Name: Fall Forward With AI: Your Summer Roadmap to Success
Uploaded: 2025-05-28T18:53:03.635Z
Duration: 37 min 4 s
Description: Fall Forward With AI: Your Summer Roadmap to Success

Transcript for "Fall Forward With AI: Your Summer Roadmap to Success": When I move about it just like this, I don't know why, but I feel like freedom. I feel some that takes me back, When I move about it just like this, Hello, and welcome everybody to our call forward with AI discussion. I'm really excited to be having this conversation with you and, bringing on a special guest to to join me in this conversation. So let's just get going. Eddie, would you like to introduce yourself? Yes. I'm Eddie Watson. I'm the vice president for digital innovation at the AAC&U. Welcome, Eddie. I know we've had, several conversations together in the last year. I'm always excited to hear what's the latest and greatest on AI trends. Everybody, I'm Jenny Maxwell. I have the privilege of leading the Grammarly team, and we're gonna have a really timely discussion today around, first of all, where are things in 2025 in relation to AI, kind of what's been happening in the last several years. We're gonna talk about three big trends today. The first trend being from where things might have been two years ago, around banning AI to this notion of responsible use and and leveraging guardrails of AI. We're gonna talk about agentic AI, and then we're gonna talk about all of this under the umbrella of responsible use. And then, we're gonna hear, from Eddie. He's gonna give us some, some really great feedback and ideas around how we can start integrating AI ahead of all courses. So we'll also spend some time on q and a. And with that, let's get started. Let's have this conversation today. So first of all, what's been exciting from where I sit, at Grammarly is to see sort of the the perception and, acceptance of AI move from fear two and a half years ago towards fascination. And I think, there's several buckets of, different stages of optimism around AI, that we're noticing in the market. And, obviously, you know, Wharton talked about this a few months ago in this notion of are you a doomer, are you a gloomer, a Zoomer, or a boomer, and and what that means in terms of your willingness to embrace different AI technologies. C. Edward, where where you know, I'm putting you on the spot here. Where do you see yourself, in the acceptance of AI personally as we get going in this conversation? Well, it's definitely increasing. I think a year ago, I think there was a lot of ambivalence, especially among senior leaders within higher education, sort of like trying to discern whether or not this is really a thing that's going to impact us. But I saw a real shift from spring of twenty twenty four to fall of twenty twenty four where the majority of senior leaders do see this as, I mean, minimally essential learning for college students, but also that it was going to impact their, array of different business practices on their campus. So at at AAC&U, we did a survey that, was filled at about five months ago and published in January, freely available online called Leading Through Disruption. And we saw that, you know, most campuses are making movements. I mean, at least policies are are, becoming in place, regarding academic integrity and acceptable use regarding AI in some cases around ethics. But even sort of pushing further into sort of the curricular food chain, we're seeing that some universities have, added, at least courses, but in some cases, minors on AI. And what we're also seeing is within the the general education domain that AI literacy is becoming a more popular gen ed learning outcome. Back where we were, in in the study as of late late of twenty twenty four, we found, through our survey of senior leaders that about 15% of college campuses had already adopted AI literacy as a learning outcome. And what's unique about that seemingly low statistic is that we don't do curriculum reform very quickly within higher education. And to already see 15% of schools in just the span of two years make that movement, I think, is really suggestive of the direction that we're going to see ahead. I agree. I I have been absolutely delighted by sort of the response in innovation and collaboration thinking, you know, maybe not to make giant sweeping changes, but just to get the work started. And it's been really wonderful to partner with you at AAC&U around this work so we can help support it in in ways that are meaningful. Take us, like, I'll I'll say one of the most surprising headlines that has come out this year was one, about the largest system in education, which is, higher education, which is the Cal State system making this Herculean investment to the tune of over $18,000,000, to deploy OpenAI across, you know, system wide, campus wide, students, faculty, administrators. You know, thinking about all of this happening and then putting a sort of, you know, a financial investment in less than three years that this technology even was in market is it's it's it's like, if I didn't see it, then I wouldn't believe it. I'm curious, about your, sort of, like, you know, feelings about that headline and what do you think that that will do to the pace at which that we move out of the 15%, to even, you know, north of 50 in the next several years? Well, I think it's a real recognition that, you know, AI literacy or having competencies around the use of AI may be becoming essential learning for college students in the same way that we have critical thinking and written communication as essential learning outcomes for students. So, likely, we're seeing rapidly, broad agreement that indeed AI literacy is a new learning outcome, but then there's some really unique challenges associated with that. If if students are left to their own devices to choose a tool to use, you know, there's there's gonna be some students that will pay for the best version or the latest version of technology, and there's other students that will use the free versions. And there's definitely differences between the quality of collaborator you have in AI if you're using a paid version versus a free version. And, of course, who's more likely to use the paid version? Is it your affluent students or is it your Pell eligible students? So, of course, it's the affluent students. So recognizing that there's digital inequities that are gonna be inherently introduced if we just leave it up to students and their own devices to choose which tools to use, we, you know, we right now, we have a number of things in place to ensure equitable learning environments. You know, everyone on a campus has equal access to the learning management system. You know, people don't have different versions of access to the email client. And if AI is an essential tool for learning and an essential tool as an outcome, then partnerships like the one that we've seen, in California make really good sense to ensure that everyone, faculty and students, all have equal access to, the best tools that they could have for the work that lies ahead of them. Yeah. I I I think, from my conversations with leaders within that system, that that disparity that technology disparity is very real. It's a driving force, and they were willing to say, like, we if we are who we say we are in the, equity and access of education, you know, I I would expect to see more investments at this scale, in the coming months and even, you know, over the course of the next several years. So, love the feedback. I I I would, I know we're thinking about fall, so I'd love to sort of change gears and talk about what are the big themes ahead of, faculty and administrators thinking about getting ready for fall that you you you can tell them are are ahead of them this summer. What are some of these forces? Well, one of the most interesting outcomes from our survey of senior leaders was senior leaders were very hopeful that AI was going to improve the learning process, but then it was also, an equal number of senior leaders were thinking it was going to disrupt the learning process. So in other words, they see there's lots of opportunity here, but there's also a lot of challenge that's ahead. And I think that we are moving away from the notion of a few early adopting faculty sort of, like, leading the charge, and we'll see where they're going to go. I think we're sort of moving beyond that phase of early adoption into sort of like a early majority or more more broadly the majority of faculty using AI. As I go from one campus to the next, I'm finding that fewer and fewer you know, I always ask the question, how many of you are using AI? And the percentage in the room is getting smaller from one week to the next of those that really haven't touched it. I'll in fact, I was on campus just yesterday, a small rural university, a state school that, I think in a room of it was it could have been under 10% that said that they hadn't tried AI at all yet at that point. So I think we're we're moving into broader adoption, and there's still little pockets of resistance. And I think those resisting voices that are critical of AI are really important as we think about best practice moving forward. But we are seeing it move from experimentation to just a more more broad adoption, somewhat driven by changes that we're seeing within the world of work and the expectations that the world of work has regarding competencies that students would have post graduation. Yeah. We're we're hearing that as well. It's and and also seeing that the sort of population who are, resistant are now, I guess, moving more along the lines of I'm, accepting as long as, certain learning outcomes are met. And and what's really interesting to see is sort of the the innovation around what learning outcomes should be in in higher ed as and I know you mentioned that earlier. Right? Where the acquisition of content or knowledge is not just the explicit learning outcome anymore. It's really in partnership with leveraging all these tools to to create, you know, better measures of of learning that is indicative of the things and the goals that institutions put forth for their students. I I also see a lot more, less about experimentation and really about understanding what is great implementation look like, what are like, how are we gonna measure results? We, you know, we just launched a big impact study about things that we're starting to see with definitive outcomes for students, and faculty who who use our specific tool. But it's exciting to see, the less, like, some of the superficial play around and and to try new things. People are really saying, like, we're gonna spend the time, the resources on in deploying this, and we need to really make sure that we're measuring for what great looks like. And a lot of that is really, like you said, driven by what these employers are saying are gonna be, absolutely necessary for for students when they start their professional journeys. Yeah. I think there's a challenge I think there really is a grand challenge ahead of us that really drives into each individual classroom where we recognize we do need to be infusing these AI learning outcomes into our courses or listen to the curriculum more broadly. But at the same time, there's other logic paths that lead us to want to resist using AI. Like, is it a good idea to teach students to use a tool that they could use, you know, for cheating purposes or to use to diminish the achievement of other learning outcomes? So navigating that space is our new challenge. I think that's gonna be the, coin of the realm in 2025, '20 '20 '6 academic year is figuring out how to engender those skills while also ensuring students still richly achieve the learning outcomes we previously had in our curriculum for them. Yeah. It it's been interesting. You know, I was you and I actually, our paths crossed, because of this notion around, you know, our students leveraging tools like Grammarly or ChatGPT to outsource, content and therefore submit, you know, work that isn't their original thought. And what's interesting to some of these trends around what's shifting, you know, 69% of schools now have policy in place. Right? Like, number one, that feels like the, like, the lowest, like, lowest fruit everybody should just get around, which is do you definitively outline what your policy is for students in your course, let alone, you know, your department or your school or across your university. I think that's a good start. Little scary that we don't have that as minimally a %. Right? Like, give students some, real clarity on what is acceptable use from class to class. I love the 59% of schools have doubts about academic integrity around the era of AI because I think that goes back to the like you said, we we need some of the naysayers here to hold us accountable to what great standards look like in learning output outputs. And so, you know, I think academic integrity and and that is like this big swirl of, like, you know, are you at risk of, not having an integrity if you are leveraging these tools? I think it all comes back to, well, what is what is the guardrails that your instructor gave to you? What is the policy that you are supposed to be adhering to? And and how can, faculty have more conversations about the process and less about the output? And then I also think the stat around 54% of schools having doubts about detection is great. We you have a lot to say about detection, so I think that has been, an interesting shift in that, you know, we we know detector detectors are not reliable. And I think that status showing institutions like, hey. This technology is here to stay, and how are we going to actually create learning and, workflows for students so that they can co navigate experiences. I'd love your high level here, thoughts on, any of those stats you find surprising or are you optimistic about the movement? You know, those stats really don't surprise me. I it's I think maybe one of the more surprising is that the number of policies, you know, is and your your number came close to matching numbers from our own surveys at AAC&U, that seven and ten have policies, but that means three and ten don't. But often those campuses are sort of just leaving it up to the faculty. It's like you need to write this into your syllabus that you need to address this. And and I think I think we need to do more than even that. I think that given that there are times when we do wanna see what students can do without technology, maybe we're at the point where every assignment needs to have some kind of AI policy statement that, yes, you can use AI in this way for this assignment or, no, you can't. But I think one of the key points in having an AI policy statement on an assignment would be to communicate to students the the answer to the question why. Like, why can't I use it? And, you know, part of the answer might be, well, you know, for the first twelve weeks of the semester, you can't use AI because you don't have enough foundational knowledge to be a collaborator with AI. So we're gonna help you develop those foundational skills, and then once you get to a point of having competency to collaborate with AI, will that last assignment within this semester? And that kind of discussion is what we need to have transparently with our students. I mean, there's research that shows if we're transparent about our learning and teaching practice, about our pedagogy, students will be more likely to adopt and follow along and participate. So transparency is really key in our policies. Yeah. It's really about trust. And what you're describing, really aligns well with this matrix. And I we kind of pivoted in, you know, we thought this AI adoption is really this sort of, like, sliding scale as linear. But, really, it's not. It's around, you know, what it what is it that will get the job done for you in your course or your department or your institution this summer so you can create some tactical application in in making changes for fall. And so I'd love you know, we have this matrix here. There's several different examples of how, if you're watching this, you could get started for fall around creating more trust around, this notion of, you know, from moving away from outright banning to some level of, both acceptance and then leveraging this tool in a in a pedagogically effective way. So and, you know, you mentioned a few here. And any of these that you think are gonna be really great for certain parts of of higher ed? I do. I think that really just about everything on the screen makes really good sense as sort of a a strategy for moving forward. And, again, those that are are new to AI probably diving in the deep end, doesn't necessarily make great sense. And so, you know, find your way your way in. And there are resources that we're providing at AAC&U early in the in the month of May 2025. We released a new iteration of our student guide to AI. So go to studentstudentguideto AI Org, and you you can download this free guide that we're encouraging campuses to give out to students, especially during summer orientation as they're entering the institutes institution to help sort of manage some of their behavior. So it's just sort of like a level set as people come into your institution. That might be a really good resource. And then the notion of having a a task force that's thinking through some of these issues, not just about policy, the policy is a piece of it, but also sort of like understanding the evolution of the technology and what its implications are for the campus. And I've been advising campus leaders whenever you establish a task force and if they do great work and produce a policy after six months, do not disband the task force. Tell people in your task force, it might be like a two to five year tour of duty, And the expectation is is, yeah, you put out a policy, and then you see how that policy functions in the wild given that it's a new domain and and new technologies are emerging. So I think that's the that's the real notion here is that it isn't this isn't a one and done sort of change that's occurring within higher ed. This is something that requires monitoring. In fact, I've been talking about about where we are at this current moment. We're sort of in the ask Jeeves phase of of the development of AI, if you remember those old, search engines. So, there's a lot of things that are still in flux. So, yeah, task force, yes, but not to comp to complete a policy and then disband, but rather complete the policy, collect data from your campus to see how it is indeed performing in real life context, especially as things change. I love the call out to do it over time. Right? Just think about how our conversations have changed in the last eighteen months, just you and I. So I I love the call out to, you know, this tour of duty, You know, four three, four years of watching opinions and and use cases really inform, you know, the the task force recommendations based off of each campus' unique perspective or or goals. So great great call out there. Let's talk about the next trend. You know, this notion of agentic AI, I feel like, you know, we were kind of talking about this six months ago and it was even just sort of, like, foreign to us a little. We are trying to sort of make sense of what what does that even mean. And and now here we are, and I will say I have more conversations with senior leaders across higher ed around the impact of what a agentic AI will be doing for them than anything in the like, than than anything I can remember, honestly, this this last semester particularly. So, let's define it first. So Agentic AI are these are tools that live and act autonomously with you, and they serve up information ideally proactively. And, you know, an example would be that you'd have an invite advising box that could scan your, LMS data that could flag at risk students and then schedule outreaches between faculty or, counselors and those students to be very proactive and make sure that you head off issues well well ahead of them, being issues that are, you know, pretty final for students. So, I'd I'd love Eddie, how is your how have your conversation shifted around this really big idea that is Agentic AI in education? Well, I hear sort of two broader conversations. One being around, oh, how might we automate and actually improve our processes to support students or actually save money for our our institutions? So that's one sort of boss. Like, how do we leverage it to do our work better on campuses? There's also the concern around how students might be able to leverage an agentic AI to actually, like, take an online course, for instance. And I have colleagues that have been sort of, like, pushing that space, and they're getting close to seeing that, you know, you could give your login credentials to an agent like AI, and it it could work its way, you know, largely through a course with maybe just a few interventions from from a student or from a guide. But that's that's what the current, sort of almost pre first generation of these agentic AI tools. So there's definitely I mean, you know, this this notion of 48% expect a major model shift. Agentic AI, I think, is really gonna create I mean, I think specifically for the asynchronous online course, there are real challenges ahead of us as AI continues to mature. Yes. And I think, you know, also just thinking about the the type of students who go into an asynchronous course. Right? You know, what are some of the psychological, sort of check box marks that a student says that's the right path for me. Maybe some of that those just reasons could be, augmented to push them back into different types of learning environments because of what AgenTic AI can do to support them, in terms of their own student success. So, like, I think it's all really up for grabs in the next several months and years. And, you know, this notion that 35% are behind, I would say that that is a that's that's probably padded. Or I think most of institutions, even the the biggest institutions in America right now tell us, like, we we are we feel like we're already behind. And I think, gosh, you guys are the first movers around defining us and getting this going for fall. So we'll see really the pace at which these, institutions pilot and get going with some of these agents that are gonna come to market. On the matrix again, in terms of impact and effort, you know, how would you recommend, you know, low hanging fruit, easiest way for an institution to get started with the agentic AI would be, this AI workflow or one zero one drop ins. So do you have any other recommendations around a quick way for someone to get familiar, with with agents? Well, I mean, I think one of the first things is for campus campuses to do a bit of their own, you know, recon regarding what some of the leaders in this space are doing. And so, you know, the the usual players are probably campuses to keep an eye on, like University of Michigan, Georgia Tech, UCF, Arizona State. Certainly, they're doing some really forward thinking, things. But to get a sense of exactly what is possible, not that they're necessarily the models to follow because often their their, innovation forward profile and their budgeting around that make it might make some strategies impractical. But to see exactly what is possible is really, really helpful. But there's there are some lower hanging fruit. I mean, you know, building custom agents, you know, that's that's one approach is for, like, understand what that work could do for you or what those kinds of tools could do for you and for your students. That might be a good place to kind of start. You know, a lot of effort associated with it, but, you'll see increasing impact, as more things can become automated. Yeah. And do you when you think about the type of people who raised their hands three years ago to sort of really figure out the impact of generative AI broadly, there's probably a world where several of those people are doing the same work. Right? This, you know, AI technology is rapidly evolving, like, tapping into that that same sort of, personality trait, the people who love to dig in and try new things and making sure that those people also bring in different voices into that work. So we build this sort of culture of, innovation and and and sort of, you know, low lower lowering the sort of sentiment around failing, failing often and and iterating. So, let's talk about the, the next trend. The big a big trend here is if we are moving away from completely banning AI and we wanna see adoption and and and and measure impact, we really are talking about, this notion of responsible use. You know, some of these stats here are pretty big stats. 95%, of people have concerns over academic integrity. What does that really mean in 2025 if you are adopting AI? How how do how do you create policy that, that makes you feel like you are you have integrity and your degrees mean something? 76% say privacy and misinformation, must be taught. That is a new skill set around, you know, not defaulting to trust, but really being highly skeptical of your sources. And then 81% fear wider gaps in equitable access because of, you know, broad broad adoption. So I'd love your perspective here. What what do you what do you think these figures tell us on where what to focus on? I think that these are the right concerns. I think that, we we recognizing the key challenges. I don't know of of almost anyone in any discipline that's not concerned about academic integrity in one way and what what are the implications, from AI. I mean, you know, AI detectors are kind of a a nonstarter for an array of different reasons we're discovering. And so it really suggests that our strategy is probably a portfolio of strategies where we talk about academic integrity with our students. Maybe we have more flexibility regarding, students asking for extensions. I mean, maybe maybe the new best practice, the signature, syllabus, approach is that we don't have any assignments that are worth more than 15% of the final grade. Students are more likely to cheat if it's worth 50% of the final grade or a third of the course grade. So, you know, let's decrease the reasons why students choose to cheat. I mean, we have a lot of control over those things. So if if the highest grade point for anything in a course is maybe 15% of the final grade, students would be less inclined to cheat because they're not gonna fail the course if they get a bad grade on that just that one assignment. So there's lots of there's lots of practices there that these that that these certain areas, suggest. I mean, there's things that we can do. We we don't have to throw our hands up at it. Yeah. In terms of, like, the quick quick, wins matrix for this summer ahead of fall in terms of responsible use and privacy, here's some of, you know, some of the things that someone might wanna get going on, which is, you know, sharing out, you know, AI privacy and misinformation tips. Right? Like, this is something that needs to be top of mind for both students and faculty, hosting webinars around integrity and privacy and what what what your data, is either doing, because of what tools you're using and what you might wanna look for as a consumer of of AI. And then thinking about, you know, micro credentials. I know you you probably are hearing more and more of these, these things coming up. I think you mentioned, in previous conversations around, AI, you know, being even a full focal point of study. So, we'd love to hear your perspective on ways that people can get going on on this third trend this summer. Well, I think if we all agree that at least part of the purpose of higher education, regardless of institution type, is to prepare students for the world post graduation, which means it includes the world of work. And the world of work is now demanding, AI skills in its new hires. Lots of different studies regarding employers are suggesting that that is something that they're looking for. One study from Microsoft actually said two thirds of leaders, not the hiring managers, but leaders said that they wouldn't hire someone if they didn't have some level of competency with AI at this point. So that kinda suggests to me that AI literacy is essential learning for colleges I mean, for college graduate. So that doesn't mean that everyone on the college campus needs to be teaching AI literacy, but it means it's a curricular challenge. So this is a learning outcome that belongs in the curriculum. So do the curriculum map where where might it best be taught? Okay. It's these three courses or whatever in a program of study. Well, then that that's where it should be taught. Those are the faculty that should be provided the professional development opportunities or access to the tools. But I think it's really moving to the domain of a curricular challenge, and we're really good with curricular challenge. Let's see it that way, find a place for it, and then prepare students for what awaits them post graduation. Yep. Let higher ed do what higher ed does best. Right? Like, go, solve the what what learning outcomes need to be met and have I mean, look, there's everybody who's in this entire vertical has advanced degrees around, being great educators. So, it's it's really an exciting time, I think, for people to get back to doing more of what they really wanna love, which is or love, which is, innovating for the right, outcomes with students. So let's recap, on what we talked about today. The key oh, we're gonna do I I skipped ahead. I got too excited. Before we recap, let's we did have some questions that were submitted. So, I'll go ahead and and, share a question we got from, looks like Jenny, send a question. So, Eddie, there's a lot of ambiguity in, with with with AI and policy and just a lot of swirl happening in higher education. I love your perception here, but why why should people make AI a priority right now given everything going on, around education and the discourse around education? Yeah. That's a great question. I mean, you know, there's this this is almost a moment of retrenchment. Right? Because campuses are in many state context, they haven't got their state budgets. They've been told it might be July or beyond before they'll know what their budgets are. So how do you plan forward? So there's there's lots of good rationale for why maybe we shouldn't be expanding the scope of what we do. But then I also think that it's really key that higher education continue to remain relevant, toward its mission and purpose within broader society. And, ultimately, if we're not meeting the needs of students, especially around new emerging, outcomes, there are others that will will be pursuing that work. I mean, if you look right now, Microsoft, LinkedIn, and others have micro credentials and certificates in AI literacy. Though I think most still look to higher education as the logical place within society where these kinds of challenges educational challenges will be, solved. I mean, it's a bit of a Sputnik moment in some ways and that, you know, we're now competing with China and their products like DeepSeek. I mean, we're it's a different landscape. I I I think this is something that we really do have to give attention to given this specific moment in time. And, I mean, ultimately, to maintain our relevancy, if we if we shy away from something that is so critical, then as we think about next funding cycles, are we likely to be seen as the solution to challenges or or not? Yeah. Yeah. Well, it is graduation season. And so for those of you that have, graduates or, you know, are this is a personal time for lots of celebration of students moving into the world of work. What do you think is gonna happen for these students who are graduating this year as they enter, the world of work? And then also fast follow-up question from somebody named Ty. What should institutions be doing to prepare seniors for next graduation cycle next year, around this notion of the world of work in AI? Yeah. Well, there was a study last June that asked recent graduates how prepared they were for the world of work and, you know, 70% said why didn't my university prepare me for the AI skills that were required? I know that survey is gonna be repeated, you know, next month. You know, we'll see other similar studies of, recent graduates. And so I'm wondering, are we likely to see those numbers be higher or lower? I I suspect we're they're not too far off. You know? I think from last year's numbers, I think there's still gonna be a lot of frustrated students who found that they really didn't weren't prepared for the work that awaited them in terms of AI. We prepared them in lots of other ways, but in terms of AI. So I do think that I don't know what I don't know what that look is for higher ed if we have multiple years where graduates year after year after year say, why didn't you prepare me for this? I do think that this is something that we really need to lean into, going into our graduates for May of twenty twenty six, which it may simply be just looking at those senior seminars, the senior capstone experiences, and maybe that's the logical place, at least initially within the curriculum, to place AI literacy, AI competency skills. That's that's maybe the initial focus right before students graduate. But then as time passes, we can build deeper into the curriculum, maybe as students enter college, maybe as part of the gen ed experience or other places. But I think if someone was looking, where do I where should I invest first for this coming year? Maybe it is those seniors and the senior capstone courses, those last semester courses. Yep. I love that. Well, in the spirit of time, let's move on and just high level talk about the key takeaways that we shared today. Obviously, clear, transparent policy around AI is going to be important for students to build trust and really lean into new, types of assignments and new out outcomes for for their work, as as, students. Automation is gonna be a big deal. You're gonna hear way more about agents as, we start thinking about ways that, there's gonna be efficiency gains both professionally and what that might mean for student workflows. And then trust. Trust's gonna be important, you know, not only, in how, different, partners, bring transparency in their security and how they collect data and how they don't collect data, but understanding what happens with engagement of different AIs is gonna be really important for both students and administrators to to really, to know. So if if Grammarly can help you with any of this, you can engage with our teams. We also have several several, bits of reports to share, both the Grammarly's AI shortlist for 2025 for higher ed as well as AAC&U leading through disruption, higher education executive, executives are assessing AI's impact on teaching and learning. Both of those are resources for you to share now. And then, Eddie, I want you to talk about something that we've been working with you all in the last year. What's happening, for AAC&U? Absolutely. Recognizing AI as an essential learning outcome for higher education, recognizing that it's a curricular challenge, We launched an institute on AI pedagogy and the curriculum to help higher ed institutions navigate, those challenges, help them first develop an action plan, and then help them enact it. Our campuses send teams of five or more to participate within the institute. This past year, we had a 29 teams from a 24 different campuses participate, and each team is provided with a national expert on AI and higher education. It was a fantastic success. We really helped campuses move, their work forward. And so we have a call that's open until May, 2025 for the institute that launches on September 11. So if you've got a team, your campus wants to engage in some of this work at, at that scale, Come join AAC&U in accomplishing your goals. Amazing. Eddie, always a pleasure, to have the discussion. I appreciate that you and AAC&U, not only do you talk the talk, but you walk the walk with applicable ways, people can get started with AI. So thank you so much for everyone, who joined, and we look forward to continuing this important conversation.