Shortly before the start of the spring semester, Tim Curry joined us for an episode discussing his ambitious plan to create structured learning experiences for students using chatbots. In this episode, we check back to see how this experiment developed. Tim is a lecturer in the Department of Health Sciences at Northern Arizona University. He is developing AI applications for autism research and tribal health service while building Northern Arizona University’s Applied Health Analytics program. He’s also working on the completion of his PhD degree in health equity technology.
Show Notes
- Tim Curry (2026). A Curated AI Framework. Tea for Teaching podcast. Episode 431. February 4.
- Llama 4
Transcript
John: Shortly before the start of the spring semester, we had an episode discussing an ambitious plan to create structured learning experiences for students using chatbots. In this episode, we check back to see how this experiment developed.
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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.
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John: Our guest today is Tim Curry. Tim is a lecturer in the Department of Health Sciences at Northern Arizona University. He is developing AI applications for autism research and tribal health service while building Northern Arizona University’s Applied Health Analytics program. He’s also working on the completion of his PhD degree in health equity technology. Welcome back, Tim.
Tim: Hi, it’s great to be back here.
Rebecca: Today’s teas are:… Tim. Are you drinking tea with us today?
Tim: I’m not right now, but I was, and the tea I had this morning was a spice blood orange tea. It was quite tasty.
Rebecca: Looked like it was in a beautiful mug.
Tim: Oh, yeah, yeah.
Rebecca: turquoise… ribbed…
Tim: Yeah, with a little bit of a, almost a goldish highlight on the ribbings.
John: A bit iridescent.
Tim: Yeah.
Rebecca: How about you, John?
John: I am drinking a Lady Grey today.
Rebecca: Oh, I have its companion, a British breakfast.
John: Very good. Earlier this year, Tim, right before the start of the spring semester, we discussed a plan that you had developed in which students would engage in a structured sequence of interactions with a chatbot tutor that you created in each of the course modules in your health science course. The course was scheduled to begin actually the afternoon of the day when we last talked. We’re following up today to see how this plan has worked out once it hit the actual classroom. First, though, could you provide our listeners with an overview of the course, because not everyone may have listened to that, or it’s been a little while, and just remind us of what the course is and how the AI activities were structured.
Tim: So, as a rewind here, so I actually use this in two of my classes. The first one being our HS 300, which is a class focused around the diseases we get as people and how we work in that space, in more of a public health focus. And then the second class was a fitness wellness class that’s focused on how do we do physical activity more of a clinical population focus, and it had that as the topic, and then it’s also our writing-intensive higher-level course. So, in both of the classes, we had a tutor bot. The way that it functioned was I gave them a file that I built out that was a learning file that the bot would read and would have an idea about what are the topics that the student needs to learn and then would work with them in a very Socratic style to help them learn the content and the depth that was required as kind of the minimum foundation points for them walking into class in the first day and they did actually fill in the questions I had in that file, and it was required to hand that in, as we could call it proof of learning.
Rebecca: So I’m picturing the first day. How did students react to your plan?
Tim: About what I expected, honestly, which was tentative. And that first day, and I’ll actually expand that, and say that first week, we had a lot of discussion in class about what does this look like, what’s the purpose of it, as we had, I believe, discussed about six months ago. One component of that first week was about roughly half of one of the first two days of class in that first week, they had built-in time in class for them to actually dive in, learn about this GEM that was the host of our bot, and actually get to start working with the first file for that first week, and get their hands on. And I’ll say that first day it was very interesting to hear about the reactions, and some students, within the first five or 10 were like, “this is not for me,” which is fine, because that was how it was built, was that they did have an option B that they could do without having to engage with the bot. Quite a lot of them had said, “I’ve never ever engaged with an AI like this before, and I’m a little uncertain, but I’m willing to go and give it a shot.”
John: Roughly what proportion of students chose to continue with it, and what proportion chose to opt for plan B?
Tim: Yeah, that’s a great one. And in fact, I’ll say that was one I was watching throughout the entire term, because they have to hand in this like proof of learning, which allowed me to kind of track what was the proportion. Roughly, the proportion was like 70% continued with AI, and 30% chose to go the more traditional text-heavy route. I’ll go and say this. I would argue in a 16-week term, I would say just off the top of my head that by about week six the students had settled into the way that they were going to engage.
Rebecca: That’s not too bad, about a third in.
Tim: Yeah, it’s not too bad.
Rebecca: How did it work?
Tim: Really well, I would say. Overall, there were definitely things, that within the first two weeks I hit the fun point that I’m sure all three of us have at some point, which is Gemini pushed a major change in their models and updated, and suddenly the AI tutor [LAUGHTER] wasn’t working the way I was expecting it to work. When I had trained it and done the last round of kind of making sure it was working, that was end of December, start of January. By the time we hit like week two of the class, the model had been adjusted and suddenly it just kind of wanted to go off in its own in right field and treat the student as if they were like a medical student and go in way too much depth. So after that, I realized very quickly in that week, too, like, “oh, we have a problem,” so very quickly went back, adjusted the system prompt, put up some more forms of constraints in a guardrail to rein it back in, bring it back in, and effectively the way I did it was to get the bot to do less explaining and focus more on explicitly what the student needed to learn and allow the student to drive where they wanted to engage further. And after that adjustment it seemed like that solved the issue and the students were able to better engage with the bot overall and I’d say overall, for both the AI bot and the textbook route, the big change of having these effectively notes that they were expected to hand in dramatically improved their readiness to engage in a flipped classroom, which is the way I teach, and so I would count that as a win period for the AI bot, the fact that at the end of the day the grades were effectively the same regardless of the way that they engaged. So I would go and put that up as a positive sign overall that the AI at least performed as good as the traditional way.
John: And in a first iteration that’s probably a very positive outcome, because often new experiments have some rough edges on them. I was especially curious about the performance of the Gemini Gem, because I was working with a group of 18 faculty in SUNY from various campuses who were experimenting with chatbots, and many of them started with ChatGPT, but then moved to Gemini, and they had very similar experience, that the GPTs in ChatGPT seemed to pay much more attention to the guardrails that were put in, while Gemini Gems seemed to go off in directions that were different from what the instructions were, and that caused a bit of frustration for several of the faculty, because one of the reasons they moved to Gemini Gems was because their campuses had Gemini, and they thought that would allow all students to have more equitable access, but they had begun in ChatGPT because the grant had funded Chat GPT accounts for them, but again students were complaining that the free accounts didn’t allow that much interaction with it, while those who had paid accounts had much better quality of interactions, so it was a trade off, and ultimately pretty much everyone who had that choice did stay with the Gems, but it did require quite a bit more training. So, I think your experience there was not unique.
Tim: And I’ll just go and say this as well. I did also one more adjustment I did in week three which further helped was, in Gems, you can have certain variations of it, right? Just go and turn on as the default that the student can go and turn off if they want, but generally they don’t, and I defaulted on the guided learning mode, and that further enhanced that Gem as well. 8:11
Rebecca: So it’s always interesting when you try something new and something goes awry, and obviously it sounds like you adapted well. How did the students adapt to this minor interruption, especially because it happened early on.
Tim: I think the biggest item in terms of the feedback was that I was very open that first week of “this is an experiment, we don’t know what’s about to happen. I don’t know, I know what I’ve done for my testing, no idea what’s about to occur here, and I want to know your feedback, so let me know. We’ll go and talk about this.” And opening up that window of this is an experiment, you are my group. If this doesn’t work, we’ll adjust and change. I believe that it allowed that space for a dialog to happen, and that first week we did half of one class where they had a chance to go and get in there, work on it. I got a lot of feedback from them in that class, then once we got in to week two, that feedback of like, “Hey, this took a really long time because it kept like wandering off over here, and I had to bring it back, and it was really annoying,” I think was the biggest response I had, and then after we got it tuned in, I began to hear more feedback about, “Okay, I kind of like this, because if I’m totally lost on what is this problem with the heart, why do I care about it?” It really allowed them to explore if there was an area or a disease that they really found fascinating, and it just gave them more freedom to go and explore that. So, overall, the response that I had from the students was, I’d say broadly, it was kind of two broad groups. One was: this was very intriguing, and it was about the same as what I’d expect if I read the book. I’d say out of the 70%, like roughly I’d say like maybe 10 to 20 of that was that group of like it was nice I didn’t have to pay for the book, and then the rest of the group was generally that they liked the ability to have that freedom to explore or to ask the bot for more help in a space as they felt need.
John: Going back just a little bit, you mentioned you have these chatbots that are trained as Socratic tutors on that module, and then students complete an assignment at the end. Was the assignment built into the chatbot or was it something that was a standalone, and how did you receive all that? Did you get a transcript of the interactions along with some responses or something else?
Tim: So what I did was I gave them a file that was in Canvas, and the chat bot understands how the file is laid out, and it has a set of questions and tables and cases and all of that stuff without the correct responses put in there, and so the student’s job was to start a chat with this bot and to give it the file, and so that the bot knew how to drive the engagement, and then what they did was, as they engaged with the bot, they would go through and fill out each of the components of this file, and then they would just go, and it was a hand in before the first day of class that week that we did through the Canvas site. Now, a big part of not only these classes, but just the classes I go and teach across the board is that I do a contract grade, so for these items, because the focus is on “I want you to engage with the content, I want you to learn it, so in class we can work on like going further and building out skills,” so they knew that as long as they completed all the work, it got marked as done. I wasn’t about to go through with a comb and dock them points for everything that wasn’t exactly right, but once they had that handed in, it unlocked the key for them, and then they were in charge of ensuring that they went through and reviewed the key to make sure that they were in the right space.
Rebecca: Seems like a good plan, when otherwise that would sound like a lot of grading.
Tim: It did work well.
Rebecca: And you said that the students who chose the textbook method essentially did the same assignment, right?
Tim: Yeah, so it was adapted for the textbook, but exact same idea. The plan, as well, was to keep the overall load on the students the same. It seems like, based on what they reported in evaluations, that was the case, that regardless of path, it was about the same amount of time to complete each one.
Rebecca: Besides the tech surprise, were there other surprises, things that you didn’t expect? Anytime you go into an experiment, things come up that you don’t expect.
Tim: I think the one that was unexpected and interesting, and I suspect both of you, being faculty, you’ll hopefully laugh at this, was HS 300, in particular, is a content-rich class. I mean, not only is it a 300 class, but human diseases, there’s a lot of them, [LAUGHTER] like there’s far more than we can fit in one class, so we only focused on functionally the major diseases for each of the body systems, and still there’s just a lot of content that you need to know, and the feedback that I had at the end of the day kind of made me laugh, which was regardless of the path that they picked, because now we were requiring them to show at least foundational knowledge prior to walking into class as a core component of this class was that they were spending three to four hours a week outside of class doing all this work and going and like preparing for class and that it was more load than what they were used to or expecting and a lot of the feedback was “and I feel like I learned so much more because of this.”
John: That’s a nice positive outcome. We don’t always get that. We often get the “this class is so much more work than I expected,” but it’s not always combined with “and it was worth it.” That’s a really positive outcome.
Tim: Yeah.
John: You had mentioned that you were using a flipped classroom approach, and earlier when we talked to you, you mentioned that you were using active learning activities. Could you talk a little bit about what a typical class would look like in terms of a typical day in the classroom?
Tim: I’ll actually expand, I’d say a typical week, because usually things span like day one to day two. So, a typical week, the first day of class, we go and start off, and the first thing that we do… well, after the “hey, this week in class… , and don’t forget about this,” all of that fun at the start of class was we would do a tRAT, and for those who don’t know, a tRAT is a team readiness assessment test, and it is classically done with these cards that look like a card I’d buy for a lottery game, where we would code effectively a multiple choice quiz to the card, and then they work as a team to go and figure out what do they think is right. If they’re not right, they have to keep working on it until they go and get it right. I’ve created a digital version of that, so we begin with that, not only to kind of like warm their brains up, because I would get them Monday evening at 5:30.So, a lot has happened. [LAUGHTER] So that helped them kind of get their brains back into our content for the week and help them understand, like, “What do I recall now? What do I need to go work on?” and then we would dive into one of two things, if we were having a bigger application week, which was a lot of the more impactful work, we’d walk through, here’s our work for day one, day two, here’s our task for the end of the day, and then they would just dive right into it, and in those cases, day one was like they were working with a small, and by that I mean no more than four of them in a team, a small team of their peers, and they would work on doing more of the engagement part, and then day two would be wrapping up that, and then doing usually a presentation to go and share out. So, an example of a week, this one was a hit. It was new in this format, and it seemed like it went over well. When we were talking about diseases of the lung, the pulmonary system has a lot of diseases that are infectious, a lot of ones that we would have to report to the state if you happen to get it, and even if it isn’t directly involving the lung, that might be the way it’s spread. So we wanted to introduce them to the fact that there are these things called an investigator that works for the state, and all they do is investigate potential forms of these that might spread that we might need to do some public health work on. So in the first day, they were handed their initial case that they had to go and talk with this AI bot to figure out what had the patient done, where were they at? They knew that they had TB, but they didn’t know anything else. And then they were allowed to expand their investigation to potentially up to three additional bots, and they were told you might have to talk to all three of them, you might only have to talk to one of them. You have to figure this out on your own. You have to do the investigation. So they went through the path and the process to go through and investigate. As I’ll just go and say they did have to talk to all three. The first one went and led them to two of the three bots, and then one of those two went and led them into the last bot. And then they had to go and figure out what do we think happened, and then our day two of class, they wrapped up that work, and we had a chat as a whole class about what did you find out, how do you think this spread, what do we need to do next, and it was actually quite a complicated case, but that’s the way that it spread throughout that week was to go and show them, like, hey, this is an airborne thing, it’s a dangerous thing, and this is a real job you might be able to actually get, and by being able to engage with the AIs as effectively a patient, they had to go through the process of the fact that one of the bots was extremely not helpful, in fact, actually almost like was very rude, and the reason for it was because of the circumstances built into this bot if they were found out to have a TB test that was positive, they had significant potential losses that would be a major problem for them. So that allowed them to actually engage and attempt to work through real-life experiences that they might actually have to go and deal with.
Rebecca: That sounds like a fun activity, that of course leads me to want to know how did you build those bots? … and a little bit of detail about using AI in that context.
Tim: Yeah, so using AI in this format is, I’ll say for myself, has not been a new thing, it’s actually been something I’ve been doing for a while. It started for me out pre- 2022 and the world exploding and changing on us, but it started before that, because in my exercise physiology course I used to teach, engaging with a client is really important, and learning how to do that, so back in the pre-AI time [LAUGHTER] I had used IBM Watson bots that you had to build very crudely when we go and look at then and now, where they had to work with this fake form of a client to pull out all the risk factors and try to understand what were their goals and how do I work with that, and it worked okay. It didn’t work great. It worked okay, because of just the inherent limitations. After we got into our current era, the last four years, roughly, that expanded greatly, and what I would do is I’d build out a prompt for the GPTs first, and now for our gems that included all of the different things I wanted, as like building, so it did include things like here is the background of you as a person. Here is a personality. Here are the, for example, in this case, if they had had any type of testing done, what are the tests? What are the results? What are the tests that we don’t go and know about within all of those? What are the ones that you immediately share? And then there might be additional forms of like a test, like maybe an X-ray of the chest, that unless the student asks, the bot won’t just offer it up. So, what are you allowed to just go and bring up? What are you allowed to bring up only after they go and ask about this thing? And then I did find that when we get into the disease space, where I want them to model the signs and the symptoms of a certain form of a problem. I need to give them exactly what are the symptoms you’re feeling, and I never give them strictly the textbook, because that’s usually not the reality. They’ll have some, but not all. And then I found that it was also very important that I put a very strict box around the bot, this is what you have, so you are a person who has a problem A, it occurred because of B, C, D, E, F, G. You’re not allowed to share any of this. It’s only for you to use to better drive your responses to the students, and so that as they ask about a thing like, have you had a fever, if I hadn’t defined that, it at least knows which way it should kind of push.
John: One of the things you had mentioned when we talked last time is that you had students engage in some self-reflection, and you referred to this a little bit earlier. What did they reflect on? Was it a metacognitive type of reflection, or was it reflecting just on the material? Could you tell us a little bit more about that?
Tim: So this actually, I won’t say that I invented it, because it’s not mine. I actually borrowed a resource from the American College of Sports Medicine annual conference three years ago in Boston, where there’s a really good discussion about flipped classroom approaches within the exercise physiology space, and one of the items that was brought up that I borrowed because it had been used in some research work was this weekly graded survey. So, in the Canvas shell, it’s arranged as a quiz, but it’s marked as a survey that is graded, and all that that means is once they go and do it, it’s just marked as check done, and it runs through a range of different things, and it’s the very last thing that they’re in charge of doing every single week of the term. So it begins with exploring how was the week overall, and I don’t say just for this class, I just say how was the week overall for everything, and that’s a multiple choice, and then we go and walk through, how well did you feel prepared for this week in class? How was the week for you overall in your life? Because we all know that we teach folks who are increasingly more stressed out right now, like I don’t know about both of you, I might have brought this up before, but I have students who, 50% plus of my class, is in six to seven classes and working one or two part-time jobs. They are incredibly busy, and then there’s other life that happens on top of that. So, having a feeling of like maybe they were off this week and maybe their life just took a bad turn in this week, so that makes sense. And then we went and moved into some more open-ended stuff, which included: What did you learn this week? What do you have in terms of a question? Were there any types of like a moment that was an aha for you (it’s fine if there weren’t)? And then we do a bit of goal setting at the very end, which is: “What do you want to do next week to improve on what happened this week? And then when you look back at this week: Did you accomplish the goal that was set for the current week? And then finally, just kind of a broad: “Anything else you want me to know, like did your car break down on the drive up from Phoenix, and you were stuck on the side of the highway for a whole day? And it’s been a thing that I’ve used for a couple semesters now, and overall it seems like it works very well, and the feedback has been very positive, in that a lot of the students are like, “I’ve never had a class require me to, and I’ve never thought about, stopping at the end of the week and reflecting over how things went,” and it’s helped them with a thing like, especially my students, who are those “got to have an A” students, which was me, in fairness of, they might have a bad week, and then when they have to stop and reflect, they’re like, “Oh yeah, I had to randomly work more hours than I thought, and I found out that my dad has to go in for a cardiac stent, of course it was a hard week.” And so it helps them kind of put the week in context better.
Rebecca: In the spirit of reflection, now that you’ve had [LAUGHTER] this experience over a semester, would you continue the approach? What are some things that you might do differently next time? This is your moment to reflect. [LAUGHTER]
Tim: Yeah, so reflection for me would be this, I think I wouldn’t, and I’m not planning on moving forward in exactly the way that we did. Learning that just the fact of Google will push adjustments to their models regularly, and it’s not always easy to go and track it down, that makes it a little bit unpredictable, and I think there definitely is time that could be clawed back because there are times when AI was just inherently not efficient. So in the current model I think there are improvements that could be made, and how I would improve this is I am very much a fan of OER, especially at the current time when things are just expensive, so I would want to create and provide content that provides that foundation that is a little bit more controllable, so I have a better idea of like this is the time that they’ll spend here, so I don’t say like it’s going to be an hour or two, and then bringing in that AI in a more limited way, but in a higher impact way, where instead of using the AI to learn, they’re going and using it as a way to apply and test their own knowledge in a manner that’s going to give them immediate feedback and allow a challenge to the way that they actually approach the content for that week.
John: One of the big concerns with the use of AI models is personally identifiable information. Were you concerned about that issue? I know the contract that Google provides with campuses is that they don’t use the data for training, but were there any residual concerns about that issue?
Tim: This is a great point, because this is a big thing that I work with our faculty on a lot, because with AI’s advancement so fast, it’s so easy to ignore the legal terms of use, which I know everybody reads in fine print. [LAUGHTER] And so for this spring semester I was not worried about that, number one, because as you’ve alluded to, we have a Google ed license, which explicitly prohibits them from training on our chats that are through our accounts, and as a part of that, I made sure that we had a pairing up with that, with ensuring to be very clear, I want you to log in through your college accounts onto this, that’s the only way that it’s like a guaranteed private, and part two, even with that, I don’t want you to put in anything that you wouldn’t mind having as like a TikTok post, as like a public thing. It’s here to help you go and learn the content. It’s not here to help you troubleshoot why you’re not [LAUGHTER] feeling great today. So I did go and build in a bit just to help our students better understand, like, what are the safe and unsafe ways to engage with AI in this format, because I don’t think that’s talked about enough in the world. Now, with that said, I will say that there’s a very interesting change on the horizon, and that’s because our institution has been… for quite a number of years now. We have both Google and Microsoft. Don’t ask me why, I don’t know why [LAUGHTER]… but moving into this fall we’re moving to purely a Microsoft license, so we no longer have the Google license, which has been an interesting change to find out about, because it’s been very recent that we’ve found out about it, that really affects this work. So, moving forward, we, we being myself and the faculty who go and teach these classes, we’re going to have a conversation over the summer about how do we manage this, because the Microsoft format is through the Copilot, and unfortunately the way that it works is I can make these – they’re called an agent in place of a Gem, however, once I go and push them for a student, at least right now, from what we’ve been told, it costs us tokens, which means that there’s an ongoing cost that’s not like a Gem, where it doesn’t matter how much they engage, it’s all wrapped up in that fee. This is a big change, because, as you know, as I suspect, both of you are feeling like finances are a worry for a lot of institutions, so we want to be very thoughtful. So we’re having to go and talk about this, about how do we move forward in the future, is this a thing where we keep it as a G em, and we’re just explicitly clear about you should put no private information in here, because even with a free account, there’s a fair amount of use you can do with these, so that’s a big change we have to go and figure out as we’ve moved away from the Google group.
John: That’s really unfortunate, because I know in campuses where people have had both the choice of faculty is to use Google tools and to use Gemini and Gems, both because of the cost and because Copilots development is behind the others. Even though it’s based on the Open AI model, the training and everything else is unique to Microsoft, and it’s designed for a business environment to keep information locked down and also to build based on the use of the chatbots created by the businesses that are running Microsoft, because it’s designed more for commercial enterprises than for academic enterprises.
Tim: Yeah, well, and I’ll just say, as an expansion, too, because depending on the institution, I mean, one of the things I want to look into as well is there are increasingly more open source models that we can use, and there’s plenty of techniques that, if you have the compute capacity, you could potentially train a larger model, just going and thinking, like maybe you train a Llama 4 and use that as a teacher to train a student that’s smaller that then we can host locally. So there’s plenty of alternates, but it requires you to have the proper not only compute and server capacities, but also the fact that you understand how to make that work. So that is a thing I want to look into, because I do agree with you, Copilot is much more on the business versus straight up education side. So it’s going to be interesting to see how this changes, and perhaps that’s a point to go and have a chat about in like a year after we’ve had a year to explore how have we adapted to the Microsoft model.
John: And that is probably going to be a much more of a transition than adjusting to the change in Gemini.
Tim: Yes, it will be. [LAUGHTER]
Rebecca: It’s a good reminder how quickly this landscape is shifting in the role that the changes in technology have, the role that these companies play in what we’re doing, the finances around it all, they all have an impact on what we do in the classroom. We always wrap up by asking: “What’s next?”
Tim: Yeah, [LAUGHTER]I think I might have alluded there. So, what’s next is for this fall, for both of the classes where we’ve used this in. First of all, one have to figure out what to do with the fact that we will no longer have G ems in an institutional license, so have to figure that out. And then two, how are we going to do adjustments with the classes to provide content in more than just text, because that gets a little bit boring. So, how do we provide the content foundation, and then back it up with applied learning through the use of an AI to further enhance learning? So, we want to keep moving forward with this idea. We just have some hurdles we have to go and jump over first.
John: It’s going to be a challenging experience moving forward, but I hope things go well.
Tim: Me too. [LAUGHTER]
Rebecca: I hope you’re a hurdle jumper, because they’re going to keep coming. [LAUGHTER]
Tim: Yeah, I think I might be sore by the end of this fall. [LAUGHTER] It’s going to be interesting to see what happens.
John: Going back to the multimodal thing, one of the people I worked with this year from one of the other institutions in the health sciences field had put a microphone in a mannequin and a speaker there, and they had voice interactions with a patient who was basically just a plain mannequin, but they were interviewing it and asking questions. They enjoyed the multimodal interactions, probably a bit more than just text interactions.
Tim: That’s a really interesting idea. I might have to follow up with you more about that, because that’s a really clever idea.
John: It wasn’t mine.
Rebecca: I immediately saw your gears turning. [LAUGHTER]
Tim: Yeah.
Rebecca: Well, it’s always a pleasure to talk to you, Tim. Thanks for joining us again.
Tim: Yeah, thank you. I’m sure we’ll follow up again in the future about how did the transition go. [LAUGHTER]
John: You’re not alone, because institutions are cutting costs, and many institutions, including us, have access both to Microsoft and to the Google tools, so we’ll see.
Tim: Yeah, we have some strong feelings as faculty.
Rebecca: Yes, we do. [LAUGHTER] All the big feelings. [LAUGHTER]
Tim: Yes.
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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.
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