BU Virtual Connects — When the World of Work Changes Faster Than the Curriculum

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This is Wendy Colby, Vice President and Associate Provost at Boston University, and the host of BU Virtual Connects.
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I'm pleased to welcome Gates Bryant, Senior Partner at Titan Partners.
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Gates and I have known each other through a number of different chapters in higher education, and he brings a particularly broad perspective to this conversation.
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At Titan, Gates co-leads the Center for Higher Education Transformation and works extensively with institutional leaders on questions of growth, innovation, student success, and long-term sustainability.
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His work spans the education ecosystem from K-12 and higher education to the changing relationship between education and the workforce.
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And he has been a leading contributor to Titan's research on teaching and learning and the evolving student experience, including its Time for Class series.
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Titan's 2026 Time for Class, the AI tipping point, from monitoring students to engaging them, describes higher education as being at something of a tipping point.
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AI is certainly part of that story, but the questions are much broader.
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How do we prepare students for a world of work that is changing rapidly?
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How do we better connect learning and work?
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And how should universities themselves adapt from the curriculum and student experience to the programs and populations they serve?
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Gates, welcome to BU Virtual Connects.
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Thanks for having me.
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It's so fun.
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So glad you're here.
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And I was just reading the study again this morning, so I'm really excited to dig into it.
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So maybe let's start in our current moment, right?
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You've described 2026 as a tipping point.
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I love the language around monitoring students to engaging them.
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We've certainly heard predictions, right, about disruption in higher education before.
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So what feels fundamentally different about this moment?
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Is AI driving the change or accelerating shifts that are already underway?
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Yeah.
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Yeah, thanks for the question, Wendy.
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I think we described uh this moment in time as a tipping point for a few different reasons.
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Um, you know, Time for Class has been a longitudinal study that we've now been running for 11 years.
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Um we started tracking the adoption of AI by faculty administrators and students in February of 2023, right after GPT had come out in I think it was November of 2022.
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Um and so we see this current moment, now fast forwarding three years, as a tipping point because for the first time we are seeing um administrator uh use, uh frequent use, weekly or daily use, as exceeding um the use by faculty and even by students.
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Um we see that as a tipping point uh for institutions to engage in an enterprise approach to AI.
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There's a lot of conversations, a lot of headlines about the threat that AI represents to the fundamental academic enterprise.
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Um, but we see this tipping point moment as a point in time in which institutions are now really grappling more holistically about how to use the technology again as an enterprise asset.
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Um and so that's why we see this as a real kind of tipping point moment.
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Yeah, you know, one of the things I noticed in your report too, 49% of students, I think, in the report said they will continue to use the tools even if banned.
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And I find it very interesting.
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I'm really looking forward to moving on into this conversation as here at Boston University, we're wrestling with some of these same challenges, right?
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And we'll get into this as as you talk about integrators and defenders and how you think about that.
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But as we think about readiness, um, and one of the findings that really struck me in the report is students, faculty, and administrators, they don't necessarily define maybe workforce readiness in the right way.
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Yeah.
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You have again some impressive statistics here that maybe show a little bit of the divide.
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69% of students feel courses prepare them, 70% of faculty uh feel they prepare their students, right?
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Yeah.
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So as jobs and skills change more quickly, uh, what do you think it means to be career ready?
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Yeah, so so I think um you know continuing on the tipping point theme, you know, this is another element of the tipping point moment where we're seeing broad agreement actually among faculty, administrators, and students about the idea that AI is a critical um skill technology competency that students, prepared students, need to have as they enter the workforce.
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And so we spend a lot of time highlighting differences of opinion um in our space.
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We love to debate, it's all good.
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Um, but but it's it's encouraging when we see alignment.
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And now there is a difference of opinion um at a at an important point, and that is what students you you mentioned this statistic.
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We see students are asking for real-world experience as part of their college experience.
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And um faculty are more likely to report wanting to teach around the you know, the skills, the professional skills that make them career ready.
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Students say, yeah, that's good, but I also really need to be able to apply this in in real-world um experiences.
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I know you guys at BU are doing some things in this regard, um, uh launching the career accelerator, I think it's called, uh, and this career exploration, when it provides students an actual experience, you know, being able to sit in the seat of uh of an employee at a big company navigating critical business issues or what have you, those experiences are what students um are asking for.
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I think this is um something that students have appreciated for many years in various forms, internships, co-ops, increasingly now discussion around apprenticeships.
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Um, but honestly, those things just can't scale to meet the demand that's needed.
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And so our perspective is that institutions um need to offer a variety of real-world experiences.
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They need to be embedded in credit-bearing experiences, uh, credit-bearing courses, um, and uh and they need to start happening right from semester one.
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Um and it's not something that should you know, should wait very long.
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Um, students are ambitious and they want the experience to add to their um ambition.
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I love that, right?
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And I think you were referencing Boston University's career launchpad.
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Launchpad, sorry, yes.
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No, it's a new initiative we launched.
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And as you say, I think we're being very deliberate in how we think about career connectedness and relevance right from day one, right, from that freshman year on.
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And then we're also, and I know we'll get into this as we pursue the conversation, but we're also thinking about the lifelong and the career, you know, recently launching a number of new programs online, right, for that segment of the workforce.
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You know, one of the things that's coming up a lot in this dialogue, um, in addition to career connections, of course, so I want to come back to because you address this a lot in the report too, is assessment.
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Assessment being on the front line, right?
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Differentiating those who innovate from those who default, more proctored control.
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Yep.
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And I know this is something we are wrestling with, and I think many universities are wrestling with today.
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So AI is raising questions not just about the skills, which you just talked about that students need, but also about what we teach and what we ask students to do and how we know meaningful learning has taken place, right?
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Um, and so how should we be thinking or rethinking about curriculum and assessment in the age of AI?
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Can you talk about that a little bit?
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Yeah.
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Honestly, I'd I'd love to come back and do a whole session on this one.
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Yeah, maybe to part two.
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And and you know, there are many other voices that that could come into this conversation.
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Um I think I get very energized by it because it it is right at the heart of the higher education promise, which is when you come to college, whether it's a graduate degree or an undergrad, whether you're a traditional age student, an adult learner, you expect to be able to exit that experience with uh new competencies.
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And if the technology and AI is introduced in a way that shortcuts that process, the the value of productive struggle, um then the the value of that learning experience and the the signaling power of that degree um is is diminished.
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Um I think that there's not enough conversation happening right now about re thinking and redesigning what academic integrity represents.
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Um I think there's sort of a um I think folks are willing to let that conversation kind of drift to the side and are focused on, okay, how do we redesign assessment, which is important.
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But I I think in order to appropriately redesign assessment, you need to have a parallel conversation.
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Maybe it's a precedent conversation, which is how do we how do we think about academic integrity um in light of AI?
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Banning AI is completely not an option.
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Um, and if you have the I know you read the report, and if your listeners have the chance to read the report, they'll um get introduced to a segmentation of the faculty population that we undertook, which really starts to identify what are faculty doing as it relates to academic um assessment redesign.
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And I think institutions need to give faculty more support on this.
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Um, 50% or a little more than 50% of faculty say that they have not redesigned their assessments.
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Um, that's troubling to me.
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Um I think another quarter of the population um has redesigned assessments and they've done so in the form of a blue book.
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That's also troubling, although it's it's serves a purpose.
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I don't think it's sufficient.
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Um, and another 25% or so of the faculty population are um focused on uh full redesign um through uh maybe proctored environments or um other forms of authentic assessment, oral-based assessment or project-based learning or team assignments that that really work to um push the students further in applying more judgment around the knowledge that they're acquiring.
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Um and uh and I and I think there's there's the opportunity to really redesign assessment so that it is, um I heard this term the other week, ambient, ambient assessment.
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So it's in the progress of learning, you're capturing uh where that student is at in a in a learning progression.
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Um and you've you've got to do that in a way that um understands the reality, which is students are going to use AI um to help them get unstuck.
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Um, and they're gonna use AI uh to help them brainstorm, and uh, and and there are some uses of AI which are completely um out of bounds and inappropriate.
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And this is really hard to work through.
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What we'd like to see is more institutions supporting more faculty in this redesign, true and proper redesign effort.
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And how do you think about that, Gates?
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Like what can institutions do to support faculty?
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You know, here at BU, uh we're a massive place with 17 schools and colleges, as you know.
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And again, I I certainly see uh faculty here champion faculty are really embracing the change and really thinking, being very deliberate and thoughtful about how they're changing not only assessment but also curriculum, right?
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Moving away from multiple choice QA and those sorts of things, right?
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Not necessarily returning to blue books, although we have a portion of our faculty and our population doing that too.
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And I loved the the concept you had in the report about integration versus restriction.
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And I'm just wondering if you can share any examples of what you've seen in universities that have been sort of embracing how to help faculty in this uh in this evolution.
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Yeah.
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So um so on the integration front, I uh the the framing there is around the idea that this technology is going to be a cr a critical technology for uh folks in the workforce going forward, almost regardless of what industry they they go into.
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Um and so therefore integration is is really critical for the um students' learning um experience.
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Um where we see institutions um excelling in this arena um is in a couple, I think, critical areas.
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One is that they're setting the stage from an institutional policy perspective in a way that um allows faculty to very clearly say this this type of use is not okay, but this type of use is encouraged and catalyzed.
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But uh for the first three years, institutions have been very slow to build out policies either at the department level, level, school level, or institution-wide.
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And and faculty have been left to um navigate on their own.
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Um that is problematic because it produces a very inconsistent student experience.
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Um and and so I think uh creating a policy framework and foundation is um critical area number one for supporting faculty.
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Critical area number two is creating an environment for experimentation.
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So um, you know, there are a number of institutions that um are doing this.
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I think, and there are a number of um private sector companies that are building out learning tools um that are AI enabled or AI uh native in ways that um, you know, like I said, embed the assessment experience in the learning progression.
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Um and uh and and also create opportunities for students to engage in an assessment experience that is quite different than what they're used to.
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I mean, back in, you know, whatever, uh Greek times, uh it was all about, you know, oral assessment.
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It was all about articulating your point of view, um, you know, in in lengthy oratory, right?
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Yes.
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Um, that doesn't really scale uh for general-ed classes at a large university um at BU.
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Um, but there are technologies that can certainly be um leveraged to assist faculty and their teaching assistants in assessing students um on uh their ability to defend their perspective.
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Um and so just example, we've seen um, you know, uh the addition of this oral assessment concept applied to, okay, when a student submits an essay, there's a follow-up, which is, okay, now defend your uh defend your paper.
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My my son had the opportunity to do a thesis in his undergraduate work.
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He had to defend his thesis.
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Umly a subset of students did that in their undergraduate experience.
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But what if this defense of your paper, regardless of what the magnitude of the assignment is, was something that you could scale leveraging the technology that we have in AI.
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So that's that's what we've got to do.
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Yeah, no, I want to comment on a couple of things uh here before we move on to the next section.
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Uh, you know, your points here about policy, framework, literacy, you know, and I see a number of institutions doing things in different ways.
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One of the things we've tried to do here is really set up a body.
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We call it the AI Development Accelerator here, IEDA for short.
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I recently had uh John Byers, who's the executive director of that, on one of our podcasts.
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But the real notion here is how to create sort of a, I'll call it a central unit, but that works closely with our schools and colleges, right, to help advance the literacy, the governance, the ethical frameworks around it, the training, the learning, all of that.
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I also think what you said about feedback, um, assessment, you know, what when I've seen what I've seen, some I've seen some really interesting things here around assessment and around more feedback and personalization, uh, especially in our online programs right now, where it's less about using AI for grading, but more about it's like your example of your son as well, right?
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How do we provide feedback around what it is you're doing today in ways that can scale?
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Because again, we can't go back to sort of the the Greek times, right?
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Where everything becomes, you know, an oral presentation.
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You know, finally, I think this concept, and I'm hearing it a lot now, the concern here we have about the the, I'll call it cognitive disruption, how are you ensuring we're still helping students learn?
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That could be a whole other conversation as well.
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But I just wonder a closing comment on that.
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How do you think about that today in terms of for those detractors who say, you know, are we really helping students learn?
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AI is now writing their papers, AI is now coding for them.
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So how do we make sure, you know, we're institutions with a mission here to still help students learn?
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Yeah.
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Yeah, I I think um uh President Bilock at my alma mater at Dartmouth College, um, I think has uh started a conversation.
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I don't know if I can fully attribute it to her, but I saw it first with her, perhaps I'm biased in that way.
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Um that uh higher education has to lean into what has been its original core competency, which is developing students in a path toward applying human judgment.
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And this concept of judgment was has been echoed you know multiple times.
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Um Cornell had their big report that just came out this past week, and you know, they apply, they mentioned this, you know, this idea of judgment has to be um and and so I appreciate some emerging consensus um around this.
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Uh I I would say that um there is um a variety of ways in which the teaching and learning experience for students needs to evolve anchored around this idea of how do we build judgment, how do we build um that that capacity in students um so that whether they're in a human-to-human interaction and need to imply some judgment in their real world uh or or really applying some really critical thinking about the output they're getting from a collaboration with an AI tool, um, they've got lots of reps at applying judgment in a variety um of contexts.
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Um and so the question is like, how do you do that, right?
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Like what does that what does that really look like as a nice concept, nice theory?
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And I think one of the ways in which you need to be able to begin to do this is a little bit what I was saying before around building in experiences into the learning experience that is about exercising judgment, about applying judgment.
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Um, and literally every academic discipline has the opportunity to speak into applying judgment, whether you're uh in a classics class, a philosophy class, an engineering class, or anything in between.
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Um, and and and and that's that's where our I would defer to instructors and lifelong educators about how to how to do that.
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But I would I would encourage um experimentation of ways of okay, how do you build judgment in light of this new technology?
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So much of what you said there, I love.
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And really thinking about, you know, a content that comes from collaboration and then how you apply that, right?
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That human judgment and across almost every discipline.
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So that's that's really wonderful.
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Let's pivot a little bit in terms of our next section here, really thinking about we've been talking a lot about the early career experience and what's important from day one into the broader, I'll call it lifelong learning, which is of course important to a unit like uh BU Virtual from which this podcast emanates.
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But much of the discussion about career readiness today is focuses on students to prepare the workforce, prepare to enter the workforce.
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Universities increasingly serve people already well into their careers, right?
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Where jobs and industries are changing massively around them.
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So I wonder how, and I know you think about this deeply, Gates, as well, and the work you do, but thinking about early mid-career as part of that same continuum, what does that require universities to do differently?
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How, when, in what forms they provide learning, uh moving beyond the traditional degree toward a broader mix of degrees.
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I mean, this is coming up a lot to the report from Cornell that you mentioned as well.
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You know, uh, I think many universities are now looking at how to create different more impact through focused on through a focus on different segments.
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And so I wonder if you could just speak a little bit about that, moving away from assessment now to the broader landscape of learning and how universities can best address this, particularly in a time where we're facing a lot of disruption.
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I think this is a a really, a really tough one.
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Um, and and uh I I would say I I have an idea about this.
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Um that's easy to articulate.
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I think it's really hard to execute.
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Um, but a number of institutions are moving in this direction.
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It's essentially, you know, you had in your question like the the path of lifelong learning, and what does that actually look like?
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Um if we're operating in an environment where the average college graduate is gonna have, I don't know what the number is, 10 different jobs, 12, 15, maybe 20, like lots over a lifetime, um, wouldn't it make sense that you would have education experiences of at least that many to enable and support your career and professional journey?
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The system we have today in higher education is not really set up to do that.
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Um, I would argue that the like corporate training, professional training also isn't really set up um to do that.
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And the question is who has better permission?
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Who's got more of a permission to serve learners across their journey?
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I think at places like BU or you know, across over in Charlestown at Bunker Hill Community College, and everybody in between, if those institutions are establishing a learning relationship, a trusted learning relationship at a critical moment for a summative degree, doesn't that institution have permission to maintain that relationship after the student is gone?
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Nice idea, Gates.
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It is a great idea.
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Hard to execute, right?
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So institutions today are not really structured to um to serve students over their life.
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I think there's promising efforts in a number of different places.
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A lot of alumni and advancement offices are kind of rethinking their missions around lifelong learning.
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Um, and there's a lot of programming.
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I'm not sure that um institutions are necessarily meeting learners where they're at at that, you know, third job or the seventh job.
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Um and and that's you know, that's I think that's part of the that's part of the challenge.
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It's why it's very, you know, it's up for debate whether or not institutions have.