Embedding Computational Thinking Through Schooling

Welcome to the future of Education. I'm Michael Horne. Looking forward to today's conversation with someone I've known in the education space for many years now, Amber Oliver, who leads Robinhood's Learning and Tech Fund. The Learning and Tech Fund is one that I've gotten to work with. So full disclosure, as an advisor for many years and was involved in the early stages of the fund, thinking about what it would look like and what it would work on and so forth. And so I'm going to bring the Amber up to the virtual stage, if you will. And first, Amber, it is good to see you. I don't get to see you that often anymore because, you know, Covid and stuff. We don't travel to New York City as much as I used to, but it is good to see you. How are you?

I'm good. I'm so glad to be here, Michael, and so glad to see you. Yeah.

No, so we. And for everyone watching, by the way, put your questions in the comments box and whatever platform you're tuning in into, I will do my best to pull them in and ask Amber if we have time. But I'm excited about this because, Amber, you and I get to have a handful of conversations every year where you bring new ideas and are always stewing on new realizations and insights that you've gleaned from your work. Funding a really terrifically interesting set of innovative initiatives, which we'll get to in a moment. But for people who don't know you, just quickly, what's the background on you in education and how you came to be interested in. In leading this fund in the first place?

Yeah, thanks for that. So for the past, like 20 so years, I've been really thinking about how we can leverage technology to put kids in the driver's seat of their own learning. So ranging from doing it in schools, out of schools, domestically, internationally, and throughout it all, we've seen that there's so many different elements that need to be brought together. Really, if we could find a way to make the whole system work together, that we could get much further along. So my career sort of followed that path where I did this work at the United Nations, I did it domestically, starting up a nonprofit. Then I started, then we spun it out into a for profit. And then coming here into philanthropy. And throughout it all, it was really the question that I kept asking is like, how can we leverage those different, those different actors, those different forms of funding and partnerships in order to move things a little further along? And when I. So when I moved from globaloria, which was teaching kids how to code and design their own educational games with the idea that we needed to make kids be producers and creators. One of the big things that we saw was that teachers actually didn't know how to prepare and support students to do that work. And so when I left Global Ori, I went to look for a place where we could potentially shift the way teachers were trained before they came into the classrooms that we weren't then requiring them to spend hundreds of hours once they became teachers, learning how to do that. And the Learning and Technology Fund, which was all about how do we tap into the potential of technology to advance learning for kids, especially low income kids, seemed like the perfect place to do that. And five years in now, that's been a big part of the work that we've been able to do is to change how teachers are trained before they get in the classroom. And then of course, obviously hoping to give them the support once they're there too.

Cool. So I want to get into a couple things that you just teased there as we go through, but let's start maybe high level for people who aren't as familiar with the Learning and Tech Fund at Robinhood. You know, the original thesis, I guess, that I had some role in shaping and how you quickly actualized it and made it real as opposed to this sort of airy fairy thing in my head. And then what you've learned, maybe more importantly through that, that investment work, sort of the theses that you've proved or disproved as you've done the work over the last, I guess you're maybe seven years in now at this point and talk about that.

Yeah, thanks. So I think you're being humble, Michael. You were very much the architect of the thesis. So a little bit about the fund. The fund is a co created fund, so in some ways it's an innovation in its own right. It is three, three philanthropies came together, Robin Hood in New York City, the Overdeck Family foundation and Siegel Family Endowment to think about how we can tap into this opportunity that technology might bring. And the idea behind it was that it was intended to be catalytic. So it was supposed to be launching new ideas and innovations that had the potential to be really transformational. And so as we thought about how we were going to do that, we thought about really providing capital that was going to be patient and flexible and that would provide organizations at the time they needed to learn, ensure, buy in, and then, and then see whether or not it worked in collaboration with Schools and broader stakeholders. The other thing that we really, I think, is unique to the fund is that we bring a real ecosystem, ecosystem mindset, and that is because we are New York City focused. So the Robin Hood foundation exclusively focuses on the five boroughs in New York City and how we can leverage education as a poverty fighting tool to move households sustainably and measurably out of poverty. What that means is that we really know New York City well. And so we could bring together, sort of do something we call teaming, where we bring together different actors that might not work together effectively or might not have worked together before to see how they can work effectively, to be complementary to one another, so that we can move the field faster together and ultimately create an ecosystem in New York City around this idea of leveraging technology and support of kids. So that's big and broad. We focus specifically on two areas, which are computational thinking. So teaching kids how to ask questions and solve problems using computers, we do that across the K5 curriculum. So it's very much an integrated approach. And then the second one is something that we've been coining, blended literacy, or that you coined, actually blended literacy, which is really this idea that could we bring together two highly promising practices which were high quality curriculum and content rich curriculum and personalized learning. So that's a lot of jargon. It really just means curriculum that is, that is coherent, that is standards aligned, that is rigorous, and then strategies that enable that curriculum experience to be personalized and differentiated to the individual needs, context, interests of each student.

And so from those two areas, then, as you've made investments, can you give us ideas of what those investments have looked like, some of the maybe most exciting ones that you've, that you've made? I am sure all investments are created equal, but I'm sure you have a few favorites that you love to talk about and sort of what you've learned through that journey. Because obviously that was a hypothesis that computational thinking and blended literacy, which you described well, would, Would produce some really important gains in students, would, in the case of computational thinking, you know, allow us to think of measurement very differently of like what we were interested in students learning to do. Right. And how it pervaded across the curriculum. So I'm curious, some of those early investments, some of the ones that have been most promising as you made the fund, and what, what you feel like you've really proved or disproved in terms of the thesis.

Yeah, I might, I might start one other thing that I would add, which is that we're super excited about these, but we also were pretty clear that they were going to be really hard to do, which is part of what made them interesting to us. So, on the blended literacy side, early on we realized that by bringing these two strategies hadn't come together previously, not because nobody thought it was a good idea, but actually when you bring them together, you do some violence to each. So high quality instructional materials tend to think that it's really better if kids are all doing the same thing at the same time because it means that they can have whole class discussions that would happen in English class or can then be have another at bat in science class or social studies class. When everybody's doing something at a different time, it actually does a rub to that idea. Right. And similarly for personalized learning, it means that you need to be able to have kids do things at different pace, but also that they're choosing different, different, different elements that they want to focus on, which is then very difficult for teachers, teachers who might not be that comfortable with technology. And by the way, it wasn't embedded in the curriculum initially, the computational thinking side, frankly, nobody knew what computational thinking was and teachers didn't know how to do it. So it wasn't like we could just say, oh, well, you know, let's just bring this into the elementary school space. There was all this work that needed to be done in advance.

So, yeah, I actually think those are just to interrupt you for a second and highlight. I think that's right. Like on both counts. Right. A lot of energy around computational thinking, but the way people were translating it at the time was really coding and coding for high school with an eye toward, you know, frankly, the workforce in a very sort of narrow view of what computational thinking is and could be. And then on the blended literacy side, I think you summarize the debates quite well. And frankly, I think a lot of people still in sort of the core knowledge camp, where some of these ideas and research for the importance of a coherent, rigorous educational, you know, content, not just in English class, but across the curriculum. Some of this evidence has come from. In many cases, I think they still push back against the personalized notion of it on the ground and sort of what I would call the reality that you might push back against it. But students just. The reality is they have very different background experiences. And so if you think you can somehow throw the same content to them at the same time, you're not going to get the even results that you would hope for.

Yeah. In fact, when we started this work, I think what you're bringing up is something that we found to be a truth the time, which was that these were two different camps. They were communities that didn't communicate very often, and there were real tensions between them. And so we started out by trying to sort of convince each of the value of the other. And we ended up going on a different route, which was that instead of trying to do a paradigm shift, we instead talked about what I think you just raised, Michael, which was like this was happening in schools anyway. Teachers were being asked to use technology every day as part of their classroom teaching experience. And so if the high quality instructional materials weren't optimizing for that, teachers were just going to be customizing it and changing how they were teaching without guidance from the curriculum users. And on the flip side, there was even more now than then, but there was a growth in the use of those materials nationally. There's been a real push recently for coherent curriculum. And so if the personalized learning movement didn't think about how it would exist within that context, they were also going to be having a situation where teachers were trying to figure this out on their own all the time. And the real value proposition was that each of these programs needed to show gains for kids. And when kids, when teachers were changing the practice in their classroom, like one by one by one, they ran the risk of there being lack of fidelity that could then have implications for the research, efficacy research that was on there programs. And so we came at it from a much more practical perspective. And when we started to do that, we had a lot more traction in who was willing to partner with us.

That's interesting. So let's talk about some of those partnerships on both sides of the ledger that you did. And probably gets to speak to one of the things that you were excited about doing, which is helping to train teachers before they even entered the classroom in the first place.

Yeah. All right, well, thanks for that. Throw that tea up there. Yeah. So our grant to the City University of New York is, I think, is one of the ones that we were particularly excited about. So that is a grant two and a half years ago, actually the board, including you, Michael, gave us the green light to see if we couldn't influence systems to change how teachers were being trained. If we could, instead of building a new program, if we could change their standard Masters of Arts of teaching and the pre service training with college students, also to come in and see if they could just change the curriculum to introduce computational thinking into how the training was done. So it wasn't a new I'll say CT for short. It wasn't a new CT program. It was more just that every teacher that was coming in to be trained to be in the teacher to be in the classroom, would know how to use computational thinking as part of their practice. So we went out to the City University of New York. Now there are 500,000 students in the City University of New York, CUNY. Okay. It's enormous. There are 25 colleges, 15 of them have Colleges of Ed. Wow. And they are training nearly 5,000 teachers every year, pre service and in service teachers every year. Now, cuny, plus some of the other institutions in New York City actually are responsible for training nearly 16% of the country's teachers. So while we were just focused on New York City, we were showing that things ideally could happen at scale, which is a big deal if we could get CUNY on board. So we gave them initially a small grant over two years to work with two schools, Hunter and Queens, to see if they could see how to rejigger their, to rejigger their programs for training these teachers. And what they found was that it wasn't just about the curriculum, but it was actually the biggest challenge was how they were going to change the practices of the, the faculty. So they got a few faculty on board, they partnered with, we had them, we funded them to partner with Michigan State University that was doing this in elementary school space. And two and a half years in, they changed the way they're training their faculty. They were able to change the curriculum. And the governance of a number of the institutions shifted to ensure that CT would always be part of the training. And this past summer, 400 teachers, aspiring teachers, were trained in computational thinking practices. 50 faculty member across nine of the colleges. And as a result of that, actually the New York City Department of Education contributed $11 million to expand the program to all 15 colleges of ed. And there's been another $6 million in private investment so that this can be something that happens for every single one of those aspiring teachers and in service teachers that go through the CUNY system. We think that that has the potential to also then show other states, given how large this is, what they might be able to do. And so our ambitions are big. Every single teacher in New York City and ideally every single teacher in the country.

It's interesting on that one just to stay on it for a second, which is obviously the scale and the breadth is huge. But there's a couple key things you said, which is that every single teacher, so I'm an English teacher, that Presumably. Right. Or I'm different subject matters. I'm learning about computational thinking and how to put it into practice. And all these faculty are going to start becoming aware of and presumably researching it as well to start building a field around it. And again, it's not just like the computer science educators or something like that, it's much broader than that. And I think a lot of people would like to see, you know, teacher colleges not just change around computational thinking, but a whole host of things as the practice of teaching has evolved so much in the last 10, 20 years and you know, from education technology to new research and so forth about how kids learn. So I'm just interested in how widespread that is and feel like it's. It's worth maybe pulling that out is that this is really. When we're talking about computational thinking, this isn't sort of like a one off separated class. You're really talking about infusing this in a pretty significant way across all of education, if I'm reading you correctly.

Yeah, I mean this was really an equity agenda for us. When you have computer science as a standalone. We found, and we've been doing this for the past 20 years, we found that ultimately the kids who self select in tend to be the more highly resourced kids. They also tend to be primarily boys and not children from underrepresented minorities. And so we needed to find a way to better fill our pipeline if we wanted kids to engage in and more broadly STEM education. So it had to be something that happened as part of everyone's learning from an equity agenda. The other piece is from a learning perspective, like none of us use computers just for computer sake. Right. It's very much an applied science. And so if we can figure out how we're going to use it because it helps us better understand. Like an example we have is we have a fifth grade class that is looking at trends, trying to disaggregate what happened in agriculture during the Mayan period. So they can see that as corn crops shifted, it actually had a direct impact on the demographic patterns of the Mayan civilization. That kind of data science work needs you to have a computational thinking approach and helps you better understand history. So now we have kids learning how to just use every tool in the toolbox to answer big questions that they couldn't do in another way. I mean, oftentimes I use the example of art like I built when I was trying to understand Roman history. I was asked to build the Coliseum out of sugar cubes. Right. That was my history teacher Using an art tool in order for me to better understand something. When the calculator became part of our learning, we shifted the kinds of math questions we asked because we had so much more power. We can look at data and numbers and patterns in a way that we couldn't do without a computer. And it's the people who know how to do that who are ultimately going to be control of the knowledge and information, and that's where it becomes the equity piece. So we're not saying that we shouldn't have standalone computer science classes the same way we shouldn't have. We're not saying we shouldn't have standalone art classes. It's only that everyone should be computationally fluent or computationally literate. And some of us will go on to be software engineers, and the rest of us will go on probably to have to figure out how to understand data in order to use it for whatever it is that we're trying to solve for, or use all the tools at our disposal to make the cases we need to make in the world that we want to live in.

I'm intrigued on a lot of fronts, frankly, as I normally am when I talk to you, but one of them is there seems to be overlap. Right. If I'm hearing right, between computational thinking being embedded across the curriculum to build in these muscles, to use these skills over and over again in different fields and figure out how to use data and things of that nature. Right. And. But also, you know, from the blended literacy comments and how, you know, reading one's reading, quote unquote skill after you've learned how to read, is often about a broad set of knowledge across lots of different areas. There seems to be overlap then, perhaps from these two areas. So I'm curious, as you've gone into your next fund, you know, raised more money to continue this work, sort of big conclusions, future directions. Do these dovetail? How are you thinking about these different strands now?

Yeah. So the first five years of the fund, these two strands were entirely separate. And that was intentional because there were so many unknowns. Every time we threw something new into the mix, it just sort of overwhelmed. So we had to figure out what they were. Now, in the past year, five of our partners have started to explore what a pilot might look like of them coming together. And the reason why is a few. One is that schools are starting to do them together organically. We didn't actually see that. It's just that we now are in 177 schools in New York City. That's elementary schools. I'M sorry, that's still just, you know, a small portion of the almost 800 elementary schools in New York City. But still, it's enough that they're, like, bumping into each other. So going back to that. That sort of pragmatic approach of, like, well, if schools are doing it, we need to figure out how to do it in a way that's coherent and doesn't cause more chaos. So we're starting to figure that out. But we also found that there was a connective tissue that we hadn't anticipated. When students are taught how to use computational thinking practices and skills, it turns out that they actually develop. And, I'm sorry, gonna get a little wonky here, but they develop skills and knowledge, too. We haven't made it all the way across. If they do computational thinking, they'll necessarily do better on their state tests and literacy and math. But there's a piece in the middle where they really do learn how to think about thinking. The literacy community has been looking for how to do that explicitly for a number of years. So when we were able to bring to our literacy partners that computational thinking could be a repeatable, replicable strategy to develop metacognitive skills in students, all of a sudden there was, like, a real interest in seeing how they could come together, because you actually have to teach metacognitive skills explicitly. They don't just get learned by osmosis. So we have a bunch of partners now that are coming together to say, what would it mean to integrate a computational thinking practice into a literacy curriculum or into a teacher training around literacy that could actually. That we could see what happens in schools. So that'll happen this spring and is going to be a big part where. One big part of how the fund is coming together. I'll pause there before we move.

No, I think it's fascinating. I want to just stay with it for a moment. Which is what. When you say you have partners that are doing this, and so you'll presumably fund them to push further into this, into these marriages of these areas, what sort of partners are you funding to do this sort of work, and where should we keep our eye on.

Yeah. So the theory of action that the fund took on a while ago was that for blended literacy, we're going to actually invest in curriculum and. And also in aligned professional learning. So all of our partners on the blended literacy side are either curriculum players like El Education or common Lit. And then on the professional learning side, those are ones who have decided to anchor their training in a curriculum which is A very small part of the segment, but that may be groups of like Teaching Lab. Teaching Matters has been moving into that space. So those who are willing to make that connection on the computational thinking side, we were doing, as I mentioned, the pre service training, also in service training and some curriculum work. So what we ended up doing is bringing together partners like Cornell tech has a K12, has K12 work around bringing computational thinking in the classroom. And they developed both the curriculum and a teacher coaching guide they're working with. They're working with Teaching Lab to figure out if they can't because they had anchored their work around Engage New York. Sorry, these are so many references that might not be meaningful to the community. Engage in New York is an open curriculum that is in New York City, originally built off of Yale Education and Core Knowledge. But since they're doing that Teaching Lab trains on Engaged New York and Yale Education, we wanted to see if they could see how literally their tasks could be integrated in how Teaching Lab is doing their training with teachers. And so they're going to start in a small way. We also have Common lit, which is a hugely exciting curriculum that was digitally native, that is building out to be 312. It just launched the full curriculum for 6, 8 this last June. And they're working with the New York hall of Science to see if they can take their specific tasks and weave them into the kind of literacy instruction that kids are doing online. 20 million kids are going to be doing online over the next couple of years. So it's that kind of work. We really are interested in what it looks like in practice. We're trying to avoid the risk of building something in a perfect petri dish inside and then bringing it out to the world and not understanding if it really meets the needs and desires of the users that it is supposed to be catering to.

That's incredible, Amber. I'm just also thinking about the importance of importance of that metacognition skill. And I think you will, over time probably see the translation to the state tests even just because if I know how I learn and I can intentionally shape that, certainly it's going to have great impact on lifelong learning. But if it transfers into these other domains as well, it stands to reason that I'll use these strategies personally to your original reason to get into this field of driving, you know, students driving their own learning. Right. So I think there's a lot of richness here, as we have alluded to a few things. And I want to get into it because I think it's a really interesting topic. You talked a lot about coherence in the classroom. Coherence of curriculum, coherence of practice. Not having these two strategies sort of be yet two more things we layer on to schools and make teachers lives even harder than they already are because they're plenty hard as it is, but creating more coherence. You've obviously been on the side of, you know, an organization seeking grant funding. You know how we love to complain about foundations who aren't responsive or don't get us or you know, try to, or too bureaucratic, whatever it might be. How do you think about a more coherent funding landscape, maybe just in general. Right. Which I think would help people on the ground who are seeking funding, but also maybe create a more coherent education change strategy, if you will, or theory of change across the ecosystem.

Yeah, I mean, this is something that I've been thinking about a lot recently, which is, is there previous attempts at bringing together all the different funding sources, government philanthropy, early stage private funding, late stage private funding, have really struggled because they've, they've come at it from the idea that we have to all agree on the way in which we want to fund. And I'm starting to wonder, this is a question to the community, if there's a way for us instead to celebrate our comparative advantages, comparative positions of each of our funding. So, for example, philanthropic funding is particularly patient, but it can also be particularly high risk because we don't need the return on investment. Whereas some of our, if you look at the venture capital community, they come in and they're the experts in high growth and sort of inpatient funding and also can be pretty high risk. Right now our partners, like Common lit, for example, has gotten to a point where they. It's not really the philanthropic funding. I mean, they still need it for R and D, but they also need complementary funding from groups that we don't tend to syndicate with that could help them on that high growth phase that they're headed in next. I'd be interested in seeing if we can figure out a relay system that made it easier for both for profits and nonprofits that had found that intersection of return on education and return on investment to take advantage of the full suite of funding that was available to them. Because my fear is that because we don't do that efficiently now, that a lot of really good ideas don't persist because they can't access the types of funding that would be particularly well positioned for the needs that they have at that moment. We have these valleys of death. The funding that all the sectors have, and yet we're not working together to solve them for the things that we think have the greatest potential. So I'm not sure how to get there. There are a lot of friction. We don't have infrastructure to do that or the instruments to do that well. But I feel like we're maybe at a moment now, frankly, we didn't talk about COVID today, but our sector has been revolutionized by Covid. The whole world went online for the past, you know, for year and a half to learn. It's a different world when you think about EdTech. I've said this to you before, but my.

No, but say it. I think this is an important point. Yeah.

My prediction is that we won't be saying EdTech very soon. The same way we don't say work tech. That it will just be education and everybody will understand that technology has a place to play in, that it isn't the only everything, but it isn't the nothing, and it'll just be part of the way we think about teaching and learning.

Yeah, I think that's an important point also. And maybe just one more riff between us on that, because I think before COVID hit, we were both observing some backlash against educational technology. Now it's sort of almost ubiquitous. There probably will be some pushback. Some people who want to retrench to what was. But to your point, I think if you look at the bigger arc of history, like, we don't sit there and say, like, oh, that's like the Socrates people over there who learn at the feet of the master. And then there's all of us with the textbook. You know, that's education. Textbook learning or something like that. And then there's ed tech. Learning would be this new category. Like, that's just education and learning, regardless of the tools and technologies we use. And in point of fact, like I like to say, Montessori schools have plenty of technology that's just not digital in nature. They're the manipulatives and so forth. Right. And I do think you may. I think you may be on to something that in the next decade will just sort of start to take these tools that have been thrust in some cases on schools as sort of just. That's how kids learn. I'm curious what you're seeing on the ground.

Yeah, I think one of the. There are a few things that came out of COVID that I think are going to be helpful in that one is we really addressed some of the infrastructure challenges New York city. We distributed 300,000 computers. We started to think about how to improve Wi Fi to remove digital access challenges. I mean, that was just getting in the way. Every single teacher became an early adopter, whether they liked it or not. So what that means. And families were brought to the table in a way that they hadn't been able. They were given a seat that hadn't been given before. So now we have tons of stakeholders that weren't able to contribute in the past right. To this conversation and have an idea that technology is really good for some things and less good for others. And I think if we can get everybody on board on what they're good for, then we can start to see some real uptick in the places where it should be and frankly move away from where it, from where it shouldn't, which I think is the key to having it be really part of the way we're all going to teach and learn. Right. We were in a place where we were like technology should be everything. And I think that that was where we lost some people along the way. We also were a very small group. As the, as the table as we can set the table for more seats, we'll just, you know, we'll have a bigger dinner party.

I love it. I love it. And it's a seat I would love to have at that dinner party. But Amber, thank you for joining us in the future of education. Really appreciate it. I'll certainly stay tuned to your work. But for those who want to follow, where can they learn more about what Robinhood and the Learning and Tech Fund are doing?

Well, please visit robinhood.org you can find out more about Robinhood but also learning in Tech Fund. And for me, you can always reach out at oliverobinhood. Org.

Perfect. Thank you so much for joining us. For those watching, tuning in, if you liked what you heard, and I certainly did, give it a thumbs up. Allows more people to find great content like this. And with that, we'll see you next time. Thanks so much.

Thank you.