Learning Science

A Look at the Future of Learning Tools with Kumar Garg


Kumar Garg is the Managing Director of Schmidt Futures, a venture facility for public benefit that recently cosponsored the Futures Forum on Learning Tools Competition with Citadel. Kumar joins our host, Mike Palmer, to talk about the winners of the tools competition that were recently announced and to provide his insights and perspectives on learning engineering as well as trends in educational technology and computational thinking.

Kumar begins by sharing his origin story which includes an eight-year run in the Obama administration heading up its efforts to grow and develop STEM education in the US. From there we explore the idea of learning engineering which combines insights in computer science, computational thinking, and big data with emerging insights in learning science to create scalable breakthrough innovations in education. Kumar walks through the structure and design of the competition and reflects on the benefits of connecting entrepreneurial innovation with academic research and scientific methods to unlock learning innovation at scale.

From there, we discuss Rising on Air and UPchieve as case studies of the types of programs that emerged from the competition before concluding with Kumar’s thoughts on the importance of R&D and infrastructure funding to drive the next generation of the learning ecosystem.

It’s an insightful and far-reaching conversation about the future of Ed Tech that you won’t want to miss.

If you’re enjoying what you’re hearing, subscribe to Trending in Education wherever you listen to your podcasts and check us out at TrendinginEducation.com.


Mike Palmer:  Welcome to Trending in Education. Mike Palmer here as always. Delighted today to be joined by Kumar Garg, who is the Managing Director of Schmidt Futures. He’s had an interesting journey which we’re going to hear about in a bit, but before we get to any of that. Kumar,  welcome to Trending in Education.

Kumar Garg, Schmidt Futures: Thank you so much. Thank you for having me. 

Mike Palmer: You’re an ideal guest in a lot of ways.  We’re trying to figure out where the future of learning is going. You’re someone who’s doing that for a living. And in fact, you’ve just fresh off of an interesting round of  

Kumar Garg, Schmidt Futures: The Futures Forum on Learning: Tools Competition, the shorthand way I think about it is what are the sets of technologies and tools that will help us help learners recover from the pandemic. 

Mike Palmer: Exactly. So the Futures Forum on Learning, and this was the Tools Competition. 

Kumar Garg, Schmidt Futures: Yes.

Mike Palmer: Excellent. So can you describe for our listeners, your origin story, what got you to this point  in your professional life? 

Kumar Garg, Schmidt Futures: Yeah, of course.  So  I’m an immigrant.  I was born in India and we left when I was eight. I did two years in Britain and then ended up in the suburbs of New York.  It was definitely one of those experiences where, it was public education that really helped me survive and thrive.

I still remember this middle school teacher took my mom aside and said, I think he’s Really bored in school and here’s all the things that are happening. And here’s what I recommend for what happened in that  had a big impact on which high school I went to and everything else.

 I’m a huge beneficiary of a system that works in our system that is really focused on everybody.  In college I studied political science and computer science. Our college was located right near the New Hampshire Primary. So that got me interested in politics. I ended up working on a Presidential race and have gotten interested in the world of policy. And the way that I first really started working on education was in graduate school there was a lawsuit being put together, suing the state of Connecticut for underfunding its school system. And  I was really interested by the case as to what was bringing it together.

There’s been a history of litigation to try to bring more educational opportunities, starting in both New Jersey and New York, and Connecticut has had some mystery history as well. Connecticut is a interesting state for having such a large number of school districts for a pretty small state that you actually get really wide education disparities.

So I spent a lot of that time actually driving around Connecticut interviewing Superintendents and parents and teachers, and that got me a front eye view of the school system. And then has an Obama got elected  as President and I was really eager to try to find some way to support and work with the new administration and  my political science and some of my computer science background came together.

And I was able to actually get a fellowship into government, into the White House Office of Science and Technology Policy. And in my fellowship obligation, I said, Oh, I’m gonna, I had a very specific project that I had outlined around working with the Department of Education on updating their data systems and everything else.

And I got to the job. And one of the things you learn in Government is  what people think the government works on versus when you actually get into the White House and what the government work done are just two wildly different things. Government is both wider in what it works on than people imagine, but it’s also deeper.

 There’s deep technical experts working on everything. And so my actual experience is by what I wrote in my fellowship was I got there just a few weeks before I started the president had given a big speech on the importance of putting science back in its rightful place, that scientific integrity issues and the previous administration.

And in that speech, the President actually talked about science and math education. This important way that we were going to rebuild the economy and nobody was actually working on what was STEM had not really taken off as a word, and so they said, Hey, you work in the science office. And we don’t really have anyone working on science education.

You’ve done some work in education before, at least make sure that we are talking to all the right people. 

Mike Palmer: That’s amazing. Yeah.  It’s happened to me a few times. The President in his speech talks about something and then couple of weeks later, I wind up having to do it  But no, I’m kidding. I’m kidding. That’s an extraordinary experience. And then  you had a nice run there where you were then on the hook for some  serious work. 

Kumar Garg, Schmidt Futures: Yeah, so  I stayed for  basically the full eight years. And, it’s definitely an experience where I learned on the job.  I went from knowing nothing about how government work to like gray beard.

You know, Usually people  in White House time usually do about two years. They’re tough enough job that you just a high burnout, but I paid for all eight. 

Mike Palmer:  And you age at a much accelerated rate. Although   our listeners are not seeing you right now, but it looks like you’be faring relatively well for  that length of run in a pretty high pressure role and also almost definitionally cutting edge.

 You were, in some ways tasked with a re-imagining of our educational system that is more science, technology, engineering and math forward . There’s a lot of thinking about the future of work and the skills gap in ways that, we talked about it a bunch on this podcast over the years, but having someone who really was in some ways defining this conversation for the U S through the 2010s into the teens. And then fast forwarding a bit, although there’s a lot to talk about in there. There’s also this Eric Schmidt fellow who has established what you’re working on today. Can you share a little more what that is? 

Kumar Garg, Schmidt Futures: Yeah, so I left in 2017 and started working with Eric.

And, Eric is the former CEO of Google. I started working with him on what became Schmidt Futures, which is an organization that focuses on science and technology for the public good. And one of the big program areas that we’ve built here is something that we call learning engineering.

And what it’s really focused on is how do we use what are the pretty rapid advances in computer science, computational tools, computational methods – things like machine learning and computational talent – all the computer science talent that’s happening.  How do we take all of that and have it drive advances in our understanding of human learning.  What allows kids to thrive in what settings, how do we take those small insights and make them into big insights and how do we do them repeatedly?

 If you follow the role of computer science and other fields,  across the sciences, it’s starting to have this pretty profound impact. Yes. There used to be this idea that Oh , the way we understand biology is we, study cells and we studied all these different sorts of organisms.

And then in the past 20 years, we have this whole field called computational biology where we say if we’re trying to actually figure out the path of a disease,  we could actually sequence a lot of genomes and say, the cancer seems to really spike at this part of the genome that doesn’t tell you the biological understanding of why that’s happening.

Totally different clue as to where you might go looking. And that’s like a data first. Clue finding exercise. Yeah. And that’s had a big impact. So now, you had just had a few months ago, this big breakthrough on protein folding using the portable using, this was like a problem that was considered unsolvable using these methods.

So the question is if you take those methods, you take that talent. How would you apply it to understandings of human learning? And the reason why I think this is  a really interesting topic is for a long time, what learning science has actually given us are really powerful mid-level theories for learning.

 A good mid-level theory for learning is spaced repetition, which is the idea that I teach you something, and then you should probably come back to it.

 Because  in two weeks, if I say to you, do you remember that thing? I taught you trying to recall it actually puts it more firmly back into your long term memory.

Mike Palmer: Shout out to Ebbinghaus ebbinghaus was onto something, the forgetting curve. 

Kumar Garg, Schmidt Futures: Yes. Okay, so this is a powerful idea. Now the question is  when should I come back? Because even if you understand, like lots of research shows that, space repetition matters.

Mike Palmer: Yeah. 

Kumar Garg, Schmidt Futures: Should I teach it to you that night for homework. Should I bring it up tomorrow  in school and back in two weeks, should I come back in two months just to double-check? 

Mike Palmer: Right. 

Kumar Garg, Schmidt Futures: And the thing is that if you actually add up spaced repetition, worked examples, all these different important learning theories, and you start to say which combination of them should I do you end up with trillions of possibilities. Because  the theories don’t tell you when to do them 

Mike Palmer: not to mention, how do you measure whether it’s working or not.. 

Kumar Garg, Schmidt Futures: For which student in what? And so there’s two ways you could think about  that problem you could say. We’re always going to live in the world of it depends. And, that’s why we have amazing educators and they’re going to figure it out. But I think, if you take one step further, just like we have physicians who are doing really important diagnostic work, when somebody walks in, but they also have this huge, R and D infrastructure.

There’s also just testing and taking those insights that physicians are having and saying. Is this a big insight as a small? How do these things apply? How these drugs combine with each other? How do these therapies combine with each other? So the idea behind learning engineering is how do we make sure that we actually providing teachers and parents and students, the tools? Those tools are actually  testing all these different ideas at scale. So you’re not just saying, here’s one small idea and now I’m just going to apply it to everybody.  And in education – this is really informed by my experience of when I worked in the administration. I think in education, we’re constantly chasing silver bullets.

 We have one insight that seems to work and  the study seems to have a real effect and we just get so excited. We’re like, we should not do this everywhere for everybody. But I think we should think about it with more humility. Like we don’t know, but actually what we should think about it is.

That insight, plus a hundred other insights happening all the time is how we’re actually going to make education better. But right now, the way we set up the system is each individual research study is really small. They’re expensive to set up. So you read a paper in the learning sciences and there’ll be on 40 kids, it’ll take two years to do, then they’ll have some results and then eventually there’ll be some analysis seven years later on 50 of those papers. And by that time education is really changed and then people will say those results from last decade, do we really know? And we’ll end up with just stronger mid-level theories. If you take  a company like Duolingo that’s teaching  how to learn a second language.

Mike Palmer: Yeah.  

Kumar Garg, Schmidt Futures: Duolingo is running a dozen experiments a day 

Mike Palmer: And  from what I hear. They got some pretty sweet space repetition in that app. 

Kumar Garg, Schmidt Futures: Yeah. Yeah. But the amazing thing about I read about there and I then asked them about space repetition.  They looked up the learning science literature on space repetition, and they said, Oh, there must be  a whole community that is like taking this literature and testing it out and all of these things. And they couldn’t find any active algorithm other than an algorithm from the eighties. From the early work that was done to take, it was  what they call the deck of cards approach. So it’s the algorithm is basically it’s like a deck, you have a card once you use the card to go somewhere else in the deck.

And the question is, how far out into the deck do you insert it? That was the algorithm. And then you just say, you’re just testing how often to repeat? 

Mike Palmer: Interesting. But  they’re taking a swing at it, so there’s some intentionality to the build that is based on the emerging science makes a ton of sense, but there is a sense that I’ve perceived over the years, that education is somehow outside of the more hard science approach.

And that’s where I think your recent challenge was structured in such a way that.

There many applicants, and then there were some winners. I’d love to hear you expand a little more on what just happened , some of the stories coming out of it. Cause it sounds like there was an interesting contest. And then I think there’s probably a lot to learn and lots to think about as we’re looking ahead.

Kumar Garg, Schmidt Futures: Yeah.  The idea behind the tools competition, we launched it last July and  the thesis behind it when we first put it together was, we were a few months into the pandemic. We had effectively gone from, Oh, maybe schools are closed for two weeks to they’re just closed. They were more than a billion kids around the world that were effectively out of school. It is rolled through the world. And I think it was just unclear when schools were going to reopen. It was unclear to what extent they were going to reopen. I’ll just say that my kids are still in virtual schools. 

Mike Palmer:  It’s still to some extent unclear. 

Kumar Garg, Schmidt Futures:  And I was very informed by a paper I had read about the  decade long experience of New Orleans, where they said that, what the storm did and the displacement, it didn’t affect the school system for just a year. It didn’t affect them for two years. They were actually feeling the effects of it for a decade.  So how long are we going to feel what’s happening now? So the idea was there was going to be an immense amount of potential impacts both on mental health wellbeing, but also on learning. 

Mike Palmer: Sure. 

Kumar Garg, Schmidt Futures: Because of access gaps, everything else. 

Mike Palmer: This is where even though it’s charged learning loss is the term that is frequently used to describe some of what we try to be asset-based but there is this awareness that. In terms of cognitive development milestones that would have been hit relative to other cohorts, like them, there is an impact that’s likely, already been felt.

And then how do we catch back up there? Lots of talk about in that context, but I think there’s certainly some awareness that there’s an opportunity to leverage new tools informed by this media strike experience, this transformation that we’ve gone through. And that was part of what the The Future Forum on Learning: Tools Competition was about. 

Kumar Garg, Schmidt Futures: Yes. And we put it together, we launched it, we did it with our co-founders at Citadel and it was meant to be a big experiment. The big thing, we kept it pretty wide, address pandemic learning loss.

We explicitly made a couple of design decisions. One, we wanted to be global. So the theory was that this is actually happening around the world and often, especially in the U S context, people only look to other examples in the U S but actually there’s a lot to learn around the world. One was to keep it global.

The second was to very explicitly think about the fact that you wanted both the biggest players to step up as well as new ideas. So we ran the competition with multiple levels. So if you are in a large platform, you are eligible  and you had a totally new idea that was eligible. We ran multiple tracks. 

And the third thing that we did was we took our learning engineering principles  which is, do you have an underlying architecture for running experiments, testing  what your hypotheses are and how to improve them? Do you actually have that architecture built out?

And this is very easy to say, but very hard to do. Which is most of the time, people are solution-oriented. So they say, I just want to get this going. I just want to get this tool going, the teacher tool going. I want to get this content out and you say how would you actually know if it’s working, right?

 How would you run an experiment to see how you would change it?  And that requires an underlying data infrastructure. How do you do experiments? Who are your research partners? 

Mike Palmer: Right. And that’s a classic example of where people choose to take on technical debt.  It’s  thought of as a cost associated with innovation and why spend a little extra on the instrumentation or slow down the process by adopting a more structured way of thinking about how we’re going to get out there so that we can continue to measure whether this works and whether this works at scale, you can see why people do cut, right? 

Kumar Garg, Schmidt Futures: Yeah. Yeah. And I think that the problem is that sometimes it’s very hard to catch back up, right? There’s never a moment where  you get to take your collective breath and the further and further it goes away from the way you’ve designed your engineering and your business policies. And so those were our three big design decisions, but we really were open on, are you focused on math or, language acquisition, or other sort of aspects. We kept it open.

What happened was we got way, way more interest than we expected. So we had almost 900 applications come in from  almost 55 countries, five continents, that sort of thing.  So that was, I think we were blown away by the response. The second was that, there was a lot of interest in the learning engineering thesis, but also a lot of help people needed. 

So one of the requirements for the competition was you had to have a research partner.  You had to be working with somebody who was giving you advice on how you would actually be testing the ideas on your product. You had to have that to be eligible and that, weird way ended up actually being very useful because people said, Oh I should go out and get a research partner.

You guys have some ideas. And then we started reaching out to lots of academics who work on lots of these topics. And we said, there’s actually hundreds of platforms that are trying to stand up and they’re looking for recheck partners. 

Mike Palmer:  Yeah. 

Kumar Garg, Schmidt Futures: These weren’t even folks who necessarily won. 

Mike Palmer: Right. 

Kumar Garg, Schmidt Futures: Out of the competition came hundreds of research partnerships on platforms that wanted to be eligible.

They said, this is a good reason we should be having a research partner. And whether they advanced actually to be a finalist or a winner. Actually having a research partner is quite useful. 

Mike Palmer: I could see how that in and of itself is a big win to tighten up the connection between the research community and new venture activities, startup activity, because  in some scenarios that they’re pretty close to one another,  at least in terms of mindset, the best research projects are running in a way that is entrepreneurial.

And the best entrepreneurial projects are probably grounded in some good fundamentals around being scientific about your approach. 

Kumar Garg, Schmidt Futures: Right? Yeah.  I think it takes effort to build in. But there are definitely value once you start to do it. 

Mike Palmer: Yeah. And you have examples. We have case studies which I’d love to hear some of the stories of some of the winners or the ones that got your wheels turning in terms of  how we might successfully bounce back and in some ways perhaps jump forward in new ways. 

So I’d love to hear some of your thoughts around, which stories are really resonating with you that may be useful for our listeners to think about if we’re trying to think about how we’re going to really power through this transition and ideally emerge in a better tomorrow. 

Kumar Garg, Schmidt Futures: Yeah.   We just announced this about a month and a half ago.  We ran through the year process, went through multiple rounds, judging, obviously it was virtual, but they got, the finance guy to pitch live. And so then we had 18 winners sort of nine that the mid and large-scale track and nine that are in the  catalyst track of new ideas and  what was exciting for me, just as some examples.

One was that it was a really expansive view of technology. Some of the ones like Rising On Air this is a platform that actually, in the pandemic there’s been a huge loss of connectivity in some parts of the world. So they actually used radio to put the content out.

And then the project that we supported through this competition is basically adding an SMS chat bot with Oh, you get the content through the radio and you can get  help and do exercises when you’re using your parents’ phone? 

Mike Palmer: Sure. 

Kumar Garg, Schmidt Futures:  Honestly, that works in very low connectivity environments, but  potentially a very powerful experiment others could adopt. So that’s on one end. On the other end  another one of the winners was this platform called Upchieve. And what they do is they build just in time tutoring. So they build a large network of tutors and they deploy them against this challenge.

You know, tutoring is obviously an area of immense interest coming out of the pandemic because we basically have grade bands that are going to be wildly off. 

Mike Palmer: Sure. 

Kumar Garg, Schmidt Futures:  Some students that actually did fine. Some students that did worse. You’re going to need lots of one-on-one support. 

Mike Palmer: Yeah. Even on the social, emotional side too, you would imagine kids might just need some dedicated attention to make up for  just the trauma that everybody’s been going through. Just having an adult who cares about what you’re working on in addition to your parents. Kids need more help, you know?

Kumar Garg, Schmidt Futures: Yeah. And the interesting thing about something like Upchieve is,  they’re both experimenting with new business models, like how to do this cheaper by using a broader mix of volunteers and in person. What I found interesting was they wanted to actually instrument it so you could actually track to see whether these different strategies of different amounts of dosing of tutoring drive outcomes.  Given that tutoring is potentially here to stay large thing that is going to last for the next five to 10 years.

We’re not going to come up with the answer of  what is the right amount of dosing  per subject for what student on day one, you have to build an architecture where we’re trying lots of this out and saying,  this is, I think what works. 

Mike Palmer: And also, I’ve been known to tutor a little in my day, Kumar. My dosage is extremely high, so not everyone is ready to take 45 minutes of direct instruction from The Franchise.  There is also the variability of the human powering the tutoring experience.  That I’ve always thought of that as a little bit more like match.com and in some ways it sounds like Upchieve maybe doing a little bit of that matching intelligence as well. 

Kumar Garg, Schmidt Futures: Yeah.  How do you validate for quality? You want to limit the risk of harm. So obviously there i s some cutoff, but I think then giving people both the opportunity to know where the better ones, but also upskill them. Maybe upskill the tutor and that might create opportunities as well. 

So those are on two different ends, but then  the nice thing was we saw interesting experiments in a range of different additional directions. So in another one was focused on space repetition. What are ways that teachers can use space repetition in a very constructive way? 

There was another project that was focused on giving teachers a tool for assessing the sound in their room. So basically it would give them a report that says, we listened for how much talk there was, and based on our sense,  these number of kids didn’t talk.

Mike Palmer: Yes.  

Kumar Garg, Schmidt Futures: It was meant to be a teacher tool. Based on our sense of the sound of the room, here’s some of the things we picked up around ways to increase conversational tempo and these parts of areas. Like, oh, which of the places where I should be pausing more?

Where are the places where I need to be including the set of students more? It gives them  a quick way to give like a quick report on the conversation they just had around here’s how interactive it was or here’s how we talk. And then they’re going to use the teacher input to then keep improving it.

Mike Palmer: Yeah, that’s fascinating.  I immediately think about how that could translate to a corporate setting where if you’re in a meeting, there’s plenty of them that I know we’re not optimized for information exchange and the betterment of the collective because there was one person was dominating conversation.

And the more we could get that kind of feedback to the teacher or the moderator or  the person responsible for the flow of the conversation, I could see how that could ultimately train us to be better conversing with one another. 

And have you noticed some new trends in this space? You are someone who is getting tremendous access to  global innovators around educational technology. Are there broader themes that are striking you in light of the pandemic that are New surprising, useful to think about?

Kumar Garg, Schmidt Futures: Yeah. I would cluster in a couple of areas.    One is I think there’s going to be a range of innovation on direct support.

Different types of tutoring models. And I think people have been interested in tutoring and the potential for tutoring for a long time, but I think there’s going to be an immense amount of need and basically everyone I talk to is experimenting with adding maybe potentially tutoring as a service on top of whatever they’re doing.

So I both think that’s interesting, but it also means that’s like incumbent on us to create  ways to have those folks talk to each other and learn.  I think that’s one. 

 A second one that I am personally very interested in. You see the inklings of it   I think there’s  a potential revolution coming in assessment . The reason why I think , it’s a quiet revolution is I think everyone is sick of assessment. Parents don’t like tests, teachers don’t like tests, kids don’t no one liked us. And in the pandemic, a lot of tests actually got canceled. They couldn’t administer them. And so they got put on hold, which meant that a lot of systems said, Oh, you don’t need a test.

Mike Palmer: Yep. 

Kumar Garg, Schmidt Futures: So the question is like, what are we going to come back to? Are we going to come back to none of it, some of it. And the reason why I think it’s interesting is, a lot of what has existed. Might not actually be serving the goals of what created in the first place. Are we actually measuring for how much a student is learning?

Are we measuring for their future academic potential? Are we measuring some of these other things? So what is that future that we want build towards? But the example I was give is  a company like Duolingo what’s actually made them into a flagship company that is growing quickly is that they’re actually eating the TOEFL, right?

There’s this big exam that if you’re international student and you want to come stay in the U S you have to take to show proficiency in English language. It’s a site-based exam, you have to physically take it. You have to pay a certain large fee, but universities accept it. 

What Duolingo did was they created the equivalent. It’s  digital.  You don’t have to take it in person . You don’t have to wait four months for the next time it’s offered. You can take it anytime. And it’s tied to their curriculum so they can practice. And now lots of universities accept it and so  the value chain of them creating that especially in a world in which all the traditional exams got canceled. It’s huge.  People think of it as a thing that I have on my phone, but a lot of the actual economic value is that they’ve actually taken an old, older assessment and totally refashioned it and captured a lot of the value.

And so my question is are there a number of future Duolingos hiding in plain sight in the assessment area where people have just not, move quickly enough and said, we can do this a lot faster, a lot cheaper,  we can actually tie it to outcomes in a really way. We can make it easier for you to actually get better at it.

 And it can fit into what you need. So  those are at east two that I think are really powerful.

The third one that I’m personally interested in is, is this pandemic going to change some of our expectations of what kids need to know?

And one that I’m personally interested in is the growing interest in data science.  Every conversation you’re going to have about the pandemic is are we on this kind of growth curve? And, actually being able to understand all the data ends up mattering a lot in being an effective citizen around this, but also understanding how to think about trend lines.

And so I just think that increasingly this is becoming an important skill in the economy. It’s still early days on how much it’s getting integrated into the K-12 level. I think more and more it is, and  who’s actually gonna have the breakthrough set of courses and other things to make sure that students 18 and under are actually getting to really push on data. I think it’s going to be a real open area. 

Mike Palmer: Yes. And is it integrated or is it treated as a separate domain?  That’s the other thing  that I think you’re hitting on talking about Schmidt Futures and what you’re working on is this intersection between computer science and teaching and great learning science. 

It reminds me of the old Steve Jobs challenge that the artists and the technologists are not different people. It does seem like there is a different vision for the humans who could ultimately be powering this learning revolution that we’re actually hopeful about.

Can you talk a little more about how to think about the skills and the profiles that will thrive in the emerging learning ecosystem ? 

Kumar Garg, Schmidt Futures: Yeah, so I don’t think this as a broad point for what every teacher needs to be, but I do think  one new job type that I think is poised to emerge , There’s many different ways you could frame it like a learning engineer or an educational data scientist. But there’s going to be a new category of jobs that are really built that sit at the intersection of strong computational methods.  Able to do the work computationally, trained up on the methods and be able think about it in large data systems. And you’re actually quite well versed in the domain challenges of education. What is learning science? How does it work? Instructional design, what does it mean to deliver?

And that you’re able to bring those two things together in a way that you can be both senior inside a company, senior inside an educational system, school district. And I’ll give you  one very basic example at the higher ed level. It’s like smart course recommender systems.

 You fill out your here’s the course that I want to take next semester.  The system that you fill in should say, we know that you want to graduate with this major things you have filled out get closer to graduating and actually just key course that is necessary for the majors only offered next semester and then not offerrd it again for two years.

You don’t put it in your calendar for next semester. You may not be on track to graduate. That is all known. 

Mike Palmer:  It’s a solvable problem. 

Kumar Garg, Schmidt Futures: Yeah. But you could have a smart recommender system that just says, Hey, by the way, we know some things about what your goals are. And so how do we take folks who are thinking about the computational methods of it, and then saying, how do we build that into the systems?

Mike Palmer: Connect that to the real problems that educators, instructional designers, learning professionals I like to say. How did they connect and how do we redefine  that field so that it’s a little more engineering powered where it makes sense, really interesting stuff.

 Amazing conversation. We’d love to go longer and deeper. Maybe we’ll have you back on in a future conversation. Before we wrap up, Kumar, anything else happening in this great big, wide, beautiful world around us that you think is  noteworthy? What’s capturing your imagination these days?

Kumar Garg, Schmidt Futures:  When I think about the national dialogue we’re having around infrastructure and what is it that we need to invest for America’s success in the future? We have to think about not leaving education out of it.  When we think about research and development, in the U S at least, it’s often framed around health. So things like the NIH. Or it’s framed around the Department of Defense, around military systems. 

But  it’s an accident of history that we left education out. And the fact that we spend one tenth of 1% of all education spending on R&D, and then we’re surprised that we’re on the same loop. We set ourselves up for this.

And so we actually have to invest in the research and development to develop the new ideas, the new processes. And so I just think that as were we thinking about investing in the infrastructure that fuels how are we going to solve the climate crisis? If we want the educational system to change, it’s not going to be by being like, run faster to everyone

who’s already running really fast and doing the hard work.  Invest in the bottom up so that we’re actually generating those ideas and then we can all collectively work to make those happen on behalf of our children. 

Mike Palmer: Awesome. Build them some hoverboards, some spacecrafts . Don’t just expect them to run faster. Let’s look at some tools. A really fascinating conversation. Kumar Garg is the Managing Director at Schmidt Futures. Really interesting stuff. Thanks so much for joining us, Kumar. 

Kumar Garg, Schmidt Futures: Thank you. 

Mike Palmer: And for our listeners, hopefully you enjoyed this. If you like what you hear, tell a friend, share the love.

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