What does computing education look like in 2024/25? | Special

In this one-off special visualised episode, James is joined by members across the Raspberry Pi Foundation’s learning team to reflect on the past year and look ahead. Ben, Mamta, Rachel, Liz, and Leonida share their perspectives and expertise on what computing education looks like in their part of the world, including challenges and opportunities faced by educators and students alike. The team also explores the important question of AI and its impact on society, the lives of students, and computing education.

Transcript

LIZ: 0:00

There's a lot of noise around AI education and how to do it.

RACHEL: 0:03

I think it's super important that we get it right.

BEN: 0:06

So rather than using words like, you know,"the AI", put the human in the process.

MAMTA: 0:11

Students will learn better if we– if we give examples from their own surroundings.

LEONIDA: 0:15

And when you have the educators on board, the learners will have it at the right point and in the right way.

JAMES: 0:21

Hello and welcome to this very special episode of the Hello World podcast, in which you can both see and hear us. As you'll have seen in this conversation, I'm joined by five fantastic educators and colleagues as we look back onto the year that's been 2024 and look ahead to 2025. Throughout our conversation we explore two key themes, the first being how AI is impacting on computing education, and also how computing education varies throughout the world. I thoroughly enjoyed this conversation and we hope that you do too. As ever, you can leave your feedback for us at: But let's without further ado hear from my colleagues who are joining me. I'm going to go around the table and I'd like you to introduce yourselves and perhaps share in a very short snippet of what makes it– what excites you about computing and computing education. So Ben, over to you first of all. BEN: Hello James, I am Ben Garside. I'm our Senior Learning Manager on our AI literacy team. So what excites me about computing education is this potential to solve real-world problems and putting those problem-solving capabilities in the hands of young people is really exciting.

MAMTA: 1:26

Hi, I'm Mamta Manaktala, the Senior Learning Manager on the India team and what excites me about the computing education is the way it's transforming the world. The– the new approach to solve the problems, it's– it's– it's really exciting.

JAMES: 1:37

Cool. I'm going to just say what my exciting thing is, I really enjoy the fact that computing gives students this power to be creative and express themselves in new and exciting ways.

RACHEL: 1:48

I'm Rachel Arthur, I'm the Chief Learning Officer at Raspberry Pi Foundation and what I think is amazing is there's something in computer science and computing for everyone. There's an area that you can engage all young people with. You just have to find that one thing, and then once they've got it, you see the bubbles of excitement coming from them.

LIZ: 2:08

I'm Liz Walsh, a Learning Manager on our North America team. What I'm excited about is that we're still figuring it out, especially in the United States, and there's opportunities to engage students and educators and populations that have been traditionally left out of, like, education in these decisions. So that's what I'm excited about.

LEONIDA: 2:26

I'm Leonida from Kenya and I'm a Learning Manager from Kenya, and what excites me most is the way we have the pedagogies of computing, which we've traditionally– we've not had in Kenya, and it is really changing the approach and having our learners be able to be very innovative and creative and adaptive to the environments that there are.

JAMES: 2:47

I think it's really interesting, the variety of answers we've heard there, and I really like the point that everyone has made. I think it's really– the– the fact that we don't know it yet, I think that's really exciting. The fact that pedagogy is something that really kind of drives the work we do. Maybe we want to expand on– on any of that. Like what– what other things do people want to kind of add? Like AI's been a really exciting topic over the last year. What– what do we want to say about maybe about AI, but I'm going to look to you, Ben, I am going to look to you Ben.

BEN: 3:12

It's alright, I will talk about that. Yeah, well I think it's– it's this different way of solving problems. I mean, traditionally when we think about computational thinking, we're talking about this like, rule-based approach. I think machine learning is opening up loads of new possibilities and exciting new possibilities for people to solve these problems. You know, some real kind of life-changing things, you know, climate, you know, mitigation problems have been solved and I think that's something that young people really care about, right? And I think pointing out the benefits that that can have and feeling that they feel– young people can feel empowered maybe to be part of that future.

JAMES: 3:44

And what– what's other people's experience been of AI and– and their reflections on– on its progress and– and impact on education over the last year?

RACHEL: 3:51

I think it's super important that we get it right. It scare– it– I love that we've got resources around AI that are supporting people all over the world to access and teach about AI, but we have to get it right because it could be– it could split the digital divide even further than what we've currently seen and if we have teachers in classrooms that aren't comfortable to teach about AI, predominantly from the research that's been done so far are from areas with less funding, less opportunity. I think we're seeing the same things globally that that could cause a greater divide, so I'm– I'm so excited about it. I think it could really change things but we need to make sure that everyone has fair access to those resources.

MAMTA: 4:38

Yeah, I– I would say that the– the challenge of differentiated learning that we've been facing over the years in the classroom to provide the customised learning journey to students' needs, I think that's what AI is helping us with majorly. The t ools of of each student and pre– prepare the journey for– for themselves and the teacher will have just a role to play in– in– like, in implementing those ways. LIZ: Yeah I think where I've been concerned a little bit is there's a lot of noise around AI education and how to do it, and thinking back to like my experience in the classroom is you're dealing with so much, it's hard to like differentiate, like, what is like an actual good resource that I should be learning about and using with my students when there's all of these products and a bunch of like AI experts that are telling– telling teachers like, this is what you should be doing, this is how you should be doing it, but they don't have experience in the classroom. I think that's where we're unique, where we have– our team is built of educators, and we're like taking in that educator voice and like preparing them not only to like, use generative AI to like, support them in their teaching, but like an understanding of AI, how it works, when to use it, and when to maybe not use it as well.

LEONIDA: 5:55

So what I look at in the part of Kenya is that we are at a younger stage in the digital literacy level. There's that scarcity of that. People will get into tech, AI, and forget the innovativeness, but the– what I love with it is having the educators on board and when you have the educators on board, the learners will have it at the right point and in the right way so that we will not have a gap at a point whereby there's over-reliance on the AI, rather than having the innovativeness of the future generation.

JAMES: 6:30

I think that– that that gap is– is interesting because I think like, there is a lot of noise, you're right. You men– you talked about the amount of noise, like the– the number of products now that seem to have like AI integrate and you like really, has it really got– how much difference is it making? But there's so much noise in like the– in sort of popular culture and in the– in the mainstream that it means that people are chasing it and so you might end up with learners that are– and educators that are like, never mind this computing bit over here, let's go and look at the– AI is the exciting thing, that's where we've got to go. And then you miss some of the– like the fundamentals and your– your understanding is maybe a bit more shallow and because AI is maybe slightly more abstract and a bit more opaque in its– how it works, that– that could be really challenging, that we'd have a generation of learners that use it but don't really know what's going on under the hood.

BEN: 7:15

I hear all the time this phrase that AI is going to democratise education, and it really frustrates me because I think it's this assumption that it can, you know, just do all these great things. Of course there's a potential that it– it could do but as soon as we assume it's going to democratise, I think we lose all control because, you know, that's making huge assumptions around the fact that everyone has equal access to even the technology in their school, their classroom, at home, even things like just assuming that young people can even understand the feedback that they get from a large language model, that's quite an assumption to make. So, yeah, I think we've just got to be really careful around that. I think we've got to educate young people to understand how they work, but I think getting down to the nitty gritty of like, what are those crucial things that they do need to learn, and I think critical thinking skills. As a computing teacher I've always found, you know, critical thinking to be really important. But I think in AI, critical thinking is becoming even more important, right?

RACHEL: 8:08

I think we have to be careful not to lose the focus on computer science in a world of AI, where AI is the new topic that everyone wants to talk about and it is exciting. The possibilities will change the world of work. We're already seeing it happen, but we can't lose the importance of the broader teaching of computer science and computing alongside it. I think there's a lot of confusion in– in different countries when I've been speaking to colleagues around whose responsibility is it to teach artificial intelligence. Should it be something that sits as part of a national curriculum that all teachers teach and engage with? Does it sit in a more of a E-safety bucket? And then we in computer science where you can teach what AI is, how it works under the hood a little bit more, and allow us to focus on the pure teaching of computer science rather than trying to address all the world around AI literacy as well as under the hood of it.

JAMES: 9:05

I was going to come back to this, like this point about I think creativity and agency was something that was a bit of a theme in our introductions, and I was just reminded at the weekend we ran a– a Code Club here in the office, and we had some AI activities and it was– I was surprised by how quickly some of the young people took the ideas and the projects that we were providing them with and had been thinking about, oh, I'm going to make a thing, which is going to analyse my movie review or whatever it might have been, and they just would applying it to their real lives and the problems, like really quickly, and that was really like, exciting to see. And I guess my question is, what's the role of AI in engaging, like all learners, sort of equitably? Is it– does it have the power to bring more girls and more disenfranchised learners into computing?

LIZ: 9:48

I can speak like in Minnesota, like AI has like brought the topic of computer science, like into, like the spotlight. There's been a lot of– like a small group of people for several years that have been trying and like advocating for computer science education and with AI, now people are starting to talk more about computer science education and how we might bring that, like nationally– not nationally, like state-wide as well. So I think it's– I can't answer like how yet, but I think it's a conversation starter that allows us to like dive deeper into different topics in computer science and like how we bring equitable access to all students no matter where they are.

MAMTA: 10:30

I think AI has created a buzz all across the demographies I would say. It's not only the urban population that– that has access to computers. Now we– what we talk about the disadvantaged and marginalised sections also. And they are getting into that. They might not have access to the devices as yet, but still it's– it's the buzzword, right. Everybody's talking about AI and so that– that means we are reaching at a level where– where we all feel the same and we all feel empowered, we all feel– we've got that thing to transform our lives and– and it's just to channelise them in the correct direction how to use it, and like you s– Rachel mentioned that it's– it's the way how– how to access it, how to ensure that it's still ethical.

JAMES: 11:19

I was gonna– won– I was wondering with Leonida, is– in– in Kenya, where the– some of the learners may not regularly interact with like a– a computing device, they might have a smartphone, for example, how much of a buzz is there amongst the sort of urban and rural communities around AI? What's– what's that– li– like in Kenya? Yeah, it is there but there is an issue of– the fear of this AI, like in the education sector there's a fear of suppressing the use of this AI. So you would find maybe learners would get access, but check it in a way that maybe it is not well guided. We don't have a platform that really helps to explore it in the right way, which I'm seeing when we have the educators on board to be able to guide these learners and also to the policymakers, because also you'll find the policymakers has a fear that maybe it's going to come and distract the way– the ability of our learners and everything so there should be a better approach, which now, it is not there. And, you'd find learners are using it. It's not that it's not there, but now is it really in the right way, are they using it? And in the urban setup it is there, in the rural setups you'd find they don't get exposed, but you'd find they know it is there. You'd find somebody young, like my daughter in grade six

all the time: 12:39

"there is an app I want on my phone.""I realise there's an AI that you can maybe question and get answers of–" Like no, it's not right. You need to be guided at this time. So they have not been told by the teachers at school, but within their circle they already exposed to it.

JAMES: 12:54

Yeah.

LEONIDA: 12:54

So it's how are we coming in at this level.

JAMES: 12:57

And I think that's probably not dissimilar to what I think we're finding around the world. You remind– I– I was having a conversation with my daughter at the weekend who said like:"Oh, I need to be better at my prompt engineering." And I'm like, I don't know where that phrase came from because it's not a conversation that we've had. But, you know, it's– it's definitely like– and it's not something she's talking about at school particularly, so it's definitely like in their friendship group this– they're exploring. And Ben you're doing lots of work adapting resources for different audiences around the world through our Experience AI content. So what's your reflection, possibly less like tied to a specific market, but like what's your reflection on the power of AI to engage, like different groups?

BEN: 13:32

I think it's all to do with context. I mean, when we created resources, we can only think of our own surroundings and what interests us, and we know interests, you know, young people maybe in the United Kingdom. I think what's been really powerful working with educators from across the world is them– it's for them to identify what works for their students, what doesn't. And I think the best example I can give of that is we created this resource where– in our Experience AI Lessons, where students had to classify for a supermarket and classify apples and tomatoes. And when we worked with our partners in Kenya, they said to us:"Well, that's great, but we don't really have supermarkets like you do and even if we did, they wouldn't eat apples and tomatoes." So essentially that activity was not relevant at all. MAMTA: Same in India. Yeah. But the feedback we got as well, you know, a lot of these young people will go and work in agriculture and such. It's making a scenario there that makes them understand this is a powerful tool to solve this problem, so it– we changed that scenario to be to do with crop disease, so identifying where the disease is in crops, and all of a sudden this is a powerful tool that they can use and actually see themselves using hopefully.

JAMES: 14:33

And I think that could have connected with– we've done– there's been lots of work done by the research sort of group at the Foundation here to– thinking about culturally relevant pedagogy and sort of embedding that into our content is really important. And I think that's the– the work we've been doing across our different markets as well. So is it– what– what– how do we– how do we go about doing that, apart from the example Ben's given? How do we go about adapting content to make it really relevant?

MAMTA: 14:54

The research has definitely stated that– that students will learn better if we– if we give examples from their own surroundings for any new learnings as the Foundation. So that– that works well, I mean we must start with all these examples I think that they can relate with, for example, as simple as preparing a recipe. Right. So– so if– th– that– that cuisine is from their local area, they will be most likely to be developed with and– and then how to use technology to– to document that or to prepare that, or to add where to share it with friends also. So that will be one thing, because that's another stage of learning that they learn to– that they see it around the world, and then they pick up the recipes or the cuisines from the global world also. But– but beginning from their own surroundings is the way to go I would say. That's why adaptation is important. That's why contextualisation the resources is important. Less of effort in the beginning, more of effort on learning the– about the technology tools instead of learning what recipes or a new term that's coming with that. So that's why adaptation is important and we've done that for India market, like for the Telangana state and for Odisha state. We've done that. And– and student there are– has students and educators, the whole of community is accepting it pretty well. We will be building it further and adding more of the global things as well so that they learn about the world as well through these resources but first focus is on to getting them exposed to the technology by exposing them by using the– their own context. Yeah.

LEONIDA: 16:35

I think also it's true back in Kenya, you'd find if it comes in a way like the learners are able to look at the surroundings, because there's so much that goes around them, that they can look at this AI, that it can come and solve a situation here. So it creates a platform where they– they are able to showcase what it can do. Also, it creates a ripple effect into the policy and the entire education sector on what can this AI bring out of these learners? Because I think there is a tendency on– maybe the– very nice that they are there. They look at what is the negative part that comes with it. But when the learner themselves comes out with projects based on this AI, it will bring out also to the educators, because also you'd find our educators currently, they would use for their preparation and everything in the classroom. But are they doing it right? Yeah. Have they been given because they don't have prior knowledge maybe in computing? It's maybe in the– the other learning areas? So are they presenting the right information in the classroom or is it AI now that is just generating that kind of information. So I think it is a sort of, having the basis of introduction and having to showcase what it can do in our environment, that means it can be picked on a– on a better platform.

LIZ: 17:56

Yeah and I think like in the US like context, like I think it goes beyond AI, like when we look at like who's participating in computer science courses and who isn't, and like access to like these different opportunities is like– there are schools that are offering like high school computer science courses, but like a small population are actually participating in it. Typically it's like one demographic and like what that means for like CS pathways and like the workforce beyond is if we're only training and supporting one type of learner, like that's who's going to be creating our technology and we're going to be missing voices and perspectives. So like when we think about localising resources, I think it's beyond just like showing like students like in images like, oh look, that's you. But like, how are we being really intentional about localising beyond images of like making sure that all students, no matter their background and experiences, feel like they have a place in a computer science course.

JAMES: 18:52

We were talking about AI potentially has the power to change the world, to empower learners, but I think the fundamental thing is we can't be complacent. Like it's not something that's just going to happen on its own. We have to be actively kind of pursuing that goal and being very deliberate about how we go about it.

BEN: 19:09

I think there's something that Rachel mentioned earlier about– particularly this equity in terms of gender bias. I'm really curious. I– I don't have an answer to this, but I suppose I feel, though, with the problem-solving element, that is something that maybe does appeal to– to young women. But I wonder how– I'd really like to know whether or not they're put off by some of the things that happen in the news around AI because, you know, it does increase inequity. There is gender bias in AI and we're seeing it, right? I mean, there was that news story last summer about the AI beauty contest. I mean, you know, how are young people– young women reacting to that when they see that in the news and seeing that AI is being generated that, if they go to the App Store, they might be able to scroll down the top ten apps and see "AI girlfriend", for example. And so I think we've got to be really careful that they're not put off by that and they see it as the positive things that AI can do rather than– rather than some of the negative elements to it.

RACHEL: 19:57

I think I've done some research on that for my master's into whether or not AI impacts on girls' uptake of GCSE computer science, very English-centric, but I think the same messages apply internationally, and I was really surprised to find how big a part teachers' attitudes had– had to play in it, and I was expecting AI is really engaging for young people so– and it's problem-solving and all the research that we've got into what engages young women in computing is those things so I thought ah brilliant, this is box ticked, they can just deliver an AI scheme of work, and then suddenly we'll have a much more diverse demographic of girls choosing to go on to study GCSE computer science. That wasn't the case, but I did find that teachers' attitudes to it really influenced the girls' uptake on it and that's why educators have such an important role to play, that if you believe that everyone has a place in the computer science classroom, then that comes across in the way you localise your content, in the examples that you give, in the role models that you show and the people that you talk about, and that's why I'm so passionate about the support we give to educators being a big piece of our jigsaw puzzle. You can create a set of resources, but influencing how they are delivered in the classroom and empowering people to localise to their exact context. You know, I used to teach in a classroom in Oldham, that was very different to the days I spent teaching in a school in London or Croydon. Those contexts are different, and that matters even within a country, so empowering educators to make sure they can do that is massive in this.

JAMES: 21:39

So we were just talking about– a little while ago about like, there's noise in the marketplace and I think there's lots of sort of products and curricula and I think one of the things I want to come to you, Ben, about is we've done some work with Experience AI on developing some resources. What kind of differentiates us from what's out there on the market? Are there are things that you think should be avoided? But yeah, tell us a bit about like the design approach to that– that content.

BEN: 22:02

So I think what we're really, really proud about with Experience AI is this fact that we are research-informed. I– I can describe it like a triangle. So we are– we've got the pedagogical experts at the Raspberry Pi Foundation, we've worked with the research team, who are experts in research obviously at the Foundation, but also with the industry experts at Google DeepMind. And I think what really sets our resources apart is this research-informed approach. I think we– we feel very strongly about some of these principles that we've embedded, such as we work on this thing called the SEAME framework. But we also have put in– kind of focused in this shift of mindset from a rule-based approach to data-driven. I suppose if I was, for the basis of a podcast, the one thing I would get– you know, talk about and hopefully advise educators on is this thing called anthropomorphism. Only just learnt to spell it. I've been trying to say it for ages. But essentially that's when we assign human characteristics to things that aren't human. And as human beings, we do this all the time. You know, you just need to turn on the TV and watch a children's cartoon, and it's got something that's not human with a smiley face. Not so problematic, I don't think, when it's cartoons, but I think– well we've got to think about, as educators, this– this importance of making sure young people have an accurate mental model of the world around them, and I think as adults, it's very easy for us to see something

like an Alexa in the home and say: 23:17

"Well, that's not– that's not a human being." But young people are growing up with this technology all around them, and it more and more behaving human-like. I think it's very– I think it's easy to forget that young people might see these as human, and there's so much research around the dangers of that, you know, being the fact that it can distract from young people wanting to be involved in it, not being critical thinkers, not questioning the outputs that they make, and all of those things combined, I think will, you know, increa – or dan – and dangerously increase in inequity and bias in society, so we've got to make sure that young people don't see them as human beings, essentially. The advice that we give is just be so careful over the images that you're using, you know, it's very– there's a website called "Better Images of AI", and that's a really nice website because it shows these different images we can use instead of the, you know, the– the smiley face robots or even the more sinister-looking robots or even female-looking robots, right? So we're really careful of– over the– the images, but I think also over language, right, because I think all educators know that, you know, words are really important when we're speaking to young people in their development of their understanding. So rather than using words like, you know, "the AI", you know, "the AI learns", I mean it's problematic in itself anyway because we have machine learning and, you know, and things like that, and neural networks. But rather than using those terms, put the human in the process.

So: 24:39

"AI developers build these systems to". It's just a slight shift in language, but we're putting the human in the process and constantly– constantly reminding young people that humans develop these and they're responsible for these systems. Or instead of like, "look, see here", it's like, "they pattern match","they detect", "they recognise". It's not really technical language, but we're moving away from direct human-like capabilities.

RACHEL: 25:00

That's so important for engaging girls as well. We know that if girls don't see themselves in having a role in creating those technologies, that they won't feel that that's important so that will completely alienate a whole half of the population just in doing that language change.

JAMES: 25:16

And I think it goes– like you were saying about like– it– it– it helps them understand it from a system kind of perspective but it also I think it's just what we were saying earlier on about not hiding sort of what's going on underneath. If we just reduce it down to"oh it, it hears and it–", which is wrong, then we are– we are masking some of that– what's going on under the hood that we– that's so important for the learners to understand. I can attest to how much time and research went in. I watched from the sidelines as you and the research team I think, spent like, was it like 18 months nearly? Just reviewing and– and researching content and approaches before we even put pen to paper to write a resource. That really speaks and you can see it in the quality of the resources that we produce. Yeah. BEN: Yeah, and to go on Rachel's point again I think one of our goals, and this is where we align really closely with Google DeepMind, is that we really think it's important that we get people to really understand the technology to– partly to diversify the tech industry. We know that's an issue, even more of an issue with AI because if we want to build fairer systems, you've got to make sure there's a diverse range of people involved in the building of these systems. But equally we don't expect every young people learning about AI to go and want to be that industry expert or developer of these systems. But we do need to– young people to realise that this will affect their futures, and we need to empower them to question the decisions that have been made, so you know, the– the predictions that they make or, you know, be able to just like, harness it, and har– you know– and– oh I'm losing my words here but– and harness the technology rather than just be these passive consumers of it really. JAMES: It's not repeating the mistakes of the past. Like previously we've gone down more of a consumer IT kind of approach and we've shifted back towards more creative– you know, and I think it's just making sure we don't go down that path again. Because I think one of the things that we do here at the Foundation is we work really carefully on curriculum development around the world. And so it'd be really interesting to hear from just how curriculum and systems differ around the world. Maybe we'll hear from some of our different markets first, and then we'll talk about where we are in England and I might come to Rachel for that, if that's alright. So who– who wants to go first and say a bit about what does curriculum look like in– in Kenya or Minnesota or– or India?

LEONIDA: 27:19

Okay I can go first. In Kenya, computing curriculum has been– in history has been only at the secondary level. Rarely do we have in primary level. So even the educators at the primary level are not really exposed to computing and even to the digital literacy. There's less use even in the classroom, in the other learning areas. But now with the new curriculum, the emphasis comes down to the primary level, which is bringing in now a challenge on both the educator and also to the learner. So educator needs training, digital literacy, and bringing in on board so that they can present and deliver the content in the right way. And also the pedagogy is– even in the secondary level, we have half the resources. Yes, there's been there, the content is there, but the challenge has been the pedagogies that the teachers are using. You find it is all that the content is not delivered well and you'll find learners don't leave the system with the necessary skills. They live with the knowledge that cannot be transmitted into the skills. So that has been a challenge, and I look at it as a highlight when you bring the– what the Foundation is bringing in, I look at it on the pedagogy level. People might talk of the resources, that we have less resources, but I think when we have the right pedagogies, even with the resources that we have there, we are able to transform what we are doing on the ground.

JAMES: 28:43

I find that work really exciting as well because we've– we've developed our own pedagogical approaches here based upon our experience in the UK and– and– and I think learning with you about like the different– the challenges that we face there with diff– like different access to kit and that kind of thing, changes or it– I think will inform and– and enrich the pedagogy that we– we– we sort of talk about around the world. Yeah Liz what about in the US or Minnesota specifically? Either one.

LIZ: 29:09

Yeah, similar to Leonida, I like think about how computer science starter, computer science pathways is– it was a high school course. It might be AP computer science principles, AP computer science A and the problem is, oh we don't have students joining the class. And it's like, well what do you expect? Like they don't know what computer science is. So a lot of work in Minnesota right now is the K-8 integrated standards. And what they're doing is with each revision of the academic standards in science, math, language arts, is they're adding in these computer science benchmarks as opportunities for teachers to integrate computer science. The big problem is, is there's no guidance, no curriculum, and no professional development, so many teachers, and they're open to interpretation too, so it's a little bit of a mess, and I hate to say that, I'm sorry, any Minnesotan that's listening, but it's like, figuring out like as the Raspberry Pi Foundation like, where do we fit in and how can we support, and I think integration in the US, is like, yes it's big in Minnesota, but like in conversations that I've had with educators in Georgia, like that's their approach in elementary as well, is how can we integrate computational thinking on these different topics and computer science into what teachers are already doing because like, time is an issue. I was talking to a friend who's a kindergarten teacher about this,

and I was like: 30:33

"You should really be like bringing computer science in."

And he was like: 30:36

"Liz, when?""We have to teach reading for two and a half hours, we have to have playtime, then we have to have a social studies block and math."

And I was like: 30:46

"Oh, dang, you're right. Where?" So I think the only way in like, the elementary space specifically is how can we meaningfully integrate computer science so that teachers are meeting standards in math and they're meeting standards in computer science? And we're in a weird spot too with the computer sci– the CSTA standards, which are like national standards that a lot of states like, reference for their own, are under revision right now. So creating curriculum when you know in 2026 there's going to be a whole new set of standards, kind of makes you like, oh, should we start yet or– so it's like a weird spot. But I think it's exciting as well, like I said earlier is, we kind of get to bring in teacher voices and student voices when we're creating curriculum for teachers and students, which I think is really unique and exciting.

JAMES: 31:36

I think it is exciting. I think the integration piece, I'm really looking forward to how we figure that out. And I think there's some research that our colleague Jane was talking about recently, and I've forgotten the name of it but it's about teaching multiple things at the same time, so teaching computing concepts whilst teaching maths and how you do that well, and that's going to be really exciting to apply some of that.

LEONIDA: 31:56

Yeah, and also maybe to add on, the integration also happens at the primary level. Computing is not independent. It's integrated in science. So also in primary school, that sense of time when do I do computing, when do I do science, so integration also has been a challenge also to the teachers at that level.

MAMTA: 32:13

So in India, the computer science education has been there for I think more than 20, 25 years now, but it was only for the senior schools, right. For grade 11 and 12, it was always part of the curriculum CBSE going as an elective, so students should– or used to opt for it and they used to learn C++ directly, compute like one of the computer programming languages, which was popular at that time. It's been a journey now and it's– it's going down to– to the lower levels also. But it picked up, it really got picked up when– when the introduction of MEP came in in 2020. People started talking about it, there was an EdTech boom bringing in their solutions to all of this coding and computational thinking and all of that, which– which again is a huge– so there is a huge gap in the population in India, like I would say, hardly 30% of the population who's privileged to one and– and gaining access to all sorts of resources and the computers in their schoo– own schools where it's like it starts from K– K to 12, they have access, they have computer labs and all that. And a computer science education is in their curriculum too, as again, as an act– activity. It's not one of the mainstream subject, but– but people are thinking of integrating that into their like– actually coming with solution of interdisciplinary projects where– where they use technology to solve problems in the science and maths and English and the presenting work through technology for other subjects also. That's where the 30% of the population is but– but for the rest of the 70% population, it's still a– it's hard to crack the game. I mean the senior officials have started talking about– about bringing this computing education into the mainstream thing. We are talking about it but we are still not there, where we first find solution to provide resources to this– this audience, which– which is a barrier, which is a challenge for anyone like us to do– provide solution because we– we say that we will give you the curriculum, the best curriculum in the world, research-informed curriculum with great pedagogy and all that, which will solve problems for your students. We will empower your teachers. We will do the capacity-building, we'll train your teachers but what is missing is still resources, the infrastructure. That's– that's where we're still lagging. Sorry Indians. That's the place we are, at the moment, and we really need to come together to find solutions to that, but we can't just stop at that, saying that that's– this is a challenge so what we are trying to do is we are localising our content that– that's there. Well, with RPF, we are introducing more of unplugged activities so that even in the absence of the computers to do the hands-on activities, we still are able to achieve those learning objectives to some extent. And– and slowly, gradually, when we say that we have got funds and in like two years from now, we will be able to provide resources that students will be able to go to the computer lab, they will be able to do– get their hands dirty, and they will be do– able to practise, they– they– like, they do the practicals also. But– but till that time, otherwise we– we will be– we will be behind the world. So that's why we can't just wait and stop and– and wait for things to fall in place from the government side and– and all of that thing. We will have to take a step and we are doing what we can– in– what– with what's in our hands we can do that.

JAMES: 35:58

I think there's an interesting kind of thing, both between specifically India and the US but– and I think to an extent, Kenya, and I wonder– I'm going to come to Rachel on this, I wonder how much has the fact that in the UK or in England specifically, we have a national curriculum helped move computing forward? Because that's not something that we necessarily have. We have very disparate state-based systems. So have a ponder on that question but also where are– where– where– where are we in the UK? What's the sort of– what's the– what is the UK sort of like?

RACHEL: 36:25

So it is so interesting listening to everyone talk because actually there's some similarities and you wouldn't expect maybe there to be the similarities between what's happening in India and what's happening in England, but, you know, we do have schools that have– that struggle to access the internet, ri– that don't have a reliable, stable internet connection. We do have schools that– we have a real lack of specialist teachers. Computer science is one of the hardest subjects to get specialist teachers so even though we have the infrastructure of a national curriculum that sits underneath it, we still are facing the problems that we're hearing around the room. You know, we're ten years in, 2024, ten years into the national curriculum being introduced for computing. We had a national curriculum before for IT, ICT, and it's still in schools I go into now called ICT in the curriculum even though it is a computing national curriculum. It's a divisive sor– topic. Have we covered the right things? Have we moved too far towards programming, AI isn't that explicitly included on it so are we moving quickly enough? Computing is such a challenging topic area to have a national curriculum for because the speed in which our education systems work do not match the speed in which technology advancements work. I know with our own curriculum resources, we're having to revise them faster than we maybe planned because of how quickly technology is moving. But where are we? We're having a curriculum review currently. We're contributing to that. We're excited about the possibility of where computing can go, and having a national curriculum that underpins it can bring us the– the benefits are being able to have banks of resources. We're working on the Oak contract to develop resources. We've got a whole computing curriculum available to all teachers, so that's– makes it easy. The problems that Mamta's talking about with not having a resource bank, we've got that for– for England mapped to a national curriculum standard. It makes it harder for integration because, you know, it's taught very explicitly as a separate subject, and I'm so excited to learn from the integration work that we're doing in the US, especially for our primary settings that face the same problems of curriculum time. You know, they've got to do everything. Where does computing fit in that? So I think there's a lot of lessons to learn there. But there's a whole area that we don't talk about in digital skills. Has that been forgotten in the move to a computer science, that computer science GCSE is not offered widely in schools? I think it's in about 80% of schools in England. Schools are struggling to offer it because of a lack of specialist teachers and the problem only gets worse as we go up to A level right? So we– that means that we have a– a majority of young people leaving school without any digital qualification, because of the move away from IT, which was offered more broadly. We're in an amazing position to be developing a– a digital qualification with Greater Manchester Combined Authority, the Raspberry Pi Applied Certificate, which I'm delighted to be working with James on and he's doing an incredible job on that. But that's not part of the national curriculum. And we need to– you know, we did a workshop this week with schools and– and employers, and they can't believe that young people are leaving school without digital skills. So, you know, we owe it to young people to make sure that everyone has fair access to learning those digital skills that will be needed in every job, not just technical jobs, and then we also need to make sure those that want to pursue jobs have fair and equitable access to it. So I'm hoping that the curriculum reform will lead to that as a national change. Delighted to be involved in that conversation and hope that it goes that way and hope that we can learn from the work that other countries are doing as well, to influence the curriculum we create for here.

JAMES: 40:20

I think that's one of the really exciting things is I think– look– like– so what we've said– like learning about integration, learning about sort of adapting and thinking about how we teach when there's no kit present so how we do more unplugged activities, and then I think the work we're doing on– in the– in the UK, where we have fairly, you know, compared– compared to lots of other places around the world, fairly high levels of digital literacy, how we– like the– the sort of work we're doing there to build that digital literacy capability so everybody has it will inform and– our work in other parts of the market, because I think those digital literacy skills, without them, learners can't engage with the wider content and so we have to make sure that they're first.

BEN: 40:56

Don't you think it's a really interesting place for us to be in though, because I think whilst you're right, Rachel, we haven't– we haven't fixed all the problems, we've had ten years of this and we've still got lots of problems, right. But equally we've also come on a massive journey since then. I've done an awful lot of learning. I mean, ten years ago, I don't think we were talking about the computer science pedagogy and how much do we know about that now? So I think we're in a good place that we recognise that things aren't perfect. We've– we're working towards working out what the error– issues are and how to address them, and now we've got that fantastic experience of everybody here in the room from different areas of the world. I think, we're in a good position really, although I think it's important that we always recognise that we haven't fixed any problems but– but, we– you know, I think we– like I say, I think we're in a quite unique position where we're– we're doing an awful lot of learning and now bringing upon the learning from international teams as well, it's an exciting place to be.

RACHEL: 41:43

Yeah, I don't mean to be a negative Nelly about it all. And– and to see classrooms, like genuinely, to walk into classrooms in England and see people teaching Python programming, that is a moment that I didn't think I'd see in my career, so to have come that far is brilliant. I just want fair, equitable access, everyone doing it and everyone to have the digital skills as well if that's not too much to ask. But, you know, we've got to have an– we've got to have a goal, we've got to have an aim, and we all are committed to driving towards that aim internationally. And it– I just find it fascinating that there's– there's similar problems, localised problems too but similar problems, different solutions to them maybe, but I feel so privileged to– to hear, listen, and work those out together, and I'm con– convinced that us coming together on this will mean that we have a better solution for all of those countries going forward.

JAMES: 42:39

Yeah. And I think while you say, Ben, there's lots of things we haven't solved, I think actually we can look at it– there's lots of– there's lots of still problems for us still to solve and I think it's quite an exciting kind of space to be in. Well I've really enjoyed that conversation today. It's been great to have so many different perspectives. So thank you to all of my fantastic guests who've joined me today for sharing their expertise. It's been wonderful. Let's wrap things up now I think and ask– I'm going to go around the table and ask, I think it's really nice to look back on the year that's been 2024 and look ahead, first of all. Leonida. What has been a highlight for you of 2024 and what are you looking forward to in our work next year in– in– in the coming year?

LEONIDA: 43:19

It's having the computing curriculum in Kenya. It is– it has been good and encouraging, especially as we get into the primary level. And what I'm looking over on 2025 is how we are fitting into this mess and also how AI is coming in on board, as there's so much that is coming in and there's so much changes that is happening. And I'm hopeful in how the curriculum will be really integrating, especially in the primary level in Kenya.

JAMES: 43:47

Great. And Liz, what about you.

LIZ: 43:48

Highlight of my 2024 is I've spent a lot of time connecting with teachers and students across Minnesota about like, what do they want to see next? So I'm excited to take their ideas and feedback and like, come up with something to help them as they're looking to expand computer science. So action, I think. JAMES: Wonderful. Wonderful. Rachel.

RACHEL: 44:09

2024, joining the Foundation, getting to work with all of these amazing people. Had a baby– should– well– New Year's Eve so does it count? And just seeing the comments and response to a curriculum reform, it feels like ten years on is the right time to start looking at how we move this forward so– and I'm excited to see what that does in 2025 as the findings come out from that. But also how we can advocate for what we want from what we're learning internationally. I want a truly collaborative approach to that, so being able to bring everyone's expertise in the room and our broader teams together to work on what that could look like.

JAMES: 44:47

Great. Mamta.

MAMTA: 44:49

Yeah, so 2024 for me was quite inspiring and– and satisfying, because of our presence in Telangana and Odisha and seeing those students making projects, solving problems, using the– using our RPF's curriculum, which was a great, great, great feeling, and 2025, I think more of that, making our presence in more states, finding opportunities for endorsements, if– if that's possible, like RPF's curriculum reaching out to even more students, maybe endorsing national curriculum. Endorsement is one of the key– key thing on our pipeline, for– for the years to come, like, very soon. So that's what I'm excited about. Yeah. Seeing more people, more young people getting hands on their digital making and computing and AI and– and getting it the right way is what– what we– we aspire for. 900

BEN: 45:56

My highlight this year is I had the privilege of going to the UNESCO conference for Digital Learning Week and what struck me whilst I was at the conference is that we're in this really interesting phase, we're at the start of this really exciting wave with AI education and the whole world is thinking about it at the same time and it's such an interesting place to be at the– you know, this– you know, the forefront of that– that journey that we're on, and everyone all thinking about the same kind of challenges and whilst we've talked today about everyone having their own local challenges, there are some similarities as well and people all wanting to get it right and that was– that was a really nice feeling I would say to be at that conference.

JAMES: 46:34

Great. And– and my– my reflection probably is I think that I– I really like learning from other people. So I– I really enjoyed the conference that you, myself and– and Liz were at– was great in– in the States in July because we just heard from so many educators, learnt from them, and I'm really looking forward to 2025, many more conversations like this, because I think we– we learn loads from each other and together. That's it for today's episode. Thank you for listening and if you have any feedback on our episode,

don't forget to give it at: 47:06

Thanks everyone. Bye!

RACHEL: 47:07

Bye. JAMES: Let's do a bye, I don't know.(laughter)(upbeat music)