Ask Us Anything: Workforce ROI, AI Hallucinations, and the 5 Pillars of World-Class CTE

Watch the episode on Youtube: https://youtu.be/f5gWUVQI0jI

Melissa Martin and Matt Kirchner are back to answer your questions, covering everything from university curriculum design, to AI in the classroom, to what employers actually expect when they invest in education.

This one moves fast, but it’s focused: how do you build programs that truly prepare students for modern work? How do you keep education from falling behind as technology accelerates? Along the way, Matt and Melissa break down what universities need to change, how to raise the bar in the age of generative AI, why ethics can’t be an afterthought, and how to help HR teams understand the value of credentials and new pathways.

Listen to learn:

• What university programs should teach (in one course) to better prepare grads for modern manufacturing work
• How educators can help students identify when AI is wrong and why we need to level-up our homework in the age of AI
• The role of ethics in modern CTE
• The five components of a world-class, modern advanced manufacturing high school program
• How educators can measure program effectiveness and show ROI to industrial partners
• What HR teams need to understand about changing credentials, degrees, and how to evaluate technical candidates

3 Big Takeaways from this Episode:

1. have to teach applied industrial skills, not just theory. Matt argues that a four-year program can cover a lot of “cool stuff in the lab,” but it still needs authentic manufacturing equipment and technology so graduates understand what they will actually see in industry. He frames this as an employer expectation problem: even when budgets are tighter at the four-year level, universities still need to build around the same core technologies students will encounter on day one in manufacturing. 

2. AI changes the standard for student work and makes ethics a core requirement. Melissa and Matt point out that AI is designed to produce an answer even when it doesn't know (causing a 'hallucination'), which means students must learn to question outputs and verify accuracy instead of treating AI as a sole source of truth. From there, the conversation moves from classroom integrity into broader ethics: what it means to do original work, and how humans should think and behave as AI becomes more capable and more embedded in decision-making. 

3. Industry and HR and educators must understand each other's needs to build a successful partnership. Education and Industry both have a responsibility to do their part in a partnership. HR departments must understand the changing landscape of certifications, 3-year degrees and other credentials that students are gaining to demonstrate their technical competency. Likewise, educators must adopt industry practices of tracking metrics to show employer partners the ROI of their investments in the program.

Access tons of links & resources on the episode page: https://techedpodcast.com/askusanything-122025/

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Transcript

TechEd Podcast Introduction: 0:09

This is the TechEd podcast, where we feature leaders who are shaping, innovating and disrupting technical education and the workforce. These are the stories of organizations leading the charge to change education, to rethink the workforce and to embrace emerging technology. You'll find us here every Tuesday on our mission to secure the American Dream for the next generation of STEM and workforce talent. And now here's your host, Matt Kirchner,

Matt Kirchner: 0:38

welcome into the TechEd podcast. This is your host. Matt Kirkner, we had such great feedback on our last episode of Ask us anything. We had great questions, first of all, from our audience, and we had so much fun answering those questions. The interest this time around, absolutely overwhelming. We put out a request. We say, hey, there's another episode coming up. And the world of technical education, TechEd nation, as we like to call it responded in droves with fantastic questions we've narrowed down to a couple. Can't answer every question every single episode, but we picked the best and brightest, and we try to tackle them here on the TechEd podcast. The other thing that we do is that it's not just Matt Kirkner speaking on this particular episode, our producer, the heart of the TechEd podcast. Ms, Melissa Martin is joining us to ask the questions and respond to a few of the answers. So Melissa, welcome back that side of the microphone, this side of the microphone again. Great to have you with us.

Melissa Martin: 1:31

Thanks, Matt. Great to be here again. It's always fun. It is always fun. All right, so we got a number of questions, again, submitted. Thank you to everyone for submitting those. And I'll tell you this, because we had so many, we have to pair it back so that we can fit into our allotted time frame. So if we didn't get to your question this time around, we'll make sure to get to it next time. So again, subscribe. Stay tuned. We'll do this every single quarter. And again, for anybody, you got ideas, you've got questions for us, you can always throw them in that, submit your questions spot on our website, and we'll save them for next time around. But Matt, are you ready for the Spanish questions? All right, so the first question comes to us from Gustavo Gomez. Gustavo is a professor over at Purdue Global University, and he says, I'm working on a new course called production, machine, technologies and tooling. I was wondering if you have a presentation geared to that subject and anything around automation and robotics, so I'll let you rephrase that question.

Matt Kirchner: 2:28

Gustavo, he said, Yes. All right. Gustavo, thank you for a terrific question. Thanks for somebody being somebody in higher education who is focusing on this. This really cool question is about, what should we be teaching in higher education when it comes to automation, robotics, machines, controls and so on. So really, really awesome that you're that you're thinking about it that way. So let's, let's start with thinking about what's important in the university program when it comes to advanced manufacturing. And you know, we've had so many guests on this podcast, folks that are working in manufacturing who have come to us, and maybe, I don't know, complaining a little bit about the whole idea that, boy, we get these engineers and these technical folks out of four year programs. They're smart, wicked smart. They're really, really good with numbers and data and theory, but then they're scared to death when they get out on the shop floor. And so in answer to the first part of the question, do we have any presentations and so on, absolutely, we've had dozens of episodes of the podcast talking more specific terms about what we should be teaching at the university level when it comes to advanced manufacturing. So we'll link a few of those up in the show notes. But let's think about this. First of all, we've got employers that are coming to us and saying, Hey, I've got engineers, for example, that are coming out of four year programs. And they're, I'm just quoting them. They're, you know, they're no good to me for the first two or three years I have them because they haven't spent any time on the shop floor. So I would say the first thing to think about is, yes, we have to have engineering talent that understands calculus and physics and has gone deep in math. I mean, we get that that's important. We know a bed has all kinds of all kinds of requirements around that. The HLC has requirements around that we I understand all that stuff, but the truth of the matter is that if we're going to produce students who are job ready to add value in manufacturing, they've got to have that hands on experience as well, and so lots of different ways to do that. I'll point as an example, because it's fresh in my mind. What's going on at the University of Wisconsin. Stout recently announced a huge partnership with with an employer in western Wisconsin. They are putting in all kinds of hands on experiential learning. So they're they're adding, in that case, you know FANUC Robo drills with with robotic machine tending fanic controls, which we know are big fan of. FANUC fans here on the TechEd podcast, where students are learning hands on technology. They're doing some things with an enterprise smart factory system, and literally learning the fine. Are aspects of data acquisition, smart sensors and smart devices. What? How you know how a PLC works, how we acquire data, what we do with that data on the cloud, how we protect data in a manufacturing operation, manage switches, unmanaged switches, all these kind of things. What is an ERP system? How do we pull data up to an enterprise level software program to be able to to work with that data. And how do we integrate all these technologies, things like conveyors, and we mentioned sensors, programmable logic controllers, stepper motors, you know, all these different technologies you see in manufacturing. It's that hands on integration part. So, so I think, you know, in any four year engineering program, yes, get to cover the theory. Let the students do some fun stuff early on. Don't save all the cool hands on stuff for junior and senior year. But then let's really embed their some awesome hands on projects, work based learning and a capstone project that requires them to put all these, all these technologies together. There's, there's more and more four year universities that are doing this now. Purdue global is a great example of a spot where folks can get good, you know, Polytechnic education, good hands on learning. But those are the kinds of things that I would be thinking about. Is that, yeah, we can do a lot of cool stuff in the lab. We can do a lot of experimental stuff and experiential stuff, but let's also make sure we're getting good hands on experience with authentic manufacturing equipment and technology.

Melissa Martin: 6:21

And I'll just maybe ask a follow up question, Matt. So it sounds like Gustavo has got, you know, one course that he's working on. So if you had to boil it down to like you've got one course to teach the most fundamental things, what would you include in that?

Matt Kirchner: 6:35

Yeah, so I'm gonna make the assumption that the students outside of this course are getting some of that fundamental, data analytics and data acquisition, and what we're doing now with AI and analysis and those kind of things. I would say it's a handful of things. I would say, first of all, let's think about that authentic manufacturing technology. So what is discrete IO or a programmable logic controller doing? That's the computer of manufacturing. I would think specifically about things like ultrasonic sensors, proximity sensors, temperature sensors, moisture sensors, force sensors. So how are we using sensor technology at the edge? I would get that in there for sure, you're going to want to teach some basic machining, or subtractive manufacturing. So you think about a machining center where you're removing metal from a part to create another part or removing metal from a substrate. You'll definitely want to get that in. You probably want some basic metal fabrication. So what is a punch press? What is a turret press? What is a press brake? How are we fabricating metal? How are we welding metal? You're going to want to work in. In addition to that, like we said, you know, conveyor technology, electric motors, you're going to want to understand electric motors, variable frequency drive. Variable frequency drives, motor control, mechanical drives, which they're going to be learning some of that outside of that course, but understanding how to gears, pull these shafts and so on. Work in a manufacturing environment. You're going to want to work in some fluid power, so hydraulics and pneumatics, that depends a little bit on, you know, which of those focuses depends a little bit on where you are and what your employers are doing, and then, you know, the automation and robotic side. So you need to have both, you know, a six axis traditional industrial robot. Everybody looks at collaboratives and says, Oh, that's what everybody's using right now. 90% of the robots, probably more, that are used in manufacturing, are still traditional six axis robots. And that's not just because that's what people have bought in the past. It's because, based on precision and payload capacity, a lot of times a you know, a traditional six axis robot is the best application. But then we also have to teach collaborative robotics as well. So I think those would be the basic elements that I would place into that program. Look, I recognize that the four year level, a lot of times we're constrained in terms of budget, our community and technical colleges, many times for equipment, are better funded than our four year universities, but those are the kinds of technologies we have to start building around, if for no other reason, that that's what our students are going to see when they get to manufacturing, and that's what employers are expecting students to know.

Melissa Martin: 8:59

100% your employers will get behind you, 100% when they percent when they hear that. That's the kind of course you're going to put your engineering students through, absolutely all right. The next question comes to us from Michael McArdle over at Western Technical College, and Michael asks students, use AI, but do not question the results. What are some strategies to have them see the futility of that approach? Yeah.

Matt Kirchner: 9:21

Well, so I guess the first thing is, if you know, looking back to all of our education journeys, don't be afraid to tell them they're wrong, right? I mean, if I, if I answered a question, whether I, you know people long before AI, whether I did it in the classroom or outside of the classroom, regardless of how I did my research, if that answer was wrong, my teachers weren't afraid to say, look, that's seen a nice try, but you're wrong there. So let's start with not being afraid to to, you know, to call that out. The truth of the matter is, accuracy is important. It's important in the workforce and in the workplace, and it should be important, and often is in education as well. But I, you know, I go back Melissa too. I had a sixth grade teacher, and Mr. Schumann, his name was, and one of the things that. We were required to do during sixth grade, and you got extra points. And this is back in the days of newspapers and magazines and whatever. Nobody was, you know, nobody was going online and looking for anything back then, you got extra points. If you could find an error in a news article, really, and bring it in, you got extra credit for that. Wow. So when you were in and, believe it or not, it happened quite often. I mean, this has been the days of typeset. And you didn't have spell check and so on. Yeah, about once a week, if you read the paper often enough, you'd find a mistake in an article, either a factual mistake or a grammatical mistake or a spelling mistake, and you bring it in and get extra credit challenge students to find where generative AI is wrong. Generative AI isn't perfect. We know that it hallucinates it's getting better. I was just listening to a podcast. It was a Joe Rogan podcast, actually, with Jensen, Jensen Wong from from Nvidia. But they were talking about how AI and generative AI is hallucinating less and less and less, which is why people are using it more and more and more. Is just becoming more and more accurate. But I would say, have a student, you know, just understand that you can't just take what that generative AI is telling you and take that as fact. And I've gotten myself into into trouble when I'm doing quick research for the podcast or something, and you jump on, you know, I won't embarrass any of the platforms, because they all do this, but it gives you a wrong answer. You write it down, and all of a sudden you use it, and then, you know, 10 listeners are commenting on whatever, saying you got this wrong. So, so at any rate, you can't. You can't just rely on the generative AI to give you the right answer. I would also so so challenge students to find it making mistakes and point out when it's making mistakes. Also let them know that they're responsible for their answers. They can't just blame generative AI for that answer. Use a transformer. Use a GPT that gives you its sources. Several of them do so you can actually go through and if it says something, it'll go back and it'll show you its source material for whatever it was telling you. Use that. But then the other part of it is we've got to put the challenge to teachers and educators and say, Look, in this age of generative artificial intelligence, you've got to step up your game, and you've got to find new ways to challenge students, whether it's talking about material, whether it's you know, rather than asking them to write a report outside of class, maybe they come in and they write a report inside of class, or you have them read an article, and then they have to come in and tell you a little bit about what they learned using generative AI as as an assistant, but Not as the as the source material. And then I think the other thing is just for students, it's time for them to step step up their game, so we can raise the bar on students. Doing research is way easier than it used to be. I mean, I don't have to sound like an old guy, but I remember, you know, we used to have to go to the library, find a book, and then, like, if you were writing a term paper, take the book over to the copy machine, make copies of the book, or do your research in the library, and then take all that home and write your term. I mean, think about that. And that's not like 300 years ago. That was like 20 years ago, 30 years ago. That was

Melissa Martin: 12:52

when I was in college. I mean, hours and hours and hours of reading all these reference materials so that you could write your paper and be well informed from, you know, these different authors who had different things to say about that, that topic, it's a lot of research,

Matt Kirchner: 13:05

absolutely so now, using AI, you can literally collapse what used to be maybe a semester to write a 20 of research to write a 20 page research paper to you could do that in a day. So Okay, step up the game. Set expectations higher. We have to find different ways to challenge students. We have to have them explain more about what they're learning, more group projects, all these kind of things, not just, you know, replacing rote memorization with the use of gender of artificial intelligence. So it is okay to expect more of your students, and the best educators and the best educational institutions are going to be doing that as the as the years go on in the in the age of artificial intelligence.

Melissa Martin: 13:38

That's absolutely right. And I would add to that, students need to understand these AI tools as they're they're designed to give you an answer, whereas a person, you ask them a question, they don't know the answer, they're going to tell you, hopefully, I don't know the answer to that. But let's look it up together. Here's where you might be able to find the solution. And AI isn't made to say, I don't know. It's May. If it doesn't know the answer, it will hallucinate, and that's what it'll make something up just to give you an answer. And so students need to understand that when they're using these AI tools, that they are designed to give you an answer, whether or not it's right, because that's just how they're programmed. So just have set that expectation with them as well, so they understand what these tools are for and what they're not for Absolutely? Yeah, great points. All right, so that kind of segues into another question, because there's this whole ethical debate around AI and you know what's right and wrong, and how much do we use it? And Holly Atha, over at the MBA research and curriculum center, asks a question. She says, what role do you feel ethics education should play in CTE, today and tomorrow?

Matt Kirchner: 14:40

Yeah, I love that question. And and a huge role is the short answer for a whole, whole collection of reasons. I mean, let's start with our last question about, you know, how students use AI for their their coursework and so on, recognizing you know that you don't, you've got to be, you've got to be doing your own work, that you don't take credit for somebody else's work, that. Kind of things really, really important, ethical questions. But it gets a lot deeper than that, you know, you start thinking about, you know, in the age of artificial intelligence, where computers are able to, at least on the technical side, you know, think as fast as humans can, and faster and no more and access more data and so on. You know, what does it mean to be truly human? Is a really, really strong question. When we start having agentic AI making all our decisions for us, and we can easily get to that point, what does it mean to be human? What does it mean to be human in an age where we don't have to work as many hours, because we can use AI robotics and automation to do a lot of the things that we used to have to do, physically, to where, literally, where, you know, anybody today can pretty much have within reach is the is the lifestyle of the wealthiest person 100 years ago, right? Like anybody today can have that can have the lifestyle of somebody that was like the wealthiest person on earth 100 years ago. And we're just gonna, that's just gonna continue. So we'll have all these questions about, what does it mean to have a soul? What does it mean to be human? How does that mean in terms of how we treat each other? How does that mean in terms of how we use artificial intelligence? We go back, oftentimes, on this podcast, to the book Genesis, which was Henry Kissinger, Eric Schmidt, as you know, and Craig Mundy, and they published that book about a year ago, give or take, and it's just an outstanding book, but they go deep into the exploration of ethics in the age of artificial intelligence and technology. So I think there, I think ethics plays a huge role. Well, you can weave it into weave it into the coursework. You can force students to think about ethical questions. I go back a lot of times. I was a business school major, but I went to a Jesuit university, and we were required to study nine credits in theology and nine credits in philosophy. And you really, you know, it didn't really, people would look at that and say, well, that has nothing to do with being a business person. Well, maybe. But what you learn in terms of how to think about humanity, how you communicate really, really important stuff. And so we're going to have tools at our disposal. In the future that can be used for all kinds of purposes. And people like, aren't you worried about AI being used for, you know, for really, really bad purposes? And the answer is, well, as long as people have good conscience are using it, and as smart, or smarter than the people that are bad actors, the better off we're going to be. But we need to weave that, that element of ethics into the into the coursework.

Melissa Martin: 17:22

Yeah, all the more reason to include it now with AI and everything, absolutely so next question comes from Bob Manning, over at Stillwater area high school, and Bob has a fantastic question. It's a little bit long, so stay long for the ride. He says, Hi, Matt, many schools, many schools would love to have the manufacturing programming that you highlight in your podcast. However, we all have different starting points and assets elements of quality programming that come to mind include visionary and strategic leadership, physical space, with modern equipment and infrastructure, genuine industry partners, teacher capabilities and buy in, funding options, etc. What do you think are the most important components a high school must have when attempting to build a robust manufacturing pathway for the sustainable future. Can you also rank them in order of importance? Or would it make the most sense to list what needs to come first, second and so on? All right? Great question. It's great question.

Matt Kirchner: 18:14

Yeah, absolutely. You know, and I spend a lot of time with educators, and I think kind of the default playbook a lot of times, is they all go to money, right? And I say all, I mean, I use that figuratively, but, but, but everybody comes back and says, Well, until somebody walks in the door with a million dollars, until we have a referendum that gives me, you know, $5 million to spend, until I have a school board, until I have a superintendent, a district administrator, you know, the list goes on that provides me the resources to be able to expand my program until I have those things. You know, I really don't have anything to do here because I couldn't afford to do it anyway. And you know, the first thing we always, and this would be number one on the list, is, before anybody's going to give you a penny, you have to have a dream. And you know, we've been involved in so many of these amazing K 12 projects and at other levels of education as well, but lots of high school programs where we're integrating all kinds of fascinating, amazing technology, autonomous vehicles, drones, flying drones, unmanned ground vehicles, 3d design and fabrication, coding, programming. I mean, all these really, really cool things. I think when Bob says the kind of programs we highlight on the podcast. Think that's what he's pointing to. All this really cool technology, robotics, automation, mechatronic systems, all those things cost money. There's no question about it. But if we start by saying, we'll, we'll, we'll work on this when we have the money, then that that never happens, right? What we have to do is have a dream that is so big that somebody's willing to fund it. And every one of these projects that I've seen where whether it's a community or an employer or a wealthy individual, or some combination, usually of all three of those, stand up and say, we're going to do this. It's because someone had a dream so big that they couldn't say no to it. So first thing I would say is, start with a dream. Think about what could be if you could have the coolest lab, the best program, regardless of what that. Costs, what would that look like? Yeah, and then create them. Create a message so compelling that nobody can say no. From there, I think I'm a huge believer in meeting every learner where they are, and I think this is really important, especially as we move into the future of education, is that we all have different learning modalities. We talk about that all the time on the podcast. I take sometimes, take this back to my days of selling manufacturing technology and so on. It's like you'd always say, Well, some people are auditory learners, or in some people are kinesthetic and some people are visual. So in other words, some people learn with their ears, some with their you know, with their eyes, some by doing, not right, wrong, good, bad. It's just that we're all different. So how do you meet every single learner, where you where they are? You have to have various modalities of learning, whether that's a lecture, whether it's hands on, learning, whether it's e learning, whether it's work based learning, all those things are great, great, great ways to learn. We have to have that. Number three, I you know, I'm a believer, as part of that, that you create some opportunity for asynchronous learning. I think we're getting away from the age of a teacher standing in front of a class and lecturing for, you know, for an hour, and then moving the class on to the next classroom and lecturing for an hour. I just that that that version of education was never for me. And so having opportunities where we take our high flyers and if they can move faster, let them go, and if a student, for whatever reason, needs a little bit more time on something that's awesome, just take the time that you need to be able to gain the competency. So I think, I think that's really important, is that is delivering asynchronous learning, and then making sure we've got a significant portion of that that's hands on, and that It's project based. And that's, I think, where the future of education is going and that puts a challenge on a teacher, right? Can you know, managing a classroom full of students working on projects all day might be better for the student. It's probably a lot harder for the teacher. Thank God for teachers that are willing to be patient enough to work through something like that. We need to have hands on learning, and the more technical and the more technology driven, the better. So that would be number three, and then the other fourth one is and all these tie together. But, you know, you got to have skills and competencies that lead to whatever comes next. And in a lot of times, I think that's, you know, that's career based stuff, right? So, you know, manufacturers who walk into a high school that wants to, you know, spend a bunch of money on a new lab that can't see a direct line from whatever that is, and, you know, a vinyl cutter sitting in the corner to a job at that employer. It's really, really hard to get them excited about that. So, and I'm all for, I mean, there's a lot of different age appropriate and great, appropriate ways to deliver learning, and we're not taking sixth graders and teaching them complex ladder logic on a programmable logic controller. Right? That comes later, but, but teaching students at the right level, you know, here, here's how to program a robot, here's how to operate a robot, here's how to program a programmable logic controller. Here's how you get data into and out of smart sensors. Here's what you do with the data set. Here's how you weld the part. Here's how you fabricate a part. Here's how you machine apart. Here's how you program a CNC machine. Having those kinds of programs in a high school, so that students are learning those competencies along the way, and then have job ready skills tied to and this would be number five certifications wherever we can so third party certifications that students can earn, that they can take to an employer and say, I know how to do this. This is what I learned in high school, creating a competency portfolio in addition to that, that high school diploma would be and I could keep going, I could come up with another probably list of 10 for Bob, but, but those would be my top five.

Melissa Martin: 23:35

All right. So, so to recap, for Bob and everyone else in our audience, and to make sure that I was listening so our five were have a dream so big that people can't say no to it. Two would be meet every learner where they are. Three would be asynchronous, hands on, project based learning. Four is make sure that it's career relevant and ties to something that they're going to see after school. And number five, ties to certifications and that they're earning something along the way. You could be a podcast.

Matt Kirchner: 24:01

Have to segue into the next question that's perfectly smooth.

Melissa Martin: 24:03

So my segue is that the next question has nothing to do with anything we're talking about. So we're gonna take a quick break from the technical education and workforce topics and go to kind of a an unrelated topic. If you've been around the TechEd podcast for a while, you'll know that sometimes we have really unique, fun episodes that kind of dive into topics outside of the classroom, but really, we always find a way to make it work within the greater technical education, data, skills, science, all that kind of fun stuff.

Matt Kirchner: 24:29

TechEd stem podcast about whatever we think is interesting.

Melissa Martin: 24:33

And so you did a really fun episode over the summer previewing the Tour de France, yeah. So we actually had somebody ask a question about that. So Bruce, Bruce Anthony reaches out and he says, Do you think today will win the 2026 Tour de France? Follow up question, who will be the next rider to win the yellow jersey competition not named today? Wow.

Matt Kirchner: 24:57

Yeah. That's an awesome, awesome question from Bruce the. Answer his first question is, yes, there's, I mean, so the thing to know about cycling, like any sport, there's a lot of wild cards, right? Yeah, but if you stay healthy and you don't crash, right, those are kind of the two big things. Then I think, you know, if today makes it to the tour without a significant crash, if he if he's as healthy next year as he was this year, no reason to believe he won't be. I don't know that there's anybody that can touch him. He ran away with the 2025, Tour de France, you know, I think, I think Jonas finger go still has few years left in him, and he was today's, you know, and has been his, his kind of most aggressive rival over the course of the last several years, five, six years or so, you know. I think Jonas has a chance, and it really depends on what his conditioning is coming into the tour next year, but if he rides at the highest level that Jonas can ride at, I think he's got a chance to at least make it a competitive tour. My bet would still be on today. Pa, gotcha next one not named today to win the Tour. If it's not Jonas, there's a lot of people I'll highlight too. Remco venopol has been one that we had our eye on last year and and I would say that he is still, I mean, if you look at the rankings, the top 10 or 20 riders in the world, Remco is still right there. And the other one I'll add is a little bit of a wild card, because I have a soft spot my heart for him. Would be Mateo Jorgensen, American writer, okay, he's probably not top 10, but he's probably top 15 right now. And as we talked about on the podcast, actually, our son, who raced for the junior development team for track bicycles for a whole bunch of years when he was growing up, actually raced against Mateo at junior nationals a couple times. So and again, got beat pretty handily by Mateo, I should say, but, but would to be, you know, be at the starting line with a guy that eventually is competitive for the tour was a really, really cool thing to look back on and and think about so, so Matteo Jorgensen, Bruce. Bruce would also, also be on that, on that list, and hard to believe. We're, you know, almost six months away, a little bit more than that, from the next year's Tour. So it won't be long before we're, you know, before we're handicapping bike racing. Maybe Jason will come back again this year, and if it's not Jason, I'll guarantee some high profile cycling expert that will will have joined us, because that was a

Melissa Martin: 27:08

really fun episode. Yeah, that was a fun one. And did did some great tying back into science, the nutrition science data, all the data that goes into preparing these teams so

Matt Kirchner: 27:18

it drives technology shifting, all that, getting excited already.

Melissa Martin: 27:23

All right. So back to our education topic. So the next question comes from Michael ezeki, and he asks, educational institutions are less tuned into dashboards? Can you suggest some good dashboard metrics for work towards development programs in education?

Matt Kirchner: 27:38

Oh, that's a good one metrics. And he's right. That premise less tuned into dashboard. So we think about, Yeah, we love metrics. You think about data and manufacturing? What's what gets measured improves? Everything's about data. Everything's about metrics. And I would just say to kind of introduce the answer to that question, having been involved in a lot of these projects where we've got manufacturing companies, private employers that are funding work, workforce, or or technical skills training programs at their high schools, for example, technical community colleges as well. That's one of the questions they'll ask. Is they're writing that check is, what are we going to measure? How do we know we're successful? And so you can make a list. We'll talk about it here in a moment. The thing that's interesting, though, is six months later, a year later, when that employer comes back and says, you know, we wrote that check for a million dollars. How we doing a lot of times, in fact, most times the educators are surprised that they're asking. And I, you know, I don't know. I won't make any judgments about that education versus versus industry. People can draw their own conclusions, but I will tell you that if you are partnering almost to that early, earlier question from Bob, if you're partnering with a private employer, and they're writing a check, and then part of the expectation is that we're going to create the next generation of workforce, that we're going to get young people excited about careers in manufacturing, that we're going to have people graduating from those programs and going on to related Programs in Higher Education, or coming to workforce and working in manufacturing, and those are the expectations that have been laid out. Yeah, those employers are going to expect you to hit them, and so expect that conversation, and it's they won't let you off the hook that way. They don't do that in manufacturing. If you say, in manufacturing, we're going to increase throughput, increase throughput to this, or we're going to get our revenue number to that, or we're going to get our gross profit margin to this. And that's a goal. You set that goal, and you come back and maniacally measure that if a if a manufacturing employer or a private employer sets a goal for a school, and you jointly agree to that, expect them to come back and ask about whether or not we got there, because they're going to So measure that all the time. Here are some of the metrics now that we've got that topic introduced. You know, the first one is, how many students are participating in the program, right? So if we put together a manufacturing or Work Based Learning program or a work based skills program, I should say in a high school, how many students are signing up for that course, how many students are completing the. Course, that's going to be a key metric. Almost every one of these now has third party credentials tied to it. So yes, the students are earning credit in the school. They may be earning dual credit at a technical college or a university related to the coursework that they're doing, and they're earning a third party certification. You know, there's lots of them out there. We talk a lot here about manufacturing skills Standards Council, the smart automation certification Alliance, the two are my favorite, nocti, this was right up there as well. So those are just some examples. But if we're tying third party credentials, how many students are earning those credentials? What credentials are they earning? And then it's going to be about All right, how many of them are working in manufacturing during the summer, in between the school year, how many of them are choosing careers in manufacturing or choosing manufacturing related coursework beyond secondary if they're going on to a technical community college or university? So those would be the ones that would be on my list. I would certainly think about how many students are participating and what certifications are they earning? And you know, where are they going after after that program, after high school? Those are probably the three, the three biggest that employers are going to want to look at perfect.

Melissa Martin: 31:10

So expect to have those metrics. If you're getting money from a private donor, it's the same thing, like you have to report back on your grants. You know, you get money from the government or from something, you have to report back on how that grant money is being used, right? It's the same thing here.

Matt Kirchner: 31:23

Yep, and you'll get follow ups too. So it's not enough to just answer the question. Or, you know, sometimes you get a little bit of the bobbing and weaving. You know, I'm not, and I'm not trying to paint these employers as mean spirited, or I mean, or what have you. It's just that they're metric driven. That's why they're I mean,

Melissa Martin: 31:36

if you think about if you put money, if you put some of your money into an investment portfolio, and then you don't find out how it's performing, you're going to take that money right back out. You're not interested in continuing to invest. And it's kind of they're looking for a return on their investment in terms of the skilled workforce coming out, students interested in manufacturing careers, as one example. And if you do give them really great metrics and show them the benefit of their investment, the upside is they're going to continue to invest got

Matt Kirchner: 32:02

it? Yep, that's a great analogy. Awesome.

Melissa Martin: 32:04

Okay, so I'm going to keep on this kind of concept of employers, workforce and certifications with a question from Brian badura and and Brian says higher education is at a tipping point with more flexibility than ever before to complete degree and sort of certificate programs. How do we help employers understand the value of these new educational choices when many HR teams and executives may not understand how to integrate educational programs like three year degrees or advanced certifications into their job descriptions and the workforce?

Matt Kirchner: 32:35

Yeah, so awesome question from Brian. Let's see. We'll take half a step back and really, you know, he has some really good examples, like, you know, you know, three year degrees and certifications and so on. You know, first, a little in defense of employers. You know, partnering with education as important as it is, is never, this is never at the top of their list. And the reason for that is that they're trying to manage a workforce. They're trying to keep customers happy. So think about somebody in human resources, the stuff they're dealing with all day might be a discipline issue. One day it might be an attendance issue. Another day it might be somebody quit their job and you need to fill that job, or you got a big project and you need to staff that up. Or, you know, you've got a regulatory audit or you I mean, their days are filled with all this kind of stuff. People in manufacturing are trying to crank orders out. They're trying to meet lead times. They're trying to improve quality. They're trying to expedite orders solve a quality issue that already got out in the field. I mean, that's the day of a manufacturing person. So, so in defense of them, you know, they've got their own priorities that they're working through, but the short answer to Brian's question is seven times seven different ways we talk about that all the time here on the podcast. It's not enough to tell somebody something once I can tell you, boy, somebody should sometimes ask me a list of my greatest frustrations in working in education and manufacturing. Near the top of the list Melissa is the number of people in HR functions that don't understand the value of third party credentials. And you know, they they obsess about wanting more people to come into manufacturing. They obsess about wanting more people to fill their workforce, to enroll in technical college programs or community college programs that are that are related, but then they they don't take the time to value and understand what's available to them. And I'll just give them not a little bit of a calm rant right now. You know, you hear a lot of you know, a lot of folks say we want, we need more skilled people. I just had a meeting like this. I was in, I won't say the state, I was in another state within the last few weeks talking to an owner of a major manufacturing company, yeah? And they were just like, Yeah, we don't, we're not seeing the people coming out of the technical college program that's related to the work that we do, it's in manufacturing. And they're like, where they're just not producing enough, enough people. You. And then I've sat in the same room with that same company as they're telling their employers, well, all we really want is people that will show up to work every day, stay off of drugs and take direction. And I'm like, and they're telling their educators that. So if I said employers, I might say, educators. You can't have it both ways, right? You can't. And this whole idea, I mean, I'm the biggest believer in soft skills. Yes, we need people that understand professional behavior, workplace behavior. Just wrote a magazine column on that for Gardner Business Media get published in January of 2026 yes, we need that, but we can't simultaneously say that that's all we're looking for and then complain when we're not getting skilled talent from our from our educational institution. So there's just a lot of things that I think are happening in education, a lot of trends, like third party credentials, like three year baccalaureate degrees. And that's, you know, that's something that's definitely on the way it's, it's a hot topic in my home state of Wisconsin, and it'll be a controversial one. So the you know that that's not going to be a heavy lift, especially for public institutions, but it's coming and but what we need to tell those HR folks, every opportunity we have them, what's available in education, what's happening in third party credentialing, what's happening in innovation, what's happening in hands on learning. I mean, there's all of these great things that are happening in education. What's happening with teaching authentic industrial skills. So if I'm a machining company and any machining talent, I need to be teaching that technology, like we said before, in the classroom, in the lab, in the high school, getting students excited about it, credentialing them, sending them direct to workforce, sending them to a Technical Community College program where they can build those skills. And that's how we create the next generation of the workforce. So there is no easy answer to Brian's question other than like anything when we say seven different ways, you can tell somebody something once, and it may not sink in. In fact, it usually doesn't once they hear it seven times through seven different modes. You know, we talk about email, social media, traditional media, having a conversation, doing a site visit, sitting in a meeting, same message over and over and over again. Sometimes people say it seems like sometimes on the podcast, you make the same points week in and week out. That's on purpose. You remember those points exactly you got. Yeah, thank you for listening. And it obviously worked, because he caught that. Yeah, it's seven times, seven different ways.

Melissa Martin: 37:16

Awesome. Yes, I don't have anything to add that. That's just absolutely true. Okay, so we've got time for one more question, all right, and this is actually with a future guest of the TechEd podcast, and we're going to end on an AI question. I love AI questions. Get so many AI questions. We love it. It's such a great topic. Okay, so Peter mera, he says AI is about to out think us in almost every technical domain, the real advantage will be in what makes us human, such as EQ, adaptability, creativity, courage, judgment, wisdom, ethics and so on. So what's going to take to blow up the old model of technical education and rebuild around the skills machines can't copy so our workforce doesn't just survive the AI era, but thrives in it?

Matt Kirchner: 38:01

Yeah, it was a great question. And I think the key, there's a key word in the first sentence which is technical, right? Just reread that first. I want to make sure that sinks in with the audience, yeah, because reread that question,

Melissa Martin: 38:10

AI is about to out think us in almost every technical domain.

Matt Kirchner: 38:14

So when we say technical domain, it's not going to out think us in every domain. It's going to think out, think us in every technical domain. And there's actually some debate about how soon that happens, right and and we'll see. I mean, some people would tell you it's going to happen in 18 months. Others are saying it might be more like 10 years. Nobody knows for sure, but certainly, if anybody who's watched the advancement, it's not just generative AI and what we're capable of doing with perplexity, cloud, meta, chat, GPT and so on, Gemini, and seeing just how that's advanced in the last year, year and a half. And it's incredible, right? So, so it's anybody's guess how quickly this is going to extend itself to physical AI, in the rest of the world. I think it's a really, really good question. You know? What happens in an age where a computer can answer any question, what happens when a computer can, or AI can program a CNC machine? What happens in an age where, where AI can program a program, a logic controller can write any code? Can, you know, fill in the blank we're already seeing now, where some of the you know, some of the opportunities for computer science majors, especially ones new to the workforce, and data science majors and so on, struggling a little bit to find jobs, or at least jobs that pay what they want them to pay, because there's so much of this can be done with AI every single day. There's another article in the in the Wall Street Journal about what AI is doing the workforce. Another one just this morning, as matter of fact. So so all. I mean, I think Pete's, I think his premise is a good one, which is, we're going to get to this point before too long, before too long, before AI can do even more than it's doing now, and that is going to have a huge disrupting impact on the workforce. And so what you know? What do we need to do to our technical programs, technical education and all that STEM programs to make sure that we are future ready in those programs? I think a lot of things. That we need to do we're already doing in education. Not enough educators doing it. We've talked on this podcast a number of times how AI education is mandatory in China. It's not in the US, and even when it is, when we're teaching it, a lot of times it's just teaching gpts and prompt engineering, which is fine, but there's so much more to AI when it comes to applied artificial intelligence, humanoid robots, quadropods, drone technology, 3d design and fabrication, some of the coding, programming, video game development, autonomous vehicles, applications for battery technology, electrical vehicles, biomimicry. I mean, all of these things are changing. The entire way that we engineer, the way that we design the way that we innovate, and so we have to prepare students with the kinds of skills that will be relevant in that age. There's schools doing this right. We talked not too long ago with the CEO of Ashley Furniture, Todd wanick, and not long before that, with the superintendent of the White House School District, Mike Bigley, about applied artificial intelligence learning about how we can put students through an E Learning course that helps them understand applied AI and what we call the edge to cloud continuum. And this is where I think we're getting to the core of Pete's question is you have to teach how. And this is nothing new to our audience, but sensors at the edge communicate with control systems communicate with regional data centers, data collectors, computer networks communicate with the cloud. And what is happening at every single level of what we call the edge to cloud continue, because AI isn't about just what the algorithm is doing and what's happening at the cloud level. What's happening, you know, behind the iPhone, if you will, it's how are we, how we're gathering data, extracting data, analyzing data, discerning data, storing data, what we're doing with it, and then how we use that to improve literally, every aspect of the economy, whether it's energy, defense, hospitality, retail, manufacturing, smartphones, every single aspect of our of our economy, precision agriculture. It's changing everything. So we have to turn our students into systems thinkers when it comes to AI and how they're analyzing every single thing they look at, as far as that edge to cloud continuum that's happening already in in technical colleges, we're doing a number of projects where we're, you know, doing cause cloud based analysis on data that's been pulled off of manufacturing equipment across an entire technical college. We have things like that going on at Gateway Technical College in Kenosha, Wisconsin. And there's a couple other great examples of how we're doing that at the technical college level, at the high school level, the whole, you know, the whole idea of discover AI and full disclosure, I think people know we have a financial interest in that effort, but discovering how artificial intelligence manifests itself across the entire economy, that's what this is about. That's how we blow up education. I mean, if Pete wants to see some really cool stuff, go to an emerging technology lab, go to a discovery I lab. See where you walk in the door and you've got, you know, three students working on drones and another three working on autonomous vehicles, another three working on, you know, 3d design and 3d scanning. Three more are, you know, are building their own, their own video game. They're earning competency credentials and creating that competency portfolio the whole way through kind of stringing to a bunch through a bunch of themes we've had on this episode of The TechEd podcast. That is the future of education, and we can do it at every level. It's asynchronous, it's student driven, meets every student where they are, and it prefer, prepares the workforce of the future. I think, I think pizza asked a really, really good question, and it was one I was happy to answer.

Melissa Martin: 43:25

So that's future of technical education. That's going to be a really, really exciting time. And I think a great way to end this episode. As we wrap up, 2025 look forward to 2026 think about what the year ahead holds for technical education. I think that this is there's a lot. It can feel overwhelming to educators, but I think that there's a once in a lifetime opportunity for us in the world of education, if we can embrace the change and really do it for our students and for the right reason, because if we don't, we're doing our students a disservice for their future. So I'm excited about 2026

Matt Kirchner: 44:00

How about you. It's gonna be amazing. Yeah. In fact, speaking of being excited about 2026 we've got some really cool episodes teed up, right? A predictions episode, which we do every year.

Melissa Martin: 44:08

Yeah, that's coming out next week. And you guys love our predictions episode. And in case you don't know, every single year, Matt makes predictions about what the future will hold for that year, and he always ranks himself on how well he did the previous year, and you You're pretty good, right? Reading for years?

Matt Kirchner: 44:23

Yeah, we'll see how we did this year. I have an inkling that we were pretty solid.

Melissa Martin: 44:26

I have an inkling as well. So, yeah, excited to release that next one to our audience. So if you aren't subscribed, make sure you subscribe. That one comes out next week, Tuesday.

Matt Kirchner: 44:37

Wow, awesome. Yeah, super, super excited for that. Any other episodes coming up, the audience should be thinking about

Melissa Martin: 44:42

there are. But I I'll just say you have to say subscribe, because we got some really high profile guests coming out in early January. So make sure that you're subscribed. We're on Apple, Spotify, any other podcast platform that you might be listening to, if you're only listening to this, by the way, we're on YouTube and so. If you like watching rather than listening, you can go find us on YouTube. Watch those episodes there. If you're watching us on YouTube, hi, it's great to see you, and you can always catch us again on Apple Spotify or wherever else. Tell your friends awesome.

Matt Kirchner: 45:13

Please. Tell your friends glad to be here with my friend Melissa Martin. We had a great conversation. She does such a wonderful job of pitching those questions up and responding to the answers as well. Always a lot of fun. We'll keep teeing up these episodes of Ask us anything, so be sure to keep sending your questions our way. We'll get through as many of them as we possibly can. Can never hit on all of them, but love to, love to pull the best and brightest and kick them around here on the TechEd podcast at least once every three months or so. So thank you to our audience for being with us. It's been a wonderful episode of The TechEd podcast. Don't forget to check out the show notes. We referenced a few things we promised to link up for folks that asked those great questions and the folks that listen to the answers as well. So check out the show notes. Those will be at TechEd podcast.com/ask us anything that's TechEd podcast.com/ask us anything where you will find loaded up, not just this episode, but every episode of Ask us anything. So you can go back, if you like, this format, and check those out when you're done checking those out. Check us out as well. On social media, you'll find us on Instagram. We are on LinkedIn. We are on Tiktok, on Facebook, anywhere you go for your social media, and on YouTube, by the way, as well. You can check us out there. Make your comments there as well, but please comment, reach out, let us know you're out there. We would love to hear from you. Thanks for being with us on this episode of The TechEd podcast. For our producer, Melissa Martin. My name is Matt Kirkner. I'm your host. We'll see you next week. You.