With the rise of AI, institutions are scrambling to provide guidance and policies for students and faculty. In this episode, Kathleen Landy and Joshua Foster join us to discuss a collaborative approach involving student government, administration, and faculty.
Kathleen is the Provost and Vice President for Academic Affairs at Genesee Community College. Prior to this, Kathleen has served in leadership roles at teaching centers at Cornell University, Queensborough Community College, and Mercy College. She has taught in multiple modalities and also has extensive K-12 teaching experience. Kathleen also served on the Pod Network Core Committee from 2022 through 2025 and currently serves as a co-chair of the SUNY Council on Assessment. Joshua is the Vice President for Academic Affairs for the Student Government Association at Genesee Community College.
Show Notes
- Kathleen Landy (2026). Program-Level AI Responses. Tea for Teaching podcast. Episode 440. April 8.
- Draft GCC AI Guidelines for faculty and students
- The wordcloud discussed in the pod
Transcript
John: With the rise of AI, institutions are scrambling to provide guidance and policies for students and faculty. In this episode, we discuss a collaborative approach involving student government, administration, and faculty.
[MUSIC]
John: Thanks for joining us for Tea for Teaching, an informal discussion of innovative and effective practices in teaching and learning.
Rebecca: This podcast series is hosted by John Kane, an economist…
John: …and Rebecca Mushtare, a graphic designer…
Rebecca: …and features guests doing important research and advocacy work to make higher education more inclusive and supportive of all learners.
[MUSIC]
John: Our guests today are Kathleen Landy and Joshua Foster. Kathleen is the Provost and Vice President for Academic Affairs at Genesee Community College. Prior to this, Kathleen has served in leadership roles at teaching centers at Cornell University, Queensborough Community College, and Mercy College. She has taught in multiple modalities and also has extensive K-12 teaching experience. Kathleen also served on the Pod Network Core Committee from 2022 through 2025 and currently serves as a co-chair of the SUNY Council on Assessment. Joshua is the Vice President for Academic Affairs for the Student Government Association at Genesee Community College. Welcome, Joshua, and welcome back, Kathleen.
Kathleen: Thank you so much. Great to see you again.
Joshua: Thank you for having me here.
John: Thanks to both of you for joining.
Rebecca: Today’s teas are:… Joshua, are you drinking tea with us today?
Joshua: I am. I am having some Japanese Sencha green tea here in my GCC mug.
Rebecca: Amazing. And how about you, Kathleen?
Kathleen: Well, I don’t know if this is like wearing the concert T-shirt to the concert, like the band T-shirt to the concert, but I have a Tea for Teaching mug, and I’m defaulting to Irish breakfast tea.
Rebecca: Clearly one of the cool kids. [LAUGHTER]
Kathleen: That’s right, that’s right. [LAUGHTER]
Rebecca: How about you, John?
John: I have a Twinings English Breakfast tea today.
Rebecca: Oh, nice.
Kathleen: Very lovely.
Rebecca: I think I have… maybe I should verify…
John: Another imperial tea?
Rebecca: I do, [LAUGHTER] I have a Scottish breakfast tea today.
Kathleen: That sounds lovely. I don’t think I’ve ever had a Scottish breakfast tea.
Rebecca: It’s got a little more oomph to it. [LAUGHTER]
Kathleen: Okay.
Rebecca: A little bolder, I feel like.
Kathleen: There you go. Okay, I’ll have to check it out.
John: This is a follow-up to our earlier podcast, where we talked a little bit about program- level AI policies, and you mentioned that you had been working with a member of the Student Government Association to come up with some recommendations for faculty and students. Could you tell us a little bit about the origin of this collaboration on the policy?
Joshua: Sure, I would be happy to do that. As a liaison between students and faculty on campus, students often approach me with various concerns, and one concern that came up multiple times during the fall semester was students having their legitimate work flagged as partially or even completely AI-generated. This initially prompted a discussion in one of my classes, at which time I learned that many students actually avoid the use of, or even the mention of, AI in order to avoid the potential of a suspected academic integrity violation, but I also learned how frequently academic integrity violations related to AI do occur. So I realized this was a topic that necessitated a more direct and open conversation involving both the faculty and the student body, and that is what led Kathleen and I to develop these guidelines as a way to guide those conversations,
Kathleen: I’m happy to add to that, Joshua, because this came up organically in one of our routine meetings. So, Joshua and I, as part of his role at the SGA (Student Government Association), and my role in Academic Affairs, we meet every three weeks, and so this came up in one of our conversations, and it was so timely, and it was totally a function of happenstance that at the time I had been having conversations with academic program directors and multiple faculty about the necessity of having course-level AI policies, and so it was very serendipitous, almost, that there was this student concern that Joshua articulated, and I had been exploring this question with faculty, and it seemed like a really lovely opportunity to bring everyone together and explore this topic.,
Joshua: And I had actually heard at the time members of the faculty discussing that they did have concerns as well, and so it sounds like the people who we serve both had concerns, and so we could kind of bring those concerns together, merge them together in the development of these guidelines.
Rebecca: Can you talk a little bit about how you facilitated the creation of the guidelines? Who participated in developing this initial round and this initial draft?
Kathleen: So, Joshua and I, we opened a shared Word document, and we just got some thoughts together, and we thought initially it was a no-brainer to have this set of guidelines have two parts, one that was faculty facing and one that was student facing, and we knew that they would kind of run parallel to each other and reinforce each other, but we started with a little bit of a brain dump, and we just kind of mapped what we thought were good ideas and good starting points and points of entry for the conversations about AI and academic integrity, and we landed on, I guess, we would call a sacrificial draft that we thought we could both bring to our respective colleagues and get more input. So it was with real humility and curiosity that we did a little road tour. We hit the ground running with this document that we’ve shared with you as well, and I personally brought it to colleagues in Academic Senate. We have a standards committee, and so I brought it to the chairs of that committee and shared it with our academic program directors, and we went from there. We solicited feedback, and it was great feedback that we got. And Joshua, I don’t know if you want to speak to folks that you brought it to. I don’t know if it was the SGA cabinet.
Joshua: Yes, so I initially didn’t bring it to too many students. What I did rather was I sort of took what the guidelines were without actually taking the draft, and I took that and I talked to different stakeholders about their concerns, and I brought up where different points that were covered in those draft guidelines and got their feedback on each point that I thought was relevant to them, and then I would take that and contribute it back in, and then I would also look at what some of the different faculty members are who I talk with and get their feedback and kind of combine that feedback with the feedback from the students and bring that back to Kathleen and to her colleagues, and I think that was really a good collaborative way that we took this, to include both levels of feedback, but not have the students edit the guidelines, but have them indirectly contribute through my contribution, I think, allowed them to really be able to express their thoughts and their concerns more clearly.
John: We have a student committee on learning and teaching here, and this came up in all of our discussions with that group, and the same sort of concerns that you mentioned, Joshua, appeared, that some students were really upset that they were accused falsely of engaging in academic integrity violations, and also others were concerned about whether it was safe to use it, because they’d like to be able to develop skills in this, because it may be relevant for their careers. It’s a topic that I think applies to a lot of people. Could you give us an overview of the guidelines, both for faculty and for students in this draft document?
Kathleen: The guidelines are surprisingly simple, but we strove for them to be very clear. So, the guidelines include having a clear AI policy that’s articulated in every syllabus, even though that’s a soft expectation, we wanted to make it a little bit more concrete and a little bit more pronounced, and so we wanted to encourage faculty to have a clear policy that includes specific examples of acceptable and less acceptable uses of generative AI, and a disclaimer or an explanation about any possible AI detection platforms that might be in use for the course. So that’s kind of an equity issue. It’s a social justice, it’s a transparency related issue that if there are detection platforms in play, students should be aware of that. That should be a known element in any learning environment, and importantly, this same AI policy should have a clear list of consequences for initial and possibly for subsequent violations of the class policy. So we wanted to start with having something concrete in place, something that’s published for students and faculty alike to refer to. And then the second part of the guidelines for faculty involve posting open and candid conversations at the beginning of any course or assignment, something that came up in the previous discussion that we had was this idea that in sympathy for the schedules that students have and the potential for them having five different course level policies to keep track of, it’s really not realistic for any given course level policy to be expressed once and then never mentioned again, or to be published on page eight of the syllabus, and then never revisited again. So, the idea of not only having a clear AI policy, but revisiting that and explaining it and communicating it frequently and clearly, that’s a kindness that we can show to students. It’s a good practice. So, this idea of hosting ongoing and candid conversations within the class, especially at the beginning of a course or the beginning of an assignment, that’s really critical. And then finally, the guidelines involve one or two strategies for fostering greater student buy-in, for lack of a better term, or a greater sense of accountability among students for the policy, so things like having students sign an integrity statement, a commitment to acting within the confines of an academic integrity policy, having students sign an integrity statement, or including a question about AI use and implications within the context of a syllabus quiz, or something that’s a little bit more interactive. We thought that would allow for a structuring of engagement with the policy, to not just have it live somewhere, but to have students actually engage with the policy.
Rebecca: It seems really important not to just have something exist on paper or some virtual ether, right? [LAUGHTER] It’s like have people actually interact with it.
Kathleen: That’s right, especially because for many students, and this will change over time, of course, but they might not be accustomed to having to check with the course-level policy. These are relatively new and emerging caveats or elements of a syllabus. So, how could we not redirect students to say, “Hey, remember we have this policy, we have this expectation?” It’s really a kindness, I think, to students. And then Joshua, I’m happy to turn it to you for the student side.
Joshua: Yeah, thank you, Kathleen. So, the guidelines for students really do mirror and complement the guidelines for faculty, and I want to start by pointing out that, similarly to the guidelines for faculty, the guidelines for students do not dictate when the use of AI is appropriate or not appropriate. Instead, the goal of the guidelines is to help students learn how to communicate with their instructors to be sure that the course policies are clearly understood prior to any misunderstandings happening. So, with that in mind, the guidelines mentioned topics like requesting a course policy on AI, if one is not provided, and asking questions of the professor or the instructor to understand that policy. They encourage attending office hours, sending a professor an email with questions, or even asking a question in class, so that other students can benefit. Maybe other students have that same question, and maybe they don’t want to ask for the reasons that we discussed earlier. So, the guidelines, in addition to this, include steps for how a student could start a conversation with a faculty member if that student’s work has been flagged as having been AI generated, regardless of whether or not that work was correctly flagged as having been AI generated. The guidelines stress being respectful and aware that misunderstandings do occur, but they also encourage students to advocate for themselves when necessary, and I personally believe that student self-advocacy is a very important skill for students to learn early on during their college experience. The last major focus of the guidelines for students is the importance of building strong and collegial relationships with faculty members, which can be difficult or is something that is even avoided by some students, especially younger or first- nyear college students who are still adjusting to leaving a high school environment, and I believe that this is actually one of the most important parts of the guidelines.
Rebecca: I think I hear some really common themes around transparency and relationship building.
Kathleen: There’s no doubt. I was speaking with Joshua. We had a debrief of an event that we co-facilitated this past Friday, and I was struck by the extent to which the following statement is true. Almost all of my recommendations or strategies or suggestions for how to handle issues involving academic integrity and the use of AI, in particular, almost all of my strategies involve the human elements in a learning environment, and they’re all relational. It all comes down to either communicate… not all, but it often comes down to communication and relationships rather than the tech itself, and so I think that’s a really interesting relationship: that the tech challenges that we encounter often have very human or relationship-centered solutions. That’s been my experience to date. So I agree with you, Rebecca. There are trends in the solutions that we keep coming to.
John: I believe you also did some sessions with faculty, staff, and students about this. Could you tell us a little bit about that, and what sort of reactions were received?
Kathleen: So, we’ve had one session, and we hope it will be the first of many, and I have to tell you, it was awesome. We were delighted, we had over 50 participants on a Friday afternoon, no less, which is no small feat. We were very excited by the turnout, and we tried to be very mindful of how we engaged folks from the beginning. We wanted to set the right tone, and so we started with a little bit of a series of short interactive polls to let folks know that we’re all coming at this from a point of intellectual curiosity, and we wanted to build a little bit of a sense of community around this topic, and so the very simple question that we started with, it was a simple qualitative poll everywhere to just text your answer in, and we asked a very simple question. We asked what word best captures how you feel about generative AI in your classes, very simple, and we knew we could get anything, and so we gave everyone simple directions. Everyone had the option to pass if they wanted to, but everyone had the option to text a single word, and we generated a word cloud right there. I can send you, if you like, a picture of this word cloud. I’m looking right at it. I have to say, it was really lovely to see the extent to which students could see the faculty’s human responses to this question, and faculty could see students’ human responses to this question, and so the responses were anonymous, but the word cloud was really thought-provoking, and it was populated with words like conflicted, concerned, curious, complicated, stressful, uneasy, overwhelmed. I think it set a tone where everyone could kind of check their egos at the door, or check their personas of being an academic, or a scholar, or an honor student, what have you, fill in the blank. Everyone could check that at the door, and we all kind of became students of this together, and it was, I thought, surprisingly effective at just setting a nice tone of inquiry for the remainder of the session. The session was about an hour long, and so we had interactive polls and a bit of an overview of the guidelines. We distributed a physical copy, like a paper copy of these brief guidelines in the room, and we posted them for the hybrid. It was a hybrid session, that’s worth noting. We posted them for the online participants, and it generated rich discussion. We got some great suggestions from both instructors and staff alike. We had students there who weighed in. We had folks, both students and instructors, share experiences, times where they wish they had these guidelines. Some expressed a concern about having or desiring more robust guidelines, like they wanted more of the same. And I’ll maybe stop there, because Joshua, I’m sure you want to add to that, but I was surprised at how eager folks were, and I was gratified by the enthusiasm that the group expressed.
Joshua: I was very excited as well, after having been at that session, and I joked with Kathleen a little bit at our follow-up that I wish we had had two or three more hours to go on, because I think that we certainly could have, but I think that the thing I was most pleased about was that we had a good amount of both faculty and students in attendance, and that they could see that, in most cases, they are in agreement with each other on these issues, or at least there is some mutual common ground between our students and our faculty, and I think that was the first thing that was really important for both of those groups to see, and then the second thing was that a lot of students came to me afterwards and said that they were really excited to have learned about how AI is becoming a common issue and how interested people are in it. As an accounting student, I have found that within my classes I’ve had a lot of people who are both interested in AI and who are both very hesitant about it, and ironically, if I had to make a really, really wide swoop with a brush to say who is more pro the implementation of AI, at least in the specific classes that I have been in, it’s the faculty, not the students, and so I think that the students being able to see that was really helpful, that that may be what we students imagine that the faculty are thinking about, and what the faculty maybe imagine that the students are thinking about maybe those are being too heavily stereotyped, maybe those aren’t really, really how we are seeing this, and so I think that was really good to have experienced, and I just think it was the meeting was very well received. There was obviously a lot of desire for follow up to it, for more conversations, but I think that the conversation that we did have was a very good starting point, and it helped to really demonstrate that where the direction that we’re going is really the direction that we should be going.
Kathleen: Thanks, Joshua. The only thing I would add, because I don’t want to paint this picture that it’s all rainbows, and we all sang together at the end of this session. I did have a couple of faculty members, and I was super grateful that they attended. They didn’t express frustration, per se, but their response was more like, “yeah, and…” like they were just ready, and I’m loosely paraphrasing, but this is close to the exact language. They said, “this is good, this is fine, Kathleen, but this isn’t the real work. The real work has to come in the articulation of departmental policies, and what’s that look like?” And I guess my response to that was, “well, yeah, of course, that’s the departmental next step, and that’s not for Academic Affairs or SGA, for that matter, to dictate to departments what their departmental or course level policy should be,” and so I think the workshop work is what should follow. So, there was a little bit of maybe frustration, that might be too charged of a word, but there was a little bit of feedback that was, “yeah, and okay, like, get to it, get to the next step,” which indirectly I interpret as affirming feedback that we’re on the right track, that folks are eager for guidance or at least engagement on this topic.
Joshua: And I believe that the same is true for students. I think that students really want that greater level of course-level policy or program-level policy, but I think that we’re not to that point yet, and so at this point a student came to me today and asked me. My response would be, “think about communication, because that’s what we are able to do now. That’s what we can do now.” Those other more clear things will come, but now we have to focus on what we can realistically do together.
Rebecca: It seems like a really valuable opportunity to demystify what people are thinking about, and that’s a really important first step into moving towards policy, or something that’s more formalized. You’ve certainly presented this as a working draft, and some revisions, and things like that. What do you see as the next steps to maybe formalizing this work at an institutional level, and then obviously there’s some work that would need to follow at the departmental level.
Kathleen:I think there’s a few next steps, and one has to deal with instructional practice and faculty development, and the other has to deal with steps to take leading towards policy articulation. I think the immediate next step involves endorsement, to take the feedback, the great feedback we’ve been given, and refine these guidelines, share them again, probably have a few more rounds to get some greater input, but then go through the formal channels of shared governance to have endorsements, formal endorsements, so that we can say “here are some endorsed guidelines, and those endorsements are coming from Academic Senate, from our local union, from Cabinet, from SGA, from program chairs.” We can get a lot of structures on board to kind of promote these and broadly share them. On the instructional side of things, and this is connected closely, of course, to faculty development, I think we can generate conversations about all the things that we’ve been discussing and all the things that are focused on in these guidelines. One of the polls that we asked, one of the questions we asked this group, and we had some questions restricted to students and some restricted to faculty in this one- hour session that we had, and one of the faculty questions was very simple, yes or no question: “Do you presently have a clear published AI policy for your courses?” And 57% of faculty said yes, and clearly 43%, my follow-up question is, “why not?” Let’s get that number a little higher of those that do have a clear policy, and I think that’s really good for that 43% of faculty to see, like, “oh, wow, 57% of my colleagues present at this session have something in place. Let’s talk about what that is, and maybe I should have that,” and I think that those collegial conversations, and then doing the work of adopting, crafting your own AI policy, and publishing that in the context of whether it’s a Brightspace shell or a syllabus, likely multiple places, that’s part of what’s involved in the next steps from my perspective.
John:I know in our campus there’s been a fairly wide range of perceptions concerning AI detection software. Some faculty trust them very strongly, even when the evidence suggests otherwise. Other faculty very reluctant to rely on them at all, except maybe as a signal that they may want to contact a student to talk about the issue. I was really pleased to see that your guidelines explicitly stated that AI detection software is fallible. Could you talk a little bit about that, and whether people in general have accepted that message there?
Kathleen: I’d like to think they have accepted it, I think, and I also think it’s a case that folks are still exploring what detection platforms do and how they operate, and how they might be of use to them in their own classes. So, I do think it’s variable in terms of comfort with and knowledge of these platforms, but I think there’s a lot of false positives, there’s a lot of false detections, and I think disclaiming that and modeling how to have the conversations about that, that’s something that we hoped the guidelines would get into. I think dragging that issue into the light is part of the intent of these sessions. I think folks are pretty receptive to it, because there might even be a self-consciousness about what we don’t yet know. So once again, I do think there’s a dotted line to faculty development there, and I think we have to model the questions that we ask as we analyze the efficacy of these platforms. So I think it’s time for candor, and I think it’s a time for inquiry, and just the humble recognition that we have to talk about what we need, what we want, and how good these platforms are. How efficacious are they?
Joshua: And something that one of the faculty members, who was present at our session, brought up, and something that I really appreciated from the student perspective is the acknowledgement that because these AI detection platforms are not perfect, they can actually serve to erode the level of trust that has been built between students and faculty members. And so it’s unfortunate that they do that, but that’s one thing that will have to be accepted when using an AI detection platform, and so, as a student, I appreciate that faculty are acknowledging that reality, and so that means to me that they will be more sympathetic and more understanding, because obviously in some cases those tools, those positives, are accurate, but in other cases they may be a false positive. And so just having that awareness and the fact that faculty members are acknowledging that level of student trust that may be called into question, I think is really good for them to be able to recognize.
Kathleen: Well, it’s great that you say that, Joshua, and I do want to respond to it. It prompts me to underscore this. I think the disclaimers regarding the effectiveness of AI detection platforms, it drives the conversation to prevention rather than detection, and I think that’s a huge part of not only instructional and assessment practices, but also the learning environment, and it goes back to the relationships and the trust that you mentioned, Joshua. So, I think that’s a huge part of it, the shift from detection to prevention, that’s a nice point of entry for me, and the conversations with faculty.
Joshua: And I think that that level of trust between students and faculty may be the first step. probably is the first step, in that prevention.
Kathleen: That’s right. Agreed.
Rebecca: So, you’ve talked a little bit about wanting, or even departments, maybe, being eager for like the next steps. Can you talk a little bit about what movement there has been in terms of the course-level or program-level policies on AI, or what you maybe expect to see as we enter into the fall?
Kathleen: We’ve had a few departments, a few programs, or program clusters, I should say. We’ve had a few folks self-organize, and they’ve proven to be self-starters in this domain, and they’re really gathering and just meeting routinely to articulate policies and to explore what other institutions have to craft that together, and that’s inspiring. That’s really great to see. Our business department comes to mind immediately. They’re doing great work, and there are others that I think are curious, and folks are kind of coming to those realizations of, hey, we need to huddle up and figure this out. I think folks are coming to that conclusion on slightly different yet overlapping timelines. So, I think there’s a role for my role and Academic Affairs Administration to prompt that collaboration a bit more intentionally, whether it’s the articulation of a strategic objective relative to having a target, the number of academic programs to articulate as policy, regardless of what it is, I think we can prompt that a bit with the strategic planning that we do, with the faculty development planning that we do, and I think to a certain extent we’ve done that, but I think we can turn that up a little bit. I think we can be a bit more intentional about it, but it’s happening just at different degrees and varying by program.
John: We talked a little bit about AI detection and how perhaps that could be used to nudge people in ways to use AI within the guidelines of the course, but are there other strategies that faculty are using to encourage students to use AI ethically rather than to shortcut their learning?
Kathleen: It’s a great question. I think, and this will vary by discipline, so I don’t want to speak in too broad of terms here, but I might end up doing so. I think to the extent that AI can be leveraged to enhance or scaffold or facilitate a process, I think that’s always a good thing. And I think if the use of AI can underscore the importance of the integrity or ethics-related outcomes for a course or a discipline, that’s great. I think there’s incredible potential for use cases, in terms of here’s how to use, here’s how not to use, here’s how this could go really well, or here’s the quickest way to work yourself out of a position, a passion, a process, whatever is appropriate there. So, I think there are examples, but they’re highly discipline-specific, and I know that that’s not the most robust answer, but I do see evidence across disciplines that folks are incorporating AI in really transparent ways that scaffold learning rather than inhibit it.
John: Joshua, do you want to take a stab at that in terms of things that you’ve seen where faculty are encouraging students to use AI in productive ways,
Rebecca: …or even how students are doing that on their own. [LAUGHTER]
Kathleen: Yeah, yeah.
Joshua: True. Yes, I have seen it. So, Kathleen shared briefly earlier that one of our questions was how many faculty members have an AI course policy, but another one of our questions that was restricted to students was, “How many of you, how many students used AI to complete their coursework?” …and that’s not meant to be AI that’s sanctioned, that is meant to be using AI in appropriate ways, assumingly, and that answer was 89%. 89% answered yes. And this is an interesting thing, because in my personal experience, the people I’ve talked to, I would say that that percentage is probably lower, maybe more around 60% but I found that answer quite interesting, and from the students that I’ve talked to, even the faculty that I’ve talked to, or other tutors, people who work with students, a lot of students are using AI in ways, for example, they may ask for help coming up with a topic idea, or maybe to brainstorm a topic, or maybe they’re brainstorming a first paragraph, or a direction that they could go within an assignment, or maybe they’re comparing scenario, and I think that those things, those getting started is one way that I’ve seen a lot of my peers using AI. Another thing that I have seen is where they use it for research. Now that will get into another topic, which is the reliability of that research, and so that’s something that would be important to talk about, but I do see students using it. I also see a lot of students using it, and they have very good reasons for that. But I think that it is something that is becoming more in use. I’ve also seen faculty members, and not in particular any faculty members that I have personally had a class with, but who I have talked to, or have actually had assignments in which they ask students to use an AI tool to begin an assignment. For example, there was an assignment in one class that was used for the creation of a resume, and one of the parts of the assignment was to take the resume and run it through an AI tool and have it give you suggestions and feedback on where you could make some words stronger, and so I think that those are ways that AI could be used in ways that are actually helpful or productive for learning.
Kathleen: If I can add one additional comment, and Josh, your comments prompted this thought. One of the more valuable pieces of feedback that we received on the guidelines was our oversight or negligence in not mentioning the library and the learning center in the guidelines, and so to your question, John, I think it’s a really good opportunity, a great idea, in fact, to leverage the use of AI to facilitate engagement with the other support services and the library on our respective campuses. So I think to build that kind of analytical info literacy related analysis of AI generated content as part of a process for a course-based assignment, I think that kind of a no brainer that we have this fodder, this generated content that we can use to engage with tutors and librarians, and of course, faculty, TAs, fellow students to kind of engage in the analysis, the fact finding, the verification of information, all of the info lit and AI enhanced info lit competencies that we’re looking to develop. I think there’s opportunities there as well.
Joshua: The other thing that I have had some students tell me is that they turn to AI because they genuinely need help thinking through something, or they struggle with a certain topic. So, for example, I know a couple of students who use grammarly because they struggle with their grammar, and I think that one thing that we are encouraging faculty to do with these guidelines, and thus also encouraging students to do these guidelines, is to have faculty make clear when these tools are allowed, and have students understand when they’re not allowed, because sometimes there’s a fine line between when is something like Grammarly, when is that allowed, or when is it allowed to use Chat GPT to think through your thought versus when is that prohibited, and I think that having those guidelines is essential, including those in your course policy is essential. The other thing that Kathleen was mentioning with the library and with the tutoring, is those are alternatives, so when AI is not permitted, there are other things that can help students. They aren’t just left on their own. There are tutors. Tutors can help you think through your ideas. There are librarians. Librarians can help find information. They’re very good at information literacy and finding those information. They can also help to verify research, and maybe if research was done via an AI tool, maybe that information needs to be verified from another more academic source. And so librarians are very helpful with that as well.
Kathleen: Now, Joshua, I kind of want to jump in, and I want to challenge one phrase that you mentioned, and I’m doing so as your thought partner in this, so you’ll appreciate the sentiments and the collegial approach here, but I would not want to take away from your comments to be that librarians and the Learning Center are alternatives to generative AI. I think that’s a dangerous framing, and I know that you don’t mean to say that they’re like alternatives to AI, but I think that distinguishing between the tool and the resource that many AI platforms offer, distinguishing between that and the human-centered expert librarian and the qualified and well-situated, well-resourced tutor, they can help us use this tool to our advantage and help us navigate the best uses, for that’s often a distinction. I wouldn’t want any of our librarian and tutor colleagues to say, “Wait a minute,” of course, if you don’t mind me clarifying what I think I know you mean by that. I think that’s important.
Joshua: I don’t mind, and I think that there are going to be times, though, when students choose not to use AI, and when they choose that they would rather have that more experienced human they can go and talk to, and I think that’s what I was trying to say, is that you don’t have to use AI to succeed in your learning. There was so long that this wasn’t available, and so I think that it’s coming available, and it’s a great tool, but it’s not the be all end all. It’s becoming a great tool, but you still need to be able to learn as a student and be able to talk to people, and I think that is really, really important.
Kathleen: Yeah, and I think going back to the spirit of our session, we have to figure out what this means together, what AI use means in our respective disciplines and our respective classes, which is absolutely how we approached this set of conversations. So, I think it may be the be all end all, it may not be. I think we got to figure that out together, which is the spirit of these guidelines, certainly, and the conversations around them. It’s important.
Rebecca: And pointing students and faculty to all the available resources and the roles that they can play in learning is always really important.
Kathleen: Yes.
Rebecca: So we always wrap up by asking: “what’s next?”
Kathleen: In terms of what’s next. I think it’s a clear next step for us to continue bringing faculty and students together, that was so elucidating. It was really great for that exchange of perspectives and for that shared exploration of this really important and impactful topic. But I think we got to keep at it. We got to keep bringing people together in thoughtful ways. That’s what’s next from my perspective.
Joshua: Yeah, I agree with that, and I think whether it’s bringing students and faculty together again or talking among students, talking among faculty, and then coming back together, regardless of how it’s done, just continuing that conversation is really the next step. You know, I agree, Kathleen, having that continued conversation is just really important.
John: We know AI has been somewhat disruptive for students and for faculty, and it’s nice to see this sort of collaboration, and it’s also something that can take place really nicely at the class level as well as at the institutional level. And it sounds like you are making some really good progress there at GCC.
Kathleen: We’re really trying. Thanks so much to you both. Thank you.
Joshua: Thank you. It’s been wonderful to be here to talk with him today.
Rebecca: Yeah, it’s great to have both of your perspectives, because I think the model you’re sharing around the topic of AI could be applied to many other challenging topics that challenge both faculty and students, and bringing those two groups together to work through those challenges and establish guidelines and other strategies is really helpful.
Kathleen: Thank you. I think so too. One of the goals is to model. We’re trying to model as a campus community for each other, whether you’re a faculty, staff, student. We’re trying to model how to problem solve and how to figure things out together and do so in a way that’s ethically sound and mission-centered, and focused on learning. So, we’re trying, we’re hopeful, but we’ll get through it together.
John: And when both students and faculty are involved in making these policies and have a say, there’s going to be a lot more buy-in to the policies than if they were just imposed.
Kathleen: That’s right. We agree.
[MUSIC]
John: If you’ve enjoyed this podcast, please subscribe and leave a review on Apple Podcasts or your favorite podcast service. To continue the conversation, join us on our Tea for Teaching Facebook page.
Rebecca: You can find show notes, transcripts and other materials on teaforteaching.com. Music by Michael Gary Brewer.
[MUSIC]