Building Workforce Readiness Through Real Startup Experience

[Music] Welcome to Changing Higher Ed, a podcast dedicated to helping higher education leaders improve their institutions. With your host Dr. Drum McNaughton, CEO of The Change Leader, a consultancy that helps higher ed leaders holistically transform their institutions. Learn more at ChangingHierEd.com. And now here's your host, Drum McNaughton. Thank you, David. My guest today is Chris Crittenden, founder of Sandbox. A university for credit startup incubator now offered at eight universities. Sandbox provides cross-disciplinary experiential education to students. The premise is this. Students work collaboratively to build actual companies that can receive funding from venture capitalists and become viable commercial entities. But that isn't all that the program does. It's graduates. If they don't go on to build their companies, are more hierarchical because they have far deeper experience than someone with an internship. To wit, Sandbox companies are valued at more than 200 million and alums make significantly higher starting salaries. From selling a startup to Walmart to leading the Entrepreneur Center at BYU and now building Sandbox, Chris has the experience and vision to change the way universities prepare students to enter the field of technology. And he joins me today to talk about these things and how Sandbox students really excel. Chris, welcome to the program. That's great to be here. Thanks, Drum. Good to have you on the program as well. You've been doing some incredible things with entrepreneurship and teaching in a new way different from the sage on the stage and you've been doing it with multiple higher institutions. Before we get into it, please give us a little bit of your background. Yeah, so I started, I think very traditionally, I went to a consulting firm. I was at McKinsey and did some normal stuff there. But one part of it was spent doing education, which is a nice tide of what I was doing later. I was doing education work with at the time, the Obama administration, the Gates Foundation. But after that, I left and started a tech company. So it was a decade ago over that now. And we were doing like an AI version of Pinterest. This is way before people were talking about AI at all, at least in the mainstream, obviously in certain realms, they're up to talking about a lot. But did that ended up selling that company to a Walmart, bought another company after that, grew that a bunch. And then about eight years ago, said I really want to get back into education. It's always been a passion of mine. I wanted to think about how we could do it differently. And so I went to my alma mater, which is a very young university, and said, hey, if I come and I'm willing to work for free, can I come and just try some things, try some new ways of learning. I had some connections there as well, so that wasn't just some guy off the street. And they said, yes, we started experimenting and that eventually led to sandbox and all that we're doing across all the other universities. And I love that when I get to speak to somebody with a non-traditional background, mine is about as without going into details, because listeners have heard it before. Mine's very non-traditional. Everything from flying airplanes and spying on people for living, to working as a adjunct, to consulting business, et cetera, and working for BCG, with a subcontractor, et cetera. Of course, you don't know BCG being from McKenzie. I worked for them as well, actually. I interned for them before I reached McKenzie. Good for you. Good for you. Now sandbox. Sandbox is really interesting. Tell us about it, please. It's an experiential learning program, but I think what's really, really unique about it is that it's a very, very real life opportunity for students to start a tech company while they're still in school, getting a ton of credit to do it. So in sandbox, students get 18 credits spread across two semesters. So all the schools are out on a semester system, so they're getting nine credits and fall on the nine credits in spring. All of that program, all those 18 credits are treated as one, basically, giant class, where all they do is launch a tech company. They work on interdisciplinary teams, so it's a big cross-campus collaboration, so between computer science, math, design, and business, or typically a lot of the typical partners. There are students all come together into one cohort, and they get all these credits in the last tech companies, and they've been really successful. So we've had 18 of them so far get venture back, the combined valuation of those companies is now $205 million. Wow. And those that don't get a lot better jobs, and that was the original thesis, and that was one of the things I wanted to explore when I went back to BYU was, how do we really take experiential learning to the next level? Every university is doing some form of it, project-based learning, case studies, sometimes simulations, what I really wanted to do is, how do I say, let's make your experiential learning real, like really, really, really real, where they're doing something that's not just a project, but something that's going to actually go out and exist in the world. And so a start-up is that, right? And what is proven to us is that when you do that, students learn way more. And so we've had the great start-up outcomes from it, but we have found that everyone else gets better jobs, right? Our grads tend to be the most in-demand young tech hires and the ecosystems that we're in, because they have this phenomenal experience of going all the way from zero to one launching a company. And I think, as we're going to probably talk about today, I think there's a lot of principles here that apply to how you really do experiential learning well, regardless of the exact context that you're in. Our context just happens to be startups. Well, this is fascinating for me. Having started companies before my own consulting firm, and then working as a advisor to other startup companies back many, many years ago. In fact, more years ago than I wish to remember, but that's okay. What you're doing, I think, is a new way, especially with the workforce development initiatives that are going on right now. What you're doing, it's a new way of teaching tech and business entrepreneurship, and you're turning the sage on the stage on its head. Yeah, well, I think what I would add is I wouldn't even, I mean, yes, it is entrepreneurship, but again, the way I really think about this is what we're teaching, we're preparing kids for jobs and tech and business and tech, right? Entrepreneurship is just the ground in which we're doing it, right? The process of creation, launching something, those all are relevant if you go work for a company too. I think that's one of the big things that we've maybe done differently. We don't just think about this as entrepreneurship. We think about this as the best learning ground to become an engineer, to become a designer, to become a business student. So, sorry, that doesn't matter. So, with that, you're taking the students are basically from concept up to potentially funding in a year, 18 credits, a year, that's highly accelerated for a startup company. What you're doing is making this real, more experiential. You made it use as we were preparing for this, you said something to me that really stuck is the experiential learning that we're doing nowadays is too shallow that students need to go deeper. Yeah, and I think that was like the first insight is that I think about a typical student in a day, they're taking, I don't know, four or five classes at a time during a semester, right? It just splits their attention between so many things, right? And naturally, they can only get so deep as a result. And so, one of the big learning shifts we made was to say, rather than having students in five different classes that are all disjointed to a degree, we're going to put them in three classes and treat it like one, right? And that allows students to now go way, way, way deeper, right? So, our students will spend a minimum of 25 hours a week building their companies, but the best students are spending 40, 50, 60 hours a week. And so, that just pushes them to a much, a much different level of depth than they typically get in school. And that's where we found a lot of the big learning gains are way, way, way down, right? You only get so much on it shallow, right? The other piece of this though is that a lot of experiential learning doesn't really engage their hearts, right? It's something they're assigned to do. So, they do it, they get it done, they get their grade. What we've done is we said, we want them to actually care so much about this that they push themselves into situations that they wouldn't otherwise do. So, for example, you know, a typical class project, right? Even if it's a really great, well designed one. The team starts to have friction. Maybe one person is not carrying the load, right? Every student's experiences. You're on team of three, one student just never shows up, doesn't do anything, the other two are doing all the heavy lifting. The project is going to end though in two weeks. The students strike like, I don't want to deal with like the drama of all of this. And so, I'm just going to push through, I'm going to be super annoyed, I'm going to complain to all my roommates, but I'm just going to push through and get this done with. That doesn't happen in sandbox, right? Because these students are thinking about this company for the long term. They're thinking, I want to build this company for the next 10 years. And so, now when they're having conflict with their teammates, there's not an option to ignore this. So, they now have to go and maybe for the first time in their lives, give really hard feedback to appear or work really hard through team conflict because they can't get aligned on a vision. There's not an option just to say, hey, this doesn't really matter that much. I'll just get the grade and do what I need to do. And so, I think that's a big part of experiential. If you really want to unlock the power, you have to get their hearts into it. You have to get them to actually care so that, yeah, so that they'll push themselves into all of these hard arenas. And that again, that comes with depth, right? For this, what year, and we're going to get into how you got into this for just a moment, but you raised a question with me, what year? freshmen soft more junior senior, are they doing this? I would guess junior. - Yeah, junior or senior? So, I mean, in our particular context, this is because it's startups. We like them to be either a junior or a senior. Seniors are nice because if their startup goes really well, they can just continue and not have to worry about school. If you're a junior and your startup goes well, often you're faced with this challenge of like, well, how do I go, you know, investors not gonna give me money and let me stay in school. But on the flip side, if you're a junior and it doesn't go well, you now have all this amazing experience that you can leverage to go out and get great jobs, right? So yeah, junior or senior? - Yeah, well, frankly, I would think that, you know, not everybody is a Bill Gates and can just leave Harvard or whatever the school is to do that. You know, my mind goes back to Michael Dell and, you know, I know he started Dell computer when he was still at UT. - Yep. Getting started, you had this idea, you went to BYU, tell us about the process that you went through to get this thing off the ground and, you know, and what you did. - Yeah, I mean, it's a longer story, but I mean, I think the short answer is we didn't start with this, right? There were all these pieces that I was curious about, right? I was curious about, you know, some of the learning methodologies, so I actually just started with classes, like a single class that was focused on specific elements that eventually became sandbox, right? But after we worked through that, had a bunch of the building blocks kind of proven out of the kind of the learning approach. Yeah, I basically said, okay, now to really do this right, again, if it's gonna be real experiential learning, well, in the real world, it's interdisciplinary. You're never on a team of just engineers or just business students or just designers in tech, right? You're always on an interdisciplinary team. - Especially with the startup. - Especially with the startup, yeah. So I said, somehow we've got to get all of these departments who almost never talked to each other. In fact, many didn't even know each other, right? To come together behind a unified program, right? And so, yeah, I just, I went out across campus with my, you know, pitch deck, you know, into the design program first and pitched them on why this would be a great partner, or a great partnership that I went to the CS program, did the same, went to the math program, did the same, and eventually got them to come together. Now we did some interesting things to make it work, which I think could be useful as people start to think about, and especially interdisciplinary collaboration. But yeah, how about you, die back in? - Well, when we talked before, you said there were three keys, and you're about to talk about the first one, is this learning being interdisciplinary and how you brought together the department chairs? - Yeah, yeah. So the department chairs coming together, obviously like you've got to de-risk things, right? So what we really did is we said, "Hey, we don't want to go through a really complicated curriculum review process." So instead of what we did, we said, "Let's look at your existing curriculum. Let's identify courses that are already approved that meet the learning outcomes that this program will have." In our case, it's fairly easy, 'cause a lot of these programs already had capstone programs that obviously the learning outcomes of their capstone programs were very similar to what we were proposing doing. And then they had these other, often they have electives or special topics or independent study courses that they could stand up. And so we're actually able to really quickly carve out enough credits from each of the majors that allowed it to come together fairly quickly for each of the departments, right? Everyone who's been through a curriculum review process knows how long it can take. And we didn't want to go through that for something that we wanted to experiment with, right? And so for this first year, we just used the existing courses and created special sections and other ad codes and it came together really, really quickly, right? It just, it really took the political will just of the department to decide, yeah, it's worth a shot. - And then the second key, you said, "It's the students have to have the time and credits to do something meaningful." - That's right. And so that's, again, that's related to the first, but we said, "Hey, this won't work if students are only getting three credits for this." You just can't do something like start to come. A real company. Now you can, sure, you can go out and do some business model canvases and whatever else and do some exploration, ideation, but if you're gonna start a real company, it's gonna take you 50 hours a week, right? And so if you want students to have that level of engagement, you've got to give them enough credit so that they can not be distracted by other things. And so yeah, so we didn't know the magic number was gonna be, but we pushed for as much as we could get and that kind of was maxed out at nine credits a semester. - So, and then the last one is assessment. All any academic knows, student learning outcomes is king. - Yeah, so this is, I think, one of the biggest challenges of experiential learning, right? Is that, one of the things we believe, one of the big learning outcomes, I think, of experiential learning is learning how to deal with ambiguity and create value, right? So a lot of it. - I'm sorry, I don't understand what you mean, ambiguity, no, I'm just kidding. (laughing) - Yeah, so I mean, you're joking, but I mean, to elaborate on how, you think about most of the students' experience up to this point has been highly structured, right? It's like, do this, do this, do this, do this, and you'll get this, right? - Yeah. - That's not how the real world works. And so by its nature, we had to make sandbox a highly ambiguous experience. We needed students to experience that for the first time and to learn to navigate it. The challenge with that is, is that their paths through it end up being very unpredictable. It ends up being very hard, so you can't, at the outset, say, okay, by midpoint of the semester, you are going to have done X, right? Which like a typical class of the structure that way you're gonna have done this thing by this point. Because that may be the wrong thing to do, you know? And startups, in particular, they might get started on an idea, realize it's not good, and then what will them to do is you should pivot and start over. But if we were enforcing like really rigid learning outcomes by certain points, they'd be like, well, I can't, 'cause I've got this grade that I've got to turn in at this point. So, so the really, really challenging situation for learning outcomes, I don't know if we're going to go into it now. One of the things we've really pushed to actually, is AI is opening up a whole new frontier of how to assess learning outcomes in these ambiguous environments. What we have essentially built, I think of it as like an AI oral exam. The students come into our system, and our AI just starts to interview them, right? About what they're doing, about what they're building, and it keeps pushing deeper and deeper and deeper and deeper. Right? The AI knows all of our 20 learning outcomes from the program, right? And it then like knows the questions it needs to ask to understand how the student is doing on those learning outcomes. And then when the session wraps up, it gives them some feedback so that the student can go act on it, and then they come back for their next session whenever they're ready to come back and have their next session. So, we've had to be really innovative on how you actually can rigorously assess learning outcomes, because again, you can't disrupt the ambiguous nature of experiential learning, or else you actually kill the actual thing. And a startup, a lot of it, I'd say probably 80% is all ambiguous. You've got to be able to step by step by step. One of our favorite sayings around our household is how do you eat an elephant one bite at a time? That's right. And so what you're doing is you're treating these students more like PhD students who are going forward and building something or discovering new knowledge versus an undergraduate where your quizzes, your really, your quizzes are just your assessing knowledge and understanding, whereas you're really going for a synthesis and evaluation. - That's right. And that's what I think what's exciting is that, I mean, I think a lot of an academic were worried about AI and what that will do in the classroom, but actually we're actually seeing this is a huge opportunity, because this was a struggle for us, right? Because you think about a PhD program. They've got an advisor who has maybe them and a couple other undergrad or a PhD students working with them. It's really high student to teacher, or really good student teacher ratios, right? And a program like this, you've got a pretty lean faculty structure over a lot of students. And so to really give that level of feedback is really hard. But AI is opening that up, as I'm saying. So we've got got this program where they can come in and do these oral exams with this AI and get incredible feedback in a very scalable way. - Yeah, I'm going off on a tangent, I think it's very good. - Well, the other piece with that, which I think is important, is it's not so much AI native as it is AI enabled. You still got the expert there who's gonna review the questions, you know, are the responses making sense, et cetera? How do we dig forward rather than AI native where it's just all AI? That doesn't work. - I think if we could just give, we wanna make a professor superhuman, right? And the professor still sits at the center of it, right? - Yes. - But we're making them superhuman. Where giving them tools that allow them to engage much more personally with students. - There was another piece that came to mind about the accreditation. What we've already talked about that, you're not changing student learning outcomes, you're not changing credit hours, you're fitting your model within that. So you're staying below that 25% required for a substantive change. - That's right, yeah. And so you think about like, again, in sandbox, the learning outcomes we're achieving are the same learning outcomes that they're trying to achieve in all of these other classes. What we're really doing is we're creating all this glue that's like connective tissue almost that pulls all of these classes together to a really cohesive framework that allows students to go really deep and to thrive. So I would say we're keeping the intention and the spirit of all of those classes that we're just adding all of this other benefit on top of it. And if an institution wanted to put together a program like this, what are some of the considerations they should be thinking about? - You know, it's funny, like in some ways, it's like really simple to do this in other ways, it's really, really hard, right? And-- - Welcome to the world we live in. - It's simple and theory and really hard in practice, right? And the hard part really is that, as you know, Dram, like universities are really like, you know, as many business units as there are professors, right? Each professor tends to be kind of their own thing. They're running their classes, doing their own research. And a program like this is not that way. It's a highly coordinated thing. You're coordinating with all of these different majors, all of these different advisors, all of these different professors. And I think universities aren't used to working in these really highly coordinated, interdisciplinary ways. And so that's the first one. That's the way I think, like, if you want to do this, it really takes leadership from someone who can get all of those cats to come together. And the second I would say is that in exponential learning, you have to flip your paradigm. It's really, a lot of times we think about class as kind of being the main piece of the learning system, right? Maybe class in your midterms or whatever. In this model, it's actually the environment. So you've got to create the right environment for people to learn to succeed. And then you've got to really hold them accountable, right? So accountability now becomes your north star. Because without accountability, in a really ambiguous environment, you will get a lot of students doing nothing. And so you really have to have really sophisticated accountability systems. Yeah. With those accountability systems, do the fledgling businesses, the entrepreneurs working on this, do they put together advisory boards, even boards and directors? Do they go to that? I would assume that if you're getting, up to 205 million in venture funding, you've already got an advisory board put together, isn't that an accountability system? Yeah, but that's going to come later. So you think about the program itself. They don't even have teammates. Most of them don't even have teammates when they come to the program, right? So they're coming all the way from finding a team, defining an actual good idea. They've all got ideas, like splitting bills with their roommates or something like that. But you've got to get into actually a good idea, a big market idea. So that's actually a pretty long journey. So they raise either at the end of the program or in the three to six months afterwards. So during the program, no. They don't typically have an advisory board, right? Because they're too early. So that's not the account of assistant we've used. We actually do a lot of weekly reporting. So they do weekly reporting and weekly planning. And we require them to do what we call a founder sink, which is like a required like peer feedback session. Those are actually both things that, as startup, I would advise them to do the same thing, right? We just make them document it, which you may not do, and as startup. And we have a bunch of other kind of things as well. And then they also have a local director who's then taking all the data that's coming from this, identifying who needs their time, and then coming in and spending time with them. Sure. How do they interact with the community going forward? Yeah. I think we personally have a long ways to go. But I just think in general and higher ed, we have so much opportunity to-- I always call it like make every alum a teacher. It's because you think about your alumni network. They're off doing these amazing things. But how do you get them to engage in deep meaningful ways with students? If you can do that, you suddenly just-- I don't know-- 1,000 extra workforce in terms of your ability to teach and mentor students. I know every university has a mentor, network, or whatever, but they tend to not be super effective. And so we've spent a lot of time thinking about, how do we decrease the friction between a student having a need and getting time with the person or the alum that can help them? So we've built systems on our side where they can instantly book time on alum's calendars and things like that. Middle-epieces exposure. You've got to get students exposed to these people as well. So we spend a lot of effort bringing them into the classroom so that the students have exposure to them and things like that. It is amazing. I think some of the alum's are better than others. But when you get the right ones engaged in the right way, I was talking to a team last night who was just going on and on about this CEO that's helping them with their startup. And it's just magic. When you can turn every alum into a good instructor or mentor. Yeah. I remember years ago, this is Pac Bell. That's how much I'm dating myself. And became SBC Global. Now it's AT&T. It was a sandbox similar to what you have. Foundation that they would invest in promising companies. Yeah. And they would bring their resources to bear on this. That seems like a model that maybe after they graduate or whatever, that's one way of funding, obviously. Yeah, no. So we've cultivated that. Yeah. I mean, at the end of the day, like, businesses aren't charities. And so if you create really quality companies out of the program, or out of your school, investors will come naturally. You can also speed that up by helping them to understand how great these companies are. And so, yeah. So most of the companies that are raising, some of them have to go to the traditional centers. So they're heading out to San Francisco and doing their raise there. But more and more, if you look at our last cohort, I think all of them raised from their local ecosystem. And so, yeah. So you build quality companies. You build a track record of investable companies. And they will come. You don't need-- yeah, they're not going to do it out of charity. Maybe they'll donate to your school and whatever else. But you start producing things that generate returns. And they will come and invest. Early in my career, after getting out of the Navy, I worked for a business incubator. And it sounds like what you've done is you've put this business incubator in place within the framework of a university. Yeah. And it's amazing because you think about any incubator in the world. They're going to take some hefty amount of equity in your company. These kids, they graduate and have all of their equity. To now go out and sell to investors, and to keep for themselves. And it's pretty special. And we guess they're paying tuition. So that is the trade off. Give me some good examples if you would, please. I mean, all sorts. So most of our programs are in Utah. And I think Utah is known for its B2B SaaS companies. So we have a lot of those. Some fun ones. So last year, we got a company come out called Mention. They are an encrypted Slack. So you think about Slack or Teams is becoming ubiquitous across workplaces. Neither are encrypted, though. And so more and more companies are concerned about their internal communications getting leaked, or hacked, or whatever else. And so they want to move to these encrypted platforms. The only ones that exist are things like Signal. But Signal doesn't work at the scale of a million-person company. Right? And so they're building an encrypted version of Slack. That was really fun. They had to go really deep into cryptography. They're the cutting edge of these new cryptography algorithms and whatever else. And so that one was really fun. One of the current core of this really fun right now is in the dental space, you think if you go in and need to get a bite guard or you got an invisalign, right? These things are very, very expensive. So the dentist or the orthodontist or whatever will do the analysis. And then they will send off for those devices from some other company and they come back. They are building software that a dentist or an orthodontist can use in office to create those devices. And then immediately print them with just standard resin printers or whatever the dentists already tend to have in their offices. And so they can take the cost of a bite guard from $1,000 down to $50. Oh my gosh. Wow. So this one's really exciting because this involves a lot of-- I mean, not just hardware software integration, but they are also doing T3D. So they're doing a lot of 3D modeling. So they're actually using some of the game engines that drive 3D graphics and whatever else to build the product. And so you can start to think about that type of learning where they might get a little bit of that in their computer science classes. But now they're having to build a production ready 3D modeling software for dentists in their offices, right? You just think about how much they learn in that environment versus any sort of project based thing you could give them in a classroom. Those are great examples. Chris, I have thoroughly enjoyed this. It's neat to hear new learning models and how they're working, what you've done to it, to make it work, and some of the great examples coming out of it. So thank you very much for this. We always wrap up with two standard questions. First one, three takeaways for university presidents and boards. What is it that they can do to really give this deep experiential experiences to their graduates in a way like what you're talking about? Yeah. I think the first thing I would say, as I mentioned already, is leadership. Universities have incredible resources, right? Facilities, their faculty. The fact that students are there dedicating four years of their time is like in this enormous resource of things that you can do with it. But it takes real leadership to pull all of those resources together in a way that is deep and connected and exceptional. And so that's the first thing I'd say is we need university leaders to really step up into that role, to really pull together the coalition of faculty members that want to be at the cutting edge of learning and to get them to do these things. Not every faculty, but there are a lot of them that want to be doing that. So that's probably the first thing. You know, leadership, recognize that you've got the resources there, and then go get it done. Again, it's been shocking to me even the outcomes that have come from this sort of thing. So-- Yeah. That's neat. Thank you for those. What's next for you? What's next for sandbox? Well, I mentioned a little bit already. I think we think-- if you talk to any professor and say, what's the worst part of teaching? I would guess that 80% of them would say grades. I mean, every professor hates that no matter what you do on grades, you're going to lose. Because either you're not going to be rigorous enough, you make all your students happy, or you actually introduce rigor. And now you have to deal with 20 students complaining about their grades. And the same time, it's actually really hard to do grades in a really good way. And so again, this is where we've been investing-- I mean, back to the learning outcomes thing. We think there's a huge opportunity for AI to solve this problem, to basically partner an AI agent with a professor, to do things we can't do at big public universities in particular, where you've got too many students, like really in-depth oral exams that push the students learning way deeper. It's also important because with AI, you never know who's there. It's been an oral exam setting that takes away. So we're very, very excited about it. Super bullish that there's a big thing to be cracked there. Very good. Well, Chris, thanks so much for being on this show. I thoroughly enjoyed our conversation. conversation and I wish you guys the best of luck going forward. Great. Thanks, John. Appreciate it. Thanks for listening today on a special thank you to my guest, Chris Krippenden. Chris, thanks for being on the program. It's great to see a new learning model out there and thank you for putting this together. Look forward to hear more about it going forward. To my listeners, thanks again for tuning in. See you next week. Changing Higher Ed is a production of the Change Later, a consultancy committed to transforming higher ed institutions. Find more information about this topic along with show notes on this episode at changinghireed.com. If you've enjoyed this podcast, please subscribe to the show. We would also value your honest rating and review. Email any questions, comments or recommendations for topics or guests to podcast at changinghireed.com. Changing Higher Ed is produced and hosted by Dr. Drummick Norton, Post Production by David L. White.