We are hosting a series of free research seminars about how to teach artificial intelligence (AI) and data science to young people, in partnership with The Alan Turing Institute.

In the fifth seminar of this series, we heard from Rose Luckin, Professor of Learner Centred Design at the University College London (UCL) Knowledge Lab. Rose is Founder of EDUCATE Ventures Research Ltd., a London consultancy service working with start-ups, researchers, and educators to develop evidence-based educational technology.

Based on her experience at EDUCATE, Rose spoke about how AI-based analysis can help educators gain a deeper understanding of their students, and how educators can work with AI systems to provide better learning resources to their students. This provided us with a different angle to the first four seminars in our current series, where we’ve been thinking about how young people learn to understand AI systems.

Education and AI systems

AI systems have the potential to impact education in a number of different ways, which Rose distilled into three areas: 

1. Using AI in education to tackle some of the big educational challenges
2. Educating teachers about AI so that they can use it safely and effectively 
3. Changing education so that we focus on human intelligence and prepare people for an AI world

It is clear that the three areas are interconnected, meaning developments in one area will affect the others. Rose’s focus during the seminar was the second area: educating people about AI.

What can AI systems do in education? 

Through giving examples of existing AI-based systems used for education, Rose described what in particular it is about AI systems that can be useful in an education setting. The first point she raised was that AI systems can adapt based on learning from data. Her main example was the AI-based platform ENSKILLS, which detects the user’s level of competency with spoken English through the user’s interactions with a virtual character, and gradually adapts the character to the user’s level. Other examples of adaptive AI systems for education include Carnegie Learning and Century Intelligent Learning.

We know that AI systems can respond to different forms of data. Rose introduced the example of OyaLabs to demonstrate how AI systems can gather and process real-time sensory data. This is an app that parents can use in a young child’s room to monitor the child’s interactions with others. The app analyses the data it gathers and produces advice for parents on how they can support their child’s language development.

AI system creators can also combine adaptivity and real-time sensory data processing  in their systems. One example Rosa gave of this was SimSensei from the University of Southern California. This is a simulated coach, which a student can interact with and which gathers real-time data about how the student is speaking, including their tone, speed of speech, and facial expressions. The system adapts its coaching advice based on these interactions and on what it learns from interactions with other students.

Getting ready for AI systems in education

For the remainder of her presentation, Rose focused on the framework she is involved in developing, as part of the EDUCATE service, to support organisations to prepare for implementing AI systems, including educators within these organisations. The aim of this ETHICAI framework is to enable organisations and educators to understand:

• What AI systems are capable of doing
• The strengths and weaknesses of AI systems
• How data is used by AI systems to learn

Rose described the seven steps of the framework as:

1. Educate, enthuse, excite – about building an AI mindset within your community 
2. Tailor and Hone – the particular challenges you want to focus on
3. Identify – identify (wisely), collate and …
4. Collect – new data relevant to your focus
5. Apply – AI techniques to the relevant data you have brought together
6. Learn – understand what the data is telling you about your focus and return to step 5 until you are AI ready
7. Iterate

She then went on to demonstrate how the framework is applied using the example of online teaching. Online teaching has been a key part of education throughout the coronavirus pandemic; AI systems could be used to analyse datasets generated during online teaching sessions, in order to make decisions for and recommendations to educators.

The first step of the ETHICAI framework is educate, enthuse, excite. In Rose’s example, this step consisted of choosing online teaching as a scenario, because it is very pertinent to a teacher’s practice. The second step is to tailor and hone in on particular challenges that are to be the focus, capitalising on what AI systems can do. In Rose’s example, the challenge is assessing the quality of online lessons in a way that would be useful to educators. The third step of the framework is to identify what data is required to perform this quality assessment.

The fourth step is the collection of new data relevant to the focus of the project. The aim is to gain an increased understanding of what happens in online learning across thousands of schools. Walking through the online learning example, Rose suggested we might be able to collect the following types of data:

• Log data
• Audio data
• Performance data
• Video data, which includes eye-movement data
• Historical data from tests and interviews
• Behavioural data from surveying teachers and parents about how they felt about online learning

It is important to consider the ethical implications of gathering all this data about students, something that was a recurrent theme in both Rose’s presentation and the Q&A at the end.

Step five of the ETHICAI framework focuses on applying AI techniques to the relevant data to combine and process it. The figure below shows that in preparation, the various data sets need to be collated, cleaned, organised, and transformed.

From the correctly prepared data, interaction profiles can be produced in order to put characteristics from different lessons into groups/profiles. Rose described how cluster analysis using a combination of both AI and human intelligence could be used to sort lessons into groups based on common features.

The sixth step in Rose’s example focused on what may be learned from analysing collected data linked to the particular challenge of online teaching and learning. Rose said that applying an AI system to students’ behavioural data could, for example, give indications about students’ focus and confidence, and make or recommend interventions to educators accordingly.

Where might we take applications of AI systems in education in the future?

Rose described that AI systems can possess some types of intelligence humans have or can develop: interdisciplinary academic intelligence, meta-knowing intelligence, and potentially social intelligence. However, there are types such as meta-contextual intelligence and perceived self-efficacy that AI systems are not able to demonstrate in the way humans can.

The use of AI systems in education can cause ethical issues. As an example, Rose pointed out the use of virtual glasses to identify when students need help, even if they do not realise it themselves. A system like this could help educators with assessing who in their class needs more help, and could link this back to student performance. However, using such a system like this has obvious ethical implications, and some of these were the focus of the Q&A that followed Rose’s presentation.

It’s clear that, in the education domain as in all other domains, both positive and negative outcomes of integrating AI are possible. In a recent paper written by Wayne Holmes (also from the UCL Knowledge Lab) and co-authors, ‘Ethics of AI in Education: Towards a Community Wide Framework’ [1], the authors suggest that the interpretation of data, consent and privacy, data management, surveillance, and power relations are all ethical issues that should be taken into consideration. Finding consensus for a practical ethical framework or set of principles, with all stakeholders, at the very start of an AI-related project is the only way to ensure ethics are built into the project and the AI system itself from the ground up.

Ethical issues of AI systems more broadly, and how to involve young people in discussions of AI ethics, were the focus of our seminar with Dr Mhairi Aitken back in September. You can revisit the seminar recording, presentation slides, and summary blog post.

I really enjoyed both the focus and content of Rose’s talk: educators understanding how AI systems may be applied to education in order to help them make more informed decisions about how to best support their students. This is an important factor to consider in the context of the bigger picture of what young people should be learning about AI. The work that Rose and her colleagues are doing also makes an important contribution to translating research into practical models that teachers can use.

Join our next free seminars

You may still have time to sign up for our Tuesday 11 January seminar, today at 17:00–18:30 GMT, where we will welcome Dave Touretzky and Fred Martin, founders of the influential AI4K12 framework, which identifies the five big ideas of AI and how they can be integrated into education.

Next month, on 1 February at 17:00–18:30 GMT, Tara Chklovski (CEO of Technovation) will give a presentation called Teaching youth to use AI to tackle the Sustainable Development Goals at our seminar series.

If you want to join any of our seminars, click the button below to sign up and we will send you information on how to join. We look forward to seeing you there!

You’ll always find our schedule of upcoming seminars on this page. For previous seminars, you can visit our past seminars and recordings page.

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This morning, our two new Astro Pi units launched into space. Actual, real-life space. The new Astro Pi units each consist of a Raspberry Pi computer with a Raspberry Pi High Quality Camera and a host of sensors, all housed inside a special space-ready case that makes the hardware suitable for the International Space Station (ISS).

The journey to space for two special Raspberry Pi computers

Today’s launch is the culmination of a huge piece of work we’ve done for the European Space Agency to get the new Astro Pi units ready to become part of the European Astro Pi Challenge.

After lift-off from Launch Complex 39A at Kennedy Space Center in Florida, the new Astro Pi units are currently travelling on a SpaceX Falcon 9 rocket carrying the Dragon 2 spacecraft, the module atop the rocket. You can watch the launch again here.

Also travelling with our Astro Pi units are food and some Christmas presents for the astronauts on board the ISS, materials for a study of the delivery of cancer drugs; a bioprinter for experiments investigating wound healing; and materials for a study of how detergents work in microgravity.

The Dragon 2 spacecraft will berth with the ISS tomorrow, with NASA astronauts Raja Chari and Tom Marshburn monitoring its arrival. ESA astronaut Matthias Maurer and another colleague will be there to unpack its cargo. You can watch the process of unpacking tomorrow, Wed 22 December, at 8.30am GMT / 9.30am CET. In the new year, Matthias will be switching our Astro Pi units on and getting them ready to run the code written by young people participating in the European Astro Pi Challenge. The new Astro Pi units will replace Astro Pi units Ed and Izzy, which have been on the ISS for 6 years — ever since the very first Astro Pi Challenge with British ESA astronaut Tim Peake in 2015.

We’re looking forward to seeing the amazing experiments this year’s Astro Pi Mission Space Lab teams will perform on the new hardware, and what they’ll discover about life on Earth and in space. We also can’t wait to see what the young people participating in Astro Pi Mission Zero will name the new Astro Pi units!

Building space-ready Astro Pi units

None of us on the team working on the Astro Pi Challenge here at the Foundation are aerospace engineers. While building the new Astro Pi units, we’ve learned so much.

To get the Astro Pis ready to be loaded onto the rocket has been a project of more than three years. That’s because, in addition to manufacturing the Astro Pi units, we also had to ensure they pass the necessary safety and certification process. The official name for this is the Safety Gate process. It’s been set up by ESA and NASA to ensure that any items sent to the ISS are safe to operate on board the station.

For the three separate safety panels the Astro Pi units needed to get through, we put the units through different tests and completed various safety reports. The tests included:

• A vibration test: To make sure the Astro Pi units survive the rigours of the launch, we tested them using the sophisticated rigs at Airbus in Portsmouth. These rigs are capable of simulating the vibrations produced by various different launch vehicles. We needed to test all possible options, because the Astro Pi units didn’t have a confirmed vehicle to travel to the ISS yet.

• A thermal test: To make sure no harm can possibly come to the crew from the Astro Pi units, we needed to check that the touch temperature of the Astro Pi units’ surface is never above 45°C.

• A test for sharp edges: Each Astro Pi unit also needed to be manually inspected by someone wearing a latex glove who carefully feels the case for sharp edges.

• Stringent, military-grade electromagnetic emissions and susceptibility tests: These are required to guarantee that the Astro Pi units won’t interfere with any ISS systems, and that the units themselves are not affected by other equipment on board.

• We built two additional Astro Pi units and sent them to NASA so that they could test that plugging the units into the ISS power grid wouldn’t cause a power overload. 

For almost all of these tests, we created custom software to do things like stress the Astro Pi units’ processors, saturate the network links, and generally make the units work as hard as possible. 

To accompany these safety and test reports, we also had to create the Flight Safety Data Package (FSDP), which contains exact technical information about every component of the Astro Pi hardware, and about all the necessary safety controls to qualify the use of certain materials and safely manage operation of the units. The current FSDP paperwork stands at over 700 pages, which thankfully we haven’t had to actually print out!

Young people’s code will run on the new Astro Pi units next year — is yours on board?

All of this work culminated today in the Astro Pis being launched up into space from Cape Canaveral. And we’re doing all this so that more young people can take part in the European Astro Pi Challenge and send messages to the ISS astronauts using code as part of Mission Zero, or write code for new, ambitious experiments to run on the ISS as part of Mission Space Lab.

Young people can take part in Astro Pi Mission Zero right now! Mission Zero is a beginners’ coding activity for all young people under the age of 19 in ESA member and associate states. It gives them the chance to write code to show their own message to the astronauts on board the ISS using the Astro Pi units. And this time, Mission Zero participants can also vote to name the new Astro Pi units!

To participate, young people follow our step-by-step instructions to write their Mission Zero code. As an adult supporting a young person on Mission Zero, all you need to do is sign up as a mentor to get them a registration code for their Mission Zero entry. Once your young person’s code has run in space, we’ll send you a special certificate for them showing where the ISS, and the Astro Pi computers, were when their code ran.

Inspire a young person to learn about coding and space science today with Astro Pi Mission Zero!

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The global IT industry generates as much CO2 as the aviation industry. In Hello World issue 17, we learn about the hidden impact of our IT use and the changes we can make from Beverly Clarke, national community manager for Computing at School and author of Computer Science Teacher: Insight Into the Computing Classroom.

With the onset of the pandemic, the world seemed to shut down. Flights were grounded, fewer people were commuting, and companies and individuals increased their use of technology for work and communication. On the surface, this seemed like a positive time for the environment. However, I soon found myself wondering about the impact that this increased use of technology would have on our planet, in particular the increases in energy consumption and e-waste. This is a major social, moral, and ethical issue that is hiding in plain sight — green IT is big news.

This is a major social, moral, and ethical issue that is hiding in plain sight — green IT is big news.

Energy and data centres

Thinking that online is always better for the planet is not always as straightforward as it seems. If we choose to meet via conference call rather than travelling to a meeting, there are hidden environmental impacts to consider. If there are 50 people on a call from across the globe, all of the data generated is being routed around the world through data centres, and a lot of energy is being used. If all of those people are also using video, that is even more energy than audio only.

Not only is the amount of energy being used a concern, but we must also ask ourselves how these data centres are being powered. Is the energy they are using coming from a renewable source? If not, we may be replacing one environmental problem with another.

What about other areas of our lives, such as taking photos or filming videos? These two activities have probably increased as we have been separated from family and friends. They use energy, especially when the image or video is then shared with others around the world and consequently routed through data centres. A large amount of energy is being used, and more is used the further the image travels.

Not only is the amount of energy being used a concern, but we must also ask ourselves how these data centres are being powered.

Similarly, consider social media and the number of posts individuals and companies make on a daily basis. All of these are travelling through data centres and using energy, yet for the most part this is not visible to the user.

E-waste

E-waste is another green IT issue, and one that will only get worse as we rely on electronic devices more. As well as the potential eyesore of mountains of e-waste, there is also the impact upon the planet of mining the precious metals used in these electronics, such as gold, copper, aluminium, and steel.

The processes used to mine these metals lead to pollution, and we should also consider that some of the precious metals used in our devices could run out, as there is not an endless supply in the Earth’s surface.

It is also problematic that a lot of e-waste is sent to developing countries with limited recycling plants […].

It is also problematic that a lot of e-waste is sent to developing countries with limited recycling plants, and so much of the e-waste ends up in landfill. This can lead to toxic substances being leaked into the Earth’s surface.

First steps towards action

With my reflective hat on, I started to think about discussions we as teachers could have with pupils around this topic, and came up with the following:

• Help learners to talk about the cloud and where it is located. We can remind them that the cloud is a physical entity. Show them images of data centres to help make this real, and allow them to appreciate where the data we generate every day goes.
• Ask learners how many photos and videos they have on their devices, and where they think those items are stored. This can be extended to a year group or whole-school exercise so they can really appreciate the sheer amount of data being used and sent across the cloud, and how data centres fit with that energy consumption. I did this activity and found that I had 7163 photos and 304 videos on my phone — that’s using a lot of energy!

• Ask learners to research any local data centres and find out how many data centres there are in the world. You could then develop this into a discussion, including language related to data centres such as sensors, storage devices, cabling, and infrastructure. This helps learners to connect the theory to real-world examples.
• Ask learners to reflect upon how many devices they use that are connected to the Internet of Things.
• Consider for ourselves and ask parents, family, and friends how our online usage has changed since before the pandemic.
• Consider what happens to electronic devices when they are thrown away and become e-waste. Where does it all go? What is the effect of e-waste on communities and countries?

Tips for greener IT

UK-based educators can watch a recent episode of TV programme Dispatches that investigates the carbon footprint of the IT industry. You can add the following tips from the programme to your discussions:

• Turn off electronic devices when not in use
• Use audio only when on online calls
• Dispose of your old devices responsibly
• Look at company websites and see what their commitment is to green IT, and consider whether we should support companies whose commitment to the planet is poor
• Use WiFi instead of 3G/4G/5G, as it uses less energy

These lists are not exhaustive, but provide a good starting point for discussions with learners. We should all play our small part in ensuring that we #RestoreOurEarth — this year’s Earth Day theme — and having an awareness and understanding of the impact of our use of electronic devices is part of the way forward.

Some resources on green IT — do you have others?

• BCS (British Computer Society, The Charted Institute of IT) has a Green IT specialist group, a community of IT professionals and enthusiasts who are passionate about green IT
• Dispatches documentary Online Habits Killing the Planet (only available to UK and ROI residents)

What about you? In the comments below, share your thoughts, tips, and resources on green IT and how we can bring awareness of it to our learners and young people at home.

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We’re feeling nostalgic because six years ago, two special Raspberry Pi computers named Ed and Izzy were travelling to the International Space Station (ISS) from Cape Canaveral, Florida, USA. These two Astro Pi units joined British ESA astronaut Tim Peake as part of his six-month Principia space mission. Tim and Astro Pis Ed and Izzy helped hundreds of young people run their own computer programs in space as part of the first Astro Pi Challenge.

We are also feeling excited, because Tim and our Head of Youth Partnerships, Olympia Brown, are talking to British TV and radio shows today about all things space and Astro Pi, including the exciting new developments and how families can get involved! You might catch Tim on your favourite channel.

Tim Peake has been our Astro Pi champion from the start

Tim says: “I had the privilege to take the first Astro Pi computers to the International Space Station in 2015. Since then, more than 50,000 children have run experiments and sent messages into orbit. The Astro Pi Challenge is a great activity for children and their parents to discover more about coding and to use digital tools to be creative.”

During his space mission, Tim Peake deployed Astro Pi units Ed and Izzy in a number of different locations on board the ISS. He was responsible for loading the Astro Pi participants’ programs onto Ed and Izzy, collecting the data they generated, and making sure it was downlinked back to Earth for the participants.

Fast forward six years, and we’re retiring Astro Pis Ed and Izzy and sending two upgraded Astro Pi units to space – in just over a week’s time, to be precise. This year, Italian ESA astronaut Samantha Cristoforetti will be taking the helm for the Challenge on board the ISS, while Tim continues to champion the Astro Pi Challenge down here on Earth.

Thank you Tim, for inspiring so many families to get involved with STEM and coding.

Your family’s very own space mission with Astro Pi

To get involved in the Astro Pi Challenge, you and your young people don’t even have to wait until the new Raspberry Pi computers arrive on the ISS. You can do Astro Pi Mission Zero — the beginners’ coding activity of the European Astro Pi Challenge — today!

In Mission Zero, young people, by themselves or in a team of up to four, follow our step-by-step instructions to write the code for a simple program, which we will send up to ISS to run on the new Astro Pi units. With their program, young people take a humidity reading on board the ISS and show it to the astronauts stationed there, together with a personal message or colourful design. This beginner-friendly coding activity takes about an hour and can be done on any computer in a web browser. It’s completely free too.

As a parent (or educator), you support young people on Mission Zero by:

• Registering as a Mission Zero mentor on astro-pi.org so we can send you a unique code for submitting your child’s program once it’s written
• Helping them follow the step-by-step instructions so you can learn about coding together
• Motivating them to keep going if their program doesn’t work right away, and helping to spot mistakes
• Celebrating with them when they’ve finished writing the code for their Mission Zero program

After a young person’s Mission Zero code has run and their message has been shown in the ISS, we’ll send you a special certificate for them so you can commemorate their space mission.

And this year, Astro Pi Mission Zero is extra special: we are asking all participants to help us name the upgraded Raspberry Pi computers that will go to live on board the ISS. We’ve created a list of renowned European scientists whose names participants can vote for, in case you need inspiration.

Parents have lots of enthusiasm for learning about science and technology

It’s not just young people that benefit from getting involved with the Astro Pi Challenge – it’s something the whole family will enjoy doing together. And as findings from our recent UK survey showed, parents are rediscovering their passion for science, technology, and coding through helping their kids with homework. The survey found that parents of children in primary and secondary school are far more likely than any other group of adults to enjoy learning about science, with 3 in 5 parents (62%) revealing their enthusiasm for the subject. Nearly as many parents (58%) wished they had greater knowledge of STEM from school, and 62% said they are interested in learning how to code.

“It’s wonderful to find out that parents of schoolchildren are discovering a passion for science and technology, especially after a year of home-schooling where they have been able to see first-hand what their children are learning.” says Olympia Brown, our Head of Youth Partnerships. “The Astro Pi Challenge is a fun, free, and creative way to learn about coding and carry out science experiments on board the International Space Station that both children and parents can get involved in.”

Young people love Astro Pi Mission Zero

If Tim Peake and we have not convinced you how fun and inspiring the Astro Pi Challenge will be for your family, then here are some young people to tell you about their experiences. We asked learners at Linton-on-Ouse Primary School how they found taking part in this year’s Mission Zero.

This is what some of the young learners shared with us:

“I learned a bit about how to code. Everyone was very helpful. This was very fun, and I wish we can do this again. It was tricky when we tried to make the colours change.”

– A learner in Year 4

“I worked as a team by helping check all the time. Next time I want to do it on my own, because I am feeling confident.”

– A learner in Year 3

Head over to astro-pi.org to register as a Mission Zero mentor today and start coding with your children. There you’ll find all the details you need for your family space mission.

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In Hello World issue 12, our free magazine for computing educators, George Boukeas, DevOps Engineer for the Astro Pi Challenge here at the Foundation, introduces big moments in the history of artificial intelligence (AI) to share with your learners:

The story of artificial intelligence (AI) is a story about humans trying to understand what makes them human. Some of the episodes in this story are fascinating. These could help your learners catch a glimpse of what this field is about and, with luck, compel them to investigate further.                   

The imitation game

In 1950, Alan Turing published a philosophical essay titled Computing Machinery and Intelligence, which started with the words: “I propose to consider the question: Can machines think?” Yet Turing did not attempt to define what it means to think. Instead, he suggested a game as a proxy for answering the question: the imitation game. In modern terms, you can imagine a human interrogator chatting online with another human and a machine. If the interrogator does not successfully determine which of the other two is the human and which is the machine, then the question has been answered: this is a machine that can think.

This imitation game is now a fiercely debated benchmark of artificial intelligence called the Turing test. Notice the shift in focus that Turing suggests: thinking is to be identified in terms of external behaviour, not in terms of any internal processes. Humans are still the yardstick for intelligence, but there is no requirement that a machine should think the way humans do, as long as it behaves in a way that suggests some sort of thinking to humans.

In his essay, Turing also discusses learning machines. Instead of building highly complex programs that would prescribe every aspect of a machine’s behaviour, we could build simpler programs that would prescribe mechanisms for learning, and then train the machine to learn the desired behaviour. Turing’s text provides an excellent metaphor that could be used in class to describe the essence of machine learning: “Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child’s? If this were then subjected to an appropriate course of education one would obtain the adult brain. We have thus divided our problem into two parts: the child-programme and the education process.”

It is remarkable how Turing even describes approaches that have since been evolved into established machine learning methods: evolution (genetic algorithms), punishments and rewards (reinforcement learning), randomness (Monte Carlo tree search). He even forecasts the main issue with some forms of machine learning: opacity. “An important feature of a learning machine is that its teacher will often be very largely ignorant of quite what is going on inside, although he may still be able to some extent to predict his pupil’s behaviour.”

The evolution of a definition

The term ‘artificial intelligence’ was coined in 1956, at an event called the Dartmouth workshop. It was a gathering of the field’s founders, researchers who would later have a huge impact, including John McCarthy, Claude Shannon, Marvin Minsky, Herbert Simon, Allen Newell, Arthur Samuel, Ray Solomonoff, and W.S. McCulloch.   

The simple and ambitious definition for artificial intelligence, included in the proposal for the workshop, is illuminating: ‘making a machine behave in ways that would be called intelligent if a human were so behaving’. These pioneers were making the assumption that ‘every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it’. This assumption turned out to be patently false and led to unrealistic expectations and forecasts. Fifty years later, McCarthy himself stated that ‘it was harder than we thought’.

Modern definitions of intelligence are of distinctly different flavour than the original one: ‘Intelligence is the quality that enables an entity to function appropriately and with foresight in its environment’ (Nilsson). Some even speak of rationality, rather than intelligence: ‘doing the right thing, given what it knows’ (Russell and Norvig).

Read the whole of this brief history of AI in Hello World #12

In the full article, which you can read in the free PDF copy of the issue, George looks at:

• Early advances researchers made from the 1950s onwards while developing games algorithms, e.g. for chess.
• The 1997 moment when Deep Blue, a purpose-built IBM computer, beating chess world champion Garry Kasparov using a search approach.
• The 2011 moment when Watson, another IBM computer system, beating two human Jeopardy! champions using multiple techniques to answer questions posed in natural language.
• The principles behind artificial neural networks, which have been around for decades and are now underlying many AI/machine learning breakthroughs because of the growth in computing power and availability of vast datasets for training.
• The 2017 moment when AlphaGo, an artificial neural network–based computer program by Alphabet’s DeepMind, beating Ke Jie, the world’s top-ranked Go player at the time.

More on machine learning and AI education in Hello World #12

In your free PDF of Hello World issue 12, you’ll also find:

• An interview with University of Cambridge statistician David Spiegelhalter, whose work shaped some of the foundations of AI, and who shares his thoughts on data science in schools and the limits of AI 
• An introduction to Popbots, an innovative project by MIT to open AI to the youngest learners
• An article by Ken Kahn, researcher in the Department of Education at the University of Oxford, on using the block-based Snap! language to introduce your learners to natural language processing
• Unplugged and online machine learning activities for learners age 7 to 16 in the regular ‘Lesson plans’ section
• And lots of other relevant articles

You can also read many of these articles online on the Hello World website.

Find more resources for AI and data science education

In Hello World issue 16, the focus is on all things data science and data literacy for your learners. As always, you can download a free copy of the issue. And on our Hello World podcast, we chat with practicing computing educators about how they bring AI, AI ethics, machine learning, and data science to the young people they teach.

If you want a practical introduction to the basics of machine learning and how to use it, take our free online course.

There are still many open questions about what good AI and data science education looks like for young people. To learn more, you can watch our panel discussion about the topic, and join our monthly seminar series to hear insights from computing education researchers around the world.

We are also collating a growing list of educational resources about these topics based on our research seminars, seminar participants’ recommendations, and our own work. Find the resource list here.

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We and our partners ESA Education are delighted to announce that for this year’s Mission Space Lab of the European Astro Pi Challenge, a record number of 800 teams from 23 countries sent us their ideas for experiments to run on board the International Space Station (ISS).

This is an incredible 83% increase from last year and means that more than 3100 young people from across Europe and other eligible countries have taken part in Phase 1 of Mission Space Lab.

Young people’s scientific experiments in space with Mission Space Lab

Every year since 2015, thanks to our yearly Astro Pi Challenge, Mission Space Lab teams of young people have created code for their own scientific experiments to run on the ISS’s two Astro Pi units. These Astro Pi units are Raspberry Pi computers in space-proof cases, with cameras and an array of sensors. In Phase 1 of Mission Space Lab, teams submit their idea for an experiment that uses the Astro Pi hardware to investigate either the environmental conditions inside the Columbus module on the ISS, or life on the Earth’s surface.

This year, we are sending two upgraded Astro Pi units up into space to the ISS. These consist of the newest model of the Raspberry Pi computer, the newest Raspberry Pi camera, an augmented sensor board and a Coral machine learning accelerator. Young people can vote for the new Astro Pi units’ names by doing the Astro Pi beginners’ coding activity, Mission Zero.

For Mission Space Lab participants, the new hardware opens up a range of options for experiments that were not possible before. Among these are experiments using elements of artificial intelligence such as advanced machine learning, and higher-resolution photography than ever before.

It’s clear that young people are really excited about the new hardware. Not only did we see an overall increase in participating teams, but 49% of the Mission Space Lab experiment ideas that teams sent us involved machine learning.

Mission Space Lab teams are getting ready to write and test their code

We’ve now selected 502 teams for Phase 2 of Mission Space Lab based on the quality of their experiment ideas. Despite the fierce competition, this is 26% more teams than we were able to progress to Phase 2 last year.

All the teams we’ve selected are about to be sent a special Astro Pi hardware kit to help them write the programs for their experiments. These kits include all the components to replicate the new Astro Pi units that will travel to space in December: a Raspberry Pi 4 computer, a Raspberry Pi High Quality Camera, and the same sensors that are on the Astro Pi computers on the ISS. In addition, teams conducting experiments involving machine learning will receive a Coral machine learning accelerator, and teams conducting experiments involving Infrared photography will receive a red optical filter.

Once the teams of young people have received their hardware kits, they’ll be able to familiarise themselves with the Astro Pi sensors and cameras, and then create and test (and re-test!) their code.

Young people’s code will run in space next year

The teams’ deadline for submitting the code for their experiments to us is Thursday 24 February 2022. Once their code has gone through our checks and tests, it will be ready to run on the shiny new Astro Pi units on board the ISS in April or May.

Congratulations to the successful teams, and thank you to everyone who sent us their ideas for Mission Space Lab this year. And a special thank you to all the teachers, educators, club volunteers, and other wonderful people who are acting as Mission Space Lab team mentors this year. You are helping your young people do something remarkable that they will remember for the rest of their lives.

If your team was unsuccessful this time, we’re sorry for the disappointment — please try again next year.

Young people up to age 19 can also take part in Mission Zero, the beginners’ coding activity of the European Astro Pi Challenge, to vote for which European scientist they think we should name the units after. All Mission Zero entries are guaranteed to run on the ISS for 30 seconds!

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AI is a broad and rapidly developing field of technology. Our goal is to make sure all young people have the skills, knowledge, and confidence to use and create AI systems. So what should AI education in schools look like?

To hear a range of insights into this, we organised a panel discussion as part of our seminar series on AI and data science education, which we co-host with The Alan Turing Institute. Here our panel chair Tabitha Goldstaub, Co-founder of CogX and Chair of the UK government’s AI Council, summarises the event. You can also watch the recording below.

As part of the Raspberry Pi Foundation’s monthly AI education seminar series, I was delighted to chair a special panel session to broaden the range of perspectives on the subject. The members of the panel were:

• Chris Philp, UK Minister for Tech and the Digital Economy
• Philip Colligan, CEO of the Raspberry Pi Foundation 
• Danielle Belgrave, Research Scientist, DeepMind
• Caitlin Glover, A level student, Sandon School, Chelmsford
• Alice Ashby, student, University of Brighton

The session explored the UK government’s commitment in the recently published UK National AI Strategy stating that “the [UK] government will continue to ensure programmes that engage children with AI concepts are accessible and reach the widest demographic.” We discussed what it will take to make this a reality, and how we will ensure young people have a seat at the table.

Why AI education for young people?

It was clear that the Minister felt it is very important for young people to understand AI. He said, “The government takes the view that AI is going to be one of the foundation stones of our future prosperity and our future growth. It’s an enabling technology that’s going to have almost universal applicability across our entire economy, and that is why it’s so important that the United Kingdom leads the world in this area. Young people are the country’s future, so nothing is complete without them being at the heart of it.”

Our panelist Caitlin Glover, an A level student at Sandon School, reiterated this from her perspective as a young person. She told us that her passion for AI started initially because she wanted to help neurodiverse young people like herself. Her idea was to start a company that would build AI-powered products to help neurodiverse students.

What careers will AI education lead to?

A theme of the Foundation’s seminar series so far has been how learning about AI early may impact young people’s career choices. Our panelist Alice Ashby, who studies Computer Science and AI at Brighton University, told us about her own process of deciding on her course of study. She pointed to the fact that terms such as machine learning, natural language processing, self-driving cars, chatbots, and many others are currently all under the umbrella of artificial intelligence, but they’re all very different. Alice thinks it’s hard for young people to know whether it’s the right decision to study something that’s still so ambiguous.

When I asked Alice what gave her the courage to take a leap of faith with her university course, she said, “I didn’t know it was the right move for me, honestly. I took a gamble, I knew I wanted to be in computer science, but I wanted to spice it up.” The AI ecosystem is very lucky that people like Alice choose to enter the field even without being taught what precisely it comprises.

We also heard from Danielle Belgrave, a Research Scientist at DeepMind with a remarkable career in AI for healthcare. Danielle explained that she was lucky to have had a Mathematics teacher who encouraged her to work in statistics for healthcare. She said she wanted to ensure she could use her technical skills and her love for math to make an impact on society, and to really help make the world a better place. Danielle works with biologists, mathematicians, philosophers, and ethicists as well as with data scientists and AI researchers at DeepMind. One possibility she suggested for improving young people’s understanding of what roles are available was industry mentorship. Linking people who work in the field of AI with school students was an idea that Caitlin was eager to confirm as very useful for young people her age.

We need investment in AI education in school

The AI Council’s Roadmap stresses how important it is to not only teach the skills needed to foster a pool of people who are able to research and build AI, but also to ensure that every child leaves school with the necessary AI and data literacy to be able to become engaged, informed, and empowered users of the technology. During the panel, the Minister, Chris Philp, spoke about the fact that people don’t have to be technical experts to come up with brilliant ideas, and that we need more people to be able to think creatively and have the confidence to adopt AI, and that this starts in schools. 

Caitlin is a perfect example of a young person who has been inspired about AI while in school. But sadly, among young people and especially girls, she’s in the minority by choosing to take computer science, which meant she had the chance to hear about AI in the classroom. But even for young people who choose computer science in school, at the moment AI isn’t in the national Computing curriculum or part of GCSE computer science, so much of their learning currently takes place outside of the classroom. Caitlin added that she had had to go out of her way to find information about AI; the majority of her peers are not even aware of opportunities that may be out there. She suggested that we ensure AI is taught across all subjects, so that every learner sees how it can make their favourite subject even more magical and thinks “AI’s cool!”.

Philip Colligan, the CEO here at the Foundation, also described how AI could be integrated into existing subjects including maths, geography, biology, and citizenship classes. Danielle thoroughly agreed and made the very good point that teaching this way across the school would help prepare young people for the world of work in AI, where cross-disciplinary science is so important. She reminded us that AI is not one single discipline. Instead, many different skill sets are needed, including engineering new AI systems, integrating AI systems into products, researching problems to be addressed through AI, or investigating AI’s societal impacts and how humans interact with AI systems.

On hearing about this multitude of different skills, our discussion turned to the teachers who are responsible for imparting this knowledge, and to the challenges they face. 

The challenge of AI education for teachers

When we shifted the focus of the discussion to teachers, Philip said: “If we really want to equip every young person with the knowledge and skills to thrive in a world that shaped by these technologies, then we have to find ways to evolve the curriculum and support teachers to develop the skills and confidence to teach that curriculum.”

I asked the Minister what he thought needed to happen to ensure we achieved data and AI literacy for all young people. He said, “We need to work across government, but also across business and society more widely as well.” He went on to explain how important it was that the Department for Education (DfE) gets the support to make the changes needed, and that he and the Office for AI were ready to help.

Philip explained that the Raspberry Pi Foundation is one of the organisations in the consortium running the National Centre for Computing Education (NCCE), which is funded by the DfE in England. Through the NCCE, the Foundation has already supported thousands of teachers to develop their subject knowledge and pedagogy around computer science.

A recent study recognises that the investment made by the DfE in England is the most comprehensive effort globally to implement the computing curriculum, so we are starting from a good base. But Philip made it clear that now we need to expand this investment to cover AI.

Young people engaging with AI out of school

Philip described how brilliant it is to witness young people who choose to get creative with new technologies. As an example, he shared that the Foundation is seeing more and more young people employ machine learning in the European Astro Pi Challenge, where participants run experiments using Raspberry Pi computers on board the International Space Station. 

Philip also explained that, in the Foundation’s non-formal CoderDojo club network and its Coolest Projects tech showcase events, young people build their dream AI products supported by volunteers and mentors. Among these have been autonomous recycling robots and AI anti-collision alarms for bicycles. Like Caitlin with her company idea, this shows that young people are ready and eager to engage and create with AI.

We closed out the panel by going back to a point raised by Mhairi Aitken, who presented at the Foundation’s research seminar in September. Mhairi, an Alan Turing Institute ethics fellow, argues that children don’t just need to learn about AI, but that they should actually shape the direction of AI. All our panelists agreed on this point, and we discussed what it would take for young people to have a seat at the table.

Alice advised that we start by looking at our existing systems for engaging young people, such as Youth Parliament, student unions, and school groups. She also suggested adding young people to the AI Council, which I’m going to look into right away! Caitlin agreed and added that it would be great to make these forums virtual, so that young people from all over the country could participate.

The panel session was full of insight and felt very positive. Although the challenge of ensuring we have a data- and AI-literate generation of young people is tough, it’s clear that if we include them in finding the solution, we are in for a bright future. 

What’s next for AI education at the Raspberry Pi Foundation?

In the coming months, our goal at the Foundation is to increase our understanding of the concepts underlying AI education and how to teach them in an age-appropriate way. To that end, we will start to conduct a series of small AI education research projects, which will involve gathering the perspectives of a variety of stakeholders, including young people. We’ll make more information available on our research pages soon.

In the meantime, you can sign up for our upcoming research seminars on AI and data science education, and peruse the collection of related resources we’ve put together.

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Today we bring you the sixth film in our series of inspirational community stories. It’s wonderful to share how people all across the world are getting creative with tech and solving problems that matter to them.

Our next community story comes from Drogheda, Ireland, where a group of programmers set up the second ever CoderDojo coding club for young people. One of that Dojo’s attendees was Cian Martin Bohan, whose story we’re sharing today.

“I can’t create anything I want in real life, but I can create anything I want on a computer.”

Cian Martin Bohan

Watch Cian’s video to find out how this keen programmer went from his first experience with coding at his local CoderDojo as an 11-year-old, to landing a Software Engineering apprenticeship at Google.

Meet Cian

Cian (20) vividly remembers the first time he heard about CoderDojo as a shy 11-year-old: he initially told his dad he felt too nervous to attend. What Cian couldn’t have known back then was that attending CoderDojo would set him on an exciting journey of creative digital making and finding life-long friends.

Right from the beginning, the CoderDojo gave Cian space to make friends and develop his coding skills and his curiosity about creating things with technology. He started to attend the Dojo regularly, and before long he had created his own website about the planets in our solar system with basic CSS and HTML.  

“I made a website that talked about the planets, and I thought that was the coolest thing ever. In fact, I actually still have that website.”

Cian Martin Bohan

In over 6 years of being part of his CoderDojo community, Cian was able to share his passion for programming with others and grow his confidence.

From meeting like-minded peers and developing apps and websites, to serving as a youth member on the Digital Youth Council, Cian embraced the many experiences that CoderDojo opened up for him. They were all of great benefit when he decided to apply for an apprenticeship at Google.

As someone who didn’t follow the university route of education, Cian’s time at CoderDojo and the mentors he met there had a profound impact on his life and his career path. His CoderDojo mentors always encouraged Cian to learn new skills and follow his interests, and in this way they not only helped him reach his current position at Google, but also instilled in him a steady desire to always keep learning.

The future is limitless for Cian, and we cannot wait to hear what he does next.

Help us celebrate Cian, and inspire other young people to discover coding and digital making as a passion, by liking and sharing his story on Twitter, LinkedIn, and Facebook.

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Your young people don’t need to wait to become astronauts to be part of a space mission! In Mission Zero, the free beginners’ coding activity of the European Astro Pi Challenge, young people can create a simple computer program to send to the International Space Station (ISS) today.

This year, young people taking part in Astro Pi Mission Zero have the historic chance to help name the special Raspberry Pi computers we are sending up to the ISS for the Astro Pi Challenge. Their voices will decide the names of these unique pieces of space exploration hardware.

Your young people can become part of a space mission today!

The European Astro Pi Challenge is a collaboration by us and ESA Education. Astro Pi Mission Zero is free, open to all young people up to age 19 from eligible countries*, and it’s designed for beginner coders.

You can support participants easily, whether at home, in the classroom, or in a youth club. Simply sign up as a mentor and let your young people follow the step-by-step instructions we provide (in 19 European languages!) for writing their Mission Zero code online. Young people can complete Mission Zero in around an hour, and they don’t need any previous coding experience.

Mission Zero is the perfect coding activity for parents and their children at home, for STEM or Scouts club leaders and attendees, and for teachers and students who are new to computer programming. You don’t need any special tech for Mission Zero participants. Any computer with a web browser and internet connection works for Mission Zero, because everything is done online.

We need young people to help name the Raspberry Pis we’re sending to space

Mission Zero participants follow our step-by-step instructions to create a simple program that takes a humidity reading on board the ISS and displays it for the astronauts — together with the participants’ own unique messages. And as part of their messages, they can vote for the name of the new hardware for the Astro Pi Challenge, hardware with Raspberry Pi computers at its heart.

The new Astro Pi hardware, which will travel up in a rocket to the ISS on 21 December, is so new that these special augmented computers don’t even have names yet. Participants in Astro Pi Mission Zero get to vote for a name inspired by our list of ten renowned European scientists. Their vote will be part of the message they send to space.

What do your young people want to say in space?

Your young people’s messages to the ISS astronauts can say anything they like (apart from swear words, of course). Maybe they want to send some encouraging words to the astronauts or tell them a joke. They can even design a cool pixel art image to show on the Astro Pi hardware’s display:

Whatever else they code for their Mission Zero entry, they’re supporting the astronauts with their important work on board the ISS. Since Mission Zero participants tell the Astro Pi hardware to read and display the humidity level inside the ISS, they provide helpful information for the astronauts as they go about their tasks.

Their own place in space history

After a participant’s Mission Zero code has run and their message has been shown in the ISS, we’ll send you a special certificate for them so you can commemorate their space mission.

The certificate will feature their name, the exact date and time their code ran, and a world map to mark the place on Earth above which the ISS was while their message was visible up there in space.

10 key things about Astro Pi Mission Zero

1. It’s young people’s unique chance to be part of a real space mission
2. Participation is free
3. Participants send the ISS astronauts their own unique message
4. This year only, participants can help name the two special Raspberry Pi computers that are travelling up to the ISS
5. Mission Zero is open to young people up to age 19 who live in eligible countries (more about eligibility here)
6. It’s a beginners’ coding activity with step-by-step instructions, available in 19 languages
7. Completing the activity takes about one hour — at home, in the classroom, or in a Scouts or coding club session
8. The activity can be done online in a web browser on any computer
9. Participants will receive a special certificate to help celebrate their space mission
10. Mission Zero is open until 18 March 2022

If you don’t want to let any young people in your life miss out on this amazing opportunity, sign up as their Mission Zero mentor today.

* The European Astro Pi Challenge is run as a collaboration by us at the Raspberry Pi Foundation and ESA Education. That’s why participants need to be from an ESA Member State, or from Slovenia, Canada, Latvia, Lithuania, or Malta, which have agreements with ESA.

If you live elsewhere, it’s possible to partner with Mission Zero mentors and young people in an eligible country. You can work together to support the young people to form international Mission Zero teams that write programs together.

If you live elsewhere and cannot partner with people in an eligible country, Mission Zero is still an awesome and inspiring project for your young people to try out coding. While these young people’s code unfortunately won’t run on the ISS, they will receive a certificate to mark their efforts.

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This month, the team behind our Code Club programme supported nearly 6000 children across Scotland to “code against climate change” during the United Nations Climate Change Conference (COP26) in Glasgow.

“The scale of what we have achieved is outstanding. We have supported over 5750 young learners to code projects that are both engaging and meaningful to their conversations on climate.”

Louise Foreman, Education Scotland (Digital Skills team)

Creative coding to raise awareness of environmental issues

Working with teams from Education Scotland, and with e-Sgoil, our Code Club team hosted two live online code-along events that saw learners from 235 schools across Scotland come together to code and learn about protecting the environment.

“This type of event at this scale would not have been possible before the pandemic. Now joining and learning through live online events is quite normal, thanks to platforms like e-Sgoil’s DYW Live. That said, the success of these code-alongs has been above even our wildest imaginations.”

Peter Murray, Education Scotland (Developing the Young Workforce team)

Classes of young people aged 8 to 14 across Scotland joined the live online code-along through the national GLOW platform and followed Lorna from our Code Club team through a step-by-step project guide to code creative projects with an environmental theme.

At our first session, for beginners, the coding newcomers explored the importance of pollinating insects for the environment. They first learned that a third of the food we eat depends on pollinators such as bees and butterflies, and that these insects are endangered by environmental crises.

Then the young coders celebrated pollinating insects by coding a garden scene filled with butterflies, based on our popular Butterfly garden project guide. This Scratch project introduces beginner coders to loops while they code their animations, and it allows them to get creative and customise the look of their projects. Above are still images of two example animations coded by the young learners.

The second Code Club code-along event was designed for more confident coders. First, learners were asked to consider the impact of plastic in our oceans and reflect on the recent news that around 26,000 tonnes of coronavirus-related plastic waste (such as masks and gloves) has already entered our oceans. To share this message, they then coded a game based on our Save the shark Scratch project guide. In this game, players help a shark swim through the ocean trying to avoid plastic waste, which is dangerous to its health.

Supporting young people’s future together

These two Scotland-wide code-along events for schools were made possible by the long-standing collaboration between Education Scotland and our Code Club team. Over the last five years, our shared mission to grow interest for coding and computer science among children across Scotland has helped Scottish teachers start hundreds of Code Clubs.

“The code-alongs were the perfect celebration of all the brilliant work we have done together over the years. What better way to demonstrate the importance of computing science to young people than to show them that not only can they use those skills on something important like climate change, but they are also in great company with thousands of other children across Scotland. I am excited about the future.”

Kirsty McFaul, Education Scotland (Technologies team)

Join thousands of teachers around the world who run Code Clubs

We also want to give kudos to the teachers of the 235 schools who helped their learners participate in this Code Club code-along. Thanks to your skills in supporting your learners to participate in online sessions — skills hard-won during school closures — over 5000 young people have been inspired about coding and protecting the planet we all share.

Teachers around the world run Code Clubs for their learners, with the help of our free Code Club resources and support. Find out more about starting a Code Club at your school at www.codeclub.org.

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How does teaching children and young people about machine learning (ML) differ from teaching them about other aspects of computing? Professor Matti Tedre and Dr Henriikka Vartiainen from the University of Eastern Finland shared some answers at our latest research seminar.

Their presentation, titled ‘ML education for K-12: emerging trajectories’, had a profound impact on my thinking about how we teach computational thinking and programming. For this blog post, I have simplified some of the complexity associated with machine learning for the benefit of readers who are new to the topic.

Our seminars on teaching AI, ML, and data science

We’re currently partnering with The Alan Turing Institute to host a series of free research seminars about how to teach artificial intelligence (AI) and data science to young people.

The seminar with Matti and Henriikka, the third one of the series, was very well attended. Over 100 participants from San Francisco to Rajasthan, including teachers, researchers, and industry professionals, contributed to a lively and thought-provoking discussion.

Representing a large interdisciplinary team of researchers, Matti and Henriikka have been working on how to teach AI and machine learning for more than three years, which in this new area of study is a long time. So far, the Finnish team has written over a dozen academic papers based on their pilot studies with kindergarten-, primary-, and secondary-aged learners.

Current teaching in schools: classical rule-driven programming

Matti and Henriikka started by giving an overview of classical programming and how it is currently taught in schools. Classical programming can be described as rule-driven. Example features of classical computer programs and programming languages are:

• A classical language has a strict syntax, and a limited set of commands that can only be used in a predetermined way
• A classical language is deterministic, meaning we can guarantee what will happen when each line of code is run
• A classical program is executed in a strict, step-wise order following a known set of rules

When we teach this type of programming, we show learners how to use a deductive problem solving approach or workflow: defining the task, designing a possible solution, and implementing the solution by writing a stepwise program that is then run on a computer. We encourage learners to avoid using trial and error to write programs. Instead, as they develop and test a program, we ask them to trace it line by line in order to predict what will happen when each line is run (glass-box testing).

Classical programming underpins the current view of computational thinking (CT). Our speakers called this version of CT ‘CT 1.0’. So what’s the alternative Matti and Henriikka presented, and how does it affect what computational thinking is or may become?

Machine learning (data-driven) models and new computational thinking (CT 2.0) 

Rule-based programming languages are not being eradicated. Instead, software systems are being augmented through the addition of machine learning (data-driven) elements. Many of today’s successful software products, such as search engines, image classifiers, and speech recognition programs, combine rule-driven software and data-driven models. However, the workflows for these two approaches to solving problems through computing are very different.

Significantly, while in rule-based programming (and CT 1.0), the focus is on solving problems by creating algorithms, in data-driven approaches, the problem solving workflow is all about the data. To highlight the profound impact this shift in focus has on teaching and learning computing, Matti introduced us to a new version of computational thinking for machine learning, CT 2.0, which is detailed in a forthcoming research paper.

Because of the focus on data rather than algorithms, developing a machine learning model is not at all like developing a classical rule-driven program. In classical programming, programs can be traced, and we can predict what will happen when they run. But in data-driven development, there is no flow of rules, and no absolutely right or wrong answer.

Machine learning models are created iteratively using training data and must be cross-validated with test data. A tiny change in the data provided can make a model useless. We rarely know exactly why the output of an ML model is as it is, and we cannot explain each individual decision that the model might have made. When evaluating a machine learning system, we can only say how well it works based on statistical confidence and efficiency. 

Machine learning education must cover ethical and societal implications 

The ethical and societal implications of computer science have always been important for students to understand. But machine learning models open up a whole new set of topics for teachers and students to consider, because of these models’ reliance on large datasets, the difficulty of explaining their decisions, and their usefulness for automating very complex processes. This includes privacy, surveillance, diversity, bias, job losses, misinformation, accountability, democracy, and veracity, to name but a few.

I see the shift in problem solving approach as a chance to strengthen the teaching of computing in general, because it opens up opportunities to teach about systems, uncertainty, data, and society.

Jane Waite

Teaching machine learning: the challenges of magic boxes and new mental models

For teaching classical rule-driven programming, much time and effort has been put into researching learners’ understanding of what a program will do when it is run. This kind of understanding is called a learner’s mental model or notional machine. An approach teachers often use to help students develop a useful mental model of a program is to hide the detail of how the program works and only gradually reveal its complexity. This approach is described with the metaphor of hiding the detail of elements of the program in a box. 

Data-driven models in machine learning systems are highly complex and make little sense to humans. Therefore, they may appear like magic boxes to students. This view needs to be banished. Machine learning is not magic. We have just not figured out yet how to explain the detail of data-driven models in a way that allows learners to form useful mental models.

Some existing ML tools aim to help learners form mental models of ML, for example through visual representations of how a neural network works (see Figure 2). But these explanations are still very complex. Clearly, we need to find new ways to help learners of all ages form useful mental models of machine learning, so that teachers can explain to them how machine learning systems work and banish the view that machine learning is magic.

Some tools and teaching approaches for ML education

Matti and Henriikka’s team piloted different tools and pedagogical approaches with different age groups of learners. In terms of tools, since large amounts of data are needed for machine learning projects, our presenters suggested that tools that enable lots of data to be easily collected are ideal for teaching activities. Media-rich education tools provide an opportunity to capture still images, movements, sounds, or sense other inputs and then use these as data in machine learning teaching activities. For example, to create a machine learning–based rock-paper-scissors game, students can take photographs of their hands to train a machine learning model using Google Teachable Machine.

Similar to tools that teach classic programming to novice students (e.g. Scratch), some of the new classroom tools for teaching machine learning have a drag-and-drop interface (e.g. Cognimates). Using such tools means that in lessons, there can be less focus on one of the more complex aspects of learning to program, learning programming language syntax. However, not all machine learning education products include drag-and-drop interaction, some instead have their own complex languages (e.g. Wolfram Programming Lab), which are less attractive to teachers and learners. In their pilot studies, the Finnish team found that drag-and-drop machine learning tools appeared to work well with students of all ages.

The different pedagogical approaches the Finnish research team used in their pilot studies included an exploratory approach with preschool children, who investigated machine learning recognition of happy or sad faces; and a project-based approach with older students, who co-created machine learning apps with web-based tools such as Teachable Machine and Learn Machine Learning (built by the research team), supported by machine learning experts.

What impact these pedagogies have on students’ long-term mental models about machine learning has yet to be researched. If you want to find out more about the classroom pilot studies, the academic paper is a very accessible read.

My take-aways: new opportunities, new research questions

We all learned a tremendous amount from Matti and Henriikka and their perspectives on this important topic. Our seminar participants asked them many questions about the pedagogies and practicalities of teaching machine learning in class, and raised concerns about squeezing more into an already packed computing curriculum.

For me, the most significant take-away from the seminar was the need to shift focus from algorithms to data and from CT 1.0 to CT 2.0. Learning how to best teach classical rule-driven programming has been a long journey that we have not yet completed. We are forming an understanding of what concepts learners need to be taught, the progression of learning, key mental models, pedagogical options, and assessment approaches. For teaching data-driven development, we need to do the same.  

The question of how we make sure teachers have the necessary understanding is key.

Jane Waite

I see the shift in problem solving approach as a chance to strengthen the teaching of computing in general, because it opens up opportunities to teach about systems, uncertainty, data, and society. I think it will help us raise awareness about design, context, creativity, and student agency. But I worry about how we will introduce this shift. In my view, there is a considerable risk that we will be sucked into open-ended, project-based learning, with busy and fun but shallow learning experiences that result in restricted conceptual development for students.

I also worry about how we can best help teachers build up the knowledge and experience to support their students. In the Q&A after the seminar, I asked Matti and Henriikka about the role of their team’s machine learning experts in their pilot studies. It seemed to me that without them, the pilot lessons would not have worked, as the participating teachers and students would not have had the vocabulary to talk about the process and would not have known what was doable given the available time, tools, and student knowledge.

The question of how we make sure teachers have the necessary understanding is key. Many existing professional development resources for teachers wanting to learn about ML seem to imply that teachers will all need a PhD in statistics and neural network optimisation to engage with machine learning education. This is misleading. But teachers do need to understand the machine learning concepts that their students need to learn about, and I think we don’t yet know exactly what these concepts are. 

In summary, clearly more research is needed. There are fundamental questions still to be answered about what, when, and how we teach data-driven approaches to software systems development and how this impacts what we teach about classical, rule-based programming. But to me, that is exciting, and I am very much looking forward to the journey ahead.

Join our next free seminar

To find out what others recommend about teaching AI and ML, catch up on last month’s seminar with Professor Carsten Schulte and colleagues on centring data instead of code in the teaching of AI.

We have another four seminars in our monthly series on AI, machine learning, and data science education. Find out more about them on this page, and catch up on past seminar blogs and recordings here.

At our next seminar on Tuesday 7 December at 17:00–18:30 GMT, we will welcome Professor Rose Luckin from University College London. She will be presenting on what it is about AI that makes it useful for teachers and learners.

We look forward to meeting you there!

PS You can build your understanding of machine learning by joining our latest free online course, where you’ll learn foundational concepts and train your own ML model!

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Today we are introducing you to Code Club World — a free online platform where young people aged 9 to 13 can learn to make stuff with code.

In Code Club World, young people can:

• Start out by creating their personal robot avatar
• Make music, design a t-shirt, and teach their robot avatar to dance!
• Learn to code on islands with structured activities
• Discover block-based and text-based coding in Scratch and Python
• Earn badges for their progress 
• Share their coding creations with family, friends, and the Code Club World community

Learning to code at home with Code Club World: meaningful, fun, flexible

When we spoke to parents and children about learning at home during the pandemic, it became clear to us that they were looking for educational tools that the children can enjoy and master independently, and that are as fun and social as the computer games and other apps the children love.

What’s more, a free tool for learning to code at home is particularly important for young people who are unable to attend coding clubs in person. We believe every child should have access to a high-quality coding and digital making education. And with this in mind, we set out to create Code Club World, an online environment as rich and engaging as a face-to-face extracurricular learning experience, where all young people can learn to code.

The Code Club World activities are mapped to our research-informed Digital Making Framework — a coding and digital making curriculum for non-formal settings. That means when children are in the Code Club World environment, they are learning to code and use digital making to independently create their ideas and address challenges that matter to them.

By providing a structured pathway through the coding activities, a reward system of badges to engage and motivate learners, and a broad range of projects covering different topics, Code Club World supports learners at every stage, while making the activities meaningful, fun, and flexible.

We’ve also designed Code Club World to be mobile-friendly, so if a young person uses a phone or tablet to visit the platform, they can still code cool things they will be proud of.

Created with the community

Since we started developing Code Club World, we have been working with a community of more than 1000 parents, educators, and children who are giving us valuable input to shape the direction of the platform. We’ve had some fantastic feedback from them:

“I’ve not coded before, but found this really fun! … I LOVED making the dance. It was so much fun and made me laugh!”

Learner, aged 11

“I love the concept of having islands to explore in making the journey through learning coding, it is fabulous and eye-catching.”

Parent

The platform is still in beta status — this means we’d love you to share it with young people in your family, school, or community so they can give their feedback and help make Code Club World even better.

Together, we will ensure every child has an equal opportunity to learn to code and make things that change their world.

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Source: Raspberry Pi – Introducing Code Club World: a new way for young people to learn to code at home

As so many CoderDojos around the world, our office-based CoderDojo hadn’t been able to bring learners together in person since the start of the coronavirus pandemic. So we decided that our first time back in the Raspberry Pi Foundation headquarters should be something special. Having literally just launched the new Raspberry Pi Build HAT for programming LEGO® projects with Raspberry Pi computers, we wanted to celebrate our Dojo’s triumphant return to in-person session by offering a ‘LEGO bricks and Raspberry Pi’ activity!

Back in person, with new ways to create with code

The Raspberry Pi Build HAT allows learners to build and program projects with Raspberry Pi computers and LEGO® Technic™ motors and sensors from the LEGO® Education SPIKE™ Portfolio.

What better way could there be to get the more experienced coders among our Dojo’s young people (Ninjas) properly excited to be back? We knew they were fond of building things with LEGO bricks, as so many young people are, so we were sure they would have great fun with this activity!

For our beginners, we set up Raspberry Pi workstations and got them coding the projects on the Home island on our brand-new Code Club World platform, which they absolutely loved, so their jealousy was mitigated somewhat. 

Being able to rely on your learners’ existing skills in making the physical build leaves you a lot more time to support them with what they’re actually here to learn: the coding and digital making skills.

We wanted to keep our first Dojo back small, so for the ‘LEGO bricks and Raspberry Pi’ activity, we set up just four workstations, each with a Raspberry Pi 4, with 4GB RAM and a Raspberry Pi Build HAT on top, and a LEGO Education SPIKE Prime set. We put eight participants into teams of two, and made sure that all of them brought a little experience with text-based coding, because we wanted them to be able to focus on making projects in their own style, rather than first learning the basics of coding in Python. Then we offered our Ninjas the choice of the first two projects in the Introduction to the Raspberry Pi Build HAT and LEGO path: make Pong game controllers, or make a remote-controlled robot buggy. As I had predicted, all the teams chose to make a robot buggy!

Teamwork and design

The teams of Ninjas were immediately off and making — in fact, they couldn’t wait to get the lids off the boxes of brightly coloured bricks and beams!

Our project instructions focus primarily on supporting learners through coding and testing the mechanics of their creations, leaving the design and build totally up to them. This was evidenced by the variety of buggy designs we saw at the project showcase at the end of the two-hour Dojo session!

One of the amazing things Raspberry Pi makes possible when you use it with the Raspberry Pi Build HAT and SPIKE™ Prime set: it’s simple to make the Raspberry Pi at the heart of the creation talk to a mobile device via Bluetooth, and off you go controlling what you’ve created via a phone or tablet.

While beginner-friendly, the projects in the Introduction path involve a mix of coding, testing, designing, and building. So it required focus and solid teamwork for the Ninjas to finish their buggies in time for the project showcase. And this is where building with LEGO pieces was really helpful.

Coding front and centre, thanks to the Raspberry Pi Build HAT

Having LEGO bricks and the Build HAT available to create their Raspberry Pi–powered robot buggies made it easy for our Ninjas to focus on writing the code to get their buggies to work. They weren’t relying on crafting skills or duct tape and glue guns to make a chassis in the relatively short time they had, and the coding could be front and centre for them.

The most exciting part for the Ninjas was that they were building remote-controlled robot buggies. This is one of the amazing things Raspberry Pi makes possible when you use it with the Build HAT and SPIKE™ Prime set: it’s simple to make the Raspberry Pi at the heart of the creation talk to a mobile device via Bluetooth, and off you go controlling what you’ve created via a phone or tablet.

The LEGO Technic motors that are part of the LEGO Education SPIKE Prime set are of really high quality, and they’re super easy to program with the Build HAT and its Python library! You can change the motors’ speed by setting a single parameter in your code. You can also easily write code to set or read the motors’ exact angle (their absolute position). That allows you to finely control the motors’ movements, or to use them as sensors.

Some of our teams, inspired by everything the SPIKE Prime set has to offer, tried out programming the set’s sensors, to switch their robot buggy on or help it avoid obstacles. Because we only had about 90 minutes of digital making, not all teams managed to finish adding the extra features they wanted — but next time for sure!

With a little more time (or another Dojo session), it would have been possible for the Ninjas to make some very advanced remote-controlled buggies indeed, complete with headlights, brake lights, sensors, and sound.

Learning with LEGO® elements and Raspberry Pi computers

If you have access to LEGO Education SPIKE Prime sets for your learners, then the Raspberry Pi Build HAT is a great addition that allows them to build complex robotics projects with very simple code — but I think that’s not its main benefit.

Because the Build HAT allows your learners to work with LEGO elements, you know that many of them already understand one aspect of the creation process: they’ve got experience of using LEGO bricks to solve a problem. In a coding or STEM club session, or in a classroom lesson, you can only give your learners limited amount of time to complete a project, or get their project prototype to a stable point. So being able to rely on your learners’ existing skills in making the physical build leaves you a lot more time to support them with what they’re actually here to learn: the coding and digital making skills.

You and your young people next!

The projects using the Raspberry Pi Build HATs were such a hit, we’ll be getting them and the LEGO Education SPIKE Prime sets out at every Dojo session from now on! We’re excited to see what young people around the world will be creating thanks to our new collaboration with LEGO Education.

Have you used the Raspberry Pi Build HAT with your learners or young people at home yet? Share their stories and creations in the comments here, or on social media using #BuildHAT.

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Source: Raspberry Pi – The Raspberry Pi Build HAT and LEGO® components at our CoderDojo

In Hello World issue 17, Raspberry Pi Certified Educator Cat Lamin talks about how building connections and sharing the burden can help make us better educators, even in times of great stress:

“I felt like I needed to play my part”

In March 2020, the world suddenly changed. For educators, we jumped from face-to-face teaching to a stark new landscape, with no idea of how the future would look. As generous teachers pushed out free resources, I felt like I needed to play my part. Suddenly, an idea struck me. In September 2017, I had decided to be brave and submit a talk to PyConUK to discuss my mental health. Afterwards, several people in the audience shared their own stories with me or let me know that it helped them just to hear that someone else struggled too. I realised that in times of pressure, we need a chance to talk and we had lost these outlets. In school, we would pop to the staffroom or a friend’s classroom for a quick vent, but that wasn’t an option anymore. People were feeling isolated, scared, stressed and didn’t have anyone to turn to.

I realised that in times of pressure, we need a chance to talk, and we had lost these outlets.

Cat Lamin

Thus, the first Global Google Educator Group Staffroom: Mental Health Matters was launched on 14 March 2020, which coincided with the US government announcing school closures and UK teachers still waiting anxiously to hear when doors would close. The aim of Staffroom was to give teachers a safe space to talk about how they’re feeling under the overwhelming weight of school closures. To say it was a success would be an understatement, with teachers joining the calls from Australia, Malaysia, the USA, Colombia, Mexico, Brazil, Europe and more!

“Staffroom for me is a place and time to connect with other teachers from around the world. I remember seeing the calendar invites by mail and I kept thinking I should join but was afraid to do it. The first time I did it, I listened first and it made me realize that my struggles during pandemic online teaching were the same struggles as everywhere else.” – Pily Hernandez, Monterrey, Mexico

Which William are you today?

In those early days, we just gave teachers a chance to talk. The format of our meetings was simple: what’s your name, where are you from, and then an ice breaker question like ‘What colour do you feel like?’ or ‘What song represents your current mood?’ It wasn’t long before we hit upon a winning formula by making our own ‘Which image are you today?’ picture scale (see the ‘Which William’ image below!). Using the picture scales allowed people to really express how they felt. Often someone who had been happily chatting would explain that they were actually struggling to keep their head above water because a silly image allowed them to be honest.

One of the most important messages from Staffroom was that many people involved with technology in schools were feeling alone. After years of suggesting teachers use technology, suddenly they were blamed for schools not being properly prepared. They were struggling with not necessarily knowing what to suggest to teachers with technology difficulties, as they were grappling with their own personal lockdown situations. Hearing that other people, all around the world, were experiencing something similar was hugely eye-opening and took a great amount of weight off their shoulders.

“As someone who thrived from having in person connections and networking opportunities, lockdown hit me hard. Staffroom really helped to keep those connections going and has developed into such a lovely safe space to talk and connect with others.” – Abid Patel, London, UK

We varied the tone of the sessions depending on the needs of the attendees. In the first few months, we shared our lockdown situations and our different experiences across the world. We could share advice and tips, as well as best practice for delivering content and things that had gone terribly wrong since switching to remote teaching. Or we’d discuss food in different countries around the world (did you know that in Australia, fish and chips is made from shark?) or joke about whether Vegemite was actually an edible product (it’s ok, I tried it live on camera during one Staffroom). Other days, we would discuss how difficult we were finding teaching, isolation or life in general during a pandemic.

An honest environment

One of the things that people continuously mentioned was that Staffroom was a safe place where they felt they could share, be listened to, and be understood. We made it clear that no one had to speak unless they wanted to. I made a point of always being completely honest about my own mental health. As a person who had suffered from depression and anxiety in the past, it was no surprise to me when I was diagnosed with both near the end of 2020, and I was fortunate enough to get virtual therapy. I shared my story with the group, which allowed attendees to feel more comfortable being open and talking about their own struggles, in some cases leading to their own diagnosis and getting much-needed support.

“Staffroom has been the best ‘out of my comfort zone’ leap that I have ever taken. I have met educators from all over the world and learned that there are more things that unite us than divide us in this world of education.” – Frederick Ballew, Minnesota, USA

People would join Staffroom to share new jobs, engagements, even cross-country moves, but equally they would join after losing a loved one or hearing of a pupil sick in hospital. Staffroom became a safe haven for teachers, coaches, IT directors, and pretty much anyone involved in technology within education. It is a place where we could bond over shared experience, share a joke, ask questions, get ideas, and even plan our futures.

Do not underestimate the power of connections, and of sharing your story.

Cat Lamin

Alongside Staffroom, I also built a website to allow teachers to share their mental health stories and to feel a little less alone (mentalhealthineducation.com). I continue to host regular Staffrooms, although less frequently. 18 months ago, we needed a chance to talk three times a week, but now we meet two or three times a month instead. You can find current Staffroom dates at www.globalgeg.org/events. If you take one thing away from this article, however, it is this: do not underestimate the power of connections, and of sharing your story.

Cat Lamin is a Raspberry Pi Certified Educator, CAS Master Teacher, and Google Certified Innovator who works as a freelance trainer and coach, supporting schools with digital strategy and enabling educators to use technology more effectively. For running this regular mental health staffroom, she was awarded a Mental Health Champion Award from Edufuturist.

Share your thoughts about Hello World with me!

Your insights are invaluable to help us make Hello World as useful as it can be for computing educators around the globe. Hello World is a magazine for educators from educators — so if you are interested in having a 20-minute chat with me about what you like about the magazine, and what you would like to change, then please sign up here. I look forward to speaking with you.

Download Hello World for free

The brand-new issue of our free Hello World magazine for computing educators focuses on all things health and well-being.

It is full of inspiring stories and practical ideas for teaching your learners about computing in this context, and supporting them to use digital technologies in beneficial ways.

Download the new issue of Hello World for free today:

To never miss a new issue, you can subscribe to Hello World for free. We’ve also just released the first-ever special edition of Hello World — The Big Book of Pedagogy — which focuses on approaches to teaching computing in the classroom. Download the special issue for free.

And wherever you are in the world, don’t forget to listen to the Hello World podcast, where each episode we dive into a new topic from the magazine with some of the computing educators who’ve written for us.

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Source: Raspberry Pi – Cat Lamin on building a global educator family | Hello World #17

For the last two years, I’ve been one of the advisors to the Center for Universal Education at the Brookings Institution, a US-based think tank, on their project to survey formal computing education systems across the world. The resulting education policy report, Building skills for life: How to expand and improve computer science education around the world, pulls together the findings of their research. I’ll highlight key lessons policymakers and educators can benefit from, and what elements I think have been missed.

Why a global challenge?

Work on this new Brookings report was motivated by the belief that if our goal is to create an equitable, global society, then we need computer science (CS) in school to be accessible around the world; countries need to educate their citizens about computer science, both to strengthen their economic situation and to tackle inequality between countries. The report states that “global development gaps will only be expected to widen if low-income countries’ investments in these domains falter while high-income countries continue to move ahead” (p. 12).

The report makes an important contribution to our understanding of computer science education policy, providing a global overview as well as in-depth case studies of education policies around the world. The case studies look at 11 countries and territories, including England, South Africa, British Columbia, Chile, Uruguay, and Thailand. The map below shows an overview of the Brookings researchers’ findings. It indicates whether computer science is a mandatory or elective subject, whether it is taught in primary or secondary schools, and whether it is taught as a discrete subject or across the curriculum.

It’s a patchy picture, demonstrating both countries’ level of capacity to deliver computer science education and the different approaches countries have taken. Analysis in the Brookings report shows a correlation between a country’s economic position and implementation of computer science in schools: no low-income countries have implemented it at all, while over 20% of high-income countries have mandatory computer science education at both primary and secondary level. 

Capacity building: IT infrastructure and beyond

Given these disparities, there is a significant focus in the report on what IT infrastructure countries need in order to deliver computer science education. This infrastructure needs to be preceded by investment (funds to afford it) and policy (a clear statement of intent and an implementation plan). Many countries that the Brookings report describes as having no computer science education may still be struggling to put these in place.

The recently developed CAPE (capacity, access, participation, experience) framework offers another way of assessing disparities in education. To have capacity to make computer science part of formal education, a country needs to put in place the following elements:

• Policy
• IT infrastructure
• Computer science content in the curriculum
• Teacher education

My view is that countries that are at the beginning of this process need to focus on IT infrastructure, but also on the other elements of capacity. The Brookings report touches on these elements of capacity as well. Once these are in place in a country, the focus can shift to the next level: access for learners.

Comparing countries — what policies are in place?

In their report, the Brookings researchers identify seven complementary policy actions that a country can take to facilitate implementation of computer science education:

1. Introduction of ICT (information and communications technology) education programmes
2. Requirement for CS in primary education
3. Requirement for CS in secondary education
4. Introduction of in-service CS teacher education programmes
5. Introduction of pre-service teacher CS education programmes
6. Setup of a specialised centre or institution focused on CS education research and training
7. Regular funding allocated to CS education by the legislative branch of government

The figure below compares the 11 case-study regions in terms of how many of the seven policy actions have been taken, what IT infrastructure is in place, and when the process of implementing CS education started.

England is the only country that has taken all seven of the identified policy actions, having already had nation-wide IT infrastructure and broadband connectivity in place. Chile, Thailand, and Uruguay have made impressive progress, both on infrastructure development and on policy actions. However, it’s clear that making progress takes many years — Chile started in 1992, and Uruguay in 2007 —  and requires a considerable amount of investment and government policy direction.

Computing education policy in England

The first case study that Brookings produced for this report, back in 2019, related to England. Over the last 8 years in England, we have seen the development of computing education in the curriculum as a mandatory subject in primary and secondary schools. Initially, funding for teacher education was limited, but in 2018, the government provided £80 million of funding to us and a consortium of partners to establish the National Centre for Computing Education (NCCE). Thus, in-service teacher education in computing has been given more priority in England than probably anywhere else in the world.

Alongside teacher education, the funding also covered our development of classroom resources to cover the whole CS curriculum, and of Isaac Computer Science, our online platform for 14- to 18-year-olds learning computer science. We’re also working on a £2m government-funded research project looking at approaches to improving the gender balance in computing in English schools, which is due to report results next year.

The future of education policy in the UK as it relates to AI technologies is the topic of an upcoming panel discussion I’m inviting you to attend.

The Brookings report highlights the way in which the English government worked with non-profit organisations, including us here at the Raspberry Pi Foundation, to deliver on the seven policy actions. Partnerships and engagement with stakeholders appear to be key to effectively implementing computer science education within a country. 

Lessons learned, lessons missed

What can we learn from the Brookings report’s helicopter view of 11 case studies? How can we ensure that computer science education is going to be accessible for all children? The Brookings researchers draw our six lessons learned in their report, which I have taken the liberty of rewording and shortening here:

1. Create demand
2. Make it mandatory
3. Train teachers
4. Start early
5. Work in partnership
6. Make it engaging

In the report, the sixth lesson is phrased as, “When taught in an interactive, hands-on way, CS education builds skills for life.” The Brookings researchers conclude that focusing on project-based learning and maker spaces is the way for schools to achieve this, which I don’t find convincing. The problem with project-based learning in maker spaces is one of scale: in my experience, this approach only works well in a non-formal, small-scale setting. The other reason is that maker spaces, while being very engaging, are also very expensive. Therefore, I don’t see them as a practicable aspect of a nationally rolled-out, mandatory, formal curriculum.

When we teach computer science, it is important that we encourage young people to ask questions about ethics, power, privilege, and social justice.

Sue Sentance

We have other ways to make computer science engaging to all learners, using a breadth of pedagogical approaches. In particular, we should focus on cultural relevance, an aspect of education the Brookings report does not centre. Culturally relevant pedagogy is a framework for teaching that emphasises the importance of incorporating and valuing all learners’ knowledge, heritage, and ways of learning, and promotes the development of learners’ critical consciousness of the world. When we teach computer science, it is important that we encourage young people to ask questions about ethics, power, privilege, and social justice.

The Brookings report states that we need to develop and use evidence on how to teach computer science, and I agree with this. But to properly support teachers and learners, we need to offer them a range of approaches to teaching computing, rather than just focusing on one, such as project-based learning, however valuable that approach may be in some settings. Through the NCCE, we have embedded twelve pedagogical principles in the Teach Computing Curriculum, which is being rolled out to six million learners in England’s schools. In time, through this initiative, we will gain firm evidence on what the most effective approaches are for teaching computer science to all students in primary and secondary schools.

Moving forward together

I believe the Brookings Institution’s report has a huge contribution to make as countries around the world seek to introduce computer science in their classrooms. As we can conclude from the patchiness of the CS education world map, there is still much work to be done. I feel fortunate to be living in a country that has been able and motivated to prioritise computer science education, and I think that partnerships and working across stakeholder groups, particularly with schools and teachers, have played a large part in the progress we have made.

To my mind, the challenge now is to find ways in which countries can work together towards more equity in computer science education around the world. The findings in this report will help us make that happen.

PS We invite you to join us on 16 November for our online panel discussion on what the future of the UK’s education policy needs to look like to enable young people to navigate and shape AI technologies. Our speakers include UK Minister Chris Philp, our CEO Philip Colligan, and two young people currently in education. Tabitha Goldstaub, Chair of the UK government’s AI Council, will be chairing the discussion.

Sign up for your free ticket today and submit your questions to our panel!

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Source: Raspberry Pi – Computer science education is a global challenge

On the occasion of Black History Month UK, we speak to Joe Arday, Computer Science teacher at Woodbridge High School in Essex, UK, about his experiences in computing education, his thoughts about underrepresentation of Black students in the subject, and his ideas about what needs to be done to engage more Black students.

To start us off, can you share some of your thoughts about Black History Month as an occasion?

For me personally it’s an opportunity to celebrate our culture, but my view is it shouldn’t be a month — it should be celebrated every day. I am of Ghanaian descent, so Black History Month is an opportunity to share my culture in my school and my community. Black History Month is also an opportunity to educate yourself about what happened to the generations before you. For example, my parents lived through the Brixton riots. I was born in 1984, and I got to secondary school before I heard about the Brixton riots from a teacher. But my mother made sure that, during Black History Month, we went to a lot of extracurricular activities to learn about our culture.

For me it’s about embracing the culture I come from, being proud to be Black, and sharing that culture with the next generation, including my two kids, who are of mixed heritage. They need to know where they come from, and know their two cultures.

Tell us a bit about your own history: how did you come to computing education?

So I was a tech professional in the finance sector, and I was made redundant when the 2008 recession hit. I did a couple of consulting jobs, but I thought to myself, “I love tech, but in five years from now, do I really want to be going from job to job? There must be something else I can do.”

At that time there was a huge drive to recruit more teachers to teach what was called ICT back then and is now Computing. As a result, I started my career as a teacher in 2010. As a former software consultant, I had useful skills for teaching ICT. When Computing was introduced instead, I was fortunate to be at a school that could bring in external CPD (continued professional development) providers to teach us about programming and build our understanding and skills to deliver the new curriculum. I also did a lot of self-study and spoke to lots of teachers at other schools about how to teach the subject.

What barriers or support did you encounter in your teaching career? Did you have role models when you went into teaching?

Not really — I had to seek them out. In my environment, there are very few Black teachers, and I was often the only Black Computer Science teacher. A parent once said to me, “I hope you’re not planning to leave, because my son needs a role model in Computer Science.” And I understood exactly what she meant by that, but I’m not even a role model, I’m just someone who’s contributing to society the best way I can. I just want to pave the way for the next generation, including my children.

My current school is supporting me to lead all the STEM engagement for students, and in that role, some of the things I do are running a STEM club that focuses a lot on computing, and running new programmes to encourage girls into tech roles. I’ve also become a CAS Master Teacher and been part of a careers panel at Queen Mary University London about the tech sector, for hundreds of school students from across London. And I was selected by the National Centre for Computing Education as one of their facilitators in the Computer Science Accelerator CPD programme.

But there’s been a lack of leadership opportunities for me in schools. I’ve applied for middle-leadership roles and have been told my face doesn’t fit in an interview in a previous school. And I’m just as skilled and experienced as other candidates: I’ve been acting Head of Department, acting Head of Year — what more do I need to do? But I’ve not had access to middle-leadership roles. I’ve been told I’m an average teacher, but then I’ve been put onto dealing with “difficult” students if they’re Black, because a few of my previous schools have told me that I was “good at dealing with behaviour”. So that tells you about the role I was pigeonholed into.

It is very important for Black students to have role models, and to have a curriculum that reflects them.

Joe Arday

I’ve never worked for a Black Headteacher, and the proportion of Black teachers in senior leadership positions is very low, only 1%. So I am considering moving into a different area of computing education, such as edtech or academia, because in schools I don’t have the opportunities to progress because of my ethnicity.

Do you think this lack of leadership opportunities is an experience other Black teachers share?

I think it is, that’s why the number of Black teachers is so low. And as a Black student of Computer Science considering a teaching role, I would look around my school and think, if I go into teaching, where are the opportunities going to come from?

Black students are underrepresented in computing. Could you share your thoughts about why that’s the case?

There’s a lack of role models across the board: in schools, but also in tech leadership roles, CEOs and company directors. And the interest of Black students isn’t fostered early on, in Year 8, Year 9 (ages 12–14). If they don’t have a teacher who is able to take them to career fairs or to tech companies, they’re not going to get exposure, they’re not going to think, “Oh, I can see myself doing that.” So unless they have a lot of interest already, they’re not going to pick Computer Science when it comes to choosing their GCSEs, because it doesn’t look like it’s for them.

But we need diverse people in computing and STEM, especially girls. As the father of a boy and a girl of mixed heritage, that’s very important to me. Some schools I’ve worked in, they pushed computer science into the background, and it’s such a shame. They don’t have the money or the time for their teachers to do the CPD to teach it properly. And if attitudes at the top are negative, that’s going to filter down. But even if students don’t go into the tech industry, they still need digital skills to go into any number of sectors. Every young person needs them.

It is very important for Black students to have role models, and to have a curriculum that reflects them. Students need to see themselves in their lessons and not feel ignored by what is being taught. I was very fortunate to be selected for the working group for the Raspberry Pi Foundation’s culturally relevant teaching guidelines, and I’m currently running some CPD for teachers around this. I bet in the future Ofsted will look at how diverse the curriculum of schools is.

What do you think tech organisations can do in order to engage more Black students in computing?

I think tech organisations need to work with schools and offer work experience placements. When I was a student, 20 years ago, I went on a placement, and that set me on the right path. Nowadays, many students don’t do work experience, they are school leavers before they do an internship. So why do so many schools and organisations not help 14- or 15-year-olds spend a week or two doing a placement and learning some real-life skills?

And I think it’s very important for teachers to be able to keep up to date with the latest technologies so they can support their students with what they need to know when they start their own careers, and can be convincing doing it. I encourage my GCSE Computer Science students to learn about things like cloud computing and cybersecurity, about the newest types of technologies that are being used in the tech sector now. That way they’re preparing themselves. And if I was a Headteacher, I would help my students gain professional certifications that they can use when they apply for jobs.

What is a key thing that people in computing education can do to engage more Black students?

Teachers could run a STEM or computing club with a Black History Month theme to get Black students interested — and it doesn’t have to stop at Black History Month. And you can make computing cross-curricular, so there could be a project with all teachers, where each one runs a lesson that involves a bit of coding, so that all students can see that computing really is for everyone.

What would you say to teachers to encourage them to take up Computer Science as a subject?

Because of my role working for the NCCE, I always encourage teachers to join the NCCE’s Computer Science Accelerator programme and to retrain to teach Computer Science. It’s a beautiful subject, all you need to do is give it a chance.

Thank you, Joe, for sharing your thoughts with us!

Joe was part of the group of teachers we worked with to create our practical guide on culturally relevant teaching in the computing classroom. You can download it as a free PDF now to help you think about how to reflect all your students in your lessons.

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We are inviting you all to a very special event this week: the CoderDojo team is hosting a 10th birthday livestream to celebrate the CoderDojo community and all that they have achieved over the last ten years.

Everyone is welcome, so mark your diary and make sure you and your favourite young coders join us for all the fun at 18:00 BST this Thursday, 28 October! 

Together we will hear stories from young people and volunteers around the world, and from James Whelton and Bill Liao, the co-founders of CoderDojo.

Ten years of community spirit

In July 2011, James Whelton and Bill Liao held the first-ever CoderDojo session in Cork, Ireland. They created a space for young people to learn how to create a website, design a game, or write their first program. The session was also a chance for volunteers to share their experience and time with a younger generation and their peers. It was here that the CoderDojo grassroots community came into existence, built on the values of ‘being cool’: creativity, collaboration, openness, and fun.

These values continue to inspire young people (Ninjas) and volunteers around the world to be part of their local Dojos. In 2017, the CoderDojo Foundation, which was founded to support the CoderDojo movement, and the Raspberry Pi Foundation joined forces to better support the community to bring opportunities to more young people worldwide.

The tenth year of the movement is an especially important time for us to celebrate the volunteers who have put so much into CoderDojo. As well as the livestream celebration on 28 October, the CoderDojo team has put together free digital assets to get volunteers and Ninjas in the birthday spirit, and a special birthday giveaway for Ninjas who are coding projects to mark this momentous anniversary.

Ten things we love about you

In celebration of the CoderDojo movement’s 10th birthday, here’s a list of some of our favourite things about the CoderDojo community.  

1. You are always having so much fun!

Whether you’re working together in person or online, you are always having a blast!

2. You are resilient and committed to your club 

The pandemic has been an extremely difficult time for Dojos. It has also been a time of adaptation. We have been so impressed by how community members have switched their ways of running with positivity and commitment to 6. do what is best for their clubs.

3. You support each other

Every day, Dojo volunteers support each other locally and globally to sustain the movement and help Ninjas learn — from sharing how they run sessions when social distancing is necessary, to translating online resources and web pages so that more people around the world can join the CoderDojo community.

“We know that we’re not out there alone, that there’s a whole world of people who are all collaborating with the same mission in mind is really thrilling as well.”

Nikole Vaughn, CoderDojo Collaborative in San Antonio, Texas

4. You tell the team how to support you 

Filling in surveys, emailing the CoderDojo team here, attending webinars, sharing your insights — these are all the ways you’re great at communicating your Dojo’s needs. We love supporting you!

5. You help young people create positive change in their community 

We love to hear about how CoderDojo volunteers help young people to create and learn with technology, and to become mentors for their peers. Recently we shared the stories of Avye, Laura, and Toshan, three incredible digital makers who, thanks to CoderDojo, are using technology to shape the world around them.

6. You love a challenge

From coding for the CoderDojo 10th birthday giveaway to the European Astro Pi Challenge, CoderDojo members love to put themselves to the test!   

7. You brought Coolest Projects into the world 

Coolest Projects is the world-leading technology fair for young people, and it originated in the CoderDojo community!

This year, in its ninth year running, Coolest Projects again was a platform for fantastic tech projects from Ninjas, including an AI bicycle app and a glove that makes music.

8. You are committed to creating inclusive spaces 

CoderDojo is a space for everyone to create and learn with technology. We love that Dojos get involved in projects such as the ‘Empowering the future’ guide to getting more girls involved in coding, and the CoderDojo Accessibility Guide to making Dojo sessions accessible for young people of all abilities and neurodiversity.

9. You are a community that continues to grow stronger

Over the last ten years, more than 3900 Dojos in 115 countries have run sessions for over 270000 young people and have been regularly supporting 100000 young coders! You’ve certainly brought the movement a long way from that very first session in Cork.   

10. You are simply the best grassroots community on the planet! 

All the volunteers who have put their time and energy into CoderDojo have made the movement what it is today, and we’d like to say a massive thank you to each and every one of you.

Let’s celebrate together! 

So prepare your favourite celebratory food and join us for the birthday livestream on Thursday 28 October at 18:00 BST! Take this chance to say hi to community members and celebrate everything that they have achieved in the last ten years.

Set a reminder for the livestream, and tell us how you are celebrating CoderDojo’s 10th birthday using the hashtag #10YearsOfCoderDojo on Twitter. 

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Hello World, our free magazine for computing and digital making educators, has just published its very first special edition: The Big Book of Computing Pedagogy!

“When I started to peruse the draft for The Big Book of Computing Pedagogy, I was simply stunned.”

Monica McGill, founder & CEO of CSEDResearch.org

This special edition focuses on practical approaches to teaching computing in the classroom, and includes some of our favourite pedagogically themed articles from previous issues of Hello World, as well as a few never-seen-before pieces. It is structured around twelve pedagogical principles, first developed by us as part of our work related to the National Centre for Computing Education in England. These twelve principles are based on up-to-date research around the best ways of approaching the teaching and learning of computing.

Grounded in research and practice

Computing education is still relatively new, and it’s a field that’s constantly changing and adapting. Despite leaving school less than ten years ago, I remember my days in the computer lab being limited to learning about how to add animations on PowerPoints and trying out basic Excel formulas (and yes, there was still the odd mouse with a ball knocking about!).

Computing education research is even younger, and we are proud to be an important part of this growing space. As an organisation, we engage in rigorous original research around computing education and learning for young people, and we share all of our research work through blogs, reports, research seminars, and academic publications. We’re particularly proud to have partnered with the University of Cambridge to establish the Raspberry Pi Computing Education Research Centre. 

The Big Book of Computing Pedagogy represents another way in which we bring research and practice to computing educators in an accessible and engaging way. The book aims to be an educator’s companion to learning about tried and tested approaches to teaching computing.

It includes articles on techniques for fostering program comprehension, advice for bringing physical computing to your classroom, and introductions to frameworks for structuring your computing lessons. As with all Hello World content, we’re bridging the gap between research and practice by giving you accessible chunks of research, followed by stories of trusty educators who have tried out the approaches in their classroom or educational space.

Monica McGill, founder and CEO of CSEDResearch.org, says about Hello World’s latest offering, “When I started to peruse the draft for The Big Book of Computing Pedagogy, I was simply stunned. I found the ready-to-consume content to be solidly based on research evidence and tried-and-true best practices from teachers themselves. This resource provides valuable insights into introducing computing to students via unplugged activities, integrating the Predict–Run–Investigate–Modify–Make (PRIMM) pedagogical model, and introducing physical devices for computing — all written in a way that teachers can adopt and use in their own classrooms.”

We’ve been thrilled to see the reaction of educators to this special edition, with many teachers already using it as a reference guide and for a spot of CPD. Why not join them and download it for free today?

Subscribe now to get each new Hello World — whether regular issue or special edition — straight to your digital inbox, for free! And if you’re based in the UK and do paid or unpaid work in education, you can subscribe for free print issues.

PS Have you listened to our Hello World podcast yet? A new episode has just come out, and it’s great! Listen and subscribe wherever you get your podcasts.

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The annual UK Bebras Computational Thinking Challenge is back to provide fun, brain-teasing puzzles for schools from 8 to 19 November!

In the free Bebras Challenge, your students get to practise their computational thinking skills while solving a set of accessible, puzzling, and engaging tasks over 40 minutes. It’s tailored for age groups from 6 to 18.

“I just want to say how much the children are enjoying this competition. It is the first year we have entered, and I have students aged 8 to 11 participating in my Computing lessons, with some of our older students also taking on the challenges. It is really helping to challenge their thinking, and they are showing great determination to try and complete each task!”

– A UK-based teacher

Ten key facts about Bebras

1. It’s free!
2. The challenge takes place in school, and it’s a great whole-school activity
3. It’s open to learners aged 6 to 18, with activities for different age groups
4. The challenge is made up of a set of short tasks, and completing it takes 40 minutes
5. The closing date for registering your school is 4 November
6. Your learners need to complete the challenge between 8 and 19 November 2021
7. All the marking is done for you (hurrah!)
8. You’ll receive the results and answers the week after the challenge ends, so you can go through them with your learners and help them learn more
9. The tasks are logical thinking puzzles, so taking part does not require any computing knowledge
10. There are practice questions you can use to help your learners prepare for the challenge, and throughout the year to help them practice their computational thinking

Do you want to support your learners to take on the Bebras Challenge? Then register your school today!

Remember to sign up by 4 November!

The benefits of Bebras

Bebras is an international challenge that started in Lithuania in 2004 and has grown into a worldwide event. The UK became involved in Bebras for the first time in 2013, and the number of participating students has increased from 21,000 in the first year to more than half a million over the last two years! Internationally, nearly 2.5 million learners took part in 2020 despite the disruptions to schools.

Bebras, brought to you in the UK by us and Oxford University, is a great way to give your learners of all age groups a taste of the principles behind computing by engaging them in fun problem-solving activities. The challenge results highlight computing principles, so Bebras can be educational for you as a teacher too.

Throughout the year, questions from previous years of the challenge are available to registered teachers on the bebras.uk website, where you can create self-marking quizzes to help you deliver the computational thinking part of the curriculum for your classes.

You can register your school at bebras.uk/admin.

Learn more about our work to support learners with computational thinking.

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Join our free online course Introduction to Machine Learning and AI to discover the fundamentals of machine learning and learn to train your own machine learning models using free online tools.

Although artificial intelligence (AI) was once the province of science fiction, these days you’re very likely to hear the term in relation to new technologies, whether that’s facial recognition, medical diagnostic tools, or self-driving cars, which use AI systems to make decisions or predictions.

By the end of this free online course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.

Machine learning — a brief overview

You’ll also often hear about AI systems that use machine learning (ML). Very simply, we can say that programs created using ML are ‘trained’ on large collections of data to ‘learn’ to produce more accurate outputs over time. One rather funny application you might have heard of is the ‘muffin or chihuahua?’ image recognition task.

More precisely, we would say that a ML algorithm builds a model, based on large collections of data (the training data), without being explicitly programmed to do so. The model is ‘finished’ when it makes predictions or decisions with an acceptable level of accuracy. (For example, it rarely mistakes a muffin for a chihuahua in a photo.) It is then considered to be able to make predictions or decisions using new data in the real world.

It’s important to understand AI and ML — especially for educators

But how does all this actually work? If you don’t know, it’s hard to judge what the impacts of these technologies might be, and how we can be sure they benefit everyone — an important discussion that needs to involve people from across all of society. Not knowing can also be a barrier to using AI, whether that’s for a hobby, as part of your job, or to help your community solve a problem.

For teachers and educators it’s particularly important to have a good foundational knowledge of AI and ML, as they need to teach their learners what the young people need to know about these technologies and how they impact their lives. (We’ve also got a free seminar series about teaching these topics.)

To help you understand the fundamentals of AI and ML, we’ve put together a free online course: Introduction to Machine Learning and AI. Over four weeks in two hours per week, you’ll learn how machine learning can be used to solve problems, without going too deeply into the mathematical details. You’ll also get to grips with the different ways that machines ‘learn’, and you will try out online tools such as Machine Learning for Kids and Teachable Machine to design and train your own machine learning programs.

What types of problems and tasks are AI systems used for?

As well as finding out how these AI systems work, you’ll look at the different types of tasks that they can help us address. One of these is classification — working out which group (or groups) something fits in, such as distinguishing between positive and negative product reviews, identifying an animal (or a muffin) in an image, or spotting potential medical problems in patient data.

You’ll also learn about other types of tasks ML programs are used for, such as regression (predicting a numerical value from a continuous range) and knowledge organisation (spotting links between different pieces of data or clusters of similar data). Towards the end of the course you’ll dive into one of the hottest topics in AI today: neural networks, which are ML models whose design is inspired by networks of brain cells (neurons).

Before an ML program can be trained, you need to collect data to train it with. During the course you’ll see how tools from statistics and data science are important for ML — but also how ethical issues can arise both when data is collected and when the outputs of an ML program are used.

By the end of the course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.

Sign up to the course today, for free

The Introduction to Machine Learning and AI course is open for you to sign up to now. Sign-ups will pause after 12 December. Once you sign up, you’ll have access for six weeks. During this time you’ll be able to interact with your fellow learners, and before 25 October, you’ll also benefit from the support of our expert facilitators. So what are you waiting for?

Share your views as part of our research

As part of our research on computing education, we would like to find out about educators’ views on machine learning. Before you start the course, we will ask you to complete a short survey. As a thank you for helping us with our research, you will be offered the chance to take part in a prize draw for a £50 book token!

Learn more about AI, its impacts, and teaching learners about them

To develop your computing knowledge and skills, you might also want to:

• Attend our free online research seminars on teaching young people about AI and data science
• Take our free Impact of Technology: How To Lead Classroom Discussions course to help you think more about the impacts of AI (although the course is aimed at teachers, it is open and useful for everyone

If you are a teacher in England, you can develop your teaching skills through the National Centre for Computing Education, which will give you free upgrades for our courses (including Introduction to Machine Learning and AI) so you’ll receive certificates and unlimited access.

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