How a University Teaches AI, Then Checks the Work | Cate Tolnai

In this episode of the Getting Smart Podcast, Mason Pashia talks with Cate Tolnai, director of Microcredentials and Innovation Credential Strategy at the University of Phoenix, about how skills-aligned micro-credentials can help learners show what they know and take their next step. Cate shares how Phoenix is building verified, portable credentials and Learning and Employment Records, how AI use can be taught and assessed as a skill, and what K-12 schools, community colleges and career and technical education programs can do to connect to this work. It’s a conversation about treating every micro-credential as a milestone on a lifelong learning journey.

Transcript

Introduction

Mason Pashia: You’re listening to the Getting Smart Podcast. I’m Mason Pashia. We recently put out a conversation with Kelly Page and another with Jacksón Smith, both individuals that I met at this year’s Digital Badge Summit, and in their conversations, they helped me to chart the current landscape and direction of digital badging and credentials. Today, we have another Badge Summit connection and a further unpacking of what credentials are, what they mean, and how they’re being used today, with Cate Tolnai, director of Microcredentials and Credential Strategy at the University of Phoenix, and the person with the best sketchnoting doodles at any conference. Cate, thanks for joining me.

Cate Tolnai: Thank you, Mason. This is awesome. I’m so glad we’re getting to do it.

Mason Pashia: I know. Good to see you. Not around, like, one of those gas-fueled fires at a restaurant or something.

Cate Tolnai: No, but I’ll take that too. If that’s how I get ya, I’ll take it.

Mason Pashia: Absolutely. Well, I’m excited to hear more about your backstory. I feel like somehow that never comes up when you’re chatting with people at conferences. And so tell me about how you found your way into this work to begin with.

How Cate Tolnai Found Her Way Into Micro-Credentials

Cate Tolnai: Yeah, so I was born… No, I’m just kidding. I started teaching. I taught high school and middle school English and history. Fast forward 10 years, I started really geeking out around how all of the Google-y docs and files, and this was before Google Classroom, but all the ways I was able to connect with my students through technology.

And I just thought, “This is helping me build relationships with kids that I wasn’t able to reach otherwise.” And I wanted to talk about this with teachers. I wanted to share these moments with other people, and so I ended up getting a certificate to be an ed tech specialist through Boise State online, and then that gave me the confidence to apply to be a district-level teacher on special assignment for ed tech.

And then I just kinda grew with it. I went from district level to county level in Santa Clara, California, which is Silicon adjacent, Silicon Valley adjacent, which meant, like, we were epicenter with all the different, you know, development at all the different tech companies. And we had access to all the school districts that they wanted to get.

And so it was really interesting. I started dialing into, like, how industry, how these ed tech companies were trying to position their products for teachers to reach the kids. And I was really drawn into that, just, like, personally. So when I was at the county office, we wanted to scale our support, and we knew that holding in-person PD was an equity issue for teachers that couldn’t stay after school, had to go get their kids, had to work another job.

Like, it just felt like there was a gap in support. So we continued to do in-person trainings, but we also created these asynchronous modules in Canvas to basically… Like, we took the Google for Education level one certification, and we deconstructed it into learning modules, and we offered those for free to our teachers.

And then we created micro-credentials that acknowledged these, like, chunks of learning, so that even if a teacher couldn’t finish the whole certification, they would walk away with a specialty in, like, Google Apps for Education focused on creativity or focused on collaboration, the four Cs. And I just was like, “This is…”

To be able to, like, acknowledge a teacher’s growth in these specific areas and help them gain confidence, it just was really exciting. And so that was my first opportunity to go from, like, attendance badges that I was doing at the district level to now actually, like, academic for-credit courses because we partnered with another university, and they could purchase CEUs as they were completing these modules.

So it was just like the full circle, like, “Wow, this is really something that could work and change the lives of teachers and students.” And I just kept, like, clawing at the space. I mean, like, you know, I came into the micro-credential world in, like, 2011 when it was just the baby world, and now we’re here, and I’m super honored to be a part of the work that we’re doing at Phoenix, where we’re creating industry-aligned micro-credentials with words that hiring managers are looking for and that students need to use on their resumes and in cover letters and in interviews.

And we’re putting them in these packaged micro-credentials that are verified and reliable and digital and portable, all the things. And we’re saying to the students at Phoenix, we’re just like, “Hey, if you don’t finish your program, but you walk away with these micro-credentials, like, how might that empower you in your career?

How might that empower you just in your confidence and, like, your ability to wake up every morning and, like, head into work?” So it’s been just this really special journey of personalization and just acknowledging, celebrating the work that’s happening.

Who the University of Phoenix Serves

Mason Pashia: That’s so cool. I’m excited to dig into that work that you’re doing now. But tell me what makes University of Phoenix unique? Like, who does the institution serve? What does it look like? What are people typically studying there? Tell me a little bit about that.

Cate Tolnai: Yeah. So University of Phoenix is… I like to say that the University of Phoenix serves those that our traditional systems have underserved traditionally. So, like, when you look at just our demographics, our average age is 37 years old. We are seven out of ten female versus male enrolled students, so high.

And then six out of ten identify as a minority. And so we have just mature individuals that have worked their way a lot, a huge veteran population, a large number of students that are coming back after maybe starting college or not finishing it. And so we offer just options. This is just, like, in the grand scheme of the ecosystem of learning, Phoenix serves a community that has, I don’t know, traditionally been forgotten.

And so every day I wake up driven by that concept. And I think that’s across the university. That’s how all of us feel. Like, we understand that the work we’re doing to empower learners and to, like, take these kind of overwhelming, sophisticated academic programs and deconstruct them into these skill-aligned modules of learning and these courses.

One, you know, one course at a time, five weeks, you’re gonna get your skills, industry-aligned skills. You’re gonna be able to demonstrate and earn those. You might even get a micro-credential all on your way to, you know, wherever your destination is. For some, it’s gonna be a final degree. For others, they just wanna get that next step up in their career.

And they might need just a couple credits. Others are gonna find their career opportunity mid-program and maybe not finish, and that’s okay too, because our motto is career early and often. So it’s just a really special place to be, and I think the team members that I work with, so many of them have been at the institution for ten, fifteen, twenty years.

Like, I’ve only been there a year, you know? And so I just kinda look around going, “This is incredible, the institutional knowledge and, like, the deep, deep-seated commitment to the community.”

Skills-Aligned Curriculum and Stackable Badges

Mason Pashia: So, you kind of described the current project, which is to really make these micro-credentials that are portable and verified and all this. I guess what stage in that process are you at right now? And then I have a lot of other questions.

Cate Tolnai: Yeah. So I’ll answer it really short. We skill aligned our curriculum back in 2020, which means that every credit of learning is aligned to a student learning outcome, which is assessed in a summative assessment, authentic assessment, by faculty, and then aligned to an industry skill.

And so once we did that work, we were able to start stacking skills across… At that time, we were stacking them across courses for some of them, and some were just staying within the course. But basically, we were able to stack the skills to create these micro-credentials or these badges. And I use those synonymously with different audiences, even though we know the difference.

The badge is the image, the micro-credential is the record. But for the sake of not confusing things, I’ll just call them badges. So we’ve aligned all of our courses to the skills, and then when the colleges identify an opportunity to kinda call out a set of skills because they’re trending in the job market or they’re high need within an industry.

Like, I’m working with our College of Nursing right now, and we are working on a micro-credential for medical coding because what they identified was, like, if a non-nurse practitioner can actually, like, code, understands medical coding, they’re a total asset on their team, and that is something that, like, someone within their program could earn, like, a specialty acknowledgement by getting that micro-credential, which is gonna set them ahead when they start to apply to jobs.

Mason Pashia: I really like that specificity of skill in the industry, because I think a lot of the time where people get intellectually hung up in this conversation is when you start to bring durable skills in, because they’re famously so challenging to prove. To say one context is similar to another context in which it… By focusing really on this atomized version of skills within an industry, you can make these really meaningful, laddered communication attempts to employers.

I think that’s really cool. How do you, as an institution, store this information, and then how do individual learners do anything with the image of the micro-credential, et cetera?

Cate Tolnai: Yeah. We… So within our systems, we have a pretty substantial set of microservices that we use to track this, to, like, issue the skills. And we align to the Lightcast taxonomy whenever possible, because that then allows us to validate some of those skill choices based on… Like, if you’re familiar with Lightcast taxonomy, they’re basically scraping thousands, tens of thousands of job descriptions and gleaning from those, like, the words that appear most over time.

And so if we can then crosswalk our skills to the words that are gonna appear in job descriptions, that’s just a bonus when that works. Sometimes it doesn’t though, especially with our programs that are heavily regulated, like our nursing and education. Those words are determined through our industry advisory council or even just accreditors.

You know, there’s just words we need to use that are gonna make sense within that field that might not appear in the taxonomy. Once we identify all those skills in the way that makes the most sense, and we start to organize… we have it all organized within our microservices. And we hold that data within our achievement record, which is not a fully fledged LER quite yet, Learning and Employment Record, but it is, like, dangerously close.

Learning and Employment Records and Career Navigator

Cate Tolnai: And so we’re just standing up our strategic initiative for this fiscal year that will result in a fully fledged Learning and Employment Record that will hold a comprehensive representation of not only the skills that they’ve earned currently, but any skills that we verified through our prior learning assessments, any transfer credits that are coming in that have skills in there, any of the co-curricular activities.

So even our co-curriculars are aligned to skills and evidence-based so that we can represent that with the same trustworthiness on our record. And we actually have a robust career services product side that I don’t think gets quite enough attention. It’s called Career Navigator, and it is incredible the amount of resources that are available, not only to students.

So the students can see their skills that they’ve earned inside their skills profile, and then they can look at a collection of jobs that have been curated in our talent marketplace that align to those skills, and they can apply based on how many skills they have.

But conversely, we have partnerships with just over a hundred industry partners, and they can actually put their job opportunities in our talent marketplace, and they can see how many, like, skills that they could ask students to have that will give them a specific number of applicants within our system.

Like, I just feel like there’s a whole other conversation actually, Mason. Like, I should point you to that team because it is incredible.

State Momentum and Interoperability in Digital Credentials

Mason Pashia: So I guess how’s it going? Are you hearing from employers that this is working better than other methods? Are you still a little early to make that call? How is everyone feeling about this kind of matchmaking, I guess, based on skills and demand?

Cate Tolnai: Yeah. Well, what’s really interesting to me is, like, what I’ve been paying attention to is how states are starting to stand up initiatives around learning and employment records and skills wallets. There’s several states that are leading this conversation, which means to me, when states are buying in, funding’s coming, resources are gonna start flooding the market.

And so where we are is really well-positioned to kind of meet the states and the industries within those states where they’re at, because very, very soon the infrastructure will be there, and they will be able… ’cause right now there’s an interest to hire for skills, but there’s not the infrastructure to really do so.

And that’s what I have found, is that the HR systems aren’t really able to call out for those skills in a way that our learning and employment records really are set up to do. And so if I could predict the future, in one year we should have this conversation again, because I think what will start to happen is we’re gonna see some infrastructure changes that are going to benefit from ingesting our learning and employment records that have all of this metadata, these robust records for each student and verified skills.

And so I think it’s a very exciting time, and our job as an institution is to stand up the most standardized representative record we possibly can for our students to be well-positioned in their state to go forth when the time comes. So that’s what we’re working on this year.

Mason Pashia: That’s so exciting. And California recently passed legislation on this, right? Talk to me just for a couple seconds about how you’re gonna meet that moment.

Cate Tolnai: I mean, we’re in all 50 states, so we’re not just looking at California. Arkansas is leading this as well. Idaho is leading this as well. So there’s different states that are popping up, some with more substantial initiatives now, others that are gonna be coming soon. But I will say, I feel like my job right now is just to pay attention to where those bursts are coming from and stay very well connected to the networks that I’ve built through the different professional organizations like AACRAO and UPCEA and the organizations that are dialed into these conversations.

It’s still gonna come down to, I believe, standardization because hopefully the systems and the infrastructure that stands up will be built to specifications that University of Phoenix and so many other institutions are committed to building towards. So as long as we’re building to the same specifications that the state’s building to, then our systems can talk.

So where I see it and what I’ve started to kind of put my fingers into is, who’s leading at the state level? I wanna make sure the right voices are there. I wanna believe that they are, but it’s just like when it comes to something as basic as interoperability, the whole thing falls apart if we’re not speaking the same technical language.

So that’s, I think, where we can put our effort too, is just making it really clear, like, we are building to specifications and standards. You can go to the Credential Registry, you can see our credentials, you can see our skills, like, it’s all on there. And that’s the best we can do right now.

K-12, Community Colleges and Career and Technical Education

Mason Pashia: So I wanna hold on the interoperability part because you’re really talking about this higher ed into workforce transition, so what we spend a lot of time in is K-12 into higher ed or workforce or wherever. In theory, that looks similar, but you have to, again, have that be an interoperable system so that you could go from K-12 to higher ed to workforce, or K-12 direct into workforce. I guess where is University of Phoenix on that journey of being like, “Oh, there’s this student coming out of a K-12 system with a bunch of micro-credentials and credentials.” I know your audience is different, and in some ways you probably have a more responsive admissions office than many because you’re taking people with a really wider variety of experiences. But I’m curious about where you think you all are on that, and just generally a pulse check on higher education taking in credentials.

Cate Tolnai: Yeah, it’s a really good question, and I think there’s this group that we haven’t touched on, which is community colleges, because they’re playing a huge role in articulating K-12 credits, especially through dual enrollment programs. And what I think is really something for us to watch and for higher ed to think about, but also K-12 to think about, is, what is your relationship with your local community college that can help translate some of that information up?

And so we are looking at our feeder schools in Phoenix. We still do serve a large number of people within Arizona, so we’re looking at that as almost like a mini case study of, can we figure out how to partner best with some of our local community college partners in the Maricopa County Community College District. You know, could we create an articulation that makes sense using skills and using the specifications of interoperability? And then I think for K-12, and because I spent so much time in K-12 and because I am very passionate about student opportunity and differentiation of opportunity, I see CTE, or career technical education, as really primed to be leaders in this space because they already have pathways of learning.

They already have articulated areas of focus. And I think the lift to skillify, if you will, and articulate a student’s journey through a pathway of career technical education and then acknowledge it with a skills-based micro-credential that could then be ingested by the college, that’s the magic sauce, I think. Yeah.

Mason Pashia: I mean, we’re bullish on generally competency-based education, so if you can get that in and all the other courses, then suddenly you have a similar atomized skill-based approach that could turn into a stack of micro-credentials and have those be more portable.

AI in Education and Verifying Skills

Mason Pashia: You proposed we do some myth-busting on this, so I would like to do that together. I wanna start with the proverbial elephant in every room, which is AI. It impacts this conversation in a lot of ways. Like, it impacts it from the level of generating evidence of demonstration. So like, you could fabricate that you know how to do something, in theory. It comes in at the translation layer, which is like if you call something critical thinking and someone else calls it problem-solving, maybe it can actually make an inference that those are the same skill that’s been itemized.

Then it comes in at this other side, which is really the evaluative layer, which is like if you are submitting a resume to a company, they’re likely using AI to scan your responses right now and see kinda where that matches and where it doesn’t. So I think there’s like a one that affects the user, one that affects the employer, and then one that just affects the information. Like, all of the stakeholders. I think first of all, respond to that, and then I would love to talk about this specific myth that you have proposed.

Cate Tolnai: Yeah. So I think that’s a really wise way of looking at it, and you’ve captured it really well, right? There’s a user concern, there’s an employer concern, and then there’s just an overall, like, cultural concern. And I think, like, at University of Phoenix, we have chosen to really be thoughtful around where we’re infusing AI into our courses, and then where we’re acknowledging AI being infused through our micro-credentials.

So I think every institution is going about this in a unique way, and I would say what I really appreciate and am proud of University of Phoenix for making the choice is that this isn’t about putting it everywhere, right? But when we do put it in places, and we’re going to assess it, we are going to ensure that students have been given an opportunity to practice a skill that needs AI or that uses AI.

Mason Pashia: I wanna get in the weeds with a different approach to it, which is, I think fundamentally the underlying concern with AI is this idea of credibility and trust, right? The idea that, like, AI is going to mean that someone cannot actually do something even though something else says that they can, or, like, the interpretation is gonna be off at the level of the actual AI.

Earlier you talked about these micro-credentials being verified, and I wonder if we can spend just a couple minutes talking through how you all think about that, and maybe even gaming out a thought experiment of, like, how a K-12 system might be able to think about verification. ‘Cause that’s where most people get hung up, is they talk about the sticker is pretty, it doesn’t mean anything, there’s nothing in it. Like, Google’s definition of data analysis through Google Analytics is very different from a big bucket definition of data analytics.

So I’m just curious, how do you think about verification, and maybe that starts to do some of this myth-busting, which is really to say, and let me… I’ll just state the myth now ’cause we’ve wandered into this territory, which is that if AI helped you do the work, the skill is not really yours. So that is something that we are, I think, against in this conversation, is that, like, AI is a tool. But tell me a little bit about your verification layer.

Cate Tolnai: So what’s unique about the way that we are assessing AI use, we’re in the process of ironing out, you know, there’s gonna be an opportunity for students to use AI optionally in a course, and then there’s gonna be a time where we’re actually teaching them how to use AI for a specific end result.

And when we are doing the latter, and we are including it in our authentic assessments as part of the evidence, we are requiring them to, like, upload the AI evidence, the use of AI, as they chose to explore it. Whether it’s, like, a transcript of a chat they had or evidence of it being infused into, like, a tab on their spreadsheet.

So I think it kind of breaks my heart that we’re at a point where AI use is still viewed as cheating. I’ll just say that. I think it’s a very narrow claim. And I think that anybody who uses AI to the depth and complexity that we can set them up to do so when we teach it properly would understand that, like, it’s an assistant.

It’s just there to help you along the way. And the work that you’re doing, like, the cognitive work that we’re going through as learners to interact with an AI bot or an AI tool is so sophisticated. It requires so much critical thinking. It requires so much introspection and evaluation, like all that higher order thinking, all that we want our students to do.

But I understand that the students aren’t gonna get there unless we guide them, just like they’re not gonna get to the top layers of Bloom’s Taxonomy without getting them through the bottom layers either. It’s like, I wanna look at these faculty members and not really at Phoenix, but I wanna look across the board at, like, the cultural change with AI and just go, “You’re still the expert in the room.

You still are the expert on cognitive development.” And I think about this more in K-12. Like, you know what your students need to get to a point of mastery, and now it’s a matter of adding another tool into that. And so it’s not that AI is gonna replace. It’s like, how can you now leverage a whole new tool to help them get to a new level of mastery?

It might mean rethinking assignments. It might mean rethinking assessments and rubrics. Right? Like, those are the conversations that I help guide K-12 districts to go through if and when I’m asked. And I think as far as what we do at Phoenix, it’s really if we’re going to go so far as to say this AI skill is… or there’s a micro-credential that has an AI icon on it, meaning, like, it’s signifying that AI was required in order to achieve this micro-credential, then we’re gonna ensure that we’ve taught it explicitly, the AI use explicitly.

We’ve given students opportunities to practice, formative assessments, and then there is going to be, like, required evidence in the summative assessment that shows that they’ve used it to the level of mastery that we’re expecting them to do.

Mason Pashia: Interesting. And what would that look like? Would that look like a rubric, or would it be the actual assignment in its entirety?

Cate Tolnai: Yeah, it’s rewriting the assignments and working the AI use into, like, the steps, the action steps the student has to take to complete the assignment. And, like, we won’t require a student to use AI in Excel and submit evidence of that AI in the separate tab unless we’ve given them… we’ve shown them what it looks like, we’ve walked them through the steps to take it, they’ve practiced it and gotten some feedback, and now we’re at a point where they’re gonna actually, you know, submit the evidence that they can do it on their own.

And that takes time. It takes so much time, and I think there’s, like, a race to get all AI everywhere to be the university that’s going to be right on the bleeding edge of AI and higher ed. And the work that we’re doing requires, like, some real instructional design and some very important influence from our industry advisory councils and our practitioning teachers, faculty members.

Like, we need to listen to how AI is being used in the field so we can build opportunities for them to practice it while they’re at our institution. Yeah.

Mason Pashia: Totally. I just have one clarification point on my end. So, micro-credential, like the sort of data layer of that credential, is the final submitted project or assignment stored in that? Just from, like, a verification perspective, could someone who’s looking at the badge be like, “Oh, not only did they use AI, but I can actually look at the quality of what they delivered and use my own discernment on whether or not I think that’s up to snuff.” How are you all approaching, like, the metadata at this point?

Cate Tolnai: So, in short, not yet, but that’s what’s on our roadmap for this year. That’s gonna be the difference between our achievement record right now and a true learning and employment record, is that students will have an opportunity to actually, like, turn off and on certain assessments or artifacts, which is gonna be the game changer ’cause that’s, that’s the goods, you know? And then we can actually give employers the example of it being used, like, how much more visible could we really be at that point? It’s just super cool to think about.

Credit for Prior Learning and AI Conversations

Mason Pashia: And when you have people apply for University of Phoenix, can they do credit for prior learning and just earn a ton of these micro-credentials right out of the gate? Does it have to stack alongside their time in university, or is it really just a, “Hey, we’re here to help you translate you to you. Like, we’re here to understand you”?

Cate Tolnai: We have a deep catalog of prior learning assessments and credit for prior learning, like, I’m saying 400 different topics that students could explore. That’s in addition to just accepting transfer credits and AP credits and all that, right? So this is just prior learning assessments, where students will come in and… We’re piloting this right now, actually. We’re skillifying and credentialing our PLA, and we did our first run of this. We’re in the middle of it right now, so sneak peek.

But basically, we took our most popular PLA topic, which is parenting. We currently offer up to three credits for students that come in and can show evidence of specific skills aligned to being a parent, a caregiver, and it’s very cool. And so prior to this pilot, there was a process, like a journal writing process that students would complete. And in an effort to treat all academic credits equally, we wanted to skillify PLA, just like we skillify all of our other credits.

And so we aligned to the Lightcast taxonomy, and we have three skills that we ask students to demonstrate now through our prior learning assessment. This takes place now inside of our learning management system, and we… Oh, this is gonna be another AI bubble. We use a tool called AI Conversations inside of Blackboard, and I’ll just give you an example.

One of the scenarios that we came up with. You can train the AI Conversation persona to represent an identity, and then you can give it a scenario, and then the student interacts with that persona inside of Blackboard. So one of the skills we issue is constructive feedback. As a parent, can you demonstrate that you can receive and give constructive feedback?

Which is a parenting skill. So we designed one of our personas to be a grandparent that was giving constructive feedback to a parent about a choice that the parent was making with their child. And part of the evidence is they evaluate the quality of conversation, like in a show-don’t-tell kind of vibe, where the student is getting feedback from a grandparent about an arbitrary comment they made to their kid, and the student has to demonstrate receiving constructive feedback properly in a way that would be appropriate in a work setting, right?

So they have to, you know, they can’t have a tantrum back to their grandparent, you know? If they do, then they would not pass that part of the prior learning assessment.

So that’s, yeah. And then there’s also some follow-up reflection questions where they have to, like, leverage the conversation with the bot and talk about, like, how that readies them to show this in the workplace and have to articulate that.

So they’re transferring their parenting skills into the workplace, and then we’re evaluating the quality of that.

Micro-Credentials as Milestones on a Lifelong Learning Journey

Mason Pashia: That’s awesome. Okay, cool. I’m glad I asked ’cause I think that’s a really interesting example of putting some, I guess, meat on the bones, so to speak. Okay, I have a final question. It’s another one, another myth, and I just wanna state the myth and then somehow figure out how to turn it into a question. But it says, “Credentials are simply a record of what you’ve already done.” I think we’ve talked about this a little bit already, both with, like, the Career Navigator connection pool and also some of this credit for prior learning, which directly states kind of what this is, which is, like, credentials are a record of what you’ve done. And yet, my personal belief is that LERs and wallets are actually identity formation tools rather than being like a static list.

I think that’s where a lot of the ed tech stuff is struggling right now, where, like, if updating your wallet is as painful as updating your resume, no one’s gonna wanna do it, and it’s just gonna be just as hard. Like, “Oh, I’ve been at Getting Smart for eight years. What have I done in that time?” That’s a bad feeling. So you have to make it incremental, you have to make it iterative, and you have to make it kind of fun so that, in the same way that I would put a book on Goodreads or StoryGraph or put a hike on Strava, I do it just reflexively because it’s useful to me for some reason, whether that’s understanding more about myself, whether that’s knowing I did this hike so I don’t have to do it again, or I can get to do it again and remember that it’s beautiful.

So, mangled question, but technically, looking at all of those little tiny badges or whatever that is, those help me understand me, and they help me understand what I can do. And so, I guess talk to me a little bit about how you think about this myth and how you’re busting it.

Cate Tolnai: Yeah. And can I also talk about, like, how K-12 can be a part of this too?

Mason Pashia: Please.

Cate Tolnai: In no world should we be seeing a culminating trophy of learning, AKA a badge, in, like, ninth grade. You know? Like, this should be an indication of a journey that someone’s on. Like, learning is lifelong, right? And that doesn’t mean there aren’t milestones achieved along the way that we could recognize through micro-credentials, and it also doesn’t mean that that milestone readies you for an opportunity before the end, right?

Whatever the end might be. Maybe it’s the degree, maybe it’s the promotion. I don’t know, maybe it’s that job title, like, whatever it is. So I think it’s important for all of us to understand that the role of a micro-credential is twofold. One, it’s to acknowledge the evidence of mastery, right? Like, it’s to acknowledge a skill, a demonstration of skill, if you will.

But then two, in my opinion, it’s there to empower the learner to keep going, keep going deeper into an area that you want to go, or turn it into an opportunity that you didn’t think possible. And, you know, I think back to when I got my ed tech certificate back from Boise State. That, while it acknowledged that I completed three courses and a certificate, I didn’t get to walk away with any sort of digital verification of that that could tell everybody else. So I still put it on my resume, and it did exactly what I’m describing. It gave me the confidence to apply for jobs I wouldn’t have been able to apply for, and it gave school districts an opportunity to see I had a specialty that otherwise I wouldn’t have been able to claim on my resume.

But that’s just ’cause ethically I don’t claim it unless I have it. And so the issue now, right, is that people are putting things on resumes. They have always put things on resumes. I mean, it’s our time to shine. Like, we’re gonna put our shiniest version of ourself on a resume, even if we stretch it a little.

So the point I think that this brings up is that there is so much more that a credential with metadata, with proof of learning, there’s so much more that it can do to help a student take their next step. And I love what you do around storytelling. I love that we’re acknowledging, like, what’s the student going to do with it once they get it?

I was just having a conversation with one of my colleges last week, like, why? Why this? Why do you want to credential this skill? What will a student be able to do with this skill that they wouldn’t be able to do otherwise, or this set of skills? So that’s where I look at the myth and just wanna kinda break it up and be like, it’s not a culmination. It is a culmination in a sense. That’s why I’m grappling with it a little bit, but it’s a milestone versus an end point. I don’t know. How do we say it?

Mason Pashia: Yeah, I think that’s an interesting question. I mean, it’s evidence. It’s evidence of something, but you will get more evidence also. So it’s just that it is a… I mean, how do you say it without just saying it’s data? ‘Cause it is just kind of data.

Cate Tolnai: It seems like for me, the sooner we can help issuers, whether it’s a K-12 institution, a higher ed institution, community college, the sooner we can help them understand that each micro-credential is an opportunity along the journey of life to say, “I have a specific skill set, and I have demonstrated it in a way that you can trust, and it is indicative that I’m ready to do this next.”

Versus, “I took the class, I got the credential, and now that’s over. Move along.” Keep going on the journey without being as mindful. Perhaps it’s a bit nuanced, but I do think that mindfulness and helping students understand that this is merely one other opportunity for them to put their expertise and their passions and their curiosity into the room and do it in a way that says, “And I’ve demonstrated this at an institution, and they verified it, and it’s trustworthy, and you can take it.” Like, that to me is the game changer. And now it’s just a matter of helping, like we said at the beginning, building the infrastructure to receive it.

Mason Pashia: Totally agree. And you’re doing it.

Cate Tolnai: We’re trying.

Mason Pashia: You’re on it. So thank you so much for joining me today, Cate. I think we have to wrap up just due to calendars, but I’m sure we could talk about this forever. But Cate Tolnai, it’s been an absolute pleasure to see you again. Thank you for doing the meaningful work.

And everybody listening, I’ll put links in the show notes, but keep an eye on what University of Phoenix is doing. They’re ahead of the pack on a lot of this stuff and really thinking about its implications for learners that have often been underserved or overlooked. So Cate, thanks so much for being with me today.

Cate Tolnai: Thank you.

Links

• Cate Tolnai at the 2026 Badge Summit
• At 2026 Badge Summit, University of Phoenix leader shares strategies for meaningful digital credentials
• Cate Tolnai appointed to the UPCEA Council for Credential Innovation
• University of Phoenix, career-aligned micro-credentials
• University of Phoenix, millionth digital badge
• University of Phoenix, Career Navigator
• University of Phoenix, UOPX Talent Source
• University of Phoenix, Credit for Prior Learning white paper
• Getting Smart, Are Schools Collecting Too Much Data? | Dr. Kelly Page
• University of Phoenix