Launched six years ago, Hello World magazine is the education magazine about computing and digital making. It’s made for educators by educators, and a community of teachers around the world reads and contributes to every issue. We’re now starting a monthly Hello World newsletter to bring you more great content for computing educators while you await each new magazine issue.
A monthly newsletter for Hello World readers
The Hello World community is an amazing group of people, and we love hearing your ideas about what could make Hello World even better at supporting your classroom practice. That’s why we host a fun and informative Hello World podcast to chat with educators around the globe about all things computing and digital making, and why we regularly share some of our favourite past magazine articles online to keep the conversation on important topics going.
Now we’re starting a monthly newsletter to offer you another way to get regular computing education ideas and insights you can use in your teaching. Every month, we’ll be curating a couple of interesting Hello World articles, plus news about the free education resources, research, community stories, and events from the Foundation. You can expect bite-size summaries of all items, plus links for you to explore more in your own time.
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We hope you’ll enjoy the first Hello World newsletter, which we will send out this Wednesday. As always, let us know what you think of it on Twitter or Facebook, or here in the comments.
PS Remember that if you work or volunteer as an educator in the UK, you can subscribe to receive free Hello World print copies to your home or workplace.
An absolutely huge congratulations to each and every single young creator who participated in Coolest Projects 2023, our digital technology showcase for young people! 5801 young people from 37 countries took part. This year’s participants made projects that entertained, inspired, and wowed us — creators showcased everything from robotic arms to platformer games.
We celebrated every project and maker in a special livestream event this Tuesday:
Each year, we invite VIP judges to pick their favourite projects. This year they had the difficult job of choosing between 4111 incredible projects young people showcased. Meet the judges and find out which projects were their favourites.
Yewande Akinola’s favourite projects
Yewande is a chartered engineer, innovator, and speaker. She has worked on projects in the UK, Africa, the Middle East, and East Asia, and has been named the UK Young Woman Engineer of the Year by the Institution of Engineering & Technology.
Vaishali is an Indian engineer, innovator, and revolutionary educationist. She is the co-founder of Young Tinker Academy and Young Tinker Foundation, started in 2015 to educate the less-privileged students of rural India. Her team at Young Tinker Foundation has impacted the lives of 150,000+ students.
Lella is an award-winning 18-year-old Digital Changemaker and Power of Youth Champion. Since she taught herself to code at age 8, Lella fosters purpose-driven innovation to create global industry opportunities that ensure young people are at the forefront of the ongoing digital transformation.
Aoife is the Head of Community Development for Meta Data Centres in Europe and Asia. She and her team deliver on Meta’s commitment to playing a positive role and investing in the long-term vitality of Meta Data Centre communities in Ireland, Denmark, Sweden, and Singapore.
Broadcom Foundation has partnered with us for Coolest Projects to encourage young people who are solving problems that impact their communities. Broadcom Coding with Commitment™ is a special recognition for a Coolest Projects creator aged 11–14 who has learned basic coding as an essential problem-solving tool in STEM and is “thinking globally while acting locally.”
The Broadcom Coding with Commitment™ recognition goes to Smart Farm, a project by Dang, Chi, and An from Vietnam. They designed Smart Farm to help farmers in their community regulate the temperature of animals, feed them on time, and check them for diseases. The team also built a fish pond model that tests the pH of the water and a vegetable garden model that detects when vegetables are wilting, all with the aim of helping local farmers to care for their livestock and protect their livelihoods. Huge congratulations to the team!
There’s so much more to celebrate
Our judges have chosen their favourite projects — but what about yours? You can explore thousands of incredible projects for 2023 young creators in the Coolest Projects showcase gallery and discover your favourites today.
All young creators who took part will shortly receive their own unique certificate to recognise their amazing achievements. They’ll also be able to log into their Coolest Projects account to find personalised feedback on their projects from our judging team.
Support from our Coolest Projects sponsors means we can make the online showcase and celebration livestream an inspiring experience for the young people taking part. We want to say a big thank you to all of them: Allianz Technologies, Broadcom Foundation, EPAM Systems, Liberty Global, Meta, and Qube Research and Technologies.
At the Raspberry Pi Foundation, our mission is to enable young people to realise their full potential through the power of computing and digital technologies. One way we achieve this is through supporting a global network of school-based Code Clubs for young people, in partnership with organisations that share our mission.
For the past couple of years we have been working with Mo School Abhiyan, a citizen–government partnership that aims to help people to connect, collaborate, and contribute to revamping the government schools and government-aided schools in the Indian state of Odisha. Together with Mo School Abhiyan we have established many more Code Clubs to increase access to computer science education, which is an important priority in Odisha.
We evaluate all of our projects to understand their impact, and this was no exception. We found that our training improved teachers’ skills, and we learned some valuable lessons — read on to find out more.
Background and aims of the project
After some successful small-scale trials with 5 and then 30 schools, our main project with Mo School Abhiyan began in August 2021. In the first phase, between August 2021 and January 2022, we aimed to train 1000 teachers from 1000 schools.
For a number of reasons, including coronavirus-related school closures, not all teachers were able to complete their training during this phase. Therefore we revised the programme, splitting the teachers in two groups depending on how far they had progressed with their initial training. We also added more teachers, so our overall aim became to support 1075 teachers to complete their training and start running clubs in 2022.
Our training and ongoing support for the teachers
We trained the teachers using a hybrid approach through online courses and in-person training by our team based in India. As we went along and learned more about what worked for the teachers, we adapted the training. This included making some of the content, such as the Prepare to run a Code Club online course, more suitable for an Indian context.
As most of the teachers were not computing specialists but more often teachers of other STEM subjects, we decided to focus the training on the basics of using Scratch programming in a Code Club.
We continue to provide support to the teachers now that they’ve completed their training. For instance, each Friday we run ‘Coding pe Charcha’ (translating to ‘Discussion on Coding’) sessions online. In these sessions, teachers come together, get answers to their questions about Scratch, take part in codealongs, and find out on how their students can take part in our global technology showcase Coolest Projects.
Measuring the impact of the training
To understand the impact of our partnership with Mo School Abhiyan and learn lessons we can apply in future work, we evaluated the impact of the teacher training using a mixed-methods approach. This included surveys at the start and end of the main training programme, shorter feedback forms after some elements of the training, and follow-up surveys to understand teachers’ progress with establishing clubs. We used Likert-style questions to measure impact quantitatively, and free-text questions for teachers to provide qualitative feedback.
One key lesson early on was that the teachers were using email infrequently. We adapted by setting up Whatsapp groups to keep in touch with them and send out the evaluation surveys.
Gathering feedback from teachers
Supported by our team in India, teachers progressed well through the training, with nine out of every ten teachers completing each element of the training.
Teachers’ feedback about the training was positive. The teachers who filled in the feedback survey reported increases in knowledge of coding concepts that were statistically significant. Following the training, nine out of every ten teachers agreed that they felt confident to teach children about coding. They appeared to particularly value the in-person training and the approach taken to supporting them: eight out of every ten teachers rated the trainer as “extremely engaging”.
The teachers’ feedback helped us identify possible future improvements. Some teachers indicated they would have liked more training with opportunities to practise their skills. We also learned how important it is that we tailor Code Club to suit the equipment and internet connectivity available in schools, and that we take into account that Code Clubs need to fit with school timetables and teachers’ other commitments. This feedback will inform our ongoing work.
The project’s impact for young people
In our follow-up surveys, 443 teachers have confirmed they have already started running Code Club sessions, with an estimated reach to at least 32,000 young people. And this reach has the potential to be even greater, as through our partnership with Mo School Abhiyan, teachers have registered more than 950 Code Clubs to date.
Supported by the teachers we’ve trained, each of the young people attending these Code Clubs will get the opportunity to learn to code and create with technology through our digital making projects. The projects enable young people to be creative and to share their creations with each other. Our team in India has started visiting Code Clubs to better understand how the clubs are benefiting young people.
What’s next for our work in India
The experience we’ve gained through the partnership with Mo School Abhiyan and the findings from the evaluation are helping to inform our growing work with communities in India and around the world that lack access to computing education.
In India we will continue to work with state governments and agencies to build on our experience with Mo School Abhiyan. We are also exploring opportunities to develop a computing education curriculum for governments and schools in India to adopt.
If you would like to know more about our work and impact in India, please reach out to us via india@raspberrypi.org.
How do we best prepare young children for a world filled with digital technology? This is the question the writers in our newest issue of Hello World respond to with inspiration and ideas for computing education in primary school.
It is vital that young children gain good digital literacy skills and understanding of computing concepts, which they can then build on as they grow up. Digital technology is here to stay, and as Sethi De Clercq points out in his article, we need to prepare our youngest learners for circumstances and jobs that don’t yet exist.
Primary computing education: Inspiration and ideas
Issue 21 of Hello World covers a big range of topics in the theme of primary computing education, including:
Cross-curricular project ideas to keep young learners engaged
Perfecting typing skills in the primary school classroom
Using picture books to introduce programming concepts to children
Toolkits for new and experienced computing primary teachers, by Neil Rickus and Catherine Archer
Explorations of different approaches to improving diversity in computing and instilling a sense of belonging from the very start of a child’s educational journey, by Chris Lovell and Peter Marshman
The issue also has useful news and updates about our work: we share insights from our primary-specialist learning managers, tell you a bit about the research presented at our ongoing primary education seminar series, and include some relevant lesson plans from The Computing Curriculum.
As always, you’ll find many other articles to support and inspire you in your computing teaching in this new issue. Topics include programming with dyslexia, exploring filter bubbles with your learners to teach them about data science, and using metaphors, similes, and analogies to help your learners understand abstract concepts.
What do you think?
This issue of Hello World focusses on primary computing education because readers like you told us in the annual readers’ survey that they’d like more articles for primary teachers.
We love to hear your ideas about what we can do to continue making Hello World interesting and relevant for you. So please get in touch on Twitter with your thoughts and suggestions.
Over 15,000 teams of young people from across Europe had their computer programs run on board the International Space Station (ISS) this month as part of this year’s European Astro Pi Challenge.
Astro Pi is run in collaboration by us and ESA Education, and offers two ways to get involved: Mission Zero and Mission Space Lab.
Mission Zero: Images of Earth’s fauna and flora in space
This year, 23,605 young people’s Mission Zero programs ran on the ISS. We need to check all the programs before we can send them to space and that means we got to see all the images and animations that the young people created. Their creativity was absolutely incredible! Here are some inspiring examples:
Mission Space Lab: Young people’s experiments on the ISS
Mission Space Lab runs over eight months and empowers teams of young people to design real science experiments on the ISS, executed by Python programs they write themselves. Teams choose between two themes: ‘Life in space’ and ‘Life on Earth’.
This year, the Mission Space Lab programs of 1245 young people in 294 teams from 21 countries passed our rigorous judging and testing process. These programs were awarded flight status and sent to the Astro Pis on board the ISS, where they captured data for the teams to analyse back down on Earth.
Mission Space Lab teams this year decided to design experiments such as analysing cloud formations to identify where storms commonly occur, looking at ocean colour as a measure of depth, and analysing freshwater systems and the surrounding areas they supply water to.
A selection of images taken by the Astro Pis of the Earth’s surface, including mountains, deserts, Aotearoa New Zealand south island, and lakes
Teams will be receiving their experiment data later this week, and will be analysing and interpreting it over the next few weeks. For example, the team analysing freshwater systems want to investigate how these systems may be affected by climate change. What their Mission Space Lab program has recorded while running on the Astro Pis is a unique data set that the team can compare against other scientific data.
The challenges of running programs in space
For the ‘Life on Earth’ category of Mission Space Lab experiments this year, the Astro Pis were positioned in a different place to previous years: in the Window Observational Research Facility (WORF). Therefore the Astro Pis could take photos with a wider view. Combined with the High Quality Camera of the upgraded Astro Pi computers we sent to the ISS in 2021, this means that the teams got amazing-quality photos of the Earth’s surface.
The two Astro Pis positioned in an observation window on the ISS
Once the experiments for ‘Life on Earth’ were complete, the astronauts moved the Astro Pis back to the Columbus module and replaced their SD cards, ready for capturing the data for the ‘Life in Space’ experiments.
Running programs in an environment as unique as the ISS, where all hardware and software is put to the test, brings many complexities and challenges. Everything that happens on the ISS has to be scheduled well in advance, and astronauts have a strict itinerary to follow to keep the ISS running smoothly.
The Canadarm in view on the ISS, photographed by an Astro Pi computer
As usual, this year’s experiments met with their fair share of challenges. One initial challenge the Astro Pis had this year was that the Canadarm, a robotic arm on the outside of the ISS, was in operation during some of the ‘Life on Earth’ experiments. Although it’s fascinating to see part of the ISS in-shot, it also slightly obscured some of the photos.
Another challenge was that window shutters were scheduled to close during some of the experiments, which meant we had to switch around the schedule for Mission Space Lab programs to run so that all of the experiments aiming to capture photos could do so.
What’s next for Astro Pi?
Well done to all the young people who’ve taken part in the European Astro Pi Challenge this year.
If you’ve mentored young people in Mission Zero, then we will share their unique participation certificates with you very soon.
If you are taking part in Mission Space Lab, then we wish you the best of luck with your analysis and final reports. We are excited to read about your findings.
If you’d like to hear about upcoming Astro Pi Challenges, sign up to the newsletter at astro-pi.org.
How do we teach our youngest learners digital and computing skills? Hello World‘s issue 21 will focus on this question and all things primary school computing education. We’re excited to share this new issue with you on Tuesday 30 May. Today we’re giving you a taste by sharing an article from it, written by our own Sway Grantham.
How are you preparing young children for a world filled with digital technology? Technology use of our youngest learners is a hotly debated topic. From governments to parents and from learning outcomes to screen-time rules, everyone has an opinion on the ‘right’ approach. Meanwhile, many young children encounter digital technology as a part of their world at home. For example in the UK, 87 percent of 3- to 4-year-olds and 93 percent of 5- to 7-year-olds went online at home in 2023. Schools should be no different.
As educators, we have a responsibility to prepare learners for life in a digital world. We want them to understand its uses, to be aware of its risks, and to have access to the wide range of experiences unavailable without it. And we especially need to consider the children who do not encounter technology at home. Education should be a great equaliser, so we need to ensure all our youngest learners have access to the skills they need to realise their full potential.
Exploring technology and the world
A major aspect of early-years or kindergarten education is about learners sharing their world with each other and discovering that everyone has different experiences and does things in their own way. Using digital technology is no different.
Allowing learners to share their experiences of using digital technology both accepts the central role of technology in our lives today and also introduces them to its broader uses in helping people to learn, talk to others, have fun, and do work. At home, many young learners may use technology to do just one of these things. Expanding their use of technology can encourage them to explore a wider range of skills and to see technology differently.
In their classroom environment, these explorations can first take place as part of the roleplay area of a classroom, where learners can use toys to show how they have seen people use technology. It may seem counterintuitive that play-based use of non-digital toys can contribute to reducing the digital divide, but if you don’t know what technology can do, how can you go about learning to use it? There is also a range of digital roleplay apps (such as the Toca Boca apps) that allow learners to recreate their experiences of real-world situations, such as visiting the hospital, a hair salon, or an office. Such apps are great tools for extending roleplay areas beyond the resources you already have.
Another aspect of a child’s learning that technology can facilitate is their understanding of the world beyond their local community. Technology allows learners to explore the wider world and follow their interests in ways that are otherwise largely inaccessible. For example:
Using virtual reality apps, such as Expeditions Pro, which lets learners explore Antarctica or even the bottom of the ocean
Using augmented reality apps, such as Octagon Studio’s 4D+ cards, which make sea creatures and other animals pop out of learners’ screens
Doing a joint project with a class of children in another country, where learners blog or share ‘email’ with each other
Each of these opportunities gives children a richer understanding of the world while they use technology in meaningful ways.
Technology as a learning tool
Beyond helping children to better understand our world, technology offers opportunities to be expressive and imaginative. For example, alongside your classroom art activities, how about using an app like Draw & Tell, which helps learners draw pictures and then record themselves explaining what they are drawing? Or what about using filters on photographs to create artistic portraits of themselves or their favourite toys? Digital technology should be part of the range of tools learners can access for creative play and expression, particularly where it offers opportunities that analogue tools don’t.
Using technology is also invaluable for learners who struggle with communication and language skills. When speaking is something you find challenging, it can often be intimidating to talk to others who speak much more confidently. But speaking to a tablet? A tablet only speaks as well as you do. Apps to record sounds and listen back to them are a helpful way for young children to learn about how clear their speech is and practise speech exercises. ChatterPix Kids is a great tool for this. It lets learners take a photo of an object, e.g. their favourite soft toy, and record themselves talking about it. When they play back the recording, the app makes it look like the toy is saying their words. This is a very engaging way for young learners to practise communicating.
Technology is part of young people’s world
No matter how we feel about the role of technology in the lives of young people, it is a part of their world. We need to ensure we are giving all learners opportunities to develop digital skills and understand the role of technology, including how people can use it for social good.
This is not just about preparing them for their computing education (although that’s definitely a bonus!) or about online safety (although this is vital — see my articles in Hello World issue 15 and issue 19 for more about the topic). It’s about their right to be active citizens in the digital world.
So I ask again: how are you preparing young children for a digital world?
Subscribe to the Hello World digital edition for free
The first experiences children have with learning about computing and digital technologies are formative. That’s why primary computing education should be of interest to all educators, no matter what the age of your learners is. This issue covers for example:
And there’s much more besides. So don’t miss out on this upcoming issue of Hello World — subscribe for free today to receive every PDF edition in your inbox on the day of publication.
Every day, most of us both consume and create data. For example, we interpret data from weather forecasts to predict our chances of a good weather for a special occasion, and we create data as our carbon footprint leaves a trail of energy consumption information behind us. Data is important in our lives, and countries around the world are expanding their school curricula to teach the knowledge and skills required to work with data, including at primary (K–5) level.
Kate FarrellProf. Judy Robertson
In our most recent research seminar, attendees heard about a research-based initiative called Data Education in Schools. The speakers, Kate Farrell and Professor Judy Robertson from the University of Edinburgh, Scotland, shared how this project aims to empower learners to develop data literacy skills and succeed in a data-driven world.
“Data literacy is the ability to ask questions, collect, analyse, interpret and communicate stories about data.”
– Kate Farrell & Prof. Judy Robertson
Being a data citizen
Scotland’s national curriculum does not explicitly mention data literacy, but the topic is embedded in many subjects such as Maths, English, Technologies, and Social Studies. Teachers in Scotland, particularly in primary schools, have the flexibility to deliver learning in an interdisciplinary way through project-based learning. Therefore, the team behind Data Education in Schools developed a set of cross-curricular data literacy projects. Educators and education policy makers in other countries who are looking to integrate computing topics with other subjects may also be interested in this approach.
Data citizens have skills they need to thrive in a world shaped by digital technology.
The Data Education in Schools projects are aimed not just at giving learners skills they may need for future jobs, but also at equipping them as data citizens in today’s world. A data citizen can think critically, interpret data, and share insights with others to effect change.
Kate and Judy shared an example of data citizenship from a project they had worked on with a primary school. The learners gathered data about how much plastic waste was being generated in their canteen. They created a data visualisation in the form of a giant graph of types of rubbish on the canteen floor and presented this to their local council.
Sorting food waste from lunch by type of material
As a result, the council made changes that reduced the amount of plastic used in the canteen. This shows how data citizens are able to communicate insights from data to influence decisions.
A cycle for data literacy projects
Across its projects, the Data Education in Schools initiative uses a problem-solving cycle called the PPDAC cycle. This cycle is a useful tool for creating educational resources and for teaching, as you can use it to structure resources, and to concentrate on areas to develop learner skills.
The PPDAC data problem-solving cycle
The five stages of the cycle are:
Problem: Identifying the problem or question to be answered
Plan: Deciding what data to collect or use to answer the question
Analysis: Preparing, modelling, and visualising the data, e.g. in a graph or pictogram
Conclusion: Reviewing what has been learned about the problem and communicating this with others
Smaller data literacy projects may focus on one or two stages within the cycle so learners can develop specific skills or build on previous learning. A large project usually includes all five stages, and sometimes involves moving backwards — for example, to refine the problem — as well as forwards.
Data literacy for primary school learners
At primary school, the aim of data literacy projects is to give learners an intuitive grasp of what data looks like and how to make sense of graphs and tables. Our speakers gave some great examples of playful approaches to data. This can be helpful because younger learners may benefit from working with tangible objects, e.g. LEGO bricks, which can be sorted by their characteristics. Kate and Judy told us about one learner who collected data about their clothes and drew the results in the form of clothes on a washing line — a great example of how tangible objects also inspire young people’s creativity.
As learners get older, they can begin to work with digital data, including data they collect themselves using physical computing devices such as BBC micro:bit microcontrollers or Raspberry Pi computers.
Coming soon: the recording of Kate’s and Judy’s seminar for you to watch. You can access their slides here.
Free resources for primary (and secondary) schools
For many attendees, one of the highlights of the seminar was seeing the range of high-quality teaching resources for learners aged 3–18 that are part of the Data Education in Schools project. These include:
Data 101 videos: A set of 11 videos to help primary and secondary teachers understand data literacy better.
Lesson resources: Lots of projects to develop learners’ data literacy skills. These are mapped to the Scottish primary and secondary curriculum, but can be adapted for use in other countries too.
More resources are due to be published later in 2023, including a set of prompt cards to guide learners through the PPDAC cycle, a handbook for teachers to support the teaching of data literacy, and a set of virtual data-themed escape rooms.
You may also be interested in the units of work on data literacy skills that are part of The Computing Curriculum, our complete set of classroom resources to teach computing to 5- to 16-year-olds.
Join our next seminar on primary computing education
At our next seminar we welcome Aim Unahalekhaka from Tufts University, USA,who will share research about a rubric to evaluate young learners’ ScratchJr projects. If you have a tablet with ScratchJr installed, make sure to have it available to try out some activities. The seminar will take place online on Tuesday 6 June at 17.00 UK time, sign up now to not miss out.
To find out more about connecting research to practice for primary computing education, you can see a list of our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.
Non-formal learning initiatives are a popular way to engage children in computing from a young age and introduce them to the fun, creative world of coding and digital making. As part of our commitment to an evidence-based approach, we are partnering with Durham University on an exciting evaluation project to study the impact non-formal activities like Code Club have on young people in UK schools. Your school is invited to take part in the project.
We’re inviting UK schools to take part
The project will explore students’ attitudes to learning coding, and to learning generally. We hope to understand more about how extracurricular activities affect students’ confidence and skills. If you’re a teacher at a UK school, we would love for you to register your interest in taking part — your school doesn’t need to have a Code Club to participate. Taking part is easy: simply have some of your students fill in a few short surveys.
As a token of our appreciation for your school’s involvement, you will receive some cool swag and an exclusive invitation to an online, educator-focused workshop where you will explore digital making with us. We’ll even provide you with all the kit you need to make something great, including a Raspberry Pi Pico. Your involvement will contribute to better computing education for UK students.
Computing in UK classrooms and in Code Clubs
In the UK, computing is taught at school, providing children with the opportunity to learn the importance of the subject and its many applications from a young age. In addition, non-formal education can play a pivotal role in fostering a positive learning experience, particularly in computing. Research on computing education indicates that non-formal settings are linked to improvement in students’ self-efficacy and interest in computing. Through participation in non-formal computing education, learners can gain valuable hands-on experience and develop problem-solving, collaboration, and presentation skills.
That’s the thinking behind Code Clubs, which offer students a relaxed environment that encourages creativity, teamwork, and self-paced learning. By providing students with project-based learning opportunities and access to resources and mentors, Code Clubs help foster a passion for computing while also strengthening their understanding of key concepts.
A previous evaluation showed that students who participated in Code Clubs reported improvement in their coding skills and a positive perception about their coding abilities. Code Clubs have already made a significant impact on learners worldwide, with over 3500 Code Clubs around the world currently reaching tens of thousands of young people and inspiring a new generation of digital makers.
Help us with this project
Your school’s participation in this project will help increase our understanding of what works in computing education. Together we can ensure that young people are equipped with the skills and confidence to realise their full potential through the power of computing and digital technologies.
To register your interest in joining the project, simply fill out our short form and we’ll be in touch soon.
Today we share a guest blog from Chris Roffey, who manages the UK Bebras Challenge, a computational thinking challenge we run every year in partnership with the University of Oxford.
Bebras is a free annual challenge that helps schools introduce computational thinking to their learners through online, self-marking tasks. Taking part in Bebras, students solve accessible, interesting problems using their developing computational thinking skills. No programming is involved in taking part. The UK challenge is for school students aged 6 to 18 years old, with a special category for students with severe visual impairments.
Bebras means ‘beaver’
Preparing the UK Bebras Challenge for schools
While UK schools take part in Bebras throughout two weeks in November, for me the annual cycle starts much earlier. May is the time of the annual Bebras international workshop where the year’s new tasks get decided. In 2022, 60 countries were represented — some online, some in person. For nearly a week, computer scientists and computing teachers met to discuss and work on the new cycle’s task proposals submitted by participating countries a little earlier.
After the workshop, in collaboration with teams from other European countries, the UK Bebras team chose its task sets and then worked to localise, copy-edit, and test them to get them ready for schools participating in Bebras during November. From September, schools across the UK create accounts for their students, with over 360,000 students ultimately taking part in 2022. All in all, more than 3 million students from 59 countries took part in the 2022/2023 Bebras challenge cycle.
An invitation to the Oxford University Computing Challenge
In this cycle, the UK Bebras partnership between the Raspberry Pi Foundation and the University of Oxford has been extended to include the Oxford University Computing Challenge (OUCC). This is an invitation-based, online coding challenge for students aged 10 to 18, offered in the UK as well as Australia, Jamaica, and China. We invited the students with the top 10% best results in the UK Bebras challenge to take part in the OUCC — an exciting opportunity for them.
In contrast to Bebras, which doesn’t require participants to do any coding, the OUCC asks students to create code to solve computational thinking problems. This requires students to prepare and challenges them to develop their computational thinking skills further. The two younger age groups, 10- to 14-year-olds, solve problems using the Blockly programming language. The older two age groups can use one of the 11 programming languages that Bebras supports, including all the most common ones taught in UK schools.
Over 20,000 Bebras participants took up the invitation to the first round of the OUCC in the third week of January. Then in March, the top 20 participants from each of the four OUCC age groups took part in the final round. The finalists all did amazingly well. In the first round, many of them had solved all the available tasks correctly, even though the expectation is that participants only try to solve as many as they can within the round’s time limit. In the final round, a few of the finalists managed to repeat this feat with the even more advanced tasks — which is, in modern parlance, literally impossible!
Celebrating together
Many of the participants are about to take school exams, so the last stage of the annual cycle — the prize winners’ celebration day— takes place when the exam period has ended. This year we are holding this celebration on Friday 30 June at the Raspberry Pi Foundation’s headquarters in Cambridge. It will be a lovely way to finish the annual Bebras cycle and I am looking forward to it immensely.
Broadening participation and finding new entry points for young people to engage with computing is part of how we pursue our mission here at the Raspberry Pi Foundation. It was also the focus of our March online seminar, led by our own Dr Bobby Whyte. In this third seminar of our series on computing education for primary-aged children, Bobby presented his work on ‘designing multimodal composition activities for integrated K-5 programming and storytelling’. In this research he explored the integration of computing and literacy education, and the implications and limitations for classroom practice.
Motivated by challenges Bobby experienced first-hand as a primary school teacher, his two studies on the topic contribute to the body of research aiming to make computing less narrow and difficult. In this work, Bobby integrated programming and storytelling as a way of making the computing curriculum more applicable, relevant, and contextualised.
Critically for computing educators and researchers in the area, Bobby explored how theories related to ‘programming as writing’ translate into practice, and what the implications of designing and delivering integrated lessons in classrooms are. While the two studies described here took place in the context of UK schooling, we can learn universal lessons from this work.
What is multimodal composition?
In the seminar Bobby made a distinction between applying computing to literacy (or vice versa) and true integration of programming and storytelling. To achieve true integration in the two studies he conducted, Bobby used the idea of ‘multimodal composition’ (MMC). A multimodal composition is defined as “a composition that employs a variety of modes, including sound, writing, image, and gesture/movement [… with] a communicative function”.
Storytelling comes together with programming in a multimodal composition as learners create a program to tell a story where they:
Decide on content and representation (the characters, the setting, the backdrop)
Structure text they’ve written
Use technical aspects (i.e. motion blocks, tension) to achieve effects for narrative purposes
Defining multimodal composition (MMC) for a visual programming context
Multimodality for programming and storytelling in the classroom
To investigate the use of MMC in the classroom, Bobby started by designing a curriculum unit of lessons. He mapped the unit’s MMC activities to specific storytelling and programming learning objectives. The MMC activities were designed using design-based research, an approach in which something is designed and tested iteratively in real-world contexts. In practice that means Bobby collaborated with teachers and students to analyse, evaluate, and adapt the unit’s activities.
Mapping of the MMC activities to storytelling and programming learning objectives
The first of two studies to explore the design and implementation of MMC activities was conducted with 10 K-5 students (age 9 to 11) and showed promising results. All students approached the composition task multimodally, using multiple representations for specific purposes. In other words, they conveyed different parts of their stories using either text, sound, or images.
Bobby found that broadcast messages and loops were the least used blocks among the group. As a consequence, he modified the curriculum unit to include additional scaffolding and instructional support on how and why the students might embed these elements.
Bobby modified the classroom unit based on findings from his first study
In the second study, the MMC activities were evaluated in a classroom of 28 K-5 students led by one teacher over two weeks. Findings indicated that students appreciated the longer multi-session project. The teacher reported being satisfied with the project work the learners completed and the skills they practised. The teacher also further integrated and adapted the unit into their classroom practice after the research project had been completed.
How might you use these research findings?
Factors that impacted the integration of storytelling and programming included the teacher’s confidence to teach programming as well as the teacher’s ability to differentiate between students and what kind of support they needed depending on their previous programming experience.
In addition, there are considerations regarding the curriculum. The school where the second study took place considered the activities in the unit to be literacy-light, as the English literacy curriculum is ‘text-heavy’ and the addition of multimodal elements ‘wastes’ opportunities to produce stories that are more text-based.
Bobby’s research indicates that MMC provides useful opportunities for learners to simultaneously pursue storytelling and programming goals, and the curriculum unit designed in the research proved adaptable for the teacher to integrate into their classroom practice. However, Bobby cautioned that there’s a need to carefully consider both the benefits and trade-offs when designing cross-curricular integration projects in order to ensure a fair representation of both subjects.
Can you see an opportunity for integrating programming and storytelling in your classroom? Let us know your thoughts or questions in the comments below.
Join our next seminar on primary computing education
At our next seminar, we welcome Kate Farrell and Professor Judy Robertson (University of Edinburgh). This session will introduce you to how data literacy can be taught in primary and early-years education across different curricular areas. It will take place online on Tuesday 9 May at 17.00 UK time, don’t miss out and sign up now.
Yo find out more about connecting research to practice for primary computing education, you can find other our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.
Programming is becoming an increasingly useful skill in today’s society. As we continue to rely more and more on software and digital technology, knowing how to code is also more and more valuable. That’s why many parents are looking for ways to introduce their children to programming. You might find it difficult to know where to begin, with so many different kids’ coding languages and platforms available. In this blog post, we explore how children can progress through different programming languages to realise their potential as proficient coders and creators of digital technology.
ScratchJr
Everyone needs to start somewhere, and one great option for children aged 5–7 is ScratchJr (Scratch Junior), a visual programming language with drag-and-drop blocks for creating simple programs. ScratchJr is available for free on Android and iOS mobile devices. It’s great for introducing young children to the basics of programming, and they can use it to create interactive stories and games.
Scratch
Moving on from ScratchJr, there’s its web-based sibling Scratch. Scratch offers drag-and-drop blocks for creating programs and comes with an assortment of graphics, sounds, and music for your child to bring their programs to life. This visual programming language is designed specifically for children to learn programming fundamentals. Scratch is available in multiple spoken languages and is perfect for beginners. It allows kids to create interactive stories, animations, and games with ease.
The Raspberry Pi Foundation has a wealth of free Scratch resources we have created specifically for young people who are beginners, such as the ‘Introduction to Scratch’ project path. And if your child is interested in physical computing to interact with the real world using code, they can also learn how to use electronic components, such as buzzers and LEDs, with Scratch and a Raspberry Pi computer.
MakeCode
Another fun option for children who want to explore coding and physical computing is the micro:bit. This is a small programmable device with an LED display, buttons, and sensors, and it can be used to create games, animations, interactive projects, and lots more. To control a micro:bit, a visual programming language called MakeCode can be used. The micro:bit can also be programmed using Scratch or text-based languages such as Python, offering an easy transition for children as their coding skills progress. Have a look at our free collection of micro:bit resources to learn more.
HTML
Everyone is familiar with websites, but fewer people know how they are coded. HTML is a markup language that is used to create the webpages we use every day. It’s a great language for children to learn because they can see the results of their code in real time, in their web browser. They can use HTML and CSS to create simple webpages that include links, videos, pictures, and interactive elements, all the while learning how websites are structured and designed. We have many free web design resources for your child, including a basic ‘Introduction to web development’ project path.
Python
If your child is becoming confident with Scratch and HTML, then using Python is the recommended next stage in their learning. Python is a high-level text-based programming language that is easy to read and learn. It is a popular choice for beginners as it has a simple syntax that often reads like plain English. Many free Python projects for young people are available on our website, including the ‘Introduction to Python’ path.
The Python community is also really welcoming and has produced a myriad of online tutorials and videos to help learners explore this language. Python can be used to do some very powerful things with ease, which is why it is so popular. For example, it is relatively simple to create Python programs to engage in machine learning and data analysis. If you wanted to explore large language models such as GPT, on which the ChatGPT chatbot is based, then Python would be the language of choice.
JavaScript
JavaScript is the language of the web, and if your child has become proficient in HTML, then this is the next language for them. JavaScript is used to create interactive websites and web applications. As young people become more comfortable with programming, JavaScript is a useful language to progress to, given how ubiquitous the web is today. It can be tricky to learn, but like Python, it has a vast number of libraries of functions that people have already created for it to achieve things more quickly. These libraries make JavaScript a very powerful language to use.
Try out kids’ coding languages
There are many different programming languages, and each one has its own strengths and weaknesses. Some are easy to learn and use, some are really fast, and some are very secure.
Starting with visual languages such as Scratch or MakeCode allows your child to begin to understand the basic concepts of programming without needing any developed reading and keyboard skills. Once their understanding and skills have improved, they can try out text-based languages, find the one that they are comfortable with, and then continue to learn. It’s fairly common for people who are proficient in one programming language to learn other languages quite quickly, so don’t worry about which programming language your child starts with.
Whether your child is interested in working in software development or just wants to learn a valuable — and creative — skill, helping them learn to code and try out different kids’ coding languages is a great way for you to open up new opportunities for them.
We are excited to share that 294 teams of young people participating in this year’s Astro Pi Mission Space Lab achieved Flight Status: their programs will run on the Astro Pis installed on the International Space Station (ISS) in April.
Mission Space Lab is part of the European Astro Pi Challenge, an ESA Education project run in collaboration with the Raspberry Pi Foundation. 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.
In depth
To take part in Mission Space Lab, young people form teams and choose between two themes for their experiments, investigating either ‘Life in space’ or ‘Life on Earth’. They send us their experiment ideas in Phase 1, and in Phase 2 they write Python programs to execute their experiments on the Astro Pis onboard the ISS. As we sent upgraded Astro Pis to space at the end of 2021, Mission Space Lab teams can now also choose to use a machine learning accelerator during their experiment time.
In total, 771 teams sent us ideas during Phase 1 in September 2022, so achieving Flight Status is a huge accomplishment for the successful teams. We are delighted that 391 teams submitted programs for their experiments. Teams who submitted had their programs checked for errors and their experiments tested, resulting in 294 teams being granted Flight Status. 134 of these teams included some aspects of machine learning in their experiments using the upgraded Astro Pis’ machine learning accelerator.
The 294 teams to whom we were able to award Flight Status this year represent 1245 young people. 34% of team members are female, and the average participant age is 15. The 294 successful teams hail from 21 countries; Italy has the most teams progressing to the next phase (48), closely followed by Spain (37), the UK (34), Greece (25), and the Czech Republic (25).
Life in space
Mark II Astro Pis on the ISS
Teams can use the Astro Pis to investigate life inside ESA’s Columbus module of the ISS, by writing a program to detect things with at least one of the Astro Pi’s sensors. This can include for example the colour and intensity of light in the module, or the temperature and humidity.
81 teams that created ‘Life in space’ experiments have achieved Flight Status this year. Examples of experiments from this year are investigating how the Earth’s magnetic field is felt on the ISS, what environmental conditions the astronauts experience compared to those on Earth directly beneath the ISS as it orbits, or whether the cabin might be suitable for other lifeforms, such as plants or bacteria.
Life on Earth
Astro Pi VIS in the window on the ISS
In the ‘Life on Earth’ theme, teams investigate features on the Earth’s surface using the cameras on the Astro Pis, which are positioned to view Earth from a window on the ISS.
This year the Astro Pis will be located in the Window Observational Research Facility (WORF), which is larger than the window the computers were positioned in in previous years. This means that teams running ‘Life on Earth’ experiments can capture better images. 206 teams that created experiments in the ‘Life on Earth’ theme have achieved Flight Status.
Thanks to the upgraded Astro Pi hardware, this is the second year that teams could decide whether to use visible-light or infrared (IR) photography. Teams running experiments using IR photography have chosen to examine topics such as plant health in different regions, the effects of deforestation, and desertification. Teams collecting visible light photography have chosen to design experiments analysing clouds in different regions, changes in ocean colour, the velocity of the ISS, and classification of biomes (e.g. desert, forest, grassland, wetland).
Testing, testing
Images taken by Astro Pi VIS on the ISS in Mission Space Lab 2021/22
Each of this year’s 391 submissions has been through a number of tests to ensure they follow the challenge rules, meet the ISS security requirements, and can run without errors on the Astro Pis. Once the experiments have started, we can’t rely on astronaut intervention to resolve any issues, so we have to make sure that all of the programs will run without any problems.
This means that the start of the year is a very busy time for us. We run tests on Mission Space Lab teams’ programs on a number of exact replicas of the Astro Pis, including a final test to run every experiment that has passed all tests for the full three-hour experiment duration. The 294 experiments that received Flight Status will take over 5 weeks to run.
97 programs submitted by teams during Phase 2 of Mission Space Lab this year did not pass testing and so could not be awarded Flight Status. We wish we could run every experiment that is submitted, but there is only limited time available for the Astro Pis to be positioned in the ISS window. Therefore, we have to be extremely rigorous in our selection, and many of the 97 teams were not successful because of only small issues in their programs. We recognise how much work every Mission Space Lab team does, and all teams can be very proud of designing and creating an experiment.
Even if you weren’t successful this year, we hope you enjoyed participating and will take part again in next year’s challenge.
What next?
Once all of the experiments have run, we will send the teams the data collected during their experiments. Teams will then have time to analyse their data and write a short report to share their findings. Based on these reports, we will select winners of this year’s Mission Space Lab. The winning and highly commended teams will receive a special surprise.
Congratulations to all successful teams! We are really looking forward to seeing your results.
We are delighted to announce that we’ve launched Experience AI, our new learning programme to help educators to teach, inspire, and engage young people in the subject of artificial intelligence (AI) and machine learning (ML).
Experience AI is a new educational programme that offers cutting-edge secondary school resources on AI and machine learning for teachers and their students. Developed in partnership by the Raspberry Pi Foundation and DeepMind, the programme aims to support teachers in the exciting and fast-moving area of AI, and get young people passionate about the subject.
The importance of AI and machine learning education
Artificial intelligence and machine learning applications are already changing many aspects of our lives. From search engines, social media content recommenders, self-driving cars, and facial recognition software, to AI chatbots and image generation, these technologies are increasingly common in our everyday world.
Young people who understand how AI works will be better equipped to engage with the changes AI applications bring to the world, to make informed decisions about using and creating AI applications, and to choose what role AI should play in their futures. They will also gain critical thinking skills and awareness of how they might use AI to come up with new, creative solutions to problems they care about.
The AI applications people are building today are predicted to affect many career paths. In 2020, the World Economic Forum estimated that AI would replace some 85 million jobs by 2025 and create 97 million new ones. Many of these future jobs will require some knowledge of AI and ML, so it’s important that young people develop a strong understanding from an early age.
Develop a strong understanding of the concepts of AI and machine learning with your learners.
Experience AI Lessons
Something we get asked a lot is: “How do I teach AI and machine learning with my class?”. To answer this question, we have developed a set of free lessons for secondary school students (age 11 to 14) that give you everything you need including lesson plans, slide decks, worksheets, and videos.
The lessons are also for you if you’re an educator or volunteer outside of a school setting, such as in a coding club.
The six lessons
What is AI?: Learners explore the current context of artificial intelligence (AI) and how it is used in the world around them. Looking at the differences between rule-based and data-driven approaches to programming, they consider the benefits and challenges that AI could bring to society.
How computers learn: Learners focus on the role of data-driven models in AI systems. They are introduced to machine learning and find out about three common approaches to creating ML models. Finally the learners explore classification, a specific application of ML.
Bias in, bias out: Learners create their own machine learning model to classify images of apples and tomatoes. They discover that a limited dataset is likely to lead to a flawed ML model. Then they explore how bias can appear in a dataset, resulting in biased predictions produced by a ML model.
Decision trees: Learners take their first in-depth look at a specific type of machine learning model: decision trees. They see how different training datasets result in the creation of different ML models, experiencing first-hand what the term ‘data-driven’ means.
Solving problems with ML models: Learners are introduced to the AI project lifecycle and use it to create a machine learning model. They apply a human-focused approach to working on their project, train a ML model, and finally test their model to find out its accuracy.
Model cards and careers: Learners finish the AI project lifecycle by creating a model card to explain their machine learning model. To finish off the unit, they explore a range of AI-related careers, hear from people working in AI research at DeepMind, and explore how they might apply AI and ML to their interests.
As part of this exciting first phase, we’re inviting teachers to participate in research to help us further develop the resources. All you need to do is sign up through our website, download the lessons, use them in your classroom, and give us your valuable feedback.
Ben Garside, one of our lead educators working on Experience AI, takes a group of students through one of the new lessons.
Support for teachers
We’ve designed the Experience AI lessons with teacher support in mind, and so that you can deliver them to your learners aged 11 to 14 no matter what your subject area is. Each of the lesson plans includes a section that explains new concepts, and the slide decks feature embedded videos in which DeepMind’s AI researchers describe and bring these concepts to life for your learners.
We will also be offering you a range of new teacher training opportunities later this year, including a free online CPD course — Introduction to AI and Machine Learning — and a series of AI-themed webinars.
Tell us your feedback
We will be inviting schools across the UK to test and improve the Experience AI lessons through feedback. We are really looking forward to working with you to shape the future of AI and machine learning education.
In the 1950s, Alan Turing explored the central question of artificial intelligence (AI). He thought that the original question, “Can machines think?”, would not provide useful answers because the terms “machine” and “think” are hard to define. Instead, he proposed changing the question to something more provable: “Can a computer imitate intelligent behaviour well enough to convince someone they are talking to a human?” This is commonly referred to as the Turing test.
It’s been hard to miss the newest generation of AI chatbots that companies have released over the last year. News articles and stories about them seem to be everywhere at the moment. So you may have heard of machine learning (ML) chatbots such as ChatGPT and LaMDA. These chatbots are advanced enough to have caused renewed discussions about the Turing Test and whether the chatbots are sentient.
Chatbots are not sentient
Without any knowledge of how people create such chatbots, it’s easy to imagine how someone might develop an incorrect mental model around these chatbots being living entities. With some awareness of Sci-Fi stories, you might even start to imagine what they could look like or associate a gender with them.
The reality is that these new chatbots are applications based on a large language model (LLM) — a type of machine learning model that has been trained with huge quantities of text, written by people and taken from places such as books and the internet, e.g. social media posts. An LLM predicts the probable order of combinations of words, a bit like the autocomplete function on a smartphone. Based on these probabilities, it can produce text outputs. LLM chatbots run on servers with huge amounts of computing power that people have built in data centres around the world.
Our AI education resources for young people
AI applications are often described as “black boxes” or “closed boxes”: they may be relatively easy to use, but it’s not as easy to understand how they work. We believe that it’s fundamentally important to help everyone, especially young people, to understand the potential of AI technologies and to open these closed boxes to understand how they actually work.
As always, we want to demystify digital technology for young people, to empower them to be thoughtful creators of technology and to make informed choices about how they engage with technology — rather than just being passive consumers.
That’s the goal we have in mind as we’re working on lesson resources to help teachers and other educators introduce KS3 students (ages 11 to 14) to AI and ML. We will release these Experience AI lessons very soon.
Why we avoid describing AI as human-like
Our researchers at the Raspberry Pi Computing Education Research Centre have started investigating the topic of AI and ML, including thinking deeply about how AI and ML applications are described to educators and learners.
To support learners to form accurate mental models of AI and ML, we believe it is important to avoid using words that can lead to learners developing misconceptions around machines being human-like in their abilities. That’s why ‘anthropomorphism’ is a term that comes up regularly in our conversations about the Experience AI lessons we are developing.
To anthropomorphise: “to show or treat an animal, god, or object as if it is human in appearance, character, or behaviour”
Anthropomorphising AI in teaching materials might lead to learners believing that there is sentience or intention within AI applications. That misconception would distract learners from the fact that it is people who design AI applications and decide how they are used. It also risks reducing learners’ desire to take an active role in understanding AI applications, and in the design of future applications.
Examples of how anthropomorphism is misleading
Avoiding anthropomorphism helps young people to open the closed box of AI applications. Take the example of a smart speaker. It’s easy to describe a smart speaker’s functionality in anthropomorphic terms such as “it listens” or “it understands”. However, we think it’s more accurate and empowering to explain smart speakers as systems developed by people to process sound and carry out specific tasks. Rather than telling young people that a smart speaker “listens” and “understands”, it’s more accurate to say that the speaker receives input, processes the data, and produces an output. This language helps to distinguish how the device actually works from the illusion of a persona the speaker’s voice might conjure for learners.
Another example is the use of AI in computer vision. ML models can, for example, be trained to identify when there is a dog or a cat in an image. An accurate ML model, on the surface, displays human-like behaviour. However, the model operates very differently to how a human might identify animals in images. Where humans would point to features such as whiskers and ear shapes, ML models process pixels in images to make predictions based on probabilities.
Better ways to describe AI
The Experience AI lesson resources we are developing introduce students to AI applications and teach them about the ML models that are used to power them. We have put a lot of work into thinking about the language we use in the lessons and the impact it might have on the emerging mental models of the young people (and their teachers) who will be engaging with our resources.
It’s not easy to avoid anthropomorphism while talking about AI, especially considering the industry standard language in the area: artificial intelligence, machine learning, computer vision, to name but a few examples. At the Foundation, we are still training ourselves not to anthropomorphise AI, and we take a little bit of pleasure in picking each other up on the odd slip-up.
Here are some suggestions to help you describe AI better:
Avoid using
Instead use
Avoid using phrases such as “AI learns” or “AI/ML does”
Use phrases such as “AI applications are designed to…” or “AI developers build applications that…”
Avoid words that describe the behaviour of people (e.g. see, look, recognise, create, make)
Use system type words (e.g. detect, input, pattern match, generate, produce)
Avoid using AI/ML as a countable noun, e.g. “new artificial intelligences emerged in 2022”
Refer to ‘AI/ML’ as a scientific discipline, similarly to how you use the term “biology”
The purpose of our AI education resources
If we are correct in our approach, then whether or not the young people who engage in Experience AI grow up to become AI developers, we will have helped them to become discerning users of AI technologies and to be more likely to see such products for what they are: data-driven applications and not sentient machines.
On 24 and 25 March, more than 140 members of the Code Club and CoderDojo communities joined us in Cambridge for our first-ever Clubs Conference.
At the Clubs Conference, volunteers and educators came together to celebrate their achievements and explore new ways to support young people to create with technology. The event included community display tables, interactive workshops, discussions,poster sessions, and talks.
For everyone who couldn’t join us in person, we recorded all of the talks that community members gave on the main stage. Here’s what you can learn from the speakers.
Running your club
Jane Waite from our team offered a taste of the research we do and how you can get insights from it to help you run your own coding club. Watch Jane’s talk to learn about the research that informs our projects for your club.
Rhodri Smith, who runs a Code Club, shared how you can use assistive technologies to open your club experience to more young people. Watch Rhodri’s talk for some fantastic tips on how assistive technology can make Code Club accessible to children of all ages and abilities.
Dave Morley, who volunteers at the CoderDojo at Royal Museums Greenwich, presented his way of using Scratch projects to keep engaging Dojo participants. Watch Dave’s talk for tips on how to create your own coding projects for young people.
Tim Duffey, who is part of the West Sound CoderDojo, shared how his Dojo ran successful online sessions during the coronavirus pandemic. Watch Tim’s talk for great advice on how to run successful coding clubs for young people online.
Steph Burton from our team presented new resources we’re working on to help clubs recruit and train volunteers. Watch Steph’s talk for tips on how to recruit new volunteers for your coding club.
Engaging young people in your club
Sophie Hudson, who runs a Code Club in rural Yorkshire, told us how her school’s Code Club turned taking part in Astro Pi Mission Zero into a cross-curricular activity, and how she partnered older learners with younger ones for peer mentoring that engaged new learners in coding. Watch Sophie’s talk to learn how you can get your school involved in Astro Pi, especially if you don’t have much adult support available.
We brought a replica of the Astro Pi computers to the Clubs Conference.
Helen Gardner from our team shared how you can motivate and inspire your coders by supporting them to share their projects in the Coolest Projects showcase — even their very first Scratch animation. Watch Helen’s talk if you’re looking for something new for your club.
The benefits of Code Club and CoderDojo for your community
Fiona Lindsay, who leads a Code Club, presented her insights into the skills beyond coding that young people learn at Code Club, and she shared some wonderful videos of her coders talking about their experience. Watch Fiona’s talk to hear young girls talk about how to get more girls into coding, and for evidence of why every school should have a Code Club.
Last year, Fiona’s Code Club held a special event to celebrate the tenth birthday of Code Club.
Bruce Harms, who is involved in AruCoderDojo, shared how he and his team are making the CoderDojo model part of their wider work to bring digital skills and infrastructure to Aruba. Watch Bruce’s talk to learn how his team has tailored their coding clubs for their local community.
What is volunteering for CoderDojo and Code Club like?
Marcus Davage, who volunteers at a Code Club, shared his journey as a volunteer translator of our resources, and how he engaged colleagues at his workplace in also supporting translations to make coding skills available to more young people across the world. Watch Marcus’s talk if you speak more than one language.
To end the day, we hosted a group of community members onstage to have a chat about their journeys with CoderDojo and Code Club, what they’ve learned, and how they see the future of their clubs. Watch the panel conversation if you want inspiration and advice for getting involved in helping kids create with tech.
Thank you to everyone who gave talks, ran workshops, presented posters, and had conversations to share their questions and insights. It was wonderful to meet all of you, and we came away from the Clubs Conference feeling super inspired by the amazing work Code Club and CoderDojo volunteers all over the world do to help young people learn to create with digital technologies.
We learned so much from listening to you, and we will take the lessons into our work to support you and your clubs in the best way we can.
We are building a new online text-based Code Editor to help young people aged 7 and older learn to write code. It’s free and designed for young people who attend Code Clubs and CoderDojos, students in schools, and learners at home.
The Code Editor interface
At this stage of development, the Code Editor enables learners to:
Write and run Python code right in their browser, with no setup required. The interface is simple and intuitive, which makes getting started with text-based coding easier.
Save their code using their Raspberry Pi Foundation account. We want learners to easily build on projects they start in the classroom at home, or bring a project they’ve started at home to their coding club.
We’ve chosen Python as the first programming language our Code Editor supports because it is popular in schools, CoderDojos, and Code Clubs. Many educators and young people like Python because they see it as similar to the English language. It is often the text-based language young people learn when they take their first steps away from a block-based programming environment, such as Scratch.
Python is also widely used by professional programmers and usually tops at least one of the industry-standard indexes that ranks programming languages.
We will be adding support for web development languages (HTML/CSS/JavaScript) to the Editor in the near future.
We’re also planning to add features such as project sharing and collaboration, which we know young people will love. We want the Editor to be safe, accessible, and age-appropriate. As safeguarding is always at the core of what we do, we’ll only make new features available once we’ve ensured they comply with the ICO’s age-appropriate design code and our safeguarding policies.
Test the Code Editor and tell us what you think
We are inviting you to test the Code Editor as part of what we call the beta phase of development. As the Editor is still in development, some things might not look or work as well as we’d like — and this is why we need your help.
Text output in the Code Editor
We’d love you to try the Editor out and let us know what worked well for you, what didn’t work well, and what you’d like to see next.
You can now try out the Code Editor in the first two projects of our ‘Intro to Python’ path. We’ve included a feedback form for you to let us know which project you tried, and what you think of the Editor. We’d love to hear from you.
Your feedback helps us decide what to do next. Based on what learners, educators, volunteers, teachers, and parents tell us, we will make the improvements to the Editor that matter most to the young people we aim to support.
Where next for the Code Editor?
One of our long-term goals is to engage millions of young people in learning about computing and how to create with digital technologies. We’re developing the Code Editor with three main aims in mind.
1. Supporting young people’s learning journeys
We aim to build the Code Editor so it:
Suits beginners and also supports them as their confidence and independence grows, so they can take on their own coding projects in a familiar environment
Helps learners to transition from block-based to text-based, informed by our deep understanding of pedagogy and computing education
Brings together projects instructions and code editing into a single interface so that young people do not have to switch screens, which makes coding easier
2. Removing barriers to accessing computing education
Our work on the Code Editor will:
Ensure it works well on mobile and tablet devices, and low-cost computers including the Raspberry Pi 4 2GB
Support localisation and translation, so we can tailor the Editor for the needs of young people all over the world
3. Making learning to program engaging for more young people
We want to offer a Code Editor that:
Enables young people to build a vast variety of projects because it supports graphic user interface output and supplies images and sprites for use in multimedia projects
We’re also planning on making the Editor available as an open source project so that other projects and organisations focussed on helping people learn to code can benefit. More on this soon.
Our work on the Code Editor has been generously funded by Endless and the Algorand Foundation, and we thank them for their support. If you are interested in partnering with us to fund this key work, please reach out to us via email.
We meet many young people with an astounding passion for tech, and we also meet the incredible volunteers and educators who help them find their feet in the digital world. Our series of community stories is one way we share their journeys with you.
Today we’re introducing you to Nadia from Maysan, Iraq. Nadia’s achievements speak for themselves, and we encourage you to watch her video to see some of the remarkable things she has accomplished.
Nadia’s journey with the Raspberry Pi Foundation started when she moved to England to pursue a PhD at Brunel University. As an international student, she wanted to find a way to be part of the local community and make the most of her time abroad. Through her university’s volunteer department, she was introduced to Code Club and began supporting club sessions for children in her local library. The opportunity to share her personal passion for all things computer science and coding with young people felt like the perfect fit.
“[Code Club] added to my skills. And at the same time, I was able to share my expertise with the young children and to learn from them as well.”
Nadia Al-Aboody
Soon, Nadia saw that the skills young people learned at her Code Club weren’t just technical, but included team building and communication as well. That’s when she realised she needed to take Code Club with her when she moved back home to Iraq.
A Code Club in every school in Iraq
With personal awareness of just how important it is to encourage girls to engage with computing and digital technologies, Nadia set about training the Code Club network’s first female-only training team. Her group of 15 trainers now runs nine clubs — and counting— throughout Iraq, with their goal being to open a club in every single school in the country.
Reaching new areas can be a challenge, one that Nadia is addressing by using Code Club resources offline:
“Not every child has a smartphone or a device, and that was one of the biggest challenges. The [Raspberry Pi] Foundation also introduced the unplugged activities, which was amazing. It was very important to us because we can teach computer science without the need for a computer or a smart device.”
Nadia Al-Aboody
Nadia also works with a team of other volunteers to translate our free resources related to Code Club and other initiatives for young people into Arabic, making them accessible to many more young people around the world.
Tamasin Greenough Graham, Head of Code Club here at the Foundation, shares just how important volunteers like Nadia are in actively pushing our shared mission forwards.
“Volunteers like Nadia really show us why we do the work we do. Our Code Club team exists to support volunteers who are out there on the ground, making a real difference to young people. Nadia is a true champion for Code Club, and goes out of her way to help give more children access to learning about computing. By translating resources, alongside overseeing a growing network of clubs, she helps to support more volunteers and, in turn, reach more young people. Having Nadia as a member of the community is really valuable.”
Tamasin Greenough Graham, Head of Code Club
If you are interested in becoming a Code Club volunteer, visit codeclub.org for all the information you need to get started.
Help us celebrate Nadia and her commendable commitment to growing the Code Club community in Iraq by sharing her story on Twitter, LinkedIn, and Facebook.
People have many different reasons to think that children and teenagers need to learn about artificial intelligence (AI) technologies. Whether it’s that AI impacts young people’s lives today, or that understanding these technologies may open up careers in their future — there is broad agreement that school-level education about AI is important.
But how do you actually design lessons about AI, a technical area that is entirely new to young people? That was the question we needed to answer as we started Experience AI, our exciting collaboration with DeepMind, a leading AI company.
Our approach to developing AI education resources
As part of Experience AI, we are creating a free set of lesson resources to help teachers introduce AI and machine learning (ML) to KS3 students (ages 11 to 14). In England this area is not currently part of the national curriculum, but it’s starting to appear in all sorts of learning materials for young people.
We reviewed over 500 existing resources that are used to teach AI and ML.
As part of this research, we reviewed over 500 existing resources that are used to teach AI and ML. We found that the vast majority of them were one-off activities, and many claimed to be appropriate for learners of any age. There were very few sets of lessons, or units of work, that were tailored to a specific age group. Activities often had vague learning objectives, or none at all. We rarely found associated assessment activities. These were all shortcomings we wanted to avoid in our set of lessons.
The SEAME framework gives you a simple way to group learning objectives and resources related to teaching AI and ML, based on whether they focus on social and ethical aspects (SE), applications (A), models (M), or engines (E, i.e. how AI works). We hope that it will be a useful tool for anyone who is interested in looking at resources to teach AI.
What do AI education resources focus on?
The four levels of the SEAME framework do not indicate a hierarchy or sequence. Instead, they offer a way for teachers, resource developers, and researchers to talk about the focus of AI learning activities.
Social and ethical aspects (SE)
The SE level covers activities that relate to the impact of AI on everyday life, and to its implications for society. Learning objectives and their related resources categorised at this level introduce students to issues such as privacy or bias concerns, the impact of AI on employment, misinformation, and the potential benefits of AI applications.
An example activity in the Experience AI lessons where learners think about the social and ethical issues of an AI application that predicts what subjects they might want to study. This activity is mostly focused on the social and ethical level of the SEAME framework, but also links to the applications and models levels.
Applications (A)
The A level refers to activities related to applications and systems that use AI or ML models. At this level, learners do not learn how to train models themselves, or how such models work. Learning objectives at this level include knowing a range of AI applications and starting to understand the difference between rule-based and data-driven approaches to developing applications.
Models (M)
The M level concerns the models underlying AI and ML applications. Learning objectives at this level include learners understanding the processes used to train and test models. For example, through resources focused on the M level, students could learn about the different learning paradigms of ML (i.e., supervised, unsupervised, or reinforcement learning).
An example activity in the Experience AI lessons where students learn about classification. This activity is mostly focused on the models level of the SEAME framework, but also links to the social and ethical and the applications levels.
Engines (E)
The E level is related to the engines that make AI models work. This is the most hidden and complex level, and for school-aged learners may need to be taught using unplugged activities and visualisations. Learning objectives could include understanding the basic workings of systems such as data-driven decision trees and artificial neural networks.
Covering the four levels
Some learning activities may focus on a single level, but activities can also span more than one level. For example, an activity may start with learners trying out an existing ‘rock-paper-scissors’ application that uses an ML model to recognise hand shapes. This would cover the applications level. If learners then move on to train the model to improve its accuracy by adding more image data, they work at the models level.
Other activities cover several SEAME levels to address a specific concept. For example, an activity focussed on bias might start with an example of the societal impact of bias (SE level). Learners could then discuss the AI applications they use and reflect on how bias impacts them personally (A level). The activity could finish with learners exploring related data in a simple ML model and thinking about how representative the data is of all potential application users (M level).
The set of lessons on AI we are developing in collaboration with DeepMind covers all four levels of SEAME.
The set of Experience AI lessons we are developing in collaboration with DeepMind covers all four levels of SEAME. The lessons are based on carefully designed learning objectives and specifically targeted to KS3 students. Lesson materials include presentations, videos, student activities, and assessment questions.
We’re releasing the Experience AI lessons very soon — if you want to be the first to hear news about them, please sign up here.
The SEAME framework as a tool for research on AI education
For researchers, we think the SEAME framework will, for example, be useful to analyse school curriculum material to see whether some age groups have more learning activities available at one level than another, and whether this changes over time. We may find that primary school learners work mostly at the SE and A levels, and secondary school learners move between the levels with increasing clarity as they develop their knowledge. It may also be the case that some learners or teachers prefer activities focused on one level rather than another. However, we can’t be sure: research is needed to investigate the teaching and learning of AI and ML across all year groups.
That’s why we’re excited to welcome Salomey Afua Addo to the Raspberry Pi Computing Education Research Centre. Salomey joined the Centre as a PhD student in January, and her research will focus on approaches to the teaching and learning of AI. We’re looking forward to seeing the results of her work.
We are excited to launch Ada Computer Science, the new online learning platform for teachers, students, and anyone interested in learning about computer science.
With the rapid advances being made in AI systems and chatbots built on large language models, such as ChatGPT, it’s more important than ever that all young people understand the fundamentals of computer science.
Our aim is to enable young people all over the world to learn about computer science through providing access to free, high-quality and engaging resources that can be used by both students and teachers.
A partnership between the Raspberry Pi Foundation and the University of Cambridge, Ada Computer Science offers comprehensive resources covering everything from algorithms and data structures to computational thinking and cybersecurity. It also has nearly 1000 rigorously researched and automatically marked interactive questions to test your understanding. Ada Computer Science is improving all the time, with new content developed in response to user feedback and the latest research. Whatever your interest in computer science, Ada is the place for you.
If you’re teaching or studying a computer science qualification at school, you can use Ada Computer Science for classwork, homework, and revision. Computer science teachers can select questions to set as assignments for their students and have the assignments marked directly. The assignment results help you and your students understand how well they have grasped the key concepts and highlights areas where they would benefit from further tuition. Students can learn with the help of written materials, concept illustrations, and videos, and they can test their knowledge and prepare for exams.
A comprehensive resource for computing education
Ada Computer Science builds on work we’ve done to support the English school system as part of the National Centre for Computing Education, funded by the Department for Education.
The topics on the website map to exam board specifications for England’s Computer Science GCSE and A level, and will map to other curricula in the future.
In addition, we want to make it easy for educators and learners across the globe to use Ada Computer Science. That’s why each topic is aligned to our own comprehensive taxonomy of computing content for education, which is independent of the English curriculum, and organises the content into 11 strands, including programming, computing systems, data and information, artificial intelligence, creating media, and societal impacts of digital technology.
If you are interested in how we can specifically adapt Ada Computer Science for your region, exam specification, or specialist area, please contact us.
Why use Ada Computer Science at school?
Ada Computer Science enables teachers to:
Plan lessons around high-quality content
Set self-marking homework questions
Pinpoint areas to work on with students
Manage students’ progress in a personal markbook
Students get:
Free computer science resources, written by specialist teachers
A huge bank of interactive questions, designed to support learning
A powerful revision tool for exams
Access wherever and whenever you want
In addition:
The topics include real code examples in Python, Java, VB, and C#
The live code editor features interactive coding tasks in Python
While 14 March is an opportunity for our American friends to celebrate the mathematical constant Pi, we are also very happy to make this day a chance to say a massive thank you to everyone who supports the Raspberry Pi Foundation’s work through their generous donations.
More than computers
You may know that the Raspberry Pi story started in Cambridge, UK, in 2008 when a group of engineers-cum-entrepreneurs set out to improve computing education by inventing a programmable computer for the price of a textbook.
Fast forward 15 years and there are almost 50 million Raspberry Pi computers in the wild, being used to revolutionise education and industry alike. Removing price as a barrier for anyone to own a powerful, general-purpose computer will always be an important part of our mission to democratise access to computing.
What we’ve learned over the years is that access to low-cost, high-quality hardware is essential, but not sufficient.
If we want all young people to be able to take advantage of the potential offered by technological innovation, then we also need to support teachers to introduce computing in schools, find ways to inspire young people to learn outside of their formal education, and make sure that everything we do is informed by rigorous research.
That’s the focus of our educational mission at the Raspberry Pi Foundation, and we couldn’t do this work without your support.
What we achieve for young people thanks to your support
We are fortunate that a large and growing community of people, corporations, trusts, and foundations makes very generous donations to support our educational mission. It’s thanks to you that we are able to achieve what we do for young people and educators:
In 2022 alone, over 3.54m people engaged with our free online learning resources for young people, including brand-new pathways of projects for HTML/CSS, Python, and Raspberry Pi Pico.
Supported by us, more than 4500 Code Club and CoderDojos are running in 103 countries, and an additional 2891 clubs that were disrupted by the coronavirus pandemic tell us that they are actively planning to start running sessions for young people again soon.
We engaged over 30,000 young people in challenges such as Astro Pi and Coolest Projects, enabling them to showcase their skills, think about how to solve problems using technology, and connect with like-minded peers.
We have supported tens of thousands of computing teachers through our curriculum, resources, and online training. For example, The Computing Curriculum, which we developed as part of the National Centre for Computing Education in England, is now being used by educators all over the world, with 1.7m global downloads in 2022.
We completed and published the findings of the world’s largest-ever research programme testing how to improve the gender balance in computing. We are now working on integrating the insights from the programme into our own work and making them accessible and actionable for practitioners.
Trust me when I say this is just a small selection of highlights, all of which are made possible by our amazing supporters. Thank you, and I hope that we made you proud.
Get involved today
If you haven’t yet made a donation to our Pi Day campaign, it’s not too late to get involved. Your donation will help inspire the next generation of digital makers.
We are working in partnership with Amala Education to pilot a vocational skills course for displaced learners aged 16 to 25 in Kakuma refugee camp, Kenya.
Kakuma camp was set up in Kenya in 1992, following a civil war in neighbouring South Sudan in East Africa. Today, 2 million people are living in the camp, and 61% are 18 and younger.
We’ve designed a 100-hour, 10-week course called Using online digital technologies to create change for the Amala learners in Kakuma camp. The course focused on digital skills including making media and websites, with its content we adapted from our Computing Curriculum. The course pilot was delivered alongside Amala’s High School Diploma programme, which is the first internationally accredited course programme enabling refugee and host community youth to complete their education through flexible study.
Our thanks go to the Ezrah Charitable Trust for generously funding our work in this partnership.
Sharing lessons we are learning
We are learning a lot during this pilot, so we are writing a set of three blogs to share these lessons with you.
Today’s blog is Amala Education‘s perspective on their learners in Kakuma Camp, the purpose of digital skills education, and the course design and facilitation. We will also share our approach to adapting learning resources for the context of the Amala learners and using data to assess the course, and what other support we’ve put in place to ensure this educational project is self-sustaining.
Want to make computing education meaningful? Make it connect to learners’ lived experience
By Polly Akhurst (Co-founder and Co-Executive Director, Amala Education), Louie Barnett (Education Lead, Amala Education) & Ajak Mayen Jok (Programme Coordinator, Amala Education)
Our learners wanted a course that develops not just their digital literacy, but one that aligns with Amala’s agency-based learning model, which gives young people the skills to improve their communities. Many of our learners have limited experience of using digital tools but a huge desire to develop these skills, which they see as essential to improving their lives and the lives of their community members.
So we knew we needed a course that not just builds learners’ technical knowledge and skills but can also enrich their lived experience.
How would we do it?
Enter the Raspberry Pi Foundation team. We combined Amala’s agency-based educational approach with the Raspberry Pi Foundation’s experience in pedagogy and teaching about technology and digital literacy to design a course that truly resonates with our learners.
Developing a relevant digital skills course
Before developing the course, the Raspberry Pi Foundation team held focus groups with facilitators and learners in Kakuma camp to understand their needs. This helped them to pitch the 100 hours of course materials at the right level for the learners.
We called the course Using online technologies to create change. It takes the learners on a journey, building their foundation elements of computing and digital literacy. Learners start by finding out how digital devices work using input, process, and output. Then they move on to understanding computer networks. The course includes hands-on activities related to creating media, like filming and reviewing content and creating and choosing sounds to use in a podcast. There is also some light-touch web development with HTML and JavaScript. At the end of the course, learners design and deliver a presentation that reflects the work they’ve completed.
“Before I joined the course, I really didn’t know much about how to operate technology, but through the learning and the process, now I am able to learn something that will be beneficial for me and the people in my community.” — Learner in Kakuma refugee camp
Throughout the course, learners use their newly gained skills and knowledge to make their own project aimed at creating positive change. One example project is this website developed by Shyaka Cedric and other learners, which shares how podcasts and remote learning helped their community stay safe and healthy during the pandemic. Another group of learners used their photography and design skills to develop ID cards to keep Amala students safe within the camp. Having an Amala student ID card protects learners because they can prove their identity to their community and the police.
Facilitators from the camp make the course relatable
One of the great things about this course is that the Amala facilitators who taught the learners look, speak, and sound like them. Amala facilitators are from within the camp, and that they are relatable is great for learners’ self-confidence.
Having the course facilitated by fellow refugees removes the stigmatisation that the learners are vulnerable and sets the precedent that they can do anything if they put their mind to it.
“It gave me power of… getting involved with new things…Any challenge that comes my way I am willing to take after the Raspberry Pi class now…” — Learner in Kakuma refugee camp
While the Raspberry Pi Foundation team worked to make the course content relevant for the learners, our facilitators further localised the content to ensure its relatability for learners. Local contextualisation helps students to understand what they are learning, and to identify with the content — it’s not something out of the blue for them. Localisation is also important because it helps implement one of Amala’s cornerstones: decolonising the African curriculum.
Digital literacy is an urgent need
Because the learners in Kakuma camp lead complex social lives and face high levels of precarity, we decided to make the pilot course optional through our existing Diploma programme. We anticipated a modest enrollment rate, but instead over 100 people within the Amala learner community expressed an interest in this 75-person course. This showed us that the value and urgency of digital literacy in refugee communities is more pertinent than ever.
“I want to study this course because the current world is a digital world and I would like to acquire the skills to boost my computer skills and be able to help myself by getting a job and transforming the community through the digital world.” — Learner in Kakuma refugee camp
So what’s happening next?
We have a blueprint of what works in Kakuma refugee camp, and we are also learning what doesn’t. Bringing these lessons together will help us offer the course to more learners in Kakuma, and adapt the content in other locations, like our site in Amman, Jordan.
Look out for our follow-up blogs about the support we put in place to enable learners in Kakuma camp to participate in the course, and how we worked to create course content that is suitable for them.
This year’s International Women’s Day (IWD) focuses on innovation and technology for gender equality. This cause aligns closely with our mission as a charity: to enable young people to realise their full potential through the power of computing and digital technologies. An important part of our mission is to shift the gender balance in computing education.
Gender inequality in the digital and computing sector
As the UN Women’s announcement for IWD 2023 says: “Growing inequalities are becoming increasingly evident in the context of digital skills and access to technologies, with women being left behind as the result of this digital gender divide. The need for inclusive and transformative technology and digital education is therefore crucial for a sustainable future.”
According to the UN, women currently hold only 2 in every 10 science, engineering, and information and communication technology jobs globally. Women are a minority of university-level students in science, technology, engineering, and mathematics (STEM) courses, at only 35%, and in information and communication technology courses, at just 3%. This is especially concerning since the WEF predicts that by 2050, 75% of jobs will relate to STEM.
We see this situation reflected in England: computer science is the secondary school subject with the largest gender gap at A level, with girls accounting for only 15% of students. That’s why over the past three years, we have run a research programme to trial ways to encourage more young women to study Computer Science. The programme, Gender Balance in Computing, has produced useful insights for designing equitable computing education around the world.
Who belongs in computing?
The UN says that “across countries, girls are systematically steered away from science and math careers. Teachers and parents, intentionally or otherwise, perpetuate biases around areas of education and work best ‘suited’ for women and men.” There is strong evidence to suggest that the representation of women and girls in computing can be improved by introducing them to computing role models such as female computing students or women in tech careers.
Presenting role models was central to the Belonging trial in our Gender Balance in Computing programme. One arm of this trial used resources developed by WISE called My Skills My Life to explore the effect of introducing role models into computing lessons for primary school learners. The trial provided opportunities for learners to speak to women who work in technology. It also offered a quiz to help learners identify their strengths and characteristics and to match them with role models who were similar to them, which research shows is more effective for increasing learners’ confidence.
“Learning about computing makes me feel good because it helps me think more about what I want to be.” — Primary school learner in the Belonging trial
“When [the resources were] showing all of the females in the jobs, nobody went ‘Oh, I didn’t know that a female could do that’, but I think they were amazed by the role of jobs and the fact it was all females doing it.“ — Primary school teacher in the Belonging trial
Learning together to give everyone a voice
When teachers and students enter a computing classroom, they bring with them diverse social identities that affect the dynamics of the classroom. Although these dynamics are often unspoken, they can become apparent in which students answer questions or succeed visibly in activities. Without intervention, a dominant group of confident speakers can emerge, and students who are not in this dominant group may lose confidence in their abilities. When teachers set collaborative learning activities that use defined roles or structured discussions, this gives a wider range of students the opportunity to speak up and participate.
Pair programming is one such activity that has been used in research studies to improve learner attitudes and confidence towards computing. In pair programming, one learner is the ‘driver’. They control the keyboard and mouse to write the code. The other learner is the ‘navigator’. They read out the instructions and monitor the code for errors. Learners swap roles regularly, so that both can participate equitably. The Pair Programming trial we conducted as part of Gender Balance in Computing explored the use of this teaching approach with students aged 8 to 11. Feedback from the teachers showed that learners found working in structured pairs engaging.
“Even those who are maybe a little bit more reluctant… those who put their hands up today and said they still prefer to work independently, they are still all engaging quite clearly in that with their pair and doing it really, really well. However much they say they prefer working independently, I think they clearly showed how much they enjoy it, engage with it. And you know they’re achieving with it — so we should be doing this.” – Primary school teacher in the Pair Programming trial
Another collaborative teaching approach is peer instruction. In lessons that use peer instruction, students work in small groups to discuss the answer to carefully constructed multiple choice questions. A whole-class discussion then follows. In the Peer Instruction trial with learners aged 12 to 13 in our Gender Balance in Computing programme, we found that this approach was welcomed by the learners, and that it changed which learners offered answers and ideas.
“I prefer talking in a group because then you get the other side of other people’s thoughts.” – Secondary school learner (female) in the Peer Instruction trial
“[…] you can have a bit of time to think for yourself then you can bounce ideas off other people.” – Secondary school learner (male) in the Peer Instruction trial
“I was very pleased that a lot of the girls were doing a lot of the talking.” – Secondary school teacher in the Peer Instruction trial
We need to do more, and sooner
Our Gender Balance in Computing research programme showed that no single intervention we trialled significantly increased girls’ engagement in computing or their intention to study it further. Combining several of the approaches we tested may be more impactful. If you’re part of an educational setting where you’d like to adopt multiple approaches at the same time, you can freely access the materials associated with the research programme (see our blog posts about the trials for links).
The research programme also showed that age matters: across Gender Balance in Computing, we observed a big difference in intent to study Computing between primary school and secondary school learners (data from ages 8–11 and 12–13). Fewer secondary school learners reported intent to study the subject further, and while this difference was apparent for both girls and boys, it was more marked for girls.
This finding from England is mirrored by a study the UN Women’s Gender Snapshot 2022 refers to: “A 2020 study of Filipina girls demonstrated that loss of interest in STEM subjects started as early as age 10, when girls began perceiving STEM careers as male-dominated and believing that girls are naturally less adept in STEM subjects. The relative lack of female STEM role models reinforced such perceptions.” That’s why it’s necessary that all primary school learners — no matter what their gender is — have a successful start in the computing classroom, that they encounter role models they can relate to, and that they are supported to engage in computing and creating with technology by their parents, teachers, and communities.
The Foundation’s vision is that every young person develops the knowledge, skills, and confidence to use digital technologies effectively, and to be able to critically evaluate these technologies and confidently engage with technological change. While making changes inside the computing classroom will be beneficial for gender equality, this is just one aspect of building an equitable digital future. We all need to contribute to creating a world where innovation and technology support gender equity.
This IWD, we invite you to share your thoughts on what equitable computing education means to you, and what you think is needed to achieve it, whether that’s in your school or club, in your local community, or in your country.
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