The following is a transcribed discussion held during TAMU-CC’s Digital Literacy Symposium in February 2025. Three college professors and one student reflect on how artificial intelligence is influencing their approaches to teaching, learning, and research – from adopting practical tools to big-picture shifts.
Panelists
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Korinne Caruso is Associate Professor of Computer Science at Del Mar College and member of the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). Previously, she served as an adjunct instructor and Engineering Program Coordinator for Recruitment and STEM Outreach at Texas A&M University-Corpus Christi.
- Stephen Doolan is Professor of English at TAMU-CC, specializing in Applied Linguistics. His research focuses on reading-writing connection, corpus linguistics and second language writing. He earned his Ph.D. in Applied Linguistics from North Arizona University.
- Jamie Ehlers is a biochemistry junior at TAMU-CC who is also doing undergraduate research work as a Billiot Chemistry Laboratory Research Assistant. Jamie also is Vice President of the Islander Women’s Rugby club.
- Joshua Watson is Regents Professor and Chair in the Department of Counseling and Educational Psychology at TAMU-CC. Dr. Watson has over 22 years of counseling experience working in a variety of community mental health and private practice settings. Dr. Watson received his Ph.D. at the University of North Carolina at Greensboro in Counseling and Counselor Education.
- Tara Carlisle (Moderator) is Director of the Digital Information Literacy program, I-Know, at TAMU-CC. She has 20 years’ experience as an academic librarian, specializing in digital scholarship. She received her M.S. in Information Science and M.A. in Art History at the University of North Texas.
Tara Carlisle: Welcome everyone! We’re here to get some perspectives from our panelists about their experiences using AI in teaching and research. I’ll be asking them a series of questions and then we’ll open it up for any kind of comments or questions.
First, I’m going to start off with a question for each of you. Have you experimented with AI tools in your teaching or research or work? If so, what was that experience like?
Caruso: So, yes, I’ve experimented with AI tools in teaching and research and my own studies as a student as well, so it is something that I’ve played in, and the experience is much like everyone else’s. I think, at the start, you’re uncomfortable, you’re not sure what you can ask or what to do, so I’ve used it for many different things, integrated into my lessons. I also use it daily to ask little things. So, I’ve kind of stopped using Google search all the time and kind of integrated it into a lot of things. So, it is pretty common for me.
Watson: I started using AI a couple of years ago for my research practice. So it’s been very helpful for me as a researcher. And then the natural transition was into my teaching work because I teach in a graduate program, and we have students at the doctoral level taking a number of research courses. So, I’ve kind of integrated that into that course and kind of teaching those skills to students.
Ehlers: AI kind of became more of a popular thing to use when I was in high school. But I never really experimented with it during high school. I didn’t trust it to, you know, do the things that people were using it for, such as writing their assignments for them and doing that and whatnot. But I have used it as a college student. I’ve used it in the research lab. I found that it’s good for giving ideas and alternative viewpoints that you haven’t considered and filling in the gaps of knowledge that I don’t have by maybe suggesting, like a different technique or something that I hadn’t considered before. So that’s the way that I’ve used it in my college experience.
Doolan: And so, for me, I just want to start by saying I’m not an expert in generative AI so I will try to keep my comments as it relates to my expertise. So yeah, the most useful contribution for me has been towards my research. With some assistance from a human tutor, and then also ChatGPT 4 and 4o, I taught myself how to code using Python. I had probably low intermediate skills when I began and I planned four tutorials with this programmer who’s an expert in my area. So, my field, corpus linguistics, is the study of language through the use of computers or large bodies of text, corpus bodies. And I planned 10 tutorials, and after 3 realized that ChatGPT was doing a really good job of assisting me in the writing of code. So, I had enough coding skills to think through in prose the steps that I needed to do, and then I used ChatGPT in order to basically translate that prose into code. When I got stuck, I was constantly checking for accuracy, because that was a real issue, and when I got stuck, I often was asking too much in the prose, and I had to take a step back and make the pieces a little smaller. In my field, there’s software that exists that does a lot of what I need to do. But existing software has limitations. It limits your imagination in terms of what the software can do. Because of that, learning python has expanded the innovative potential in my research.
Carlisle: How do you envision integrating it even further in your research, teaching, or learning?
Watson: In my classes, what it’s really helped to is it allows me to personalize learning. And so I am using it now to come up with very dynamic, multi-level case studies that we’re having students work through, you know, in the counseling program. There’s going to be many layers that people present with. This allows us to then kind of tailor some of these studies that can be used longitudinally over multiple semesters in different courses as students are developing in their complexity, in their skill set. It also allows for opportunities to have students really interact with the material and learn how to add different components as well. So, I found it’s been a really great tool to help with some of the in-class activities.
Carlisle: What tools are you using?
Watson: ChatGPT to do that. But then, also, I could talk about using it for research. We’re really looking at how students can use these AI tools in a lot of different areas from the onset of generating ideas, and what I like to call kind of curating the universe in their domain, to pull ideas. There are packages that we’re looking at like Elicit, and things like that, where they could kind of get article summaries and get a good sense of, okay, am I coming up with the same key points in an article that the computer is saying? So, it gives them a sense of are they on the right track?
Caruso: That’s good. I was, going to say, some of the things that I’ve recently started playing in a new tool called Character AI, and it would be fantastic for your area. They even have the ability for a student to do a mock interview. So you can click on interview, and it’ll have an individual that’s like, what are you trying to interview for? And it’ll pull information of what your job your career outlook would be, what kind of skills that you have, and you plug all that in. And then you’re having this real-life, one-on-one kind of feeling interview. You can make mistakes and get questions asked and figure out. Oh, I should! I should prepare for something like this, and you can respond to it, and it will tell you. Oh, maybe you should phrase it this way. So, it’s a nice new one. I hadn’t played in that one a lot yet, but I’m enjoying some of the new stuff that’s out. AI has been around for so long. This is just a new flavor of it, and I think there are so many different ways that we could use it.
Carlisle: Jamie, I saw you nodding your head
Ehlers: Yeah, I think that’s very cool. I’m also not an expert on the capabilities of AI. I don’t know much about how what it can and can’t do, but I think, having an opportunity like that, to be able, like what you said, to make mistakes and not have the pressure, but also getting good experience of what kinds of questions you might be asked would be definitely helpful to me as a student, and getting some experience without having to, you know, be on somebody else’s time, or afraid of messing up. So, I thought that was really cool.
Caruso: I think that’s a really good point, Jamie. We often forget that students are afraid to ask us questions, and I think this gives them the freedom of saying, I hear it all the time in my classroom,” I don’t want to ask it, because it’s a dumb question,” and there’s not dumb questions, but there are questions that make you feel uncomfortable. And I think, having that tool to say, okay, this is something I want to know, but I’m not ready to ask them yet. So, you can ask this tool, get a response, and, if you’re not comfortable with the response, you can keep digging and get more information about it. And I think that’s the key. But at least you have something to communicate with, get your question out, get some practice at it, and feel a little more comfortable.
Watson: I didn’t even think about this until that just spurred my memory. But we are in the process right now. We are creating, for our department, a chat ot, and we’re feeding in our student handbook. So that way, if students aren’t able to get their advisor or can’t find it, don’t feel like reading the whole thing, they can ask those questions. And so, we’re going through that kind of training process right now. But that looks like that’ll be really helpful.
Caruso: Yeah, there’s a lot of ways that you can feed it – a paragraph, you can feed it a book. So, one of the greatest things that I’ve seen recently is you can upload a PDF document and say, you know, this a hundred pages that I have to read, and I just need to get the gist of it. I don’t need to know it, so you can upload it, and it gives you this little note summary, and it highlights some of the key points, and for somebody like me I’m dyslexic. So, I’m a very slow, reader, and so if I can go through and pull the key points and then go back in and say “Oh, I got it all right,” and then I can read more thoroughly later.
Carlisle: So that kind of leads towards how you see how AI changing the way we’re learning and teaching. I think Jamie kind of referenced that, building the confidence. What are what are some ways to look forward and address that in terms of learning?
Doolan: I kind of see this as two questions. So, how students learn, and then, how faculty teach, they’re related, but I see them as kind of two questions. So, first, in terms of how students learn, I’ll focus on writing, because that’s my area of expertise and try to stay in my lane as much as I can. Learning to write is likely to be totally transformed by generative AI. There was a recent publication by Overstreet in 2023, who made a distinction between brain-bound and extended. And, brain bound, he called the use of external resources, primarily to structure internal, cognitive function. So, whatever you find out in the world, you need to put it together in your brain, versus, extended, where there’s more offloading. There’s the offloading to a higher degree of the cognitive function in the writer’s environment. So, the implications of this offloading, to other external sources of managing your cognitive load, is just totally new and fundamentally transforms what writing is. That’s from the student perspective. From the teaching perspective, I kind of see three possibilities. First, I see, the early adopters, and these will be the ones who just embrace and think, you know, this extended theoretical model, let’s teach it. Let’s learn it. Then there’s the resistance that’ll be actively fighting against these changes that are barreling towards us, and just try to continue this writing instruction as it’s been conceptualized for the last 2,500 years, back to ancient Greece. And then there’s the head in the sanders, where they continue to act like things are brain bound, even though students are increasingly embracing the extended model. So those are the 3 possibilities that I see. And of these patterns, academia and how it changes, it tends to do the extreme stuff. Ultimately the answer is usually in the middle, it’s usually blended, and the head in the sanders is just not terribly defensible at the moment, it feels like, and that’ll become even more so in the future.
Carlisle: Thank you. This is good.
Caruso: And earlier, you said you were using it for computer programming. It’s a great way to think about it. And in my field, I teach computer programming. So, when my students go in and try to use it, the big fear that we all have is, well, it writes the code for you, so what is your job now? So, in the classroom, when we go through it, I’m teaching the students how to write the prose. Let’s look at the problem that we’re trying to solve. What’s important about that problem before we start writing the program. So, I know that they’re going to get the solution to the problem using whatever AI tool they’re using, but now it’s did it find the right solution? How can we make it more efficient? What is this little function doing? I can pinpoint some things that we find in the program and say, okay, what if we take this chunk out and try this instead? How will it work? Now, I can have them run a program so much faster because they can plug it right into AI and say, Oh, wow! If I change it, that worked so much better, and the user gets a better interface. So, I think it gives us a chance to work faster in the classroom, too. Just like you said, you’re able to do this quick enough and just kind of fine tune. It’s great for students.
Watson: And I think it creates a new aspect of teaching, really. Now we’re teaching students how to use the tool and how to use it effectively as well. I heard this example once in one of our administrative meetings. It’s likened to when the calculator came out. We’re never going to teach again, but it’s a tool that you must know how to use to get the complete functionality out of it. So, I think the same thing here, while these models are continually evolving, to be able to use it effectively requires some skill set.
Caruso: Yeah. And we are at the lower end of AI right now. And we’ve had AI since the fifties. But we are at the lower end of these large language models. So, if you’re not on board, there is something getting better and better every time. And one of the things to remember, you’re right. That calculator. I remember being in the classroom being told. I remember being on this campus being told, don’t use your calculator, right? And so, I know we have to be taught to use these tools, as faculty as well as students. And I think that’s the key to making sure that we’re doing a good job with using the tool.
Carlisle: Thank you, because this is the great opener for the next question, what are some ways that you can think of that will, practical ways, maybe small ways that faculty can start incorporating. I know, Korinne, you just explained what you’re doing with your students, but what are some ways to prevent students or faculty who are embarking on this from feeling overwhelmed on where to begin?
Caruso: Don’t go in thinking you’re going to get magic out of it. But you just start small. Ask it a small question, start with vocabulary, start with test reviews, things like that. Generating a review or study guide. Give it a topic to give you something to work with. I think that’s a good start for teachers, professors, students to say, I have this chapter I need to read. Give me some key points to study. I think that’s a good way to just get started.
Carlisle: Jamie, as a student from your perspective, what would help you? What might be some examples of what you would like to help you get started?
Ehlers: I do have a professor that does encourage the use of AI as a tool. And he had even sent out an email that said, this is what I would suggest using as prompts, and if you’re not getting the information you want, how to probe further. And I think that’s been very helpful in making me feel less threatened, I guess, by AI, because I never wanted to use it before I learned that it could actually be used as a tool, and not just something that does your work for you. So, my understanding of it was very, very different than I don’t know the capabilities of it. But I think, yeah, definitely, just a small introduction to how to use it as a tool would be very beneficial as a student, because it’s something that is not going to leave the education system. Now, it’s definitely going to just become more prevalent. So, I would think, just being able to know how to use it like they are saying.
Carlisle: Anything to add…Dr. Watson?
Watson: Yeah, I would just say, don’t feel overwhelmed or scared. You’re using AI now; your social media is using the algorithms to do it. If you’ve ever been in those phone trees you’re using AI now. Find where it works in your area as well. So, what are the tools that would help in what you’re doing? Then practice, initially, with what you already know, because one of the things you’ll find is sometimes it gives you incorrect information, or maybe not the spin that you were looking for. So, when you’re putting prompts into some of these generative Ai’s, do things that you already know, or things that you are aware of what you want to cover in a class, or talk about, and see if it’s prompting the same thing, and not just always assume that what you get is going to be one hundred percent accurate.
Doolan: Basically, I feel like compiling information and synthesizing research has arrived like, I think it is very good at that at this point with the caveat, of course, that the information needs to be checked for accuracy. So, a program like NotebookLM, which is free and available to people, you can feed 50 sources into it, and then you can ask questions of those 50 sources in a way where it spits back answers with citations. So, then you can go to the citations and see where in the source that information is coming from. I feel like compiling and synthesizing information is something that these large language models are doing well now, and is a wonderful resource, for academics, students, all of us.
Caruso: I think he brings up a good point. Find the one that works for you, because when it first, when LLMs first took off.
Carlisle: Large language models.
Caruso: Yes, large language models took off. It was like, do I want to pay that one? And it was like, where did I save that stuff that was useful, like, which site was the good one? So, there are so many, and you do have to identify the ones that you’re enjoying using that can back can kind of keep your backlog as well. ChatGPT does a really good job of now keeping it as notes and organizing things for people. Microsoft co-pilot all built into all our stuff. So, using some of the bigger ones that you know are being fine-tuned more often is also helpful, but pick one and don’t go crazy trying all of them because you may get overwhelmed very quickly doing that.
Carlisle: So what do you anticipate, or what are you, or what do you see now, as challenges? Again, from the vantage point of educator or from the vantage point of a student.
Doolan: From my personal experience with the coding, one day, I lost access to ChatGPT briefly, and very immediately I was reminded that I have not learned how to code, that I have learned how to use ChatGPT to code, and those two skill-sets can be easily conflated. And as students and teachers as we try to promote learning, we need to be aware that conflating those things is really problematic. So my concern is that students will conflate the accomplishment of the task with the help of ChatGPT for learning how to accomplish the task in a more traditional, brain-bound way. How might we address this concern? Well, it depends on what we want our students to learn. So, what we want them to learn should probably be influenced by their future jobs, and what do they need to learn. So, for example, I teach a class called intro to linguistics and I have them use the sounds of language, and they have to phonetically transcribe it. Yes Ipa. On the test, I let them have the cheat sheet there in front of them, because do they really need to memorize that for their future lives? Absolutely not. But I’m teaching a grammar class, And last week someone asked me, can we use a cheat sheet for the test, and I said, No, you can’t, and the reason is, you will be up in front of a class in the future, and you won’t have a cheat sheet with you. You need this information. So what are their future jobs requiring of them? And then maybe we should think about, what type of well-rounded soft skills do we want graduates to have? I don’t know if that’s too fluffy a thing to want, but I feel like there might be value to that. So, to the degree that we still think brain bound learning is important, then instructors need to change their assessment practices so that there’s positive washback, so that the learning that happens, it’s reflective of actual brain-bound learning. For example, last semester In my writing class I redesigned the class. We met in a computer lab. I used lockdown browsers. And every day students wrote; they just wrote, without AI. I had a very hard time setting this up. And I learned that I was the only one on campus who was making an attempt to try to do this. I have a daughter in high school, apparently in high school they’re doing this a lot. This is something that’s pretty regularly done. In short, it all depends on assessment and what we want our students to learn.
Carlisle: That’s interesting. So, you’re really having to take a very concerted effort at kind of closing that down. So, there isn’t that temptation?
Doolan: I mean, it totally depends on what you want people to learn.
Watson: I think, just, you know, it’s important for students to understand what you’re looking at as well. And these are all computer models that are learning based on data that is fed to it or acquired from certain sources. And so, there’s bias there depending on the information that’s being fed to it. And you know we’ve all talked about the accuracy sometimes of what you get. It may not be accurate. We were actually just doing this in a department meeting the other day, we kind of started talking about it. So we all wrote a couple of sentences, fed it through checkers or AI checkers. And they’re coming up for large percentages of “AI written” and like we just sat here and wrote it in person. And so, what are the implications if we’re using it in class, and we’re just solely going on,.oh, it’s coming back as an AI checker. What is the algorithm pulling? What’s flagging it as AI writing? So that’s something to, we’ve had faculty members who have asked. Give us a writing sample and provide some references, and they are not real references. They’re not in the journal they list. There’s not even an article in anywhere by that name. So you know you’re getting these hallucinations that are not real. But as students, if you’re just saying oh, I got a citation,I’m putting it in. And as faculty, if you’re just looking, it’s like, okay, it’s in a journal. It looks like something. So it’s creating that level, too, that we need to really look at kind of the ethics of using it and the accuracy.
Caruso: This is good. The citations…interestingly enough, before we came to the this session, I asked it for 5 top AI tools we’re using today. And all the links to the AI tools were wrong. It couldn’t find the right AI tool. So, it really is pick and choose and make sure that you’re looking at it. Additionally, I’ll tell you, this is a little story about what’s happened in my classroom, because the coding it happens so easily. I had a student who’s really struggling to learn how to use a certain device, and said, I need some help but I’ve been using AI so much, and so a lot of our students, they’ve told us yes, I have used it too much and I really, I don’t know how to program. I am. I’m kind of getting through. And so it’s going to happen. And we do have to find a way to say, Okay, if you’ve been using it, how are you using it? So, it took me sitting down and we had a two-hour conference, one on one. Let’s go through what you did. How did you do it? So, instead of, you got a 0 get out of my classroom, it was, okay, how did you do this? Let’s talk through. Why did you pick this? Why is this piece important? And walking through each step. The easier part for me is, I do have a smaller, smaller group of students, and so I can do a lot more one on one with them and guide them in that range. But it can’t be the old, you know, slap on the wrist with a ruler like it used to be, it needs to be a let me teach you those skills so that you don’t make the same mistake when an employer, or an internship, or something like that is in place. We’re here to teach them and guide them to the right path, not just give them zeros. Jamie, for you. What are the challenges?
Ehlers: I try not to use it as something that does the learning for me, because, especially as a student in science like, it’s very important that you’re learning and fully understanding, from day one, what you’re supposed to be learning about and not relying on something else to do it for you, just because you’ll get so lost longer along the way if you don’t know your fundamentals. But I can’t remember who was talking about it, but I think oh, I think like you were saying I think it would be helpful to know what times are appropriate to use it…
Carlisle: Those guidelines or that guidance.
Ehlers: Yeah, some kind of boundary that needs to be set because I’m not somebody who likes to use it very often but knowing that it’s okay to use it in this situation could be beneficial to all kinds of students that even rely on it more than I would personally.
Carlisle: What kind of support or resources would make either students or faculty using AI in their academic work. So, when we think about maybe those who are, they’re curious, but they’re not sure how to start, What resources might the library or the campus community provide and what sources for students as well.
Caruso: We can do more stuff like this. Honestly, it’s very open-ended conversations, examples, small, hands-on workshops. It would be great if faculty, I’ve got many of my colleagues in the room, faculty, staff. We’d sit down and say, let’s pick an AI tool. Let’s all work together to teach each other how to use it. And I think if we had more workshops where they just did hands on and showed what it was capable of and what it can’t do really well. It gives people the perspective of what they can use, because fortune 500 companies, 1,000 companies, whatever you want to call them, they’re all using it. It is well integrated in their workflows now, and we’re hearing it’s rising so frequently. So, the more we see it, the better. So, resources need to be something comfortable as faculty, you know, I would tell you from a faculty perspective, we don’t want somebody telling us what we can’t teach in our class, because it is our class, and we do have the academic freedom to teach. But we do want somebody to support the objective of our course. And I think there’s that fine line where people get uncomfortable with sharing what they do in their class. Same thing with students. They get uncomfortable sharing what they’ve been using,and open conversation. A safe, open conversation.
Watson: Yeah, I think I would agree with that. I did a session at a conference last year and talked about different research tools and had a pretty good audience, and a lot of people came in, and one of their concern is, I don’t know where to start. I didn’t know. Because if you just Google “AI toolsto use ,1 million things, come up and you don’t know what’s real, what’s not, what’s considered industry standard, what’s kind of fringe. And so I think, breaking down some of those barriers and making it known to people what it can do, and take it from this very global concept to, you know, practical tools that you can use.
Doolan: I’d say, one of my biggest concerns, is what I talked earlier about with the early adopters. One of my biggest concerns is that because it’s all so new, we just don’t have a lot of information on this. And, when I go to conferences, the sessions that are the most packed are the ones that are generative AI. So, there’s a lot of desire to learn about it, but we just don’t have enough research at the moment to really know how it works. Having a dedicated campus expert would be a huge, very valuable support. In my dream world, this person has, a PhD. in generative AI and educational applications, and that they would sort of be a curious consumer of all the latest generative AI tools and have the resources to be able to buy them and try them for the purposes of potential future adoption, using them in an institutional setting and then have enough of an interdisciplinary mindset to see the applications across the curriculum, and then meet with faculty individually to explore and discuss ideas. Not big lectures, but one-on-one meetings to explore specific ideas in specific contexts, and perhaps lead community of practices where faculty are paid a little to reimagine courses and integrate generative AI into their teaching and research. So obviously this individual is in super high demand right now. If they could get this job here, they could get a job a lot of other places, so it would have to be an offer to make it worth their while.
Carlisle: I’m going to push back. Does it have to be an expert?
Doolan: So, can it be an existing faculty member? You queued me up. That was my next bullet point. So, can it be an existing faculty member? Not without a lot of release time, to get that person up to speed and also a lot of institutional support. So, as the faculty member got up to speed, the technology would also just continue to improve, so that you’d be on the one of those proverbial airport walkways going in the wrong direction. It would be challenging. But could it be done? Yes, I think it is possible.
Caruso: Wouldn’t it be magical if we had one expert in every department, and they knew our area and could go, “Oh, here’s how we could do it.” It would be fantastic if we had an expert in every area, they could do it, and if it wasn’t in every area at minimum, that it was by some kind of a career path or something. I think that would help a lot to help make that connection to what we’re trying to teach. You know, in your case, doing research, it would really help to have that insight for how can I use it? Or for my research specifically in my area?
Ehlers: I think that would be very helpful like, even if a professor within a lecture was saying something about it, or what they would use, and giving a small demonstration or something like that. I feel like that would be a lot more encouraging. I, I would say, like doing some kind of workshop would be beneficial, but knowing the student population, the people who rely on it most would not be the ones that are going to workshops like that to learn how to use it. So being in a setting where they already have to be there, then that would be helpful, and having access to I guess how to how to use it. And within each department something like that, having access to that online just so you can reference at any time would be helpful.
Caruso: Jamie, that’s a really good point. As faculty we should be, and all my classes are web enhanced, so we should really be saying the very 1st module in my class is how to use some tools that we will frequently use in our course, and I think that gives everybody some perspective from the very start of the class. This is important. Let’s get started, and take the time to meet and learn your students and engage in that way. Give them the tool sets that 1st week or 2, and then like dig into your content. We have that time, we say we don’t, but we really do have that time and can build it into the curriculum that way. So, I think you’re right, because that’s where they’re in the classroom, and we’re not having to chase them down and hope they actually come.
Carlisle: Yeah, yeah, it’s interesting. I’ve been following a clearing house of where faculty are uploading their syllabi on their policies for using AI, and some are very restrictive, like absolutely not, and some require using it. So, it’s afull range, and then also, some are providing that guidance, you know, directly integrated into the curriculum. So, it’s interesting to see the full range and where that may go. As we evolve, I guess.
Korrine Caruso: And I guess the other part is, it is naive of us to believe that nobody’s using it. So, it’s very important that we realize that when you say don’t do something. I’m the 1st person that if somebody tells me not to do it, I do it. I want to see why and how, and so that curiosity builds up much more when you tell them no, so rather than telling them no, tell them how, and demonstrate it, and make it a part of the community.
Carlisle: I see nodding from Jamie.
Ehlers: I like what she’s saying. No, you can’t prevent them. Probably everybody that I’m surrounded by student wise has interacted or used AI in some sort of capacity. But yeah, I agree with, instead of saying, don’t use it at all. They’re gonna use it. Giving some guidance on at least how you’re going to use it. If you should, or if you do.
Caruso: It goes back to your calculator example. Remember, when we got the calculators on our watches, and we all were like, oh, it’s just a watch. Don’t say it didn’t happen. It happened.
Watson: Well, if you don’t normalize it or discuss it, you’re going to perpetuate the problem. Students will keep using it in secret, and maybe inaccurately, inappropriately. But if you do, you’ll have maybe, like you said more students will come to you and want to disclose, “this is what I’m doing,” and then you can kind of redirect better ways to do it.
Carlisle: Thank you all! I was thinking, maybe at this point we’ll pause and you know, and open it up to any thoughts or questions.
