Beyond the Tech Hubs: Scaling High-Impact STEM and AI Programs for Every Student

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Hi, this is Aurora from the Educating All Learners Alliance,
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and today we're speaking to Susanna Shimakian for a deep dive with the Foundation
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for Armenian Science and Technology.
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FAST is an innovative ecosystem dedicated to empowering scientists and entrepreneurs
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in Armenia and beyond to bring cutting-edge, globally competitive technological breakthroughs to life.
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And joining us today is Susanna Shimakian, the Executive Director of FAST,
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who brings over 15 years of experience in education management and international
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collaboration to her pivotal role, where she shapes programs that have impacted
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thousands of young people,
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educators, and researchers worldwide.
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First of all, a huge congratulations to FAST for being named one of the top
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two finalists at the 2026 ASU GSV Innovation Showcase.
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You brought your flagship Generation AI High School Project,
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which is all about advanced AI education to public high schools nationwide. So.
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I want to start with, you know, why AI? Why has FAST made this the cornerstone
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of its long-term vision for Armenia?
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Sure. Well, thank you, first of all. This has been a very proud moment for all
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of us because what we are doing in Armenia, we were doing in
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having in mind sort of the global challenges that kids from rural areas have
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in terms of accessing advanced education.
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And we, first of all, obviously wanted to solve this problem for Armenia,
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but also wanted to come up with something that would be replicable in other regions as well.
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And in a way, for us, this award is a recognition that this is something that
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is necessary globally, a recognized
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challenge globally, and something that could be done in other places.
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So getting this award in USA was a true remarkable moment for us.
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In terms of why we do AI, I mean, we started AI when it was less popular,
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because it was in 2017 when we still didn't have any of the generative AI tools
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and all the hype around it.
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But we did have the industry developing, the research developing,
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and a lot of things coming up.
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When the foundation was created, the idea was to help Armenia leapfrog basically
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in the space of innovation and technology. And as a small nation,
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you have to bet on a couple of things to be able to compete in the big global value chain.
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And when we were analyzing basically what are some of the verticals and industry
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fields where Armenia could compete as a small country,
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AI was one of those emerging fields where we assessed that the country can be
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competitive because we have really strong mathematical,
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legacy in the country and AI at the foundation is actually mathematics.
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So we could basically build on the mathematics. We also have a vibrant tech
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ecosystem in Armenia. So many of the big companies that you know.
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Like NVIDIA, Adobe, they have their offices in Armenia and their teams in Armenia.
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So for the last 15, 20 years, we have a lot of tech professionals in the country
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doing a lot of cutting-edge innovation, both in global companies, but also many startups.
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So there were building blocks for us to try to understand, can we create potential
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that would also help us create assets in the AI future, which we were already
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seeing sort of nine years ago.
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And this is why actually we started to focus on AI. And we actually started from the higher end.
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So we started from startups, from research teams, from PhD fellowship programs,
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and these types of things. And then only we cascaded down towards the school.
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Your mission talks about building an ecosystem that bridges education,
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research, and commercialization.
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So tell us more about FAST and how you balance global-scale innovations while
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also keeping your programs deeply rooted and relevant to the local community in Armenia.
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You know, the philosophy of what we do, again, going back to us being very small.
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We are very realistic that we cannot compete in volume of talent that we produce in-house.
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So we only can compete in quality of the talent.
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So we have to have enough, but very high-edge, senior-level engineers,
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founders, scientists, the ones
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that take longer to educate, but also are highly needed in the industry.
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Because we cannot compete with India, let's say, or even Eastern European countries
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or even Ireland because, again, we have the demographics that we have.
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So from the get-go, we knew that whatever we do and if we want Armenia to be
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relevant, it has to be deep tech, science tech, et cetera.
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And that can be produced only by people who have the depth of knowledge, which takes time.
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So that's why we actually, first of all, focused on the scientists,
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young researchers, aspiring entrepreneurs.
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But again, one of the things we realized is that at own system level,
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we don't have mechanisms of really identifying the talent, ensuring we give
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equitable opportunity to.
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People to get this advanced education and have a chance to become that top level
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engineer, AI professional, or whatever else in the high end technology.
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Because most of the good education, especially STEM education,
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is focused in private schools, in the capital city.
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So if we're talking about access to education, that is one of the patterns that
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we realize that it's just because not everyone has a chance in school to get enabled.
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That's why we don't have enough of them in the higher education.
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So that's when we started to think. And because we also work with all stakeholders,
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like anyone you can imagine, from government, again, to the NGO sector,
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to scientists, to research centers, to the tech ecosystem.
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As a result of this work, we realized that if we want really Armenia to become
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relevant, we have to do something at scale, something that can be forecastable,
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something that we can rely on.
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And when we speak to the industry or the international players,
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we can say, well, the country has committed to this type of system level change.
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Every year, we educate this amount of students with this depth,
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and we give a chance to X amount of people to become an AI innovator.
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And that is exactly why you should be present in Armenia or you should stay
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in Armenia, because that's also one of those questions, right?
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Why should companies stay in Armenia as well?
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It's a competitive market. Even if they are here, that doesn't mean that they will stay, right?
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So that's when we understood that we have to create something that can have
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the depth and the quality of a private school education, but at the same time
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could be put in a public school, which was a tricky, basically, problem to solve.
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But again, going back to the agility, and we see Armenia as a mini test bed
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for innovation when it comes to education, because we do have the culture of education.
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We have a lot of assets that are good for education, but we also have a lot
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of outdated school system, our educational system, etc.
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But the government and the civil society is really committed to make this transformation,
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which gives a very unique opportunity to experiment a little bit as well.
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And this is where we tried to bring in the entrepreneurial thinking into education program design.
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And that's how we basically created Generation AI.
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And the whole idea was, how can we make sure that we come up with some sort
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of a solution that will give a chance to any kid in any region,
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to have geographic access to really advanced math education,
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and then on top of that, obviously, AI education, and get a chance to get the
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foundational knowledge and the prerequisite knowledge for them to be able to
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come to higher education.
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And this is how we actually designed the Generation AI program.
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And that really resonates with me and probably with a lot of ELO listeners,
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the idea of accessibility and who gets access to what programs.
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It's easy to focus on some of the challenges out there, but what are some promising
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examples, some bright spots that you've seen through your work with Generation AI?
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Yeah, I think all of the spots are bright. Although like there are honestly
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like there are a lot of problems in terms of execution.
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I can describe that many of the systems which relate. And most of these problems,
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when we speak to our colleagues from China to USA, all of them relate to the problems.
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So I think one thing that unites people is the education and the learning and
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the behavioral challenges you have on the ground, because people are people
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and learning is learning. It's a very biological process.
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So I think behavioral pattern is very similar across nations and regions.
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But what I would say the brightest spot is when you truly have a very learner-centered
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approach, when you design a reform, it just has very high dividends.
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So usually what we see in terms of policymaking in the space of education,
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it's either highly political because obviously education relates to everyone.
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So that's why it's part of all the big political campaigns of presidents and governments, etc.
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Right. So oftentimes it's very political. And because it's political,
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it has to focus on short term surface wins, which never benefits the learner in the long run.
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And or because it has limited resources, oftentimes it's more focused on patching
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a problem rather than just solving the root cause.
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So in our case I would say what we have tried to do and this is why I mentioned
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we tried to be very entrepreneurial and use the opportunity like the,
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disadvantage of Armenia being small and having a lot of structural problems
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in education we tried to use it as an advantage which meant we could try to
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create something different from scratch and,
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And we really tried to put the learner journey in the center of it.
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We tried to design it from the learner perspective.
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And it's just remarkable what type of gratitude and motivation and conversion
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you see in the regions among the parents and the youth.
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The teachers, which we were thinking that would be the most resistant sort of
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stakeholder group because it's a lot of extra work.
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They don't really get much money incentive. They are the most underpaid and
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overworked people in any country and in Armenia inclusive. So there is so much
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teacher fatigue, demotivation, etc.
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We were thinking there is just no way we're going to bring this type of advanced
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curricula into regions without even sort of saying, oh, you're going to get 10 times more money.
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But it's remarkable to see what's happening because we have teachers who have
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been teaching for 20, 25 years mathematics in the same way.
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Now we have come and we told them, you know what, you have to teach it in a
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completely different way.
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But because of the way we work with the teachers and because of the way we work
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with the students, we see very motivated youth, which motivates the teacher
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because what a good educator wants is an engaged student.
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And once you sort of create an environment where the student can become engaged,
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because he or she sees that if they do well in this program,
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this will open up a gate that otherwise is closed for them, they get really excited.
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Excited they know this is a fair program it's merit-based it doesn't have any
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sort of other influences
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they know this is creating an opportunity they wouldn't have otherwise and it's
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also fun and engaging there's a lot of peer-to-peer learning there's a lot of new stuff full stuff ai,
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there is sort of the fomo that oh if you don't know ai right then something
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is wrong with you and here we are sort of teaching ai and quite completely this
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is a very rigorous curriculum this is not like AI literacy.
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They actually have to learn AP statistics and machine learning. It's pretty dense.
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But they are very, very motivated and this motivates the educators.
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And it creates an interesting pattern because then the educators go and do the
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marketing of the program themselves in the communities.
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They go and tell the middle school teachers, make sure your students apply to
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this program when they come to high school.
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And it sort of all happens naturally because they see the value of it.
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And the parents, even the parents who don't have any idea what a tech career is or what AI is, see
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the positive impact on kids and they really back the program even without really
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truly understanding what in the long run this will give.
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So I think that's the brightest thing that we see, the speed of conversion and
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the level of motivation among the stakeholders much, much higher than we ever
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anticipated in the beginning.
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We thought this will come maybe in 10 years, but now we're in the third year
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of the program and there's really a lot of excitement around it.
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And then maybe one more thing I would say that is very interesting is that.
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So because we do a lot of data analysis in terms of what their baseline knowledge
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and motivation is and then how it changes over the years, this is very important
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for us so that we understand that we truly have the impact that we hope to have.
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One of the interesting trends we see, and this is going back to what you're
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saying in terms of equity of education.
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We had an assumption that we will have a lot of bright kids who have the potential,
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but they were not lucky to get good education in middle school.
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And maybe they come with gap in math knowledge, or maybe they think that this
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is very complicated and there is no way they can do it because they are not
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an excellent student in mathematics, etc.
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So we we were hopeful that what we do would help the kids who really are not
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very good at math but have the mathematical thinking,
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and have the motivation would be able to close the knowledge gap
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and get a chance to sort of become part of this value chain and and we see very
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interesting trends we truly see a lot of kids who come with like c minus or d,
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but good algorithmic thinking and very high motivation.
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And within one year, they are able to transition into B minus,
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which is like in terms of knowledge change. It's a huge jump.
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It's a huge jump because the curriculum is rigorous. It both helps you close
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the gap and gain new knowledge in
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three subjects. That's like a lot for a teenager, but we do see it works.
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And this actually is the hopeful part for me because this means that even if
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we, let's say, lose a lot of kids in the middle school because they didn't get
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a chance to get good math education,
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it's still not too late to try to catch them on the high school level if we give them a chance.
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We are just about at the end of our time today. So before we go,
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how can folks listening, how can they stay involved, learn more,
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get connected with you and follow the work at FAST and with Generation AI?
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Well, I think the easiest way would be to connect over our website or social
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media. So it's going to be Fast.Foundation, pretty straightforward.
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And we are now happy to share the experience we have in terms of providing equitable
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access to advanced math and AI education.
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And also trying to now a little bit experiment what it takes also to have a
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bit of a ripple effect with the fact that we are creating in schools these advanced courses.
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How can we make sure that these communities actually spread out also the AI
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literacy within that same school community?
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Because now that you have experts, let's put it, teachers and
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students in the school, then you can easily do a lot of peer-to-peer learning
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and fun activities to do literacy training in the schools as well.
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So I would say this is where we would be happy also to see what the experience
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of others is and share our experience as well.
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So happy to connect with the audience and see how we can learn from each other,
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from the education design to career guidance and all of the things in between.
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Great. Thank you so much for joining us today. It's been great talking with you.
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Likewise. Thank you so much for having me. That's it for us today,
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folks. Thank you to Susanna. And to learn more, visit fast.foundation.
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If you enjoyed today's episode, don't forget to subscribe on your favorite podcast
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platform and follow us on social media.
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I'm Aurora from ILA, and this was a deep dive with the FAST Foundation.