Intro Music

Leesa Love: Welcome to Open Invitation, a podcast in which we invite students and faculty from across the University of Idaho to discuss all things open access. I'm Leesa Love, the Open Publishing Librarian here at U of I.

In this inaugural season, I and some of my fellow librarians will be talking with three recent award recipients of the University's Open Access Publishing Fund or OAPF. For those who are unaware, this limited fund is run by the Library and Issues awards to eligible faculty, staff, and students for articles published in fully open access journals. For more information on the fund, including eligibility requirements, you can visit lib.uidaho.edu/open/oapf.

In this episode, our guest is Dr. Tyler Bland, a three-time OAPF award recipient. Dr. Tyler Bland is a medical education innovator, researcher, and pharmacology professor at the University of Idaho WWAMI Medical Education Program. With a background in neuroscience and a passion for transforming complex medical concepts into memorable, learner-centered experiences, Dr. Bland has developed multiple novel educational platforms.

He is the creator of Medimon, a game-based learning system that can best be explained as "what if Pokemon went to medical school?" and which blends collectible card and video game formats to teach health science topics.

He also pioneered the Bland Pharm Cinematic Clinical Narratives, which re-imagined clinical cases as fictional movies created with generative AI tools for all aspects of video production.Dr. Bland has recently published peer-reviewed articles showing how these novel educational platforms have been used to improve academic achievement and long-term retention of health science topics.

His work is not only reshaping how medicine is taught, but also inspiring the next generation of medical educators to explore the frontiers of creativity and technology in the classroom.

The articles we'll be discussing today include, "Enhancing Medical Student Engagement Through Cinematic Clinical Narratives, a Multimodal Generative AI-based Teaching Method," published in the January 2025 volume of JMIR Medical Education and “Anti-parasitic Pharmacology Goes to the Movies: Leveraging Generative AI to Create Educational Short Films," published in the March 2025 issue of MDPI's journal AI.

Transition Music

Alright, welcome to our new studio space in the library, and thank you for agreeing to be part of our first season of the podcast. Welcome, welcome!

Dr. Tyler Bland: Great to be here.

Leesa Love: So this past year marks your second and third time receiving funding from OAPF, and today we're here to talk about two of those articles and your overall experience publishing via open access. So can we start by, I guess, just jumping into what inspired this research?

Dr. Tyler Bland: Yes. So first I'll give a little background on kind of what I do. So I'm a professor with the WWAMI Medical Education Program here, and I teach pharmacology, which means how do drugs work.

So I teach first and second year medical students all of the pharmacology they are required of on their boards, not everything they're required of in practice. We can only cover a small portion of it. But how my lectures work, typically in this, is that we have a lecture covering a certain aspect of pharmacology, say antibiotics, where I walk through the different types of antibiotics that they're required to learn. How they work, side effects, important therapeutic stuff like that.

And then we typically end every lecture with a clinical case where they get to practice the stuff that they just learned. So for instance, 23-year-old female comes to the office, complaints of fatigue, blah, blah, blah. The students are tasked with diagnosing the patient, determining what type of drugs are required for that patient, and then understanding the side effects and stuff that we just practiced.

Typically this isn't very interesting. It's more real life, but it's not super interesting or memorable. And so what I've tried to do is spice up those clinical cases, make them a little more interesting. So how I try to spice them up is I call these cinematic clinical narratives. To my students they're just known as movie cases.

What I do is I try to find a celebrity or a movie star, actor, actress that has suffered from whatever disease that we're covering, that has suffered from it in real life. And then what I do is I try to find a movie that they've either starred in and then make a fictional sequel or prequel to that movie. And then the plot is walking through diagnosing that actor actress in the case, in the movie, and then treating them.

I also try to abstract some of this information into mnemonics. And so mnemonics are mind hooks. They help you remember stuff easier. And so instead of trying to remember a big long drug name, I try to come up with some sort of, maybe visual representation that allows students to remember it easier. And so what it does is that, people remember movies fairly easily, like you can go to the new Mission Impossible movie coming out. And if you have you can probably tell me one of the scenes in it.

Very rarely do students come to me after, after class or even weeks later and go, oh, I remember that 23 year old female we treated in. They never say that. What they have said though, even months after the cases occurred, hey, I remember the Selena Gomez case and how we treated her.

And so I'm trying to make it more memorable for the students. I'm trying to make it more fun for them to help bring them into class and help them enjoy class a little bit better. But I'm also trying to make it a little bit more enjoyable on my side, where as the professor up front it's way more interesting to walk through a fictional movie where we treat Shaquille O'Neill as a fictional genie as opposed to a 48 year old male that has gout.

Leesa Love: Yeah, definitely. I mean, even I like reading through the article was like, yeah, I know all about the Selena Gomez stuff. That's so that's so funny. Awesome. Okay.

So obviously, AI is a pretty big component of all of this. So what considerations did you make when utilizing generative AI programs to develop these teaching materials?

Dr. Tyler Bland: Yeah, that's a great point. And so how these cases are laid out or how they've been laid out historically is that it's all PowerPoint based where there's text. Maybe I generate an image or two to help get the students in the mood. And then I convert that text into audio. Again, to try to set the mood, make it a little more cinematic.

Recently, we've upped our game and we've actually produced a short film. So I think about 10 minutes long where we have incorporated all of the aspects of these cases. Because I am not proficient in art, I am not proficient in script writing, I am not proficient in animation. None of this stuff.

What I am proficient in though is utilizing the tools that have been given me. And those new tools are, are generative AI tools now. And so for each aspect of the case, for plot design, for character sheets, for the animations and the voices, for all of that, I was able to utilize different generative AI models in order to put together a fictional movie with a, AI backed studio basically behind me.

So it allowed me to do it as opposed to having to farm it out to Disney to try to animate this for me.

Leesa Love: Yeah, I actually watched that, the George Clooney one. That was very funny. Very, very cool. Check it out if you haven't seen that, actually.

So that's interesting, yeah. Because I had myself thinking obviously as I was reading through it, it's such a shame that we don't have the time and the resources to, I don't know, partner up with the theater and film department and put stuff together like that. But I can see where fast pace, of academia, you really need to have stuff developed a lot simpler, I guess, like have these processes in place.

Dr. Tyler Bland: Yeah, and if I can jump in real quick. So all of this was done by myself. And some of the feedback I got was some of the acting was a little wooden, some of the lines were a little stiff. And so this was just a proof of concept. And so what I would love to do is partner with the theater department, partner with the music department to really up the game on some of the future cinematic clinical narratives that we have coming out.

Leesa Love: That would be, that would be awesome. So I was curious, how did the students initially respond? I know I've tried working with AI before and again, sometimes it is a little bit stiff, a little bit clunky, and my first thought was I feel like when I was in school, my peers probably would have been like, this is so goofy.

Dr. Tyler Bland: Right after I played the video in class, I got a round of applause.

Leesa Love: Wow.

Dr. Tyler Bland: Which is actually pretty cool, like they really enjoyed it. That's anecdotally, but we've actually looked at it scientifically. And so we published these papers that you can look at.

And what we did is we looked at achievement from students that either viewed the short film, the movie case, or did not, just got the traditional text-based, 33 year old female comes in, blah, blah, blah. And we also looked at preference. So we gave them a survey and we asked, do you prefer the traditional version of cases that are presented in class? Or do you prefer these movie cases?

And for achievement, outside of the George Clooney Alien case, all the other ones that are just mostly text based and narration, we don't really see much achievement difference. Our students performed just as well as other students that haven't received those cases. But when we actually produced the short film and had our students look at it, they scored 100% on the questions related to that case, as opposed to their peers that did not receive that case, scored lower.

So it did lead to achievement gains. And then when we look at preference, do they prefer the movie case over the traditional ones? And the majority of them preferred the movie case. There was some pushback though saying that it's a little difficult to study from, sometimes some of the abstractions that I make, some of those mnemonics were difficult to understand.

And so of course this isn't for everybody. But what we try to do is provide students with both. And so in the lecture, I give them the movie case and then outside of the lecture, I also provide them step one-like or board-like questions, which is the typical patient presents. This is what they present with, or chief complaint, diagnose, treat and so forth. So I like to use the best of both worlds.

Leesa Love: Okay, yeah. So like tailoring to different learning styles and stuff like that.

Dr. Tyler Bland: Exactly.

Leesa Love: Okay. Very, very cool. So your first article mentions the potential concerns of using real actors’ likenesses. We've already kind of covered this a little bit, but can you talk more about the level of significance that this aspect of the project carries?

Dr. Tyler Bland: Yeah. So what I try to do is, as I mentioned earlier, find a celebrity actor actress that has suffered from that. Just to make the diseases a little more real world, that's one case.

For another one, just because it makes it more memorable, like it's much easier to remember Selena Gomez has it than I don't know, Joe, Jane, Jane Doe, or just Jane Doe has it.

As well as in the future, what I hope is that, if my students that become practicing clinicians, if they have a patient that has, I don't know, maybe Lupus, perhaps they feel ashamed about it. My students can go, this is nothing to be ashamed of. Actually, Selena Gomez, like a famous person, has suffered from it. And so hopefully we can have that connection there.

Now for the movie cases themselves, though, this is not a necessity. And so not all of them have a real actor actress that is in it. We do have fictional people. And so of course, we can abstract it into a fictional person, but I try to as much as possible use a real individual that has suffered from it. And all the information that we use there is all public knowledge, like we're not making any of this stuff up.

I also say that it is based on a true story. George Clooney and Rebel Wilson never went to outer space, never fought an alien. And so it is very loosely based on reality. But I also make sure that I preface the case both before and after, stating that the actors and actresses inside of this has nothing to do with it. This is not them. These are not their voices. This is just a representation.

Leesa Love: Gotcha. That makes sense. I hadn't really considered the in practice, in the field, being able to reference that as well. That’s actually a really good point.

And then, I guess that question sort of came to my mind because I have seen sort of similar examples that have been shared in open education platforms, like Pressbooks, for example. I've seen a Pressbook for example, where people do like tiny films and they have like these activities interspersed throughout the film to like engage in that kind of practice. So I was wondering if you all had considered in the future sharing stuff like this more widely like that.

Dr. Tyler Bland: Yes, of course, and not even in the future we're already doing it. And so in the publications that I publish, these are all open access publications, which means anybody can open them. You don't have to pay for it. You don't have to go through a university.

What we've provided in the Selena Gomez case, we've provided the slides. And also a video of the narration of those slides. In the alien George Clooney case, we've provided the actual short film in the publication.

Sometimes though that's a little tricky for individuals outside of academia to find these publications and get into them. And so we've actually made it even easier is that we've uploaded the George Clooney case as well as the behind the scenes on how I made it to YouTube. And so you can actually just go to YouTube and watch it there.

Leesa Love: Gotcha. Okay, YouTube. The second article touches on the potential risk of over reliance on generative AI among educators. Can you speak more on that?

Dr. Tyler Bland: Yes. With great power comes great responsibility. And these new generative AI tools are giving people astronomical powers. They're giving them superpowers in order to do a bunch of these things, which is always a double-edged sword.

Any technology that comes out that has a good purpose to it, people always use it for evil. And so I think there can be a worry about over reliance on AI, where not only just professors, but just people in general can start depending on these AI platforms to do things that maybe they should be doing by themselves.

One example I always think of is the calculator. And so before the calculator was invented, people had to do math all in their head or on paper and figured it out. And the calculator was invented and I no longer know how to do long division. I just have the calculator on my phone do it for me.

Is that a bad thing? I don't know. I've lost that skill or society in general has lost that skill. But typically when students are going through math, they need to first learn how to do long hand division first and then the teacher gives them a calculator.

And so I worry that the open access of all of these AI learning platforms allows people to not learn the long division first and then be handed the calculator but instead be handed the calculator in kindergarten. And so that's a concern of mine. What happens in the future? I have no idea. But I just caution people to use these tools responsibly.

Leesa Love: Yeah, definitely. I know that the library has been going through a lot of steps to develop resources around that for faculty and students to ensure that like, we’re there every step of the way kind of. So we're not jumping to AI first necessarily and learning how to integrate it into what we're already doing.

Dr. Tyler Bland: Exactly. And I know there's a worry that AI is going to replace some jobs in this area. And so that's some of the push back I got with the short film I produced. Are you replacing the jobs of a music composer? Of a producer, of an artist, of all these people that would have done all the different aspects of the movie case.

And my answer to that, at least for me, the answer to that is no. Because I don't have the funds nor would I hire all of those people in order to produce the short film. And so if AI wasn't here, it's not that they would have had a job. They still wouldn’t have had a job because I wouldn't have been able to pay them for it.

But that said though, if there's movie companies out there that would have paid an actor and actress to do this and are instead using AI, then yes, in that case AI would be replacing jobs. But that's another concern that I have moving forward with AI in the future.

Leesa Love: Definitely. Definitely a valid concern.

So I guess now we can jump into the open access aspect of things. So why did you choose to publish the open access?

Dr. Tyler Bland: Two reasons. The first one is that the library has an Open Access Publishing Fund. That helped support me in publishing those. But on the second side, and I mentioned this earlier, is that the public has access to it.

And I think it's important as a scientist, especially scientists that have federal or public funding, that if people are paying their taxes and their taxes are going towards you doing your research, you should be able to supply what you have made to the public. And so with open access publishing, that's exactly what happens. And so my wife who is a stay-at-home mom is not employed by the university, she can go on and look at this. She doesn't have to either pay exorbitant amount of funds, which on non-open access publications that I've seen typically, you have to pay just per article, 60, 70, 80 dollars just to read it, which I think is absolutely ridiculous. Or you have to be employed by a university or a company that pays these journals to get access to. And so I think it opens up science to be able to have the community at large be able to view that and see it.

Leesa Love: Yeah. I mean, I definitely agree. It is my whole job to support stuff like that, but it's interesting to hear even the pushback on that sometimes, even as basic as arguing the rigorousness of it and stuff like that. Yeah. I mean, I definitely agree. It is my whole job to support stuff like that, but it's interesting to hear even the pushback on that sometimes, even as basic as arguing the rigorousness of it and stuff like that.

Dr. Tyler Bland: Exactly. I 100% agree.

Leesa Love: Yeah. So what was your experience going the open access route versus traditional publishing? And that can include your experience with the OAPF or just in general.

Dr. Tyler Bland: To be honest, almost all of my publications are open access because of the points that I just mentioned earlier.

In response to using the OAPF, the Open Access Publishing Fund, my experience has been great. It's, the website mentions that it might take some time in order to contact somebody, apply, get all those in, and get a response back. My personal interaction with it has been hours to days. And so I've been very, very pleased.

Leesa Love: Awesome. I'm glad. It's probably my nervous energy. I feel that I'm like, oh, I got to get on this really quick. So yeah.

Dr. Tyler Bland: It is very appreciated from a research side.

Leesa Love: Yeah, I'm sure. I know that we've been tracking all of this stuff over time and the issues with getting invoices from publishers and stuff is always very wonky. And so sometimes it can stretch out weeks and weeks.

Dr. Tyler Bland: Yeah. And sometimes it's tricky because they give you the invoice and they expect you to pay it within 48 hours, three days. And so when the library says, well, it might take seven to ten days in order for you to get a response, it's nerve-racking, but that has never been my experience. It's always been a direct response either that day or the day after.

Leesa Love: Yeah, for sure. I'm glad that we've been able to speed that up for people.

Okay, so we kind of covered this in the first one, but what would you say to other scholars who are deciding whether or not to publish via open access?

Dr. Tyler Bland: Selfishly, don't do it. Save all the funding for me. But in reality, do it. And I think, actually, I think that might be a requirement for some of the federal funding, for some of the NIH and NSF grants. Is that if you receive funding that comes from taxpayer dollars, those taxpayer, payers need to be able to see what you've produced. And so publish, publish, open access. Please do it.

Leesa Love: Awesome. Well, I think that's all of the official questions that I have, but is there anything else that you'd like to share about your research or your experiences in open or anything at all?

Dr. Tyler Bland: Mostly just, we publish open access. You can always see our research. We try to put that on our website, blandpharm.com, so you can see those publications there.

We also have links to YouTube links to those videos, the Alien Parasites Within short case, short film, as well as the behind the scenes. So if you're interested, you can find us there. You can find us on YouTube. Take a look, and we hope you enjoy it and we teach you something.

Leesa Love: Awesome. Well, thank you so much for being here, and hope you have a great summer.

Dr. Tyler Bland: You as well. Thanks for having me.

Outro Music

Leesa Love: Thanks for tuning in to our first season of Open Invitation. Please check out the show notes for links to the articles we discussed, as well as the Open Access Publishing Fund.

If you'd like to know more about U of I library's publishing support, or have a question about open access you'd like us to answer on future episodes, fill out the contact form on our website. See you at the library.