Beyond the Hype: Practical Applications of AI in Nursing Education

In this episode of NLN Nursing Edge Unscripted, hosts Dr. Raquel Bertiz and Dr. Kellie Bryant welcome Dr. Rachel Cox Simms to discuss the role of generative AI in nursing education. Dr. Cox Simms shares how she integrates AI tools like ChatGPT into her teaching, using them for NCLEX-style question development, case studies, and interactive learning. She emphasizes the importance of AI literacy for both students and faculty, ensuring educators understand its strengths, limitations, and ethical considerations. The conversation highlights challenges in AI adoption, including misinformation, bias, and the need for human oversight in AI-generated content. The episode concludes with practical advice for nurse educators, encouraging them to explore AI, experiment with its applications, and integrate it responsibly into nursing curricula.

Learn more about AI from Dr. Cox Simms:
Simms R. C. (2024). Work with ChatGPT, not against: 3 teaching strategies that harness the power of artificial Intelligence. Nurse educator, 49(3), 158–161. https://doi.org/10.1097/NNE.0000000000001634

Cox, R. L., Hunt, K. L., & Hill, R. R. (2023). Comparative Analysis of NCLEX-RN Questions: A Duel Between ChatGPT and Human Expertise. The Journal of nursing education, 62(12), 679–687. https://doi.org/10.3928/01484834-20231006-07

Simms, R.C. (2024). Using chatGPT for tailored NCLEX prep in virtual office hours. Nurse Educator, 49(4):p 227, DOI: 10.1097/NNE.0000000000001611

Simms, R.C. (2025).Generative artificial intelligence (AI) literacy in nursing education: A crucial call to action, Nurse Education Today, Volume 146, 106544,ISSN 0260-6917, https://doi.org/10.1016/j.nedt.2024.106544

Dedicated to excellence in nursing, the National League for Nursing is the leading organization for nurse faculty and leaders in nursing education. Find past episodes of the NLN Nursing EDge podcast online. Get instant updates by following the NLN on LinkedIn, Facebook, Instagram, Bluesky, and YouTube. For more information, visit NLN.org.

Transcript

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Welcome to this episode of the NLN podcast Nursing Edge Unscripted. I am the host of today's episode.  I'm Raquel Bertiz and co-hosting with me is Dr. Kellie Bryant and we're both from the National  League for Nursing. In this episode we will discuss generative AI in teaching and learning,  specifically ChatGPT. Our guest today is Dr. Rachel Cox Simms. She is an assistant professor  at the MGH Institute for Health Professions School of Nursing in Boston and she had  completed interesting projects in AI published them also in various peer reviewed journals. She  is also completing her PhD in health professions education at the same institution. I therefore  welcome Rachel or Dr. Cox Simms. Thank you for joining us. Thank you both for having me today.  So excited to talk about those are really exciting topics something near and dear to my heart and my  everyday life. So I'm very excited to discuss this with you both. Okay. Yeah. And I cannot wait to  get this conversation going. So let me ask you the first question. So what research projects have you  done in AI and what led you to do this projects? I'm curious about that. Great question. So let's  talk about what led me here first. So honestly, what led me here was I felt like survival. I  was pregnant, exhausted, and trying to figure out how to streamline my academic life and my  career before a little tiny human arrived and took over my life. I have a brother who's a computer  scientist very excited about AI. He like sent me a message saying "This is really cool, check  it out." So I started testing AI tools to see if there's anything I could use to help lighten my  load or be more creative and just take some things off my plate. And as it turns out, ChatGPT was a  fantastic tool. I didn't need sleep or snacks or maternity leave. So it was a win-win. It was  a very helpful tool. It helped me balance a lot that I had going on at the time and it was really  exciting to see everything it could do. So that's how I started with it is just sheer need and then  I kind of ran with it. It started with doing some research studies and comparing the quality  of NCLEX questions created by ChatGPT with those created by human experts educators. And from there  moved on to designing assignments that work with AI instead of against it. Think things like case  studies quizzes, tasks where we can use ChatGPT to actually improve learning rather than shortcut it.  So think about how we can use its weaknesses, the fact that it makes things up. It's not a perfect  tool. Use it to help our students learn and think critically and then I've got lots of other things  going on in class. Things like custom GPTs for for my pharmacology course and comparing different  AI platforms. So definitely a lot of irons in the fire right now. Yeah, I actually saw a most recent  article of yours and it's really the call for AI literacy for nursing educators or in general  nursing education. So I was thinking that's kind of like, oh, pushing this forward. So what was  that all about if you can like expand a little bit on that the call? Absolutely. So I think that AI  is going to become more prevalent in education as time goes on. It's going to be I think baked  in to some degree as like an assistant, something like autocorrect, something we use without a lot  of thought. However, as these tools become more prevalent we have to retain our critical thinking  clinical judgment. I think these tools are going to be integrated into clinical practice. We're  already seeing them being used in hospital settings to help take notes, coding, billing  things like that. So our students are going to be stepping into a world a future where health care  and AI are completely intertwined. So I believe that generative AI literacy for both faculty and  students isn't just helpful, it's crucial. We want to prepare students not just for exams but  for the like health care system that's evolving in real time. Our students need the skills and  the critical thinking not just to use these tools but to critically examine them their outputs and  use them safely ethically. And it starts with us as educators making sure that we understand even  if we don't love it. Not everybody has to love it. Not everybody has to use it. But knowing it's  good and bad and making sure we explain that to students in context is really important.  That is great. And again, I also read quite a few of your articles and I found them really,  really insightful because they're, like you said, there's a lot of educators out there who,  you know, you have the gamut. You have some who are novices who have never used it or a little  bit worried about using it and you have some people who just dive right in and pushing it to  the limits and seeing you know what other ways it can make their life a lot easier, more efficient.  You just mentioned though that it's not perfect. And I was wondering if you can expand on what  are some of the challenges and and obstacles that you see when it comes to faculty incorporating AI  into the nursing curriculum? Absolutely. So like any tool there are pros and cons. Like  any medication, I teach pharmacology, I'm always talking about risks and benefits. And this is a  tool just like anything else. There are risks and benefits. One of the big risks right now is that  AI produces factually incorrect information and it does so very confidently. It can fool even if  you're not being careful. It can fool you into believing something that is absolutely not true.  But it sounds really good. It sounds great. So we have to be aware of the fact that these tools can  provide unreliable, inaccurate, or even biased information. So it's our job as faculty to use  our expertise. We know a lot and it's our job to use our expertise to carefully look at what AI  creates. Keep what's good, reject what's bad, and then use that to help students. One of my favorite  things to do is have students use AI to generate practice questions. I give them some guidelines on  how to create them and then I make them factcheck those practice questions they create. Is it a good  question? Is it like something you'd see on the test? Was the answer correct? Was the rationale  right? And then I ask them to site their source from the book or my slides. And then at the end,  just to make sure they did it correctly, I have them submit their transcript. ChatGPT  can allow students to basically copy their entire conversation and share it with me. So I can look  to make sure that they're using it correctly and wisely and give them advice to guide them towards  better use. So right now it's not a perfect tool, but I like to harness its weakness as a learning  strength for students. Not only am I teaching them about AI and how to use it safely and wisely,  I'm strengthening their critical thinking skills having them look at text look for bias look for  factual inaccuracies and then correct it. Think bigger than just memorizing. We're not just  memorizing wrote memorization. We're thinking about things. And I think it's going to help  potentially make students stronger test takers if they understand even the questions better.  So a lot of opportunity there. Yeah. So I think that you really kind of like touched on several  challenges there and at the same time advantages of utilizing the technology that we have right  now, which is AI. So for example, I heard you say oh, it's going to make them stronger test takers.  So and I know that you mentioned earlier that you did a particular study on writing test questions.  So can you kind of like share a little bit of like what surprised you if any from that study  because I found that very interesting. Absolutely. So one of one thing that students like a lot,  for anybody who teaches in nursing education, you know students love practice questions. They're  always asking for more and more practice questions because that's a great way to learn how to take a  test. And I'm always coming up short. I never feel like I have enough practice questions. I started  using ChatGPT to create custom practice questions for students based on things they were struggling  with. And I found they were actually really good, a really great jumping off point. So I teamed up  with some other faculty at the school at the IHP and what we did is we did a comparative study.  We used ChatGPT to create practice questions and then we paired them with human generated  questions .So same topic different questions and we coupled them together. We then sent out these  questions to faculty really all over New England. It was a New England-based study and we had them  evaluate these two questions not knowing that we're comparing AI or human, but we wanted to  know did you like the questions, how clear were they, correct were the distractors good, was there  any bias? So we had them evaluate all of these questions, 20 in total, and then we compared the  human the scores on the human-based questions with those created by the AI. Interestingly enough,  we found that the scores were almost identical or very statistically similar. We found that the  questions created by AI did not necessarily score better or worse than those created by humans,  but we did find that there was a slight preference towards more of the AI questions than the humans.  So several of the AI questions were preferred, but we did find that the human created questions  were maybe a little bit harder, but the hard the degree of difficulty and the preference were not  the same. So it's not like we preferred the harder over the easier or anything like that. So we found  that the questions were pretty similar. And this was back in 2023 with ChatGPT's original model.  So things, a lot has changed since then. It's been a few years, but we found that even the more  primitive ChatGPT was able to create some really great questions. It's a lot of opportunity for  us as educators. We know how hard it is to write a good question, to write lots of good questions  over and over and over again. And we care about integrity of our exams. We don't want to always be  reusing questions. So we see this as a potential avenue to help stimulate ideas for questions,  generate new questions, mix it up on your exams. You know, make sure that we're always giving our  students up-to-date fresh questions and keeping them challenged and engaged. And I can imagine our learners are writing exams for themselves as well, right, if they learn  how to do prompts or prompt engineering of their own learning. And I think that's great,  but that brings back the point of you to say human oversight over the teaching and learning processes  and if nurse educators, human nurse educators have been creating more difficult questions. So  that brings me back to how ... how will we make sure that these questions actually align to the  level of learning that we would like to have our students achieve? Although, like at this point,  like you said, we're now at 4.5 or or even higher, maybe ChatGPT can do that also. So to me,  that's really just interesting to see all of these changes happen over time. Absolutely I  think there's a lot of avenue for future research discovery comparisons. There's other platforms now  other than just ChatGPT. There are a lot of really other great platforms who are probably capable of  creating other great questions as well. I think we're going to probably look towards a future  where maybe an AI is even customized towards health care nursing even creating and learning  and training on content specific and relevant to us. Maybe that could even enhance our ability to  create resources, materials, assignments for our students to help them, you know, learn in this new  AI-driven world. Because one of the concerns for nurse educators is that students are going to use  AI for everything and it's going to decrease their critical thinking skills and that you  know if we give them simple questions such as fill-in- the blank or multiple choice they're  just going to put in a ChatGPT and get the answer and not really. you know. think about the answer  themselves and just kind of use it to spit out the answer. So you brought up a good point and a great  example of how you can as a nurse educator use generative AI to create assignments where you're  embracing using generative AI and because it's not going anywhere. So I'm just curious if there  are any other examples of assignments that nurse educators can adopt that will help the student  number one teach them the AI literacy skills that they need and competencies but also create  a meaningful assignment like the one. the example that you gave of writing NCLEX. Do you have any  other examples for our nurse educators out there and how they can use generative AI in their  assessments and their assignments? Absolutely. So another really great opportunity for learning and  exploration of AI is having AI generate patient cases like case studies, so having students create  case studies using generative AI. You know, have them try to produce the best case study they can  using iterative process to have them refine and go back and edit their case study using generative  AI. Always having them though site their sources using the book, lecture slides, whatever resource  you deem most appropriate for your class. Make sure students are citing their work anyways but  have them create case studies, unfolding case studies, even ones that require them to think  a little further ahead, something further than AI could easily do. It could definitely be an  assistant. I like to think of AI in this case as almost like a scaffold of learning, something to  support students as they think and grow and learn, giving them a little bit of backup until they know  everything or know as much as they can and create great case studies. So using it as an assistant to  create great case studies, helping them think more about a clinical setting and about their  patients in in real time. Also having students interact with the AI like it's a patient. So ask  the AI to be a patient and roleplay with the AI and ultimately have them share their transcript  with you from the AI so you can look and see how they're using it and provide them feedback.  One of I think the most important things though is to ask students to provide a reflection at the  end. Have them think reflectively about what they did, what they liked, what they didn't like. Not  something that's graded heavily but requires them to kind of meaningly think about what they did,  what they liked about it, what was incorrect, what was correct and even have that, share that  with their peers have a discussion about it. All of that's a great way to kind of use it to  learn and use it to learn about AI at the same time. Those are great examples. Thank you. I  know and to me, like listening to how you design or integrate AI into those very specific assignments  really reflect how you would still have to have reflections in there, the value of self-reflection  perhaps, and then giving your feedback to the students is still an integral process of learning.  And then looking at AI as the scaffold. Yeah I I really like that example. So with with that  said, I'm curious about how it changed your your teaching practices or even the learning  patterns of your students and how long have you been doing this in your practice? That's a great  question. So I have a lot of thoughts about it. So I teach pharmacology primarily, which is generally  an exam-heavy course. Truthfully, even before A,I I didn't incorporate a lot of essays so there wasn't  a huge impact on the types of assignments that I gave. We still have in-person testing and I think  that's really important, in person testing where I can view my students. I can see their screens.  I know what's going on. I know they're not using AI. But for other assignments that I do in class,  I tend to make them either low stakes or not graded so that there isn't as much incentive  to try to use the AI to cheat. We're using it as a learning experience. We're doing it together. We're  trying to meaningfully engage with the material together. So there isn't that incentive to try  to use that. I know this is a bigger challenge in courses that use more assessments and assignments  that are essay based or they get sent home with assignments that they could easily cheat with  or use generative AI unethically. And I think that's a, it's a, it's a big barrier and it's a,  it's a problem that we're going to have to try to mitigate as time goes on. We know that AI checkers  like through Turnitin aren't always the most accurate. They can unfairly penalize especially  students whose language, their first language isn't English. We know that these AI checkers can  unfairly like mark them as AI created material. So I think we're going to have to be creative. I think  it's going to require us to push a lot of our work back in person on campus maybe even pencil  and paper someday, which seems counterintuitive - more technology and we're going back to pencil  and paper! But I do think that if we are going to be creating assessments and assignments that  students could easily do with ChatGPT we're going to have to be creative about it. It's going to be  a challenge. Right and yes, so creativity and still like it brings me back to your point of  human oversight, right. The expertise of the nurse educator there. Absolutely. Another quick thought  is the idea of doing video assignments. So having students create recordings and videos. Much more  difficult to use an AI to complete that. So that's another way I've seen nurse educators do this is  have, either give their assignments via video or have students create assignments that are videos  which is a great way to see how your students are engaging with the material. Yeah. And we've seen  several articles of how students or learners are responding to the use of AI or or their  preferences. So based on your own experience, how are your learners accepting or reacting to AI  in their learning process. It's a great question. So surprisingly, a lot of students at least say that  they don't know anything about AI or have not used it much yet, but for those who are using it  are using it regularly. What I hear from students is that they are using it to help them create  study guides to explain concepts that they didn't understand in class in a different way. You know,  having AI kind of simplify things. Students use it to create mnemonics. I know that's a popular  way especially in a pharmacology class. Creating mnemonics is often really important. I also  know that students are using it to create practice questions and you know other study suggestions to  help them prepare for exams and interact and role play with like almost stimulated patients using AI.  So there's definitely some positive experiences and it's interesting to see what creative things  students will do with it. I know they're going to do something great and interesting. For sure.  There's a great article out there where it's defining how the students use AI. In some ways,  I think they're probably using it more than we are as nurse educators. And all those wonderful  ways that that you stated. I had a professor who had a student who did very well on one of the  exams. And so the professor talked to the student say, "Wow there was a big jump from your last exam  and such an improvement in this exam. Like did you change your study habits?" And the answer was "I  used ChatGPT to help develop test questions." And it proved to help because the student had  a much higher grade and the professor was like, "Well that's great. You know if it worked and it  helped you, you know, to get a higher grade, you know very supportive of using it." Absolutely. I  also have a student who reached out to me. She uses an AI called NotebookLM to take basically research  articles and turn them into a podcast. So the AI reads the articles, summarizes it, and creates it in  podcast form that she listens while she commutes to campus. So she found herself keeping up with a  lot of new things through listening and then the AI was able to help streamline that for her, which  I thought was really interesting and innovative. We can learn from our students also. Right. So like  if we are really looking ahead and kind of like be two steps ahead, not just a step ahead of the  innovations that we're facing right now. It should be both ways right. So we're preparing ourselves  and our students are on this trajectory as well. So with that said, I'm curious. So what directions  do you see your works in AI going in the near future or even like maybe if you have a forecast  of what's to come with your AI projects? Well, for my work specifically, I've kind of actually gone  back to some of the basics during my process of trying to assess the quality of NCLEX questions.  I realized there wasn't like a great standard for equality. So I've gone back and I'm working with  experts to create like what makes a really great NCLEX question. That's the work I'm doing with my  PhD. And then I hope to kind of expand and start looking at other AI platforms learning about which  ones are best suited for the things that we need as nurse educators? Which ones are creating the most accurate medical information? which ones have the least amount of bias? So I'm  really hoping to kind of dive more in to a lot of the different AI platforms, not just ChatGPT, which  I love, don't get me wrong. It's the fantastic, but I want to learn more about all the different options.  What's the best and think about a future where maybe we create an AI that's maybe more custom to  what we need. I'm working now on creating a custom GPT using ChatGPT for my pharmacology course, one  that I've baked in all of my own materials, my own syllabus. I'm trying to create a resource for  students that I have a lot more control over can provide a lot more accurate information for them. It's  something they can use to kind of supplement their learning in my course. So I think the future  is probably going to involve more personalized learning but also expanding our horizons beyond  just ChatGPT, looking at other opportunities to kind of grow in this area and expand our  teaching materials and our opportunity there. Yeah. And definitely evaluating the  quality of this apps technology is one fertile ground for more exploration or investigation.  Yeah, so I'm excited for you and you're in this path of AI and where it's going  and yeah, we'll definitely be looking out for more articles from you in the future. So we're towards  the the end of our podcast here. And so for our final question, I would just like to kind of like to know if you have some lessons learned or some nuggets to share with our nursing educators out  there. Absolutely I would encourage every nursing educator to try. Try ChatGPT if you haven't  already. Just try it out. Play around with it. Spend an hour, book that hour in your day, block it off  and spend some time with ChatGPT. Talk to it like it was a person. Ask it to do various different  things just to see if it can. Try not to be afraid. I know a lot of faculty are nervous and afraid and  I think all of their concerns are valid, but not to be afraid when interacting. Ask it to do all  different things. I'm always blown away by what it can do if I just ask. AI can mimic a lot. It can do  so many different things. It creates all these different things. And I think there's a lot of  opportunity for creativity. I know nurse educators are creative people. I know nursing as a field  always steps up historically. We're always evolving and I think there's a lot of really untapped  potential there for us as nurse educators. So I'd say keep an open mind, be curious, not judgmental  and can go in and try it out and see what you can do with it. Then share it with us because we're  all excited to see. So I shared your findings! Yeah, so thank you very much  with that set of nuggets. There's, there were a lot of nuggets there and I know that Kellie, Dr.  Bryant is also steeped into AI and ChatGPT. You've done so many presentations on this as well. So  any last words for our educators also. Yeah, I just I just want to say I agree with Rachel. It's just ... you can't break it. Just the more that you use it and play with it the more comfortable you get and  you can push it to the limits. You can just play around and do things that aren't related to work.  Tell it I have these ingredients in my cabinet. Help me make a recipe for tonight. So start with  something innocent. But I know we're running out of time and I just wanted to say thank you Rachel.  You really gave us a lot of pearls of wisdom and that you know there's so many things to look  forward to in the future with AI, but I love how you talked about all the benefits, but also talked  about the things that we need to be aware of and and the limitations and some of the challenges.  So I wish you the best of luck with your PhD also with your project. Thank you so much for having me.  I really enjoyed this conversation with you both. Yes. So thank you. Thank you Kellie, Dr. Bryant.  Thank you Rachel. So that's the end of our podcast and until our next episode. Bye bye everyone.