bias, identity, and power appeared first on Raspberry Pi Foundation.
Artificial intelligence (AI) systems are often presented as objective. But plenty of evidence shows that AI systems can reflect and reinforce existing inequalities, from healthcare and education to scientific research itself. In the first seminar of our new research seminar series on applied AI, Thema Monroe-White from George Mason University explored how we can better understand — and challenge — these patterns. Her talk focused on race-conscious algorithmic approaches to AI and data, and what they reveal about how knowledge is produced, represented, and used. <img loading="lazy" decoding="async" width="320" height="320" src="https://www.raspberrypi.org/app/uploads/2026/05/image4.jpg" alt="Thema Monroe-White." class="wp-image-92995" style="width:388px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image4.jpg 320w, https://www.raspberrypi.org/app/uploads/2026/05/image4-250x250.jpg 250w, https://www.raspberrypi.org/app/uploads/2026/05/image4-150x150.jpg 150w, https://www.raspberrypi.org/app/uploads/2026/05/image4-100x100.jpg 100w, https://www.raspberrypi.org/app/uploads/2026/05/image4-300x300.jpg 300w" sizes="auto, (max-width: 320px) 100vw, 320px" /> Thema Monroe-White is Associate Professor of Artificial Intelligence and Innovation Policy at the Schar School of Policy and Government and the Department of Computer Science (joint) at George Mason University. Drawing on two large-scale studies in her seminar, Thema showed that both scientific research and AI systems are shaped by human identities and social structures, and that recognising this is essential for educators, researchers, and anyone working with data. Who produces knowledge — and why that matters A key idea running through Thema’s seminar was that data and algorithms are not neutral. They are shaped by the people, institutions, and systems that produce them. Thema uses critical quantitative and intersectional approaches in her work to: Challenge the misconception that computational methods are objective Highlight how race and gender shape data and outputs Examine how systems of power influence what gets measured, valued, and reproduced Thema and her collaborators have been conducting research in this area for more than a decade, developing techniques that systematically measure bias and its impact on society. In a groundbreaking study published in 2022, just before the release of ChatGPT, Thema’s team used large-scale computational analysis of more than 5 million research articles to explore inequalities in scientific publishing. The data analysis approaches developed for this study were later used to explore bias in large language models (LLMs). However, the 2022 study already demonstrated wide-reaching disparities in science and surfaced deep-rooted issues, showing that bias was already ingrained in the scientific data that was used to train LLM, and affecting topic choices, citation and institutional differences. Identity and topic choice The results showed clear inequalities in the relationship between identity and topic choice. Authors from marginalised groups were more likely to study topics related to their communities and lived realities, including topics such as racial disparities and discrimination. Gendered patterns also appeared, with women publishing more frequently on more feminised topics, including families, literacy, learning, nursing, and pregnancy. <img loading="lazy" decoding="async" width="557" height="442" src="https://www.raspberrypi.org/app/uploads/2026/05/image3-1.png" alt="Thema’s team demonstrated that there are clear differences in which topics are investigated and published by different groups. This has significant effects on which knowledge is available for public discourse and decision making." class="wp-image-92999" style="width:597px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image3-1.png 557w, https://www.raspberrypi.org/app/uploads/2026/05/image3-1-300x238.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image3-1-500x397.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image3-1-450x357.png 450w" sizes="auto, (max-width: 557px) 100vw, 557px" /> Thema’s team demonstrated that there are clear differences in which topics are investigated and published by different groups. This has significant effects on which knowledge is available for public discourse and decision making. Citation inequalities The study also found citation inequalities. Even among authors studying the same topic, authors from some groups were cited less often than others, with black and Latinx women the least likely to be cited. This shows that inequality is not only present in what gets studied, but also in whose work is recognised. Institutional context Institutional context mattered too. Researchers at mission-driven institutions were more likely to publish on topics connected to marginalised communities, while scholars at institutions seen as elite were more likely to publish on topics that aligned more closely with dominant groups and norms. Taken together, the findings point to a simple but important idea: who we are shapes what knowledge gets produced. That matters because when some groups are underrepresented in research, the topics that affect their lives may also be understudied. What AI-generated stories reveal about bias Having already developed their tool for name analysis for the previous study, Thema’s team was uniquely positioned to analyse the bias embedded in generative AI systems, specifically LLMs. Thema’s most recent study examined how LLM–based tools represent people in everyday scenarios. The research team prompted the base models of LLM chatbots (such as Open AI’s ChatGPT, Anthropic’s Claude, Meta’s Llama, and Google’s PaLM or Gemini) to write short stories about students, workers, and relationships, generating 500,000 outputs across different domains. They then analysed how names associated with different racial and gender identities were portrayed. <img loading="lazy" decoding="async" width="824" height="314" src="https://www.raspberrypi.org/app/uploads/2026/05/image2.png" alt="AI-generated stories showed harmful stereotypes that can directly impact student performance." class="wp-image-93001" style="width:670px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image2.png 824w, https://www.raspberrypi.org/app/uploads/2026/05/image2-300x114.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image2-500x191.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image2-768x293.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image2-800x305.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image2-450x171.png 450w" sizes="auto, (max-width: 824px) 100vw, 824px" /> AI-generated stories showed harmful stereotypes that can directly impact student performance. One example Thema shared in the seminar described a student named “John” helping “Maria,” a student who had moved from Mexico and was struggling with Spanish. At first glance, this may seem like a small or even odd detail. But when oddities like this appear again and again across thousands of stories, they reveal systematic patterns. The study found that characters with marginalised identities were more likely to be portrayed in subordinated roles in chatbot outputs. Characters with non-white-associated names were more often shown as needing help rather than offering it. Stereotypes were also reinforced, with some names repeatedly associated with struggling students, subordinate workers, or narrow professional roles. Some groups were omitted altogether, while white-associated names appeared more frequently and in more powerful positions. <img loading="lazy" decoding="async" width="500" height="329" src="https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-500x329.jpg" alt="A group of young people in a classroom" class="wp-image-81490" srcset="https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-500x329.jpg 500w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-300x197.jpg 300w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-768x505.jpg 768w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-1536x1011.jpg 1536w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-800x526.jpg 800w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-450x296.jpg 450w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024-900x592.jpg 900w, https://www.raspberrypi.org/app/uploads/2022/09/ATHENS_CODE_CLUB_024.jpg 1778w" sizes="auto, (max-width: 500px) 100vw, 500px" /> Similar biases appeared across stories related to education, work, and relationships. Across all three topics, the most common pattern was one in which white characters were more likely to lead, rescue, or mentor, while non-white characters were more likely to be helped, corrected, or spoken for. For educators, this is especially important because many AI tools are now being introduced into classroom settings as writing assistants, tutors, or sources of personalised feedback. When these tools reproduce biases and unequal assumptions, they can shape not only what students read, but also how students see themselves and one another. Towards more responsible AI tools and data practices Rather than rejecting computational methods altogether, Thema argued for using them more thoughtfully and responsibly. One approach she highlighted is the Wells-Du Bois protocol, a framework designed to support bias mitigation, transparency, and more reflective use of data and models. It encourages researchers and practitioners to think carefully about inadequate or biased data, identity proxies, subpopulation differences, and the kinds of harms that can arise when AI systems are used without sufficient context. <img loading="lazy" decoding="async" width="1448" height="501" src="https://www.raspberrypi.org/app/uploads/2026/05/image1.png" alt="" class="wp-image-93002" style="aspect-ratio:2.890322580645161;width:680px;height:auto" srcset="https://www.raspberrypi.org/app/uploads/2026/05/image1.png 1448w, https://www.raspberrypi.org/app/uploads/2026/05/image1-300x104.png 300w, https://www.raspberrypi.org/app/uploads/2026/05/image1-500x173.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/image1-768x266.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/image1-800x277.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/image1-450x156.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/image1-900x311.png 900w" sizes="auto, (max-width: 1448px) 100vw, 1448px" /> Underlying this is a broader principle: when we do not know enough, we should say so. And when systems affect marginalised communities, those communities should not be an afterthought in how we build, evaluate, or use technology. What this means for your classroom In her seminar, Thema emphasised the importance of thinking about how we respond to bias in AI tools in educational settings. Here are some starting points for meaningful discussions in your classroom: A good starting point is student agency. If AI tools are becoming part of students’ learning environments, then young people need opportunities to make informed choices about when and how to engage with them. That means not treating AI tool use as inevitable, and not assuming every student should want to use the tools in the same way. In some cases, empowering students may also mean making it clear that they can opt out. This also means helping learners ask better questions about the tools themselves. What leads to the kinds of bias we saw in these studies? What data were these systems trained on? Whose language, identities, and experiences are overrepresented, and whose are missing? Do the tools have access to student or classroom data, and if so, what are the implications? The seminar also points to the importance of resisting AI hype. In a rapidly changing landscape, it can be tempting to focus only on novelty, efficiency, or personalisation. But educators may want to take a longer-term view about AI technology use. What kinds of habits, dependencies, and expectations are these tools creating? Are they shifting students’ ideas about intelligence, creativity, or authority? What happens when biased outputs are repeated often enough to feel normal? Finally, the discussion around responsible use should include the wider costs of AI. Informing students about these tools should include not just potential benefits and risks, but also issues such as environmental impact and data use. A more balanced conversation can help prevent classroom discussions from reinforcing the hype that often surrounds AI. If you would like to find out more about Thema’s work, watch the seminar recording: You may also want to explore: Thema’s paper on intersectional inequalities in science Her work on intersectional biases in narratives produced by AI models The Wells-Du Bois protocol for more responsible data practice Join our next seminar Our research seminars bring together educators and researchers to explore key questions in computing education. Next in our series on applied AI, our Director of Research and Impact, Shuchi Grover, will talk about the role of K–12 education in developing competencies for the future of data and computing. Sign up now to join the seminar on 12 May, 17:00 BST: I want to sign up The post AI is not neutral: What recent research says about bias, identity, and power appeared first on Raspberry Pi Foundation.
A day of big ideas at Coolest Projects USA Minnesota 2026
Coolest Projects USA Minnesota returned for its second year in the state on 11 April, with the celebration of creativity and coding coming to the Science Museum of Minnesota once again. At its heart, Coolest Projects is about giving young tech creators the opportunity to be seen and heard, and to share something they’ve made… The post A day of big ideas at Coolest Projects USA Minnesota 2026 appeared first on Raspberry Pi Foundation.
Coolest Projects USA Minnesota returned for its second year in the state on 11 April, with the celebration of creativity and coding coming to the Science Museum of Minnesota once again. At its heart, Coolest Projects is about giving young tech creators the opportunity to be seen and heard, and to share something they’ve made and be celebrated for it, regardless of their experience level. With some joining in for the first time and others returning to showcase their latest build, every participant played a part in making the day special. <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1-500x333.jpg" alt="A group of children standing together at Coolest Projects event." class="wp-image-92972" srcset="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_1.jpg 800w" sizes="auto, (max-width: 500px) 100vw, 500px" /> The event welcomed 65 participants and over 150 showcase visitors, with creators talking through their ideas, the challenges they had faced, and what they had learned along the way. Visitors explored the showcase, tried out hands-on activities, and connected with a community brought together by a want to celebrate the incredible things young people can do when given the opportunity. Coding for a social purpose A key moment in the day was the presentation of the Broadcom Foundation Coding with Commitment® award, celebrating a project that aligns with 17 sustainable development goals of the United Nations. This year’s recognition went to Rikita for her project ‘Smart Electronic Fruit Sorter — An affordable assistive technology for visually impaired people’. The project is a fruit sorter designed to help visually impaired people identify fresh produce. Using a microcontroller and a gas sensor, the Fruit Sorter detects whether fruit is good or spoiled, triggering lights, sounds, and a servomechanism to either keep or discard the fruit. Rikita overcame many challenges when building her project. She told us more about her experiences: “First, I started out with a sorter made out of foam. However, when testing, I realised that the sorter would not bear the weight of the fruit. Then, I pivoted to 3D printing the sorter parts. I also faced trouble with the electronics not working. I constantly played around with the connections and got it working. YouTube videos were of great help in guiding me!” <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2-500x333.jpg" alt="Two people holding a certificate in front of a Broadcom banner." class="wp-image-92973" srcset="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_2.jpg 800w" sizes="auto, (max-width: 500px) 100vw, 500px" /> The award highlights how young people are not just learning to code, but using those skills to explore real-world challenges and ideas that matter to them. Rikita shared how she felt about receiving the award: “I felt very happy and it has motivated me to continue my journey of inventions further. I did not expect the award, and so it was a very pleasant surprise.” Celebrating ideas big and small With entries spanning multiple categories, the event featured a wide variety of creative and technical work. Here are a few highlights. ZaLayaa | FIND ME ASAP, AI FIND ME ASAP is an emergency resource platform designed to help parents and guardians act quickly and effectively in the critical first moments after a child goes missing. Built by ZaLayaa in just 15 days, it goes beyond static guides by offering real-time, tailored support that people can use in high-stress situations. The platform is intentionally inclusive, recognising groups that can often be overlooked in emergencies, with features that consider children with invisible disabilities, complex medical needs, and rare health conditions, for example. Inspired by her own experiences navigating the world with multiple invisible conditions, ZaLayaa created FIND ME ASAP to fill a vital gap. ZaLayaa shared what she found most challenging in building her project: “My biggest challenge was making sure everything was actually real, correct, and useful, not just something that looks good. This isn’t just information. It has to work when someone is stressed, scared, and trying to make fast decisions.” ZaLayaa also explained what she enjoyed most about taking part in Coolest Projects: “My favorite thing was the experience and all the lovely people there. It was really cool seeing all the different projects and what other kids built, and being in a room where it was all kids creating and sharing their ideas.” You can find out more about ZaLayaa’s project at findmeasap.com. Lawrence | Find the Chomiks, Scratch Lawrence’s project is a fun exploration game he built using Scratch. You control a character, roam around the map, and hunt for hidden chomiks, each one with its own quirky look. It’s all about exploring, discovering, and collecting them all. Lawrence shared some of the challenges he faced along the way: “It was really hard switching between settings. I overcame [the challenges] by looking for bugs within my code, but when I figured that out, I was able to complete my game.” Karin | Princess Maze, Scratch Karin created Princess Maze, a Scratch game where players navigate four maze levels and battle a witch to win, or risk being trapped. During development, a bug allowed players to win even after being hit, which she fixed by using a ‘forever’ block to properly detect collisions. Karin shared why she wanted to take part in Coolest Projects: “I found out about it through The Bakken Museum and I thought, ‘Why not? I love coding.’ My favorite thing about the day was seeing all the different projects.” Caroline | Terrapod, AI Caroline created Terrapod to make plant care more accessible, especially for people who are too busy or physically unable to tend to their plants. It aims to provide a solution that allows plants to be cared for even when their owners can’t, making plant growing easier for everyone. She told us: “I think our biggest problem was the wire management. We numbered them to be organised into numbered groups, but I’ve seen others do symbols like stars, which I think is really cool!” <img loading="lazy" decoding="async" width="500" height="667" src="https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-500x667.png" alt="A "Terrapod" project, featuring a fish tank full of plants." class="wp-image-92984" srcset="https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-500x667.png 500w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-188x250.png 188w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-768x1024.png 768w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-1152x1536.png 1152w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-800x1067.png 800w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-450x600.png 450w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1-900x1200.png 900w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN-blog-image-1-1.png 1536w" sizes="auto, (max-width: 500px) 100vw, 500px" /> Adelle, Nessa, and Matilda | Fashion Show Drama, Scratch Adelle, Nessa, and Matilda created a Scratch project that tells the story of two performers, Charlie and Emma. Charlie struggles with stage fright that Emma only discovers just before their performance. With Emma’s support, Charlie overcomes her fear and is able to go on stage. Nessa shared a challenge the team tackled during their build: “One challenge was learning how to convert images from a JPEG to a PNG for the sprites to have a dress costume change. We wanted to show a difference between before the show and then preparing to go on stage. We found dress pictures on the internet and then we had to figure out how to make it look like they were actually wearing the dresses so it wasn’t just a copied picture with a white square background. We overcame it by our mentor helping us remove the background in Canva.” Matilda also told us how the girls found working as a part of a team: “We each had a part so each of our voices could be heard. We all had a say in what was going on. Nessa was the fashion designer. Adelle was the coder. I was the visionary! It was easier to work on this project in a group than alone.” <img loading="lazy" decoding="async" width="500" height="333" src="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4-500x333.jpg" alt="Three children standing in front of their project at Coolest Projects event." class="wp-image-92975" srcset="https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4-500x333.jpg 500w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4-300x200.jpg 300w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4-768x512.jpg 768w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4-450x300.jpg 450w, https://www.raspberrypi.org/app/uploads/2026/05/CPMN_4.jpg 800w" sizes="auto, (max-width: 500px) 100vw, 500px" /> Thank you We’d like to say a big thank you to all the young people who shared their projects, the families and mentors who supported them, and the volunteers and partners who made the event possible. We would also like to thank Broadcom Foundation and Best Buy Co., Inc. for their continued support of Coolest Projects. There’s still time to get involved in Coolest Projects 2026 If you would like to take part in Coolest Projects this year, there are still ways to get involved: Young creators anywhere in the world can take part in the Coolest Projects 2026 online showcase. Entries close on 27 May. Young people in several countries can participate in local events taking place around the world over the rest of the year, including Coolest Projects UK in Bradford on 16 May and Coolest Projects Canada in Vancouver on 30 May. You can find out more at coolestprojects.org. The post A day of big ideas at Coolest Projects USA Minnesota 2026 appeared first on Raspberry Pi Foundation.