Reviewing And Planning Your School's AI Approach: A Strategic Framework [Webinar Replay]

Good afternoon. So welcome to the session on reviewing and planning your school's AI approach. We're delighted to be joined by Educate Ventures and they're group of educationalists with decades of experience in AI and education set up by Rose Luckham. Some of you may know that name. They take a very evidence led approach to working and supporting governments, school groups, universities worldwide, and they've worked with the Department of Education in the uk Ministry of Education in Singapore and international school networks. Today they're going to share key insights and learnings from this noble, this global network. And then I'm here from Third Space Learning and we've been developing an AI tutor that Educate Ventures has actually evaluated and reviewed. So I'll share some practical advice and evidence of how schools have can implement a purpose driven AI strategy. Okay, so as I mentioned, I'm here from Third Space Learning so I just want to quickly introduce today's speakers. I'm Candida Crawford and I'm Chief Learning Officer at Third Space Learning. I was a teacher on the ground for 10 years and then I've been working at third space learning for 10 years delivering impactful tutoring to thousands of schools already. And then from Educate Ventures we've got Medea and Ibrahim. So Dr. Medea Khan is director of research. She has a PhD in self regulated learning and AI and brings extensive expertise in helping schools and governments adopt AI safely and effectively. And then we've got Ibrahim Bashir and he's the Technical Projects Manager. He's a data scientist and he focuses on designing and evaluating with practical frameworks. All right, so let me give you a quick overview of today's session. So we'll start off by grounding ourselves in the basics, what AI is and where we are right now with schools. And then we'll move on to how schools can begin to develop a strategic approach to with AI. And Educate Ventures will go through a 4D framework, so looking at government and ethics, technology, data, staff capability and evaluations of AI use cases. And then we'll share practical insights using the development of the AI math tutor as a case study and reflect on what this means for schools exploring AI today. Okay, so we'll wrap up with an AI toolkit where we can share this information. And if you've got any questions, please just type in in the chat and we'll, we've got, we're monitoring the chat so you can ask questions and we'll try to answer it. And then at the end we'll send the AI toolkit and the webinar recording and any answering any of those questions that come unanswered via email, and I'll send that to you at the end. So let me hand over to Ibrahim. Off you go.

Thank you so much. Candida. Hi everyone. Great to be here. Before we begin, usually we'd like to go over a definition of what AI is. We try never to do a talk about AI without saying what that is, just so we're all on the same page. So this is the definition of AI that we like to use. It's technology that analyzes its environment and acts with some autonomy to achieve goals. It's a somewhat broad definition, but the important point to note is that it covers more than just generative AI, which is tools like ChatGPT, but also things like machine learning, which has been around for a very, very long time and in some ways has always been around this. So an example we'd like to use is that of text to speech systems. So you talk or speak into your phone or computer, it analyzes your voice, converts into text. That's an example of a typical machine learning or AI system which isn't generative AI. So just to be clear, AI is more than just your ChatGPT, but there is then obviously generative AI, and that's what all the buzz is about. It's a subset of machine learning, and the technology on which it was based was actually developed in 2017, but it wasn't until 2022, with the launch of ChatGPT, that it really took off. And now you see it basically everywhere. And with the investments that companies and governments are making into AI, it's safe to say that it's here to stay in some shape or form. So yeah, with that it brings us a lot of opportunities. And particularly generative AI, it brings us a lot of opportunities, not just for our students, but for our educators as well. Some of those examples we've listed out here, we have adaptive personalized learning, automated marking and feedback, AI powered dashboards, which are particularly powerful for helping us to understand just how our students are learning and not just what they're producing. We can get content generated, as we've seen from tools like ChatGPT and Copilot. And in fact, one of these use cases, high impact personalized tutoring and the benefits it might have on learning outcomes is something that we'll discuss more in detail later when we look at our evaluation of third space learnings, AI Tutor Sky. At the same time, with these opportunities for educators, it presents us with a few challenges, not least the messaging that Our students receive about AI that is going to make their life easier. To some extent it is, but in some ways it's not. It's because that they have these sophisticated tools. They need to be actually more intelligent when using them. We've seen a lot of attention paid to academic integrity and cheating, but there's an awful lot of concern about safeguarding and protecting children's rights. Protecting their privacy from profiling, from fakes, from misplaced trust over reliance, becoming deskilled, protecting their agency. So what we really need to understand how to do that, protect them from all of these safeguarding concerns. And amongst educators, what we generally find is that people are increasingly aware of the technologies and are aware that there are risks, but unclear how to actually put their understanding into practice to help protect students, but also to enable students and colleagues to use these tools at the same time. And so we think the best way to go about this, our motto is learn fast, act more slowly, is that I think it's really important to understand what you want the AI to do for you. Rather than thinking about what AI tool am I going to use, it's what do you want it to achieve? And a great way of doing that is by taking a strategic approach. So one of the most common questions we hear is, how do we get started? How do we do this in a way that can demonstrate that we are supporting student learning? This strategy, the 4D AI strategy framework, is based on Professor Rose Luckin and her colleague work that her colleagues have done over the last 30 years that they've been working in AI and education in the center. We have your existing vision, and that vision is fundamental to what you do now. Just because you have AI, it doesn't necessarily mean you need to change that vision, but you need to look at that vision and see how AI might impact it. Mean, for example, that you can achieve it more quickly or for more people. Basically, what is it that you're trying to achieve as an organization? And then on this framework, there are four dimensions. Governance and ethics, iterative unit applications, technology and data and staff capability. And we're going to talk about each of them in turn. And they're all highly interconnected. And some of the most powerful uses of AI come when these connections are built between these dimensions. So we're going to start with the first one, which is governance and ethics. And despite our motto of learn fast, act more slowly, this is actually something, the one area that we believe people do need to act a bit more quickly. Yeah, the space of governance and ethics, especially in Getting a policy in place so that people in your organization, students, staff, colleagues, know what it is okay to do with AI and what they shouldn't be doing with AI. So they know what tools they should be using, they know what's expected. And such policies need to be updated regularly. One of the best ways to create them is collaboratively with a team of people, because more people who know that the policy exists, the better. And we've actually created a free guide that you can get. There's a QR code, but you'll also get it at the end of the session. We'll send out an email. It's not a policy, it's a guide to creating a policy. Because it's really important that you just don't take a policy off the shelf that you create one that works for you. Also, part A part of Governance and Ethics is about evaluating the risks of the AI tools that you use. And this means that once you've decided what kind of AI tools you're using, you understand the risks that are associated with it. One way to do that is actually by conducting a DPIA or a Data Protection Impact Assessment, which you actually have to conduct whenever you're using a tool where the data processing is likely to result in a high risk to the rights and freedoms of individuals. There is a checklist available on the ICO website, the Information Commissioner Office. But at the end of the session, you'll also receive a guided checklist that we produced that's more specific to AI and education use cases, and that can help you conduct that impact assessment of any AI tool that you might be using. Also, as an organization, we do risk assessments of some of the more popularly used tools out there. So. So, for example, this one we built for sky as part of the evaluation we were doing, we also did a risk assessment. It's something you can get from our website. We post all of these up there just to give teachers and educators an idea what the risks involved with these tools are and the mitigation strategies that they can use. We're not the only organization to be doing this. There's actually some other ones that are doing some really good work on these risk assessments. Common Sense Media, for example, they also have some really good. So the idea being that whenever you're using an AI tool, you look at all these things. You look at, do you have an AI policy for this? Have you conducted, or do you need to conduct a data production assessment and whether there are already risk assessments out there for that tool? And then finally, this will also Be available to you after the session. We work with an organization, Avalane, to produce their support. It's called from the Ground up, which is a framework to help you go about implementing AI in an ethical, thoughtful way. So it's all part of that governance and ethics. And you know, in this document you basically find out, laid out in very practical terms, 12 ethical principles, what they mean for you and how you can go about thinking about them. The questions you can ask yourself to try and make sure that you're doing AI. It's ethical. Finally, we're going to move on. Sorry. Next we're going to move on to technology and data. So machine learning is basically a perfect storm. What we have today is a perfect storm of three different ingredients, data, algorithms and processing power. And you need to have the right combination of those three ingredients if you want machine learning to work. And the reason where we are, where we are in 2025 with AI is because of a perfect storm of these three ingredients coming together. And so part of that, that data part is also, you know, like one of those ingredients that needs to go in there. So, you know, I'd encourage you all to think about these four dimensions on this slide. But in particular, I think the one that's most relevant to educators, the rest are mostly related to, you know, like, might be more related to your IT teams is the data plan, which is, do you have, do. Does your organization have a strategic plan for collecting and user data that's aligned to your vision? So again, we talked about evidence based, like checking whether the interventions that you're making or what you're doing, is it actually leading? Is it actually helping you achieve your vision? And that's why you need to have a strategic plan about the data that you're collecting to evidence or signal those learning outcomes. Next, I'm going to go about staff capability because again, if we want AI to achieve the purposes that we've set out to achieve. Excuse me, we need staff to understand, who understand how to use the technologies to make sure we're supporting our teachers to be equipped with the knowledge of what AI can and can't do and where its limitations might be. So we need to support teachers through the building of AI literacy to develop skills so that AI can be used effectively and with positive impact in teaching and learning. Very few countries right now clearly define expectations around AI literacy at the moment. So I'm actually going to use for this session on the UNESCO AI Competency Framework, which is available on this QR code. This was published in 2024, it's just worth taking a moment to look at the six key principles that they outline. So essentially, as we're approaching the idea around expectations of AI literacy and AI competency, this is all built around these six different principles, ensuring that you're bringing an inclusive digital future to the forefront. That we are adapting a human centered approach to AI that teaches rights and roles are protected, you know, even though they may be redefined, they're promoting trustworthy and environmentally sustainable AI within education that actually, you know, in, in which the AI can be applied is relevant and reflected across all different types of teachers, across different levels of teaching experience. And that we're ensuring that the use of AI and AI literacy accompanies. That accompanies. It is part of that lifelong professional learning that we have set up for teachers within our profession. So again, as part of again the 4D strategic framework, it's having the right policy, having the right data and then having your teachers having the right skill set to be able to do that for the next piece. Oh, sorry, yeah, one more thing. Again, something that teachers need to be aware of are these safe AI priorities. So they have that safeguarding piece for their students. So again, they need to be aware of. Again, this is also adopted for the UNESCO framework. They need to be aware from protecting children from misplaced trust, from inappropriate tools, from bias, lack of transparency, from fake news. A lot of these things that we talked about. So they have their agency, they don't become deskilled. An example of this how we will discuss in more detail later. I have an example of how we looked at sky when we evaluated it, how that maps to these safe AI priorities. So a tool, an AI tool that matches these would be, for example, tell students that it is an AI, it's not a human tutor. It would only collect the necessary data and only for as long as possible. Any kind of content that would be on it would be human authored, it would check for bias, it would be very content gated. So it wouldn't be able to get inappropriate content from elsewhere. The students would have some control over pacing and they would be able to ask AI for explanations or simplifications. So all of this are things to be aware of when you're evaluating an AI tool. Finally, for the last part, the iterative unit applications and purpose driven AI. Basically how you can apply these AI tools to teaching practice. For that I'll pass on to Dr. Medeha. Over to you.

Thanks very much, Ibrahim. Hopefully everybody can see my screen now. Thank you. Thank you for that. And as Ibrahim was saying. So We've been through three dimensions already for the 4D strategy framework. We looked at governance and ethics, technology and data and staff capability. The fourth dimension which is particularly important, particularly in collaboration with the other three, is iterative unit applications. And what that refers to is evaluating the use of AI on an ongoing, iterative basis. The reason it's important to do it iteratively in ongoing ways because the technology is changing very, very fast. Firstly, and secondly, because the impact of the AI will vary depending on the context within which you're applying it. So being aware of that is really important. And having those processes set up for that iterative evaluation to occur, again, really important. So one, one framework that we use to help ensure that any use of AI is purpose driven is the AHEAD framework. And the first pillar of the AHEAD framework is aligned with educational goals. So that goes back to what Ibrahim said right at the very beginning, which is that we need to be making sure the use of AI is school led rather than technology led. So you need to be thinking about what are your specific opportunities, what are your specific challenges, and based on that, how do you want to be using AI? Always put that first. Secondly, we need to be thinking about enhancing human intelligence. So the goal of AI is really to augment human intelligence, not to replace that. You should always be thinking about what is the impact of AI on critical skills such as critical thinking, metacognition, reflection, all of which are becoming increasingly important in this age that we are now in, where AI is prevalent, evidence based. So of course everything should be grounded in learning science research, evidence based practices. We do actually know quite a lot about learning design in this area, what works and what doesn't, and making sure that whatever AI tool you're using does align to that learning. Science research is incredibly important. Of course things should be personalized and adaptable to individual learners needs, abilities and contexts. And finally, it must be designed and used ethically. So where an AI tool is not being transparent about its functionalities, limitations and biases, that can be a cause for concern. There are, there's a plethora of AI tools out there. And so as we said, thinking through exactly, really how you want to be using them is important. Don't be led by the technology, rather be led by how you can be using it. I mean, here on this slide we have some examples of how you could be using them. So number one, teacher admin. So you might want to use it to generate content for yourself in lesson planning and enrichment, or you might want to use it for emails or report writing as part of administration. Those are both great, both great use cases. With lesson planning and content generation, we find that you can create lots of content for lots of different types of learners and differentiate in ways that wasn't possible before. So it's a fantastic use case. Within lesson delivery, you may, for example, decide that actually you want to get learners to practice specific topics through the use of AI tools that are out there and then really build upon that within class. So orchestrate your teaching around what's happening with the use of AI. And again, that's a very powerful use case. Student assessments. There's a lot of formative assessments out there and offering personalized rich assessments to every student is a real opportunity for AI. And one use case, which is often overlooked, but we think is quite interesting, is around teacher professional development. So you can be using AI to record yourself or your teachers within your classroom and really think about what are the areas for improvement. Get personal coaching and reflect on practices based on that. So if I keep moving on. So we talked again about that importance of evaluation. You might be thinking to yourself, well, how do I evaluate what the impact of AI is? There's no one answer to that. There's a range of ways that you can be evaluating the use of AI. One approach we sometimes use is called the logic model. And an example of the logic model is laid out here. There are different steps to the logic model. Um, the first, most important is to really think about what impact you're looking to have. If you work backwards, what is the impact you're looking to have and what is the reason for introducing this AI within the system and then to break that down into midterm outcomes, outputs, and then the activities, resources and input that are required to trial up that use of AI. Um, so for example, let's take the hypothetical example of an AI which is helping you to write essays and is supporting your students with essay writing. There the impact might be that you want your students to become more engaged, entertain more highly, reflect more deeply on essay writing. But shorter term outcomes might be, for example, around behavior in class. Outputs might be around the number of times that students are actually engaging with writing essays, while the activities and the resources and inputs are more around the materials that are provided both to your students and your teachers in relation to training on that use of AI. This is the template that can be quite handy when you're thinking about the purpose of AI. So who will benefit and how? What are the challenges? What are the steps needed to implement the AI? Successfully, what are the technical and cost implications of implementing AI? What are the ethical implications of AI and what are the staff training implications for implementing this AI effectively? So this is quite a handy template. I think it's going to be provided to you within your resource pack is quite useful when you're starting up with a new AI use case as a way of really structuring your thinking around it, thinking through the benefits and the challenges as well as some of the assumptions that you're making. So on that point of evaluations, as Candida mentioned at the beginning, we did an evaluation for Skype, the AI tutor, to see how it aligns with research based principles of effective tutoring and math instructions. It was an initial study based on the data that's been collected so far, but there were some promising initial outcomes. So at this point I'd like to hand over to Candida to say more about this.

All right, thank you. Thanks for that, Medea. Okay, so before we dive into the detail and share some practical insights, I just want to give you a feel about what we mean. I mean, we've been using this word, sky. Sky is our AI one to one maths tutor and I just want to show you it in action. While you're watching, it's just going to be a 10 second clip. While you're watching it, just notice how sky is guiding the learning, asking questions and getting the student to think and explain. And then we'll go into the detail after that.

It says that in a Library There are 40 books on the trolley and 470 books on the shelves. You need to work out how many books there are altogether. First of all, tell me the calculation you need to do here. 70 add 40 equals.

Well done.

You answered correctly. Why will more than one column change when you add 40 to 470? Because it's going to go higher and higher and higher and if it's minus, it'll go lower and lower and lower. Could you please explain a bit more about why more than one column changes when you add 40 to 470? I'm interested in how the numbers in each column change because it's a higher number. Think about what happens to the tens column when you add 4 tens to 7 tens. How does this affect the hundreds column? Because look for an example, there were seven.

Okay, that gives you a good sense. Let me go to the next page. So that gives you a sense of what the AI tutor is about. So now let's look at how we've applied purposeful AI design in practice. So the first step is always to ask what, what is the problem that we're trying to solve? And for us and for schools, it is this widening maths attainment gap. Today more students are falling behind than ever. I mean 27% of 11 year olds are failing government math tests, 33% of 16 year olds. So the problem is large and it's growing. And at the same time budgets are tightening, they're really shrinking. And schools are being left in a difficult position to ration their supports, really only choosing a subset of students. And at Third Space. We've been working at this challenge for over 10 years now. Schools already know and trust us as tutoring experts. And then this has positioned us well to scale math support through AI. So always with education and pedagogy first AI is our enabler, that's helping us widen access and reduce costs for schools. But at the core is good pedagogy. So how did we actually build an AI tutor that tackles this problem? We started off with what matters most. So a strong pedagogy at the foundation and from that everything else flows. Each lesson it's grounded in learning science and the lessons follow an I do, we do, you do approach. We have explicit instruction, modeling, independent practice, extension, so that learning science is really embedded at every lesson. Our content is authored by experts, by teachers, nothing is AI generated and our curriculum has been built with 10 years of data. So we focused really tightly on those fundamental high impact maths topics. And we've built them sequentially to build understanding. And then we've also really baked in this best teaching practices. So we know what good tutoring looks like and how it should be delivered. We know that it should be personalized, so it should adapt. We know that it needs to address misconceptions so students are speaking out loud. And from their verbal responses we able to dig a bit deeper to understand what misconception there is. It's not just answering a text, text box or a worksheet and then that give, that enables us to give real time feedback, which we know is also important to make learning gains. But we also underpin it with motivation strategies, growth, mindset and built in guardrails for safety. So pedagogy is important, but so is trust. So trust, safety, transparency and that it's teacher, teacher is in control. So let me give you a few examples of how we did this. All content is curriculum appropriate and age appropriate. So because it's created by teachers, there's no bias. A lot of the maths models are really parallel to what's happening in class. We know that, you know, keep on saying that teachers retain control, they decide which lessons to run, which pupil should take part, and then safeguarding concerns are automatically red flagged. They're escalated and reported to school staff. But we also flag other issues, disruptive behavior, disengagements, and that's also reported to schools. So transparency being really important. And then data protection is also super important. No pupils data is used to train the model and only authorized staff can schedule sessions. So really important things that we embedded right from the beginning. And so, okay, so we've got pedagogy is important, safety and transparency being embedded is important. But we also built SCI in close partnerships with schools. So every element was tested in real classrooms, not, not in isolation. So we could see how it performs in authentic contexts. So in the reality, the nitty gritty of school life, you know, things like background noise, lateness, behavior problems, or even at the time of day that these, these interventions are being deployed. We ran an extensive pilot program across a diverse set of schools. We did regular visits. We iteratively developed based on what was working well and where pupils maybe were struggling. And we've got a lot of data. So we continue to refine with this. And also to ensure that schools continue to trust the impact we've had external researchers validate this claim. Okay, and then another important aspect is understanding the implications for staff. So flexibility has been central to our design. AI should be supporting teachers, not adding to their very busy workload already. So one of SCI's greatest strengths is that it can adapt to each school's needs and schedules. Okay, as I mentioned, it's teacher led, so the teachers in control. But it can work with a single pupil, a group of pupils, or whole class. We offer now on demand support, so it can be used in lots of different ways. They can be used before sats, it can be used as an intervention consolidation or even as pre teaching. And added to this, all our lessons are tailored through diagnostic questions so pupils get what they need most without burdening teachers having to do that. Okay, so importantly, schools are noticing the differences and confirming how the solution is meeting their needs. So pupils, they say pupils are happier, more confident, they're significantly more, it's significantly more affordable and can reach more students. And so with unlimited access and the flexibility to use sky whenever they want, it's really, they're really seeing the benefits. Okay, so we've talked about how SKY was built, what, what matters and how it. But what, what actually really matters now is how it Performs in real classrooms. So we've asked to educate, to evaluate it so we can share independent evidence of its impact. And Ibrahim's going to share that with you. So I will hand over to him.

Yes, Hope you can see my screen. And I am not on mute. So. So yeah, basically, like Medhi has said, we were asked to conduct an independent evaluation in sky. And we started doing that by looking at what the research evidence is actually saying about high impact tuning, whether it is effective at all. And we did find that actually the emerging evidence base points to the impact of the. The use of high impact tutoring to improve learning outcomes as long as it's aligned with established, with the principles of. Of learning design. With established principles of learning design. When we evaluated sky, we found out that, you know, their evaluation indicated that these learning design principles have been carefully integrated into Sky. And you know, like just went over some of these. For example, one of those is the scaffolded structure, the I do, we do, you do, and the emphasis on the step based learning and the immediate targeted feedback that students receive. When we were doing this evaluation, we looked at a number of things. So besides the research base, we also looked at data that the tool had been collecting from students. We interviewed several teachers and we also did a small student survey to see how students were using Sky. From the data that we collected from the tool itself, we found that from the sessions that we measured, we found that students actually demonstrated an increase in confidence when learning math using SCY. So, for example, 77% of the students reported an increase in confidence and only 15% after the lesson reported that they were less confident about their learning. When for the same student, we measured this confidence over time. So whether they were going, you know, where their confidence was increasing over time over multiple lessons, almost 66% showed an increase in confidence. Only 8.5% showed actually that the confidence decreased. Also with the tool, what it does is you have at the start a check in questions which check your knowledge about the topic. And then based on that, it kind of personalizes learning. And then at the end of it, there's a checkout question, the diagnostic question that checks how well you learned the topic. So we found that on average students would only get 34% of the check in questions. Right? But at the checkout questions, when they were asked to do that, on average they got 92% of those questions answered correctly. Additionally, and most interesting for us, we found that there are two learner groups who benefit as particular beneficiaries. You know, like emerges particular beneficiaries for this program. And those were anxious or quite pupils or pupils who usually hesitate to ask for help in class. Sky provided them with a non judgmental way to ask questions. So you know, if they had something that they were confused about, they could ask sky freely without, you know, feeling that they would be judged for not understanding something. And the second group were the students requiring immediate consolidation. So maybe you know, who were just below the expected standards and they really benefited from that targeted adaptive practice that teachers assigned to them. Finally, you can see here on this slide some of the results from this student survey. Also from the teachers. What we found when we interviewed them was for them, the biggest benefit was that SC I offers consistent availability so it's available at any time and that it's personalized depending on how well the student understands the topic and when they used it. For their students, especially those that were slightly below standard, it was very effective in improving their performance. At the same time, there are some things that remain areas of improvement. Especially there is that tech adoption curve. But there were some concerns about sky being able to hear the students properly. So a lot of schools, what we found, what they did was just creating like, you know, quiet places where students could talk to sky or having high quality headsets. But as long as that is accounted for, generally the output has been good. Yeah. And overall, I would say, you know, like as part of our evaluation, we found good signals, early indications that this kind of high impact, voice based, interactive, personalized tutoring can have beneficial outcomes, learning outcomes for students. So yeah, that was basically just an overview of our evaluation. I'll pass it back to Candida to wrap up the session.

Off mute. There we go. Okay, great. So thank you, Sky. I think sky is a result of really purposeful design and lots of work. And I hope that that's given you a practical view of how you could evaluate and then implement AI in your schools. Here are a bunch of links. An AI toolkit that you can, you can scan the QR code, but we will follow this up with an email. We'll share the slides and also this recording and hopefully you found that helpful. So a huge thank you to educate Ventures for sharing their expertise. And thank you to all of you for joining us.

I also see a bunch of questions in the chat and I see we have a few minutes remaining, so maybe we can take some time to answer questions. Yeah, yeah, yeah, I'm just gonna go on the ones I can see on my screen right now. So there was that question. Sorry, I might not do it in the right order about. So the question was from Mr. McCant. I'm not sure. I can't see the whole name. My school trust allows us to use AI and I has an AI code of conduct and guidelines. However, we have a very limited amount of tools allowed. As an example, we allowed to use Gemini, but not chatgpt. Is there a reason you can think of that this would be the case? Is it less secure? So that's a very good question. Usually what we found in our experience is that schools are already a part of a, an ecosystem. So they might be using Google Classroom, they might be a Microsoft school, and generally that is the number one consideration when they decide to go for one tool over another. Usually these companies, you know, Gemini, Google in this case might offer you a kind of protected, you know, space for you to use that AI tool without your data going to any third party or without it being used for training the model itself. So in that way it might be a bit more secure, but really the same offerings are there from other companies, from Microsoft, from OpenAI as well. Ultimately, it's mostly about what ecosystem that school is already integrated in. I will also say that despite this, about what tools are allowed or not, we often find that students and teachers often use tools outside of, you know, on their, in their personal capacity as well. So there's definitely. That's a lot of that happening. I don't know if that. I hope that helps answer some of your question.

Maybe I can grab one of these. Ask can it be used for multilingual learners? And is there a translation element at the moment? Not. Which is really exciting. We've built our AI tutor because LLMs are not that great at math. So we make sure that the maths is excellent and the pedagogy is sound. But what it's very good at is language. And so we, we are going to be experimenting with turning on certain languages and then we'll be able to respond in, in a different language back, which is quite exciting. And then also another question from Juliana, which is what the duration of an AI lesson is. So it's 30, 30 minutes long. We, we can, we, we had it longer, but we find that 30 minutes is our sweet spot at the moment. And then there were questions of how do you make sure that you. That the AI is an effective way of teaching? And I hope that we've been able to answer that as we've gone through because we've baked in all of these effective practices into how the AI delivers the session. And we also Create all the content that needs to be delivered and then it adapts in real time. Ibrahim, is there, I think there was one here about is it training available? Training?

Yes, maybe. Mediha, you want to take that one? The question was are there any training courses for staff to do so that they can learn how to use AI systems or is it just a matter of trial and error for staff who want to use AI? I'm aware that it depends on what your input is, is how well AI does the task or answer the question. If they're training, does it train you in how to set out your question instructions to get the best possible results?

Yeah, and I think what we'd say is that there absolutely is training that you can use. And I. But I think the point we'd make is that training for staff can absolutely first include literacy. So capabilities, limitations of AI. There's prompt engineering, which is I think what you're referring to there, you know, so how do you engineer your, your cue or your instruction to the AI appropriately to get the best possible result? And there is that type of prompt engineering training that that is provided fairly often. We at EVR also recommend going a little bit further and thinking about pedagogical training in relation to AI as well. So what shifts do teachers have to make in terms of their own practice to make the most effective use of AI? And that can be, that can really result in going from just using AI as tool to use it in a much more of an augmented intelligence kind of way, which is, which is really important. The other question that I've just seen in the chat, and I've lost it now, but I think the question was around policies and how do you develop a policy local authority that might be already providing some level of input there. And I think, especially if you look at the Getting started with Policy guide with the QR code that we provided earlier, you'll see that policies, when we talk about policy, we're almost talking about your approach towards AI. And while there will be some things that the local authority will dictate, there's a lot of other things which the school is likely to have flexibility over, such as the parameters around the use of AI, specific ethical considerations, and there's also a lot of thinking to do around how do you link all of that to the practical tools that you're giving your teachers in the classroom so they can actually use the policy in their practice, both to use AI safely but also to get the most out of the AI? So I hope that helps. I'm not sure if there are other questions.

There is another one I'd like to grab. So we've got from John McCullen, McCullough, McMullen. He's wanting to know how the AI works with send pupils, especially pupils with communication difficulties. And then he was highlighting how with some of his students are looking at the video, his students may not have been able to verbalize some, some of those answers. And I think this is also where the kind of magic happens because sky, there's a voice, voice to text, so there's a transcription element and that is amazingly accurate and really can pick up a, pick up a lot. It's not, it doesn't struggle to understand accents or different voice tones and it really can understand the gist of what the pupil is trying to say. So it's not expecting this like verbatim perfect answer. And because we are a voice one to one tutor, we really do want to encourage them verbalizing their thinking and even if they can't do it properly and, and, and, and we will move through different levels of scaffolding and if they don't, if it doesn't quite get to verbalizing it properly, then sky will model that correct verbiage using mathematical terminology and move on. So it's, it doesn't hinder them, it more really helps them along the way. And then there's. With SENS students, there's a wide variety with amounts of data and understanding that we're getting from these sessions. The personalization is going to just get better and better and better as we look at how we can personalize with certain send children. Do we think we should stop here?

Yeah, I think we're on time.

Yeah. Why don't we then pick up any of these other messages via email. Hopefully you find that helpful and have a lovely day.

Bye everyone.