AI, Friction, and the Future of Teaching and Learning: Lessons from Gemini 3

Welcome to another episode of AI Goes to College.I am joined, as always, by my friend, colleague, and co host, Dr. Robert E. Crossler from Washington State University, where I'm guessing it is considerably cooler than it is here in Louisiana right now.

We have snow in the forecast, Craig.

Yeah, we do not. We do not. We have sweat in the forecast. So. All right, well, let's get right to it.So I wanted to start off with a little bit of weird, upsetting experience I had with Gemini 3, which is Google's new super duper AI model. And it is supposed to be a very, very good model, arguably the best that's out there right now.And it was literally released within the last few days.And so one of the ways that I test out new models is by getting it to do a deep research report, because I think that requires it to go through its paces. It's got to avoid hallucinating. It's got to do some quote unquote reasoning and planning. And so it's a really pretty rigorous test.

And Craig, I'd like to chime in here.What I think is awesome about the tests that you do and that I see other people do as these models come out is they have the same test that they repeat over and over again, so that where they're controlling the test they're doing. So you can easily compare what you're getting from what you got in a prior version or in somebody else's deployment of one of these.So I think that's a great practice. And so I'm encouraged to hear kind of what you found from that.

What I do when I want to do a deep research report is I use meta prompting, which basically means get AI to write the prompt. And I started doing that for deep research reports because you have kind of a limited number of them and they take a while to run.You don't want to have to iterate through them. So I did what I always do and I put in I want a deep research report on whatever the topic was. Xyz, please write the deep research prompt.And Gemini went straight into its planning.So the way Gemini works a little bit different than the way some of the other deep research tools work is it presents you with a research plan that you can either approve or edit. ChatGPT will ask you some clarifying questions and then do its thing.And I said, no, I want you to write the prompt, but don't start your research yet. And it said, oh, okay, and immediately gave me its research plan again. So I thought, well, maybe there's something triggering this.And so I tried it three or four different ways. Finally, through a pretty convoluted process, I got it to write a code block that was actually a prompt instead of just launching into the research.

So let me pause there and just say what I hear you saying is that the change overnight change into Gemini, you got something completely different than what you used to get from it. So your experience had changed just in and of that self, let alone where you're going with this conversation.

Right.And so what would happen in the past, and I've done this with ChatGPT Claude Perplexity Gemini, it will write the prompt and they're usually two or three page long prompts that I'll then go in and edit if necessary, and then use that prompt to start the deep research report. But I noticed Gemini even triggered the deep research toggle. So.So there's a place where you can choose the tools in the bottom of Gemini like you can with most of the chatbots. And all of a sudden deep research just appeared down there, even though I had not selected it.And so it took me, I don't know, 10 or 15 minutes just to get this prompt. I thought, what in the world is going on here? Why is this so hard? I've done this dozens and dozens of times.And so I started to do a little bit of research into Gemini 3. And one of the things that they're really pushing with Gemini 3 is that it's more agentic.And what that basically means, and this is a very non technical definition, is that the AI is going to go off and do its thing with minimal user interaction. It's kind of like, Rob, you've got an assistant. You tell your assistant, hey, plan this meeting with these people. You've got my calendar, just do it.And your assistant goes through and organizes everything and only comes to you if there's some sort of a problem. They are acting as your agent and they go out and do what you want them to do.And what appears to be happening is that all of the major models are pushing into this agentic mode where they require less user interaction in order to get some tasks done. I want to pause here and make sure I'm explaining this reasonably well. So does that all make sense, Rob?

Yeah, absolutely.I think that analogy captures the whole idea of moving from AI as a tool that you're using to help you to almost a colleague of some level that is doing things on your behalf.

All right, on the surface that's not a bad thing. Like if I want to plan a trip, if I want to plan a meal, if I want to schedule something.Having this AI agent that just does it for me is pretty useful. And it's more useful the less effort that I have to put into it.So I can totally understand where the companies are coming from when they're making this move into more agentic AI. But here's the problem. The whole point of agentic AI is to remove friction. So you're trying to eliminate at least some of what the user has to do.You just describe what you want done. AI goes out and does it. That is great for a lot of task completion types of work. It is horrible from a learning perspective.Learning requires what they call useful friction. If you're not doing any work, you are not learning. Period. End of sentence. And when AI without being asked to, this is really the key thing.We've had AI agents for a while and you can set them up and they go out and do things for you. I have one that summarizes my week calendar. I have one that goes out and finds the latest AI news.And so I have several of these agents running around. But I specifically wanted to invoke agentic AI. When I did that, Gemini did it on its own.Imagine I'm a student who's trying to complete a research task. Now it just does it for me. And so I don't learn anything from the creation of that research report. I don't have to struggle.I don't have to make many, maybe not any decisions. It just goes out and does it for me totally without me asking it to.So I think we're moving into really dangerous territory when it comes to AI and higher ed. I'm going to go so far as to say that right now this is the first thing that's made me pessimistic about AI's long term impact on higher ed.Because I think this just changes everything. All right, I'm going to relax now.

No, no.This is the first time I've heard you be pessimistic, which to me is worth us pausing for a minute to make sure we understand where this pessimism comes from.Because I've talked to some of my colleagues who have already started using Gemini 3 in their classroom and they are super excited about what they're now able to do with it. So I've heard the complete opposite takes from other professors that I interact with regularly about how excited they are about what AI is doing.And now I'm hearing from you, who's been very excited about some Other things that has a different take. What about that makes you pessimistic towards what's going on?

So there are two or three things. The first one was I didn't ask it to be my agent.I wanted to see the prompt, I wanted to be able to edit the prompt, I wanted to be able to examine it. And it did give me kind of that opportunity with the research plan. But it's not the same. I didn't ask it to be my agent. That's the biggest thing.So I can see students going in, trying to get some help, hey, I need some help figuring out how to approach this coding problem.And instead of saying, okay, let me walk through the problem with you and help you figure it out, it just goes, I haven't tested this, by the way, so I'm way out there kind of speculating. But under an agentic model, it'll just go, here's your code and where's the learning in that?And what worries me is that students are not going to realize they're doing something that undermines their own learning. It's paternalism. So now the AI model knows what's best for us. It knows how to do what we want done and it just goes out and does it.And that's great for some things. Like I said, bad for learning well.

And I also think it's bad for differences of perspective. One of the things that, as I listened to you talk that came to my mind is the world that we live in with bias.And I'm going to use news as an example. If I go off and read a news article on Fox News, I know the perspective that I'm getting that it's more right leaning.If I go to CNN and read the exact same topical article, I know that I'm getting maybe a more left leaning perspective on that news.And as a critical thinker, I can take both perspectives and try to rationalize what I think is really going on and try to remove influence I have from a bias from one direction or another and from students in the classroom as they're beginning to learn different ways of approaching problems and different things. Differences of perspective on how you do that are actually going to be part of that friction. Of which one do I pick? These two?Both approach these problems from different perspectives. The student's going to agonize over do I pick A or do I pick B?And with what you're describing, how the agency solutions are guessing what it is that they want and giving them a solution that we're going to remove from that process, that point of struggle for the students of which model do I apply to solve this problem?

Right, right. So it's almost the difference between building a piece of furniture and getting a flat pack from ikea. If you're a craftsman, you use the tools.You've got your saw, your router, your planer. Those are all the tools I know about.I suppose there's a screwdriver in there somewhere, but you know how to use all of those tools in a way that makes a nice looking, well built piece of furniture. Ikea, you get this flat pack and it feels like you're doing something, but you're not a craftsman. Right.I mean, it's almost like using a cake mix instead of baking a cake from scratch. Yeah, you get a cake and the cake's not bad, but you're not a baker.

Well, let's even add another layer to that is I take that IKEA shelf and I build it. I'm proud of myself. Right. I built a piece of furniture.And we're gonna see similar things happening with our students is they are going to make something and they're gonna be really proud of what they made because they had the flat pack from IKEA or whatever.And it's gonna give them a false sense of their ability to do the job because they provided very little of the expertise that we would see from either a craftsman or a baker, or in this case, from a knowledge worker.

Rob, I have this memory that you actually are a craftsman, aren't you?

I have built a few pieces of furniture, yes.

So, yeah, I should let you take that metaphor because I clearly got out of my debt quite quickly. But here's the bigger point. So let's separate AI out into tool mode and authentic mode.With the tool mode, there are some clear transactional boundaries. If you say, write my essay for me, you're doing something wrong. Right.If you say, help me plan out how to research the background material for my essay, you're probably not doing something wrong. Right. So you've got much clearer boundaries.But with genetic mode, a student might say, help me develop a research plan on, you know, furniture building. God, that cannot be the right term. Furniture building. So stocking a pond.There's something I know about, and all of a sudden, because it's in agentic mode and it's got this what we might call a helpfulness bias, it goes out and writes your essay for you. Now, again, I haven't tested any of this. This is literally a hot take that just happened last night.I think and so now the student is, okay, I've got this essay that I can go in and edit a little bit and get rid of the EM dashes and the delves and the deep dives, and it's probably going to be pretty good, and I'm going to be pretty done. And I can go out and do other things that I want to do or maybe study for other classes.So it may not be they're going out partying, maybe they've got a stats test to study for, or maybe that.

Student who's working two jobs can now get eight hours of sleep tonight instead of six.

Yeah, so the temptation is great there. And I can't say that I would have resisted that temptation as an undergrad student. I mean, hopefully. But I don't know.Although I would have not gone the sleep path, I would have gone out with my buddy's path. But the point remains the same.But AI is trying to be helpful, and in a lot of business settings, that's what you want, but not in an educational setting. And so here's the other big point.I think we're seeing a sort of skill inversion where up until now you had to be pretty skilled to use AI inappropriately and get away with it.If your professor knew what was going on, you could run it through different things and you'd know what to edit, and you had to kind of know what you were doing. Now I think you have to really know what you're doing to avoid doing the wrong things. And that's a huge shift.

And I agree. And that's where the challenge is. And so as you share that, I start to think about, well, so what do we do?We've identified the problem, now what do we do?And my first reaction is, I need to care a lot less about the outcome of what is created because we're not going to be able to validate outcomes in ways that we used to be able to validate outcomes as assessment measures that tell us if the students learned the thing. And so if we can't look at outcomes, what can we look at? I think part of it is the process. How did they go about using this? Right.So if this agentic AI is going to be used, if the student can't demonstrate what they've learned in some way in the classroom, where they have to rely on the knowledge of the process, or they can't share with me how the document was created, that was the output that then I can't assess how good they are at actually using these AI. I'm going to call them tools. They're agents, but at some level they're all tools. How do they use what's available to them to create these documents?And we think about as this applies to the work setting.We need to develop students to enter the workplace as their own independent thinkers that bring added value to whatever it is that the technologies can do, which is no different than what our expectations were before. I need to add value to what Microsoft Excel can do. I need to add value to what these other things can do.But a lot of that took being able to create those outputs and manually be able to do that through the various ways of using the tools. And now it's different.And we need to change how we evaluate and how we teach so we can focus on that which is going to grow these students into the professionals that we want them to be.

So I totally agree with everything you said there.

Well, thank you.

But I'm resisting the urge to say and it's a huge but however. And it's a huge however. How do you do that at scale?So if I'm so in one of the classes that I teach, when I teach undergrads, they do a couple of big Excel projects, I can grade those things so quickly because I know where they're likely to make mistakes and I know which numbers are the key numbers. And so I can grade a pretty complicated spreadsheet pretty quickly. How do you do that with process?It's really hard to grade process and I think it's especially hard to try to automate that because there is not a process. There are many, many, almost infinite, an almost infinite number of valid processes to produce something.They're all based on your individual cognitive habits and capabilities and a thousand other things. So I don't know, I guess we can kind of fake it, require them to turn into all kinds of stuff and spot check them. But I don't know how we scale that.

Well, maybe AI helps us to do that. That'll be the next few that drops is tools that help us to accomplish those things.But one thing I keep going back to, and I've seen this in a number of different conversations, is if we go back to the origins of teaching and Socrates based dialogues and seminar based instructions where we actually.If I have a conversation with you, Craig, and you can't explain to me why you made the decisions that you made to do and this processing of what's going on, then I can assess that you really don't understand it. You don't have a firm grasp on the knowledge, the whys and so forth. Could I do that in a class of 40 students? I'm trying to do that this semester.It's a fair amount of work, but it seems to be working. As I thought about how would that scale to large classrooms that are 70, 100? I know some of us teach classrooms of 300 students.Part of it's the question of rethinking even how we teach.One of the conversations I had the other day is what if we took our class of 70 students and on Tuesday 35 of them showed up and on Thursday the other 35 showed up and we find ways for them to be doing outside of work related things that brings them to class on the day that they show up engaging with a smaller group where we can give that individualized feedback. So what I am encouraging in conversations and we're starting to talk about at WSU is how do we create a lab for radical change to how we teach?I don't know what that looks like, but let's get people thinking about it because to your point, I don't think our traditional methods of teaching are going to scale nicely with how we need to be engaging with students to ensure that learning is occurring.

No, I agree. And another reason for my pessimism, is that what you're talking about? Although I agree that it's necessary. Who's got time for that?I mean, really, who's got time?We're barely keeping our head above water as it is, with more and more reporting responsibilities and classes that are limited only by the room size and advising and a bunch of other things. I used to feel like I could see a path where this would play out. And I just, I'm not so sure I see it right now.

And that's where I think radical thinking in a lot of the things we do is what's going to get us there. Ever since I've entered administration, I like to ask the question of why are we doing this? And if it's.

I thought you were going to say, what were you thinking?

What was I thinking? Well, my wife asks me, but why are we doing this? And if the answer is it's.And the sole answer is we do it because that's the way we've always done it. If we can't get to a better why than that, then we need to quit doing things that way.And I think we need to take maybe even a more drastic approach as we think about how do we accomplish what our teaching mission is at universities in this world where AI is Going on is, are there things that we do that we do because we've always done them. That if we were to throw out how we run a university and recreate it in the world that exists today, what would that look like?And I think it would look different. Unfortunately, we have a lot of things that get in our way from actually being able to do that. I don't think we can.But I think that thought exercise begins allowing us to identify those pieces that we can then try to bureaucratically move out of the way and replace with the stuff that we should be focused on to ensure that we're doing the best for our students, to prepare them for the world that's out there.

Yeah. Now, again, I can't argue with any of that, but I just don't see how that happens.It's tough to move higher ed, so I think we need to start accelerating the conversations.I think another reason that I'm a little bit pessimistic is that we're coming up on three years and I don't know that we're substantially better off than we were two and a half years ago. So.

So I think we're going to end up in a world, Craig, of the haves and the have nots, those that are successful and those that aren't.I was just at an academic leadership conference and I saw some really encouraging things that are going on at some universities in this country and then a lot of other people taking frantic notes. I think we have those that are leading and those that are trying to get ahead of this and do it well.And then there's a lot that are going to be looking to them to say, how did you do it? How can we mirror that? You are at a cutting edge kind of forward thinking institution.I encourage you to support and help those that are in your circle that might need to lean on your thinking in order to work with their administration on getting things done.

Good advice.I want to come at this from a little bit different angle and then we can move on to the next topic because I'm starting to feel like an even older curmudgeon than I really am.I think we need to start working on the students, and we've talked about this before, that transactional mindset of education that we've baked into students. If we can convince them that learning is work and learning is worthwhile, then the work of learning has a payoff.And I just don't think we've done a good job of making that case. I know you've got Kids that have hobbies, and I know one's just a fabulous musician, you probably did not have to get on them to practice.

Oh, yes, we did.

You.

Early on, that was the parenting. And the thanks I'm finally getting is thank me. Thank you for making me practice when I didn't.

So maybe that's what we need to do, is find ways to get on the students until they come around on their own, because it does take work. But. But look, you and I both sat through classes in our undergrad where we thought, well, this is a complete waste of time.I get the feeling that more and more students feel like that about more and more classes. And frankly, that's on us. We've got to do a better job there.

Right? And I've seen two things. I've been looking at this a little bit even before Gemini 3 dropped.As we raise the bar for what we expect from our students, they're able to achieve that bar. Along with raising the bar, I think there's two things that help them to want to get there. One is the why? Why do I need to work that hard?What's in it for me, if you will? Right. How does this connect to what my industry opportunities are going to be?How does this lead to what I'm going to do after I'm done with education? Or how does this help me be prepared for that next class that really needs me to know this so I can do this other thing?And the other thing is, how do we as faculty come behind our students and support them to be able to know what it is that they need to do to achieve that higher bar?So they're going to be shocked a little bit, but if they clearly know what it is they need to do, and we're able to spell that out for them, I think it prepares them or it encourages them to be able to actually do the thing that you're challenging them to do and getting better. If there's no support, then they feel like they're lost and they don't know how to get to where that new bar might be.

And I think that's a really important point about friction. So with learning, there's a sweet spot of friction. Too little friction, you don't learn too much friction. You get frustrated and you give up.And so we've got to find where that balance is, and AI could actually push that balance, and that's okay. I do want to give a little bit of advice here. Despite my pessimism, I think individual faculty can do some things.Find a Couple of ways in the coming term that you can maybe start playing around with this assessing process idea.Having more interactivity in your classes or maybe trying to emphasize learning more than grades, whatever it is, so you can start to chip away at this. I've been coming at it today from kind of a broad higher ed institutional perspective and I am kind of pessimistic about that.But it is within our power as individual faculty members to do some good around this. And I think what individual faculty members need to do first is they need to become competent with AI.And that's one of the reasons we do this podcast is if you're kind of clueless about AI, you're not going to help anything.So you need to work with tools, learn what can be done, maybe where those lines are that shouldn't be crossed so you can help your students understand that as well. But you want to say something? I'm done.

No, I'm going to give the same challenge to listeners out there that I shared with my faculty.And that is as you enter into the next term, find one thing that you're doing in your class that you can change the perspective and try to make this approach to say, I'm going to focus on the process oriented approach of this and take that risk. Just one thing.And as you change that one thing, if you want a second person's perspective on it first, I encourage you to check with the people in your hallways and open up dialogues in your local circles.But if you want me, and I'm going to volunteer Craig to give you feedback on that, we'd be happy to give it a set of eyeballs to say, but have you thought about or. Yeah, I think that should work. Go for it. I look forward to hearing what you're doing.I'd be happy to take some time and to help the community have that confidence to say, I'm going into this not as a silo, as an individual person, but as someone who has vetted this a little bit with others who think about this a lot.

Likewise.And so it's Rob Crossler, C R O S S L e r@AI goes to college.com or craig@aigostocollege.com along those same lines, we are still moving forward with our AI assignment repository a little slower than I would have liked, but that's still in the works. We're slowly starting to pull that together. All right, it's announcement time.

Rob, what announcements do we have?

Craig? So a couple of announcements. One, we are both going to be at the Upcoming International Conference on Information Systems.So to those of you who are in the information systems discipline and you're attending the conference, make sure you reach out to us. There will be a couple of opportunities for doing so in addition to just catching us in the halls.One, Rob is going to be a panelist at the College of Academic Leadership meeting which is on Sunday, December 14th. So, you know, look it up on the agenda, stick your head in and hear what Rob has to say. Rob, do you have anything you want to add to that?

Nope.

Well, that was easy. Now here's one that any of you can participate in. So we are going to do the first ever AI Goes to College livestream.It's going to be part of the International Conference on Information Systems Education Research workshop on Saturday, December 13th. And if you're at the conference, even if you're not registered for the education research workshop, you can still attend this.We're still waiting on the exact time. We'll get that out to everybody prior.I'll create a little episode or send something out to the mailing list, put it on the website to let people know. You can also attend it remotely. I mean, it's a live stream. So if it was just live, it would just be live, it would not be a live stream.So we're going to have a zoom link that will be available. It's free. You don't have to pre register, just kind of be there.We're going to provide audience members, whether they're remote or in person, the opportunity to ask us questions. So keep that in mind if you're going to be at the conference. It's going to be a lot of fun. I think there may be cocktails associated with it.That's still being worked out. So yeah, it could be really interesting. And that's going to be Saturday, December 13, sometime in the late afternoon or early evening.Again, you do not have to be registered for the workshop to attend. You don't even have to be registered for the main conference to attend. Everybody is welcome and there will be more on that coming up soon.

Perfect. And Craig, I'll add this is in Nashville, Tennessee, so if you're unaware, you might want to know that.And Craig and I will then therefore be in Nashville, Tennessee.So if you are not part of the information systems community and you're local to that area and you want to get together for a conversation, I'm sure we can figure out a time to be able to do that. So we'd be happy to meet some of you and to Encourage you in whatever ways that we can.

It'll be a great excuse to not go to sessions.

Did you say that out loud?

Question is, will I edit it out? Probably not. I'm tenured, you know, what the heck. All right, so yes, we hope you will be able to join us either in person or remotely.This workshop is a group of very dedicated educators, so they will have some fantastic insights, I am sure. All right, so Rob, you kind of folded in our second topic, but I want to see if you have anything more to say about it.The importance of teaching How? More than what? And then when you put this in our pre show notes, you said, or in other words, grading the process instead of the outcome.But I want to separate this out into two things. So there's the teaching part and then there's the assessment part. So I'd like for you to address both of those, if you don't mind.

Sure.So when it comes to teaching, one of the things that I've been thinking about a lot and trying to see where we can play with this is to leaning into project based learning where students are working, whether it's a project that an organization provides or one that we've been able to discern from our contacts and different things. So putting things together for students to basically work on projects.And what we're really going to be working with them on is they need to have the knowledge, they need to understand the why, they need to understand the how.And they're going to get all of that through completing of a project that's hopefully a little bit ugly and a little bit messy, to where some sort of a singular prompt isn't going to create the output that's going to solve the project. I see project based learning being a really good tool in our toolkit that can allow us to do that.And then on the assessment side, and what I've seen faculty doing that's working quite well is sometimes students are working on those projects or presenting milestones along the way in the classroom, and it's how they're working and what they're doing in their engagement, that is what's being graded, or their professionalism and their presentation skills and some of those software skills that the machine can't replace, that being given some a lot more of the points for what it takes to succeed in the class. So I think stepping back and saying, okay, how can we create a project in this area? Where can we find those sources?How can we define something so the students are working purposefully, not as the goal of Creating a solution to the project, though hopefully they get that and it's good, but it's really, what do they learn about that area, that topic that I'm teaching, as they're going through the process of completing that project?And how can I along the way through in class presentations, in class work in class conversations, how can I provide a feedback, be part of the conversation so that learning's happening and focus the grading on those parts that can be observed and that can be engaged with, as opposed to just that thing that was turned in on canvas that I use a rubric to say, okay, checks all the boxes.

So that's a great idea. One thing I would add is reflection is your friend here.One of the things I learned from the Jesuits when I was at St. Louis University is the value of reflection and learning.If you build some reflection pieces into the project process as regular milestones, you encourage students to think about exactly what you just said, Rob. What have they learned along the way? And that has all kinds of benefits.It not only deepens their learning because they have to process the information more, but it also documents where they think they are for you as the instructor. And you can assess the depth or shallowness of what they think they've learned so far. It's also really hard to fake reflection with AI really hard.They can get AI to help them, and that might not be the worst thing in the world to get AI to help them organize their thoughts or improve their writing, but the actual reflection, hard to do with AI and so I think there's a lot to be added by putting in some. You know, it depends on the project. Three or four reflection prompts at various points along the way.

Right.And one of the ways you can do reflection that I think is actually really kind of cool is to have students record audio reflections to where they begin articulating what they've learned.I've been trying that this semester, and it's been really neat to see how students may have struggled at the end of a week to articulate what it was they learned that week. But the more they do it, the more confidence they have in verbally expressing what it is they've learned and what they know.And I've done it in a perspective where they have a short amount of time to be able to do it and kind of like they'd answer an interview question. Right. You don't want to ramble on a job interview. You want to be able to think about what you've learned or think about the answer to a question.And tightly articulate that. So I think there's some really neat ways.And then with AI, you can actually get transcriptions pretty easy if you want to grade words and different things like that.So I think there's some cool, fun ways of doing these things that don't become another writing exercise even, but press into the development of our students and their speaking skills.

And if they want to ramble on and on and on, they can start a podcast.

Everyone should have one.

That's right. They'll have the skills. All right, so I want to close with.Unless you have something else on that topic, I want to close with one that's pretty related to what we were just talking about, and that's the increasing importance of professionalism, including presentation skills, where, as you put it in the notes, the machine does more and more of the technical aspects of things. And I'm going to project out here, how do we help students really express the human side of things more effectively? So what were you thinking there?

So I really think, and I'm hearing this more and more from our board of advisors, from the people who are hiring our students, is the need for critical thinking, which has been requested from our externals as long as I can remember.But really the importance of professionalism and how to get up and present and do different things beyond the world of AI that we live in, I think has really been since COVID We learned how to pivot a lot of what we were doing to technologies and two machines.And as a result, there haven't been nearly as many friction points to what Craig was saying earlier, where students receive that feedback that helps them to become more confident speaking in front of others and looking people in the eyes as they're talking and knowing what they're saying before they say it.And as we have more and more AI, I'm seeing more and more students with scripts on their phones that they read for presentations and things of that nature. And that's not going to cut it when they go out into their job.So the more opportunities we have to give that feedback to students to help create those friction points is going to make them better when they leave and represent the institution.

It's sometimes fun when they try to do the script thing. The main point of this project is dramatic pause. Oh, whoops. Shouldn't have read that part.I think that's going to be huge because you have to separate yourself out somehow.What I've always told students is your job on your resume and in interviews is to stand out from everybody else in good ways you can do that in a variety of different approaches, one of which is to increase your professionalism.Business schools are generally pretty good at that, but I think other areas around campus need to pay a little bit more attention that as I sit here in a Grateful Dog T shirt. All right, so I want to reiterate.We're going to be in Nashville on Saturday, December 13, and Sunday, December 14, the 13th will be our livestream at the International Conference on Information Systems Educational Research workshop. And Rob will be speaking on Sunday at the College of Academic Leadership meeting. All right, Rob, anything else?

Yeah, I wanted to add one last encouraging word. And you know, this was more of a pessimistic podcast than we've done in some of our previous ones.But as you go out and do your job, whatever that looks like, remember that you can only control what you can control. When you start fussing over those things that are outside of your control, you're only going to get frustrated.So own your space and do the best with what you can do. If we all do that, then we're going to get to the other side of whatever this is and we'll look back on it and say, wow, we did it.So control what you can control and let everything else be what it is.

All right, on that stoic note, we will call it a day. We will see you all next time on AI GOES to College. Thanks.