The College Where Funding Follows Students’ Earnings, Not Enrollment

Relevant Links:

“If—” by Rudyard Kipling

“Inventing a Job-Skills Machine,” by Rebecca Koenig in EdSurge

“Taxonomies of Human Performance,” by Edwin A. Fleishman.

“Marc Andreessen says AI layoffs are a farce: Companies are 75% overstaffed, and AI is the ‘silver bullet excuse’ to clean house,” in Fortune.

Transcript

Michael Horn

Jeff, one of my favorite poems is If by Rudyard Kipling. And there's a line in there that I want to liberally take out of context, which is, "if you can make one heap of all your winnings and risk it on one turn of pitch-and-toss." 

And my guess is that that's a bit like it might have felt at Texas State Technical College when they, get this, went to 100% of their funding being determined by their students' earnings after leaving the school.

Jeff Selingo

Yeah, Michael. It's a crazy story. You'll hear it in our interview today. 

And you're gonna find out what happens when a school says, 'Hey, we're just gonna move to 100% outcomes-based funding and see what happens.' 

That's ahead on this episode of Future U.

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Michael Horn

I'm Michael Horn,

Jeff Selingo

And I'm Jeff Selingo.

Michael Horn

Jeff, so a few years back, I started hearing more and more about Texas State Technical College. They were being held up as an example on Capitol Hill of funding innovation and really moving to outcomes and this ROI conversation you and I keep coming back to. 

And then, you know, we've talked about them. They've come up on Future U as well before. 

But they were just really intriguing to me because of what we talked about up top, that they didn't just do, like, you know, 5% or 10% of their funding based on outcomes or graduation rate or something like that. 

But a 100% is no joke, Jeff.

Jeff Selingo

Yeah, Michael. That's right. And in this funding formula, which has been in place for now over a decade, the state is, in essence, providing the college a percentage of what they see as the additional direct and indirect tax revenues that students generate as a result of attending.

Michael Horn

And they've had some stunning outcomes, which I think we're gonna hear about in the interview, but former students' wages have increased dramatically, and the results aren't just because the college has become more selective or skimming or something like that. 

I think it's 56% or so of its students receive Pell Grants, which is the highest share in the school's history.

Jeff Selingo

Yeah, Michael. And just to put this school in context, they have multiple campuses, over 12,000 students. So it's a, you know, it's an experiment with some scale to it, for sure. 

And to tell us more, you got to interview Michael Bettersworth, who is the chief marketing officer there as well as the founder of Skills Engine. 

And as we'll hear, Michael played a key role in designing this first higher education funding model in the nation that's based entirely on student earning outcomes. 

You know, Michael has published more than 25 studies on emerging careers and technologies and their relevance to Texas business and industry. And, get this, he holds a patent in machine learning for text-to-skill translation and is a frequent adviser on workforce and education policy. And that piece around text-to-skill translation is critically important as we'll hear in your interview.

Michael Horn

Yeah. That's right. And it means he also knows a thing or two about AI, Jeff. So I'll look forward to getting your thoughts after the interview that I had with Michael. And with that, Michael, welcome to feature you.

Michael Bettersworth

Thanks. It's nice to be here, Michael. Good to meet you.

Michael Horn

Yeah. I've been looking forward to this conversation because you're at Texas, State Technical College, and you have put in place along with the state of Texas what is described as the nation's first higher education funding model based entirely on student earning outcomes rather than the standard measure of how much time, right, students are sitting in class. 

So walk us through that funding formula and how it really works.

Michael Bettersworth

Yeah. You bet. Well, so traditional higher education is paid based on seat time, contact hours. And years ago, we determined that wasn't serving us well. Basically, it was incentivizing the wrong behavior. It's like paying a company based on inventory. 

And in Texas, and in many states, they measure it on a census day. One day of the year is the basis. One day's enrollment is the basis of an entire year, or in Texas, two years of appropriations. And so that incentive just wasn't working for us. We're a technical college, and our mission is job placement. Our mission is economic development, is not conferring degrees. It is job training. The degree is a means to that when it makes sense to the labor market. So the volume-based contact hour funding formula wasn't working for us. 

How the funding formula basically works is we measure earnings five years after our students leave. And we do that with the Workforce Commission, and we can talk about the mechanics. But we look at the earnings of our students over a five-year period, and the state pays us effectively a commission based on the economic activity that that generates. 

If the student doesn't get a job, we literally do not get paid by the state.

Michael Horn

And then you guys have some set of funding, right, that's attributed to the college that's essentially contributing to the state's overall GDP or wealth or something like that, and a percentage of that, is that the idea goes into the college?

Michael Bettersworth

Basically, yeah. About 60% of Texas's technical college system, which is TSTC, is based on the state appropriation. So it's a big chunk of the operating budget. 

And that is entirely driven based on the student earnings outcome. So the idea is that student comes to TSTC to get a job. They work for a Texas company, and then a portion of that generates economic activity for the state in terms of sales tax revenue and others. 

So some economists got together and created an econometric model to basically drive that. 

Now I'll make an important point. It is not accurate in the sense that it's measuring the actual economic impact. A single cohort from the college over their lifetime generates more than a billion dollars of economic activity for the state. We'd love to have that appropriation every year, but instead, ours is in the hundreds of millions. So it's a portion of the economic activity that's generated, effectively how much they generate over that five-year sampling period. 

But the lifetime return on that graduate is exponentially more.

Michael Horn

So it's an even better deal for the state of Texas, I suppose. 

This was passed, right, some 15 years ago or so, I think, by the state. But you all were at the front door, as I understand, sort of helping them put it in place. 

Just sort of describe the mechanics of how you got that passed, and then how it was implemented. I assume it wasn't just a switch, or maybe it was.

Michael Bettersworth

Well, it was back in 2009 in the Texas legislature, and there was a chair of a committee that was asking every president and chancellor of the state's higher education institutions, A&Ms, UTs, community colleges alike. Two questions: how do you feel about outcomes funding? And most of the executives would say, 'We love it.' And then it was a setup because the next question was, 'What percentage of your budget, sir, would you like to put on the line for that?' And they would squirm in their chair. Two percent, 5%, a bonus. 

So we were watching those hearings, and we felt that the political tides were turning, and that outcomes funding was coming. And we also knew that our unique mission wasn't gonna be represented. 

We're a small part of the higher education bucket when you consider all of the state's community colleges and universities. TSTC's mission is unique. 

So we said, 'We'd rather set the table than be under the table.' And so when they asked our chancellor at the time, doctor Bill Segura, how do you feel about it? He said, 'love it.' What percentage of your budget? And he said, 'all of it.' 

So that was the beginning. And it was a record scratch moment in the hearing room late at night. 

And what the legislature did is they were actually concerned that we might hurt ourselves, so they passed a bill to do a feasibility study. And so we got together with the comptroller, governor's office, legislative budget board, Ray Marshall Center brought in some economics, and another economist, and coordinated. We sat down, and we went through the mechanics of it. 

Now, the person that originated this idea was Dr. Gary Hendrix. He was our CFO at the time. And Dr. Hendrix had designed this idea on a napkin and had it in his desk. And he had done the numbers. And we had an economist do the numbers. So we knew this was gonna work. 

And so we went through that one year of many meetings in the Lone Star Room at the old coordinating board meeting, and let me tell you. Nobody wanted ... A lot of people didn't wanna be in the meetings. You know? 'Oh my gosh. What are they dragging us into?' There was a lot of reticence. Because this was complicated. There were some mechanics involved and technical details. 

But one by one in the meetings, you would see people go, 'Oh, I get it. This is not about finance. This is about driving behavior. This is about guiding curriculum. This is about creating a culture that's responsive, and it's to the best interest of the student, the employer, the taxpayer. Everybody gets aligned.' 

So that's the real component of what this funding formula is about. It's about driving culture and behavior. 

On the mechanics, we've advised many states on how to do this. And the trick is you gotta switch. It's like switching from AC to DC or unleaded to diesel or something. You gotta switch. And the way we did it is we took the appropriation that was gonna happen in that year, and we normalized the funding formula to equal the same dollar amount. So that's how we did it. 

And then it was, like, off to the races. The next session came, and if we made more or less money, our appropriation would go up or it might go down. And, that's very accountable.

Michael Horn

Well, I was gonna say that's the perfect launching off point to say, so you've been doing it for many, many years now. 

How's it gone? What are the outcomes for the college, for the learners, for the state?

Michael Bettersworth

Sure. Well, for a second, the institution said, 'Ah this isn't gonna work. This is just us. This will this too shall pass.' You know? 

But then we started closing some programs. So we closed around 20 programs that did not meet basic earnings thresholds. 

And, we didn't do any terminations. We actually repurposed faculty and staff around those programs, and we grew the programs that had high earnings. 

Now, also, a lot of the programs that earnings might have been flat, all of a sudden, they looked to their left and right. 'We better move our dot. You know, our earnings are great.' 

So what happened is that mid-management started making all kinds of changes to their programs. The career fairs became, 'You have to apply to come to our career fair.' And they would go say, 'Do you have job postings, and what are you paying?' So all of a sudden, started to be more intentional about our labor market and business partnerships. Not that we weren't in pockets, but it became a generalized best practice. 'What are you doing to raise your earnings in your program? I need to get mine up.' Second thing, benchmark. We showed every program how their earnings compared to other programs around the state. Okay. 

Now nobody wants to be last. Most people wanna be first. So just showing people where they were, that was the most critical component. 

Since we implemented it, and since we closed some of those programs, we've grown other programs. And since doing the model, starting wages for TSTC graduates, inflation adjusted, all these numbers, are up 27%. So our students are making 24% more than they were before. 

Job placements, the number of people placed, up 40%. 

And our employment rate, six-year employment rate is a 93% employment rate. 

And we're an open-enrollment institution except for two programs out of the 100 and something that we have. 

So the metrics are huge. 

And then that's also resulted in our funding formula. The appropriation has more than doubled. Right? Because our placements and earnings have gone up.

Michael Horn

So you're literally walking the walk, if you will. 

And I could be wrong about this, but I think voters even approved an endowment for you all, recently. Am I right about that? Some $850 million?

Michael Bettersworth

Yeah. An $850-million endowment. 

The reason for that the two Texas main university systems are land-grant institutions. 

The state of Texas owned a bunch of land in West Texas back in the day, and it wasn't worth anything. But then they found oil and solar and wind and everything on it, and so that's the largest endowment in the world, is that endowment. It's don't know how many billions it is. I think $30 billion, so it's a large amount. That's A&M and UT system. 

And then we do not have any kind of property taxes as a state agency. We don't levy property taxes like community colleges. So we didn't really have any funding for infrastructure. 

And that $850 million is an endowment, and it spits out $52 million a year, which isn't a lot, actually, if you think about it. I mean, to build a building today, one of these technical buildings is $70 million just to build a building, and then you gotta you staff it and operate it. 

So we've got a start. We've got a start, and that's gonna give us infrastructure funding in addition to these other mechanisms. There's a thing called CCAP and tuition revenue bonds things that we'll continue to do as well.

Michael Horn

Gotcha. 

Alright. So let's dig in. You just talked about how you can walk away from certain programs, grow other programs, and so forth. 

You've also, though, been a leading proponent of rethinking how to better map what colleges teach onto the skills that employers are in fact looking for. 

I remember an article from a few years ago that compared your approach to how scientists have actually mapped the human genome in recent years. Only in this case, you're sort of uncoiling how the skills, if you will, that connect people into employment. 

And so I'm curious both how the labor data and the understanding of underlying skills that need to get taught actually, maybe reshape within the programs themselves to make them more relevant and to produce these sorts of job outcomes you're seeing.

Michael Bettersworth

Yeah. Not to date myself, but that work started around 2002. And we were …

The state asked TSTC to do forecasting on emerging occupations and technologies for the whole state. And so that's when I came into the college from a place called IC², and we started doing that. And we hired some folks that used to do forecasting for some three-letter agencies that happened to be in Austin, Texas, and we said, you know, 'Hey, let's work on the domestic policy here.' And we got to work with the people like doctor John Vansden in Austin and his team. 

We started doing forecasting, and we looked at 40 or 50 different topics — biotech, homeland security, nano, different things at the time. And we kept coming across some similar patterns. 

One, the SOC codes that are used at the Bureau of Labor Statistics were never designed to do supply-demand modeling at a level of detail for curriculum. They're really macroeconomic measures for labor market economists, and they come out of the Great Depression. And trying to do any kind of SIP SOC alignment is really a misappropriation of those taxonomies. You can't do it. There are more than 800 occupations in the economy. You know?

Michael Horn

Turns out.

Michael Bettersworth

There isn't a SOC code. Yeah. Turns out. Turns out. 

So any methodology that's starting off with a SIC SIP code, you know, classification of instructional programs, the serial number of the biology or engineering, mapping it to SOC code, this is not gonna get you far. And that was the frustration of a lot of the data modeling that was going on. So over those 40 publications or so, we noticed a similar pattern. It's not entire new occupations, most of the time, that are the issue. It's the skills. 

And what are skills? Well, knowledge, skills, abilities, tasks, levels of proficiency. There's ontological rigor to that. 

Today, we say skills quite loosely.

Michael Horn

Extremely loosely.

Micheal Bettersworth

Yeah. Very erroneously. To really ... There's a book called Taxonomies of Human Performance. It's right here. That's that's kind of the bible, by Ed Fleishman about this. It's what drove O*NET's creation, actually, is some of the the work that Ed Fleishman did. 

And that 250-year-old science of industrial and organizational psychology is what we started with. 

We had more than 1,000 industry advisers. We sat down with our advisory groups. We studied job analysis and DACOMs. And we said, 'You know, what we need to have is a basic taxonomy, or an ontology of understanding the labor market and skills. We need to understand criticality and proficiency, and then we need to have a translation layer.' 

Because curriculum is written in one language — student shall... And then job postings, which are just the tip of the iceberg, that really a 'help wanted' side. You gotta get into the job analysis. And guess what? That data's not public. You can't scrape a job analysis. And people have tried. 

So the technologies that scrape job postings and say, 'These are the skills.' Those are keyword mapping.

Michael Horn

It's weak. Right? Because it's more of a marketing document as opposed to a, 'What do you actually do,' in some ways.

Michael Bettersworth

So you can't avoid the heavy lifting of job analysis, and so we did that, and we built some tools and technologies to go after that called Skills Engine. 

This was during Obama, gainful employment, Perkins five, reauthorizations of WIOA, and all the regulatory bodies said you had to do skills analysis, but it turns out nobody would enforce that. 

And it also turns out that the heavy lifting of job analysis, most institutions do not do it. And you can look at their budgets and their staff, and how much time they spend on job analysis, pretty vacuous. I think as a country we've probably gone backwards where DACOMs used to be more popular. And we at ourselves, TSTC, are revisiting these kinds of approaches today. 

That granular level of ontological mapping, AI, and some of our capabilities today fundamentally make these things easier to do, but you still gotta have ontological rigor, and then not boil the ocean. 

It turns out that Ohm's law is gonna be relevant for an electrical power control technician for pretty much all time, probably. So I don't need to keep asking people, is Ohm's law relevant? Amperage voltage. Right? 

So knowing the level of confidence, how confident are we that this is still relevant? That's a vector. 

Another one is foundational skills. You know, if I'm recruiting a high school student into a program, I'm starting with a base level of knowledge and experience and skills. So I've got to fill that with these fundamentals. And then before I can get it to the highest ... versus an incumbent or a dislocated that's coming in with something. So these are all factors that are variables. 

And, by the way, the schema are not the problem. It's very popular to talk about technology and schemas and APIs and or MCP, what are we talking about now? 

You know, the people involved here. Somebody has to care. They have to put in the energy, and then they have to actually update a lesson plan. And that's 90% of the battle.

Michael Horn

Is to actually do the changes. 

So it sounds like these changes that you're describing, both in terms of the outcomes you described before, but then also, you know, being able to look at the level of a program, what are we in fact teaching, and why, what does it map to, and so forth. These are the sorts of changes you'd really want to see and change this real culture and have these incentives in place and so forth. Largely positive. 

I'm just curious, in any big change like this there's always things that surprise and some unintended consequences. 

Have there been any of those that you've seen? Have there been changes you all have had to make as you go through? What are some of the big ones?

Michael Bettersworth

Well, I mean, I'm very encouraged. I'm very encouraged by faculty. 

And most of our faculty aren't academics. They come from industry. They were nurses, pilots, line workers, welders, machinists themselves. And so they come in with a love of their craft. Okay? That is their identity. And it's particularly in technical education. It's so much about the identity. Someone is choosing to be a nurse, a pilot, a welder. That's a big thing. 

This concept of occupational identity, I first heard it from somebody, a gentleman over at WGU, and I love that appreciation for what is that person's occupational identity, not as a typecast, but as a part of their values and who they're aspiring to be. 

So what I'm really encouraged about since implementing this is that when we empower faculty and department chairs, we let them know where they stand compared to others. We get out of the way. Resource them. 

And more often than not, I mean, nine times out of ten, they're gonna move their dot up and to the right. They're gonna move the placement up. They're gonna move the earnings up. If we empower them with awareness about it. And then we have a little bit of accountability. Just a little bit of cultural accountability. Okay? That's the big part. 

And our motto at TSTC is place more Texans in great paying jobs. And you can ask anybody here, from the groundskeeper to the cafeteria, to the secretary, to the faculty. 

What's our mission? Place more Texans in great-paying jobs. 

That singular focus and mission, along with data and accountability and resources and some best practices, that's the secret sauce. 

The technology and the taxonomies and the ontologies are all enabling components, but the key is to have that singular, Lencioni-like focus of clarity on why we're all here. And then human spirit takes it the rest of the way.

Michael Horn

Let me ask this question. Like, I'm curious how broadly applicable in higher education it might be. Right? 

Is this something that really just works for technical college, short-term degrees, where there's a close feedback loop? 

Or is this something that could be extended to, say, a liberal arts institution that's maybe worried about how AI is changing jobs and things of that nature? How far can we take this performance-based approach?

Michael Bettersworth

Man, this is how you don't get invited back to dinner parties. Okay? When you answer that question.

Michael Horn

But you get invited back to ours.

Michael Bettersworth

So yeah. Oh, man. Well, so that's an important ... Here's the topic I think that really matters on those conversations about you're getting into the purpose of higher ed. You're skirting around ... That question gets it. 

And the key part of that higher education, maybe any education, is not a monolith. Right? A law degree at some schools at Baylor University, they pride themselves in teaching somebody how to be a trial lawyer. Their percentage rate, the pass rate, of the bar is exceedingly high. Now at other law schools that will go unnamed, they teach you how to, I heard this one time, ‘We don't teach you how to be a lawyer. We teach you how to think like a lawyer.’ 

And to which I responded, 'Why would you assume they're mutually exclusive? Couldn't you do both?' Right? 

So, you know, I mean, we have this, vocational versus academic humanities — these classic tropes.

Michael Horn

These dichotomies. Yeah.

Michael Bettersworth

These classic dichotomies. And they're false. Because they're an excuse. What we do is you embrace both. We have accountability to that person that's investing their time, their hope, their money, and their energy. 

And the studies on incoming freshmen that have gone on for decades, when they ask incoming freshmen — is it Harvard that does the study, I think — 'Why are you here?' Well, 'I'm here to get a job,' or, 'I'm here to get skills to get a job.'

Michael Horn

Yeah that was a UCLA study. Yeah.

Michael Bettersworth

Yeah UCLA study. And then, 'I'm here to study things that are interesting.' And those are not mutually exclusive. Now accountability to those is what we're living in today. We're living in today. 

And that is the Do No Harm legislation that's come out. That's great. These are low bars. I mean, these are low bars. So I think the revolution in student... 

We've seen what's happened when you have unchecked subsidies. And the victims of that are individuals who have signed up for degree programs in education that have dubious returns on investment and who are saddled with debt which they can't shield themselves from. That is fraudulent. It's reprehensible. And it's, I call it, like, passionately misinformed policy that has recently begun to take more-corrective courses, which we're highly encouraged by.

Michael Horn

Well, so I'm curious how much further would you go. Right? You mentioned the Do No Harm standard. We're seeing 'credentials of value.' Those things do not go as far as you all have gone around a 100% funding. 

How do you think about the different bars, and how much further should this go in your in in your view across hiring?

Michael Bettersworth

Well, I think it depends on the institution's mission. I think you could even get it down to the program's mission. 

If something is consumptive, I'm studying this because I'm purely interested and I don't expect a return on investment, okay. Well, right? We need to be cautious about how much we let somebody go into debt for that. And it's particularly how much the the taxpayer's on the hook for it. 

That doesn't deny anybody opportunity to go pursue that, but, you know, I'd like to have an F1 car. You know? You know? My wife would say, 'No.' Because I wouldn't last 30 seconds in that, right?

Michael Horn

No thanks, right. But you would like it. Yeah.

Michael Bettersworth

Yeah. So that's not the best example. But, you get the point. I think if somebody's intention is employability, and that is the overwhelming intention, then eyes wide open, they should go into that. And you shouldn't ... 

If we're teaching somebody that's not market relevant, our culture is that we're a party to fraud. Why are we teaching something that's not market relevant? And market relevant might be that it's foundational to get to something market relevant. But if we're teaching something that's outdated and is not tracking with the market, that is not about academic freedom in that instance. I'm not, 'I just teach what I want to teach regardless of any accountability.' Is not our culture. 

And I think that if you go too far the other path, you end up where we've ended up in some programs that have put people in some bad positions, and it's harder to do today, and I think that's a good thing. 

I think the Do No Harm data coming out any day now with the six digit SIP level is gonna really reveal these ROI calculations. 

And I'll be honest, some of our programs aren't at the top right now. You know? But we're looking at them, and it'll drive behavior. Yeah. 

The change over the next few years when those data come out in the next few months, is gonna be powerful.

Michael Horn

Michael, I'm curious as we wrap up here on this segment before we go to break.

Just can't go anywhere without mentioning AI. So here's your AI question, I guess. Right? Which is AI is reshaping a lot of the tasks that are being done in jobs and things of that nature and may change skills. In terms of… 

How should we think about the lag? You know, someone comes in as a first year, two years later maybe something that they've learned is no longer relevant. And then measures obviously are in some sense, right, looking backwards. How do we think about that lag with an ever increasing pace of change perhaps in the labor market?

Michael Bettersworth

The lag in terms of updating curriculum while we have a target that's moving so rapidly?

Michael Horn

Yeah. Exactly. Right? Is that something you've done? And then we measure it later. Yeah.

Michael Bettersworth

Yeah. Sure. So, I mean, as I look to my monitor over here, which is running Claude Code and Cowork and OpenClaw and doing all kinds of things. Sorry for the distraction. My Mac Minis are burning themselves away here. 

You know, we have a disruptive innovation, and we've had these before. And I'm not minimizing this. Don't get me wrong. I'm not minimizing it. But I think there's a lot of hyperbole about some of the some of the things that are happening here. Yes. We have some layoffs occurring. 

And Marc Andreessen recently, I think, colored it pretty well. Some of that was over-hiring from COVID. 

So we look at artificial intelligence through a number of lenses, and it's not a defined occupation. It's a set of competencies, knowledges, and skills. And it will trickle across multiple occupations than it already is. 

Our diesel program is using software from, well, Caterpillar and other companies that is using artificial intelligence. 

Our line worker program uses artificial intelligence to look for disruptions in a power line to predictively do maintenance. 

These things will infuse themselves across various occupations. Yes. There will be some job destruction along the way. No question about it. 

But from a technical college perspective, it's another competency skill set. It'll infuse itself in various occupations. 

Now if you have a web development program right now, an associate's degree, which we have, okay, now that's a problem because those competencies and skills are gonna change dramatically. However, the adoption in the workforce and in the industry is being quite slow. 

So we're gonna have a tapering point. And as long as we're listening to our industry advisers, as long as we're watching placement and earnings, and keeping an eye on that, and making certain we're updating iteratively, it will be self-correcting. 

The sky's not falling. We need to calm down. We need to not rush out and start slinging out AI degrees, you know, as if that's a defined occupation. It's a disruptive innovation and competency and skill set. We will infuse it as we move through time.

Michael Horn

Michael, thank you so much for joining us on Future U. And for our listeners, Michael's gonna come back at the end of the show to answer a trio of rapid fire lightning round questions. So stay tuned. We'll be right back.

Sponsor

This episode of Future U is sponsored by Ascendium, a mission-driven nonprofit committed to improving learning and training systems to better serve learners from low-income backgrounds. Ascendium envisions a world where low-income learners succeed in postsecondary education and workforce training as paths to upward mobility. Ascendium's grantees are removing systemic barriers and helping to build evidence about what works so learners can achieve their career goals. For more information, visit ascendiumphilanthropy.org.

Michael Horn

Welcome back to Future U. Jeff's, rejoining me here and, outcomes, open access, low-income students, driving behavior, changing incentives of the faculty, occupational identity. There was a lot in that conversation. 

What stood out to you, Jeff?

Jeff Selingo

Well, a couple of things. 

First, on how they were intentional about this design. Right? That the fact that students go to college to get a degree, to get a job, and in some places, you know, in this institution in particular, it's really about getting a job, and so they were very intentional about designing a system for the reason that students are going there. 

Second, it was really the focus on getting the faculty in particular on board. And in doing so, how the design of programs and courses changed as a result when your number one focus is on job placement and on what employers want, what they need. 

And there's incredible incentives that way because I think what's interesting in what Michael said to you is that if you go to most colleges and universities, even if outcomes are a piece of their funding model, you know, the faculty will still say, 'It's not our job to get students a job.' They might listen to employers. They might even have employers on advisory boards and things like that. But there's not a lot of incentive for them to redesign programs around that because, so what if your graduates don't get a job, it is what it is. 

But in this case, you know, they have to in order to get funding and they know that this is gonna require, you know, funding to continue these programs, they have to follow the lead of the employers. 

And I think that's an incredible incentive for faculty to think about doing things that they might still do no matter what, but here is something that's kinda pushing them along.

Michael Horn

Yeah. It's interesting hearing you say that, right, because it's not a tenure-based model, obviously. Right? This isn't about research output. As he said, a lot of the faculty are not from academia. They're from industry. And so they sort of know what it'll take, obviously, for them to continue to be able to teach here as well, I would imagine, is make sure you are really getting those students into jobs and making sure that they learn the relevant skills. 

And that's the other big takeaway that I had from it. You know, I've sort of gone on this rant a few times where I said, I kinda think when we're scraping skills from job placement or, you know, job descriptions, we're not really getting the actual skills at the heart of these jobs. People, you go into a room and one of my favorite questions around my book is I'll ask people, 'How many people do the job description?' You know, like, that's your actual job. And, like, no hands go up. 

He's essentially you know, the college, it sounds like they're doing cognitive task analysis, really digging into these roles and understanding. And as he said, there's some things that are pretty static. You don't have to ask people about. You don't have to check. But they really, it sounds like, went deep on the roles that they educate for, not everything in the economy, but the ones that they really focus on, and went way beyond, I think, frankly, just to be blunt, like, a lot of the chatter we hear about skills-based hiring is very sort of surface level on the job description. 

We hear a lot around learner employment records and things like that. I don't think many, if any, institutions are going to the depth that they do and then translating it to, 'Okay. So what does it mean we actually have to teach?' Right? Which is the other side of this. It's not just a nice to know that, you know, the a welder does x, but, like, what does this mean for what we actually, in fact, teach, Jeff? 

And I was really taken by that. I was taken by how seriously they took the Obama administration's push around gainful employment to really turbocharge that work, it sounded like, and maybe a little bit of longing in his voice that other institutions would do something similar.

Jeff Selingo

Yeah, Michael. I must admit I was a little embarrassed in that moment. Right? Because I've done a lot of work on the job-scraping piece of of the descriptions. 

And as you both agree, right, these are keywords, but they sometimes are the only thing we have to base, you know, a lot of our knowledge on. Right? 

So this is a lot of the work that I've done with Matt Sigelman because a lot of the work of Burning Glass and Lightcast does depend on those. 

But you're absolutely right. What a job advertises and what a job actually does is very different. I remember interviewing somebody for "Dream School," and we were talking about how she hires. This was a mother, we were talking about college, but then we ended up talking about how she hires. And it really reminded me of somebody years ago that I worked with who, during interviews, would often ask people about, like, you know, what is the different? This is back in more of the software days. Right? Like, how do you think about technology? How are you using it? 

And then would actually ask them to show them examples. Show them how you actually use this stuff in real time. 

And it's very different from describing a skill on your resume or describing a skill you've learned to actually showing them what you are able to do as a graduate. 

I think the same thing, as you said, about a job is that's the same thing. Right? Like, don't tell me what you do, but show me what you do on a day-to-day basis, and they're very different things. 

So I could tell you that I know, you know, data analytics or I know how to use Claude, or whatever it might be. But until you show me how you use it, it's a very different thing than listing that skill on a resume.

Michael Horn

That's a writing technique, too. Right? Show, don't tell. 

Let me ask you this question, which is, I asked him obviously how far outcomes funding should or could go. He came back with, I think, what's an astute answer politically. It depends on the mission, right, of the institution. 

That's the right answer, I think. But the question remains just how far, you know, for different institutions should we be going. 

And he did say we should be protecting students from downside risk and that most students, they wanna go to college to get a good job. You've written about this a lot. The ROI is important at a school. 

I'd love to put you in the hot seat. Just how far should this type of model go in your mind? You know, community colleges, not just technical colleges perhaps, regional universities, flagships? Like, where do we draw the line? 

I suppose it's most relevant for the public conversation?

Jeff Selingo

Yeah. I think it's a great question, Michael. And I think aligned to mission. 

There was a point in the interview where he was talking about the origin of this, and he said something like, know, we are watching the hearings of other colleges and universities in Texas, and that's kind of how we said, 'Well, how can we be different? Right? How can we go to the legislature with something different than what the University of Texas system is going to, them with or Texas A&M? 

And that's where I thought about this idea of mission. And, you know, as we always say, right, without margin, there is no mission. In some ways, Without a mission, there is no margin. 

And if we think about it the other way, and I think that so many colleges and universities are trying to be somebody else. And if you say our mission is to educate teachers and social workers and government workers and IT workers, if we think of the WGU. Then let's measure them by that. 

And the same thing in a regional public system, so many regional publics say, we educate the workers in our local community. Okay. Then let's measure you by that. Let's not measure you by what we're measuring the flagship by. 

And I think that's part of the problem with how we have framed outcomes-based funding right now is, first of all, it is, as we've mentioned many times, just a small proportion of overall funding. But we kinda have a one-size-fits-all model, and I would love to see a model that really leans into what we want the mission to be for these universities. 

Because one of the things I think we might see is less mission creep as a result. 

If the regional publics know that they are being measured on these four or five things that are critically important to the regional economies, they're not gonna try to be the flagships because there is no advantage for them to be more like the flagships. 

Community colleges then are no longer trying to become the regional publics and trying to offer bachelor's degrees, by the way, because they're or even dual enrollment because they're more focused on what their job is. Right? 

So it goes back to, you know, your work on jobs to be done. Like, what is the job to be done by each of these sectors of the economy and at a time when we have limited public resources, and we really need to focus on mission, and there's so much mission creep as we know in higher ed. 

I think this is a little bit of a governor on that, if we really frame the outcomes or frame the outcome funding around what the mission needs to be for those universities.

Michael Horn

I'm embarrassed. I literally never thought about it this way until you just said it, but I think you're exactly right, which is that if we fund, right, based on mission, excellence can be on delivering on the mission. 

To your point, no upside in climbing the ladder. We get rid of the arms race in some respect, within higher ed or the, we all wanna look, you know, like Harvard, just our version of this. 

And then I think the other thing is we can build prestige into each of those classifications, if you will. Right? I am fantastic at placing people into my regional economy. It can be really prestigious and can be a really valuable thing. 

And it occurs to me, Jeff, even back to our apprenticeship episode last year when we talked about the Swiss system, about how they build prestige and terminal degrees into these very workforce-based practical applications when people don't go an academic route and it's not looked down upon. Right? 

And so this is a way of signaling, I think, Hey, this is your lane, and we want you to be awesome at it, and we're gonna recognize you for it and fund you based on it. And that strikes me as a pretty big opportunity.

Jeff Selingo

I think it does, and especially if there's a new lane we want institutions to focus on. 

For example, let's go back to the regional publics for a second. Right? We talk often about, you know, all the adults with, you know, some college, no degree. 

You know, I hosted a dinner with Eli Oakley at ASUGSV. This came up repeatedly that colleges and universities are not built to serve those students. Well, why aren't they built to serve those students? As Michael said in his interview, right, they're focused on getting money for, you know, their census on a certain day, on how many students they have that particular day. 

Well, if we want to incentivize them to do something different, then let's tie their funding to that. 

Well, what if we tie their funding to how many returning adults who have some credit and no degree, how many they get, and we give them a huge upside for doing that? I guarantee you will see behavioral change among college and university leaders.

Michael Horn

Well, that's an exciting place, I think, Jeff, to leave the conversation. And, Michael, welcome back to Future U. We've got three questions for you on this lightning round segment. 

The first one is, what was your favorite class when you were a student, and why?

Michael Bettersworth

Oh, gosh. I could go back to Baylor. I took a film class. I was an engineering major, and I took a film class and changed majors. I didn't talk to my parents about that either. Was a slightly different career craft into a multidisciplinary program. 

So I'd say my film class with Dr. Michael Korpi was one of my favorite classes of all time. It was the history of film.

Michael Horn

Perfect. Perfect. And what skills do you wish you had perhaps learned in college that you didn't at that time?

Michael Bettersworth

Well, I'm 50 right now, and temperance has served me well lately, so maybe a little bit of that earlier in my career would have been helpful. Now, I think that's the answer to that.

Michael Horn

Perfect. Well, last question here, which is you're now giving advice to a new college student today. What's your go to piece of advice for them?

Michael Bettersworth

Well, I think... Gosh, that's a really good question. Go-to advice. 

You know, if you're making a monetary investment in this of your time and energy, I'd have your eyes wide open on on the risk and reward of that. I think your passion is important, but I think the second year signing a loan document or making a commitment financially, are you at this have you have you done your research? Are you making an informed commitment? Is the output of that what you like? 

Going to college right now to try to find yourself and change majors and meandering is very expensive career exploration. So I think if you're doing it on somebody else's dime, good on you. And if you're doing it on your own, then be mindful.

Michael Horn

Eyes wide open. Know the trade-offs. 

Michael, thank you so much for joining us. 

And to all of you tuning in, thank you for listening. And please remember to subscribe wherever you're listening or watching. 

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