Undergraduate nursing students' use and experiences of Large Language Models:A qualitative descriptive study
This qualitative descriptive study of fifteen undergraduate nursing students reveals that while they use Large Language Models pragmatically to enhance learning efficiency, they face challenges regarding accuracy and professional relevance, prompting recommendations for nursing-specific AI tools, ethical guidelines, and literacy training.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine the world of learning as a giant, bustling library. For decades, students have navigated this library using traditional maps: textbooks, lectures, and search engines that give them lists of links. But recently, a new kind of librarian has arrived: the Large Language Model (LLM). Think of these AI tools not as static books, but as super-fast, chatty companions who can read millions of pages in a second and then explain complex ideas to you in plain English, just like a friend helping you study for a test. They are everywhere now, from medical schools to high schools, promising to make learning faster and easier. But here's the big question: if you have a super-smart robot friend doing your homework, are you actually learning, or are you just copying? This is the mystery researchers are trying to solve, especially for nursing students. Nursing isn't just about memorizing facts; it's about caring for people, making quick decisions in emergencies, and thinking critically when things go wrong. If students lean too heavily on their AI friends, will they forget how to think for themselves?
This paper dives deep into that question by listening to the stories of 15 undergraduate nursing students who use these AI tools regularly. The researchers didn't just ask "Do you use it?" but rather "How does it feel to use it?" and "What happens when you rely on it?" They found that these students are using AI like savvy explorers. They don't just blindly accept what the AI says; they treat it like a helpful but sometimes unreliable travel guide. They use it to break down confusing medical terms, practice patient conversations, and organize their study notes. It's like having a tutor who is available 24/7, ready to chat about anything from disease mechanisms to how to write a lab report.
However, the students also found that their AI guide has some serious blind spots. Sometimes, the AI gives answers that are slightly wrong, uses outdated medical terms (like calling a bed sore a "bedsore" instead of the modern term), or just doesn't quite get the specific context of a nursing problem. It's like asking a GPS for directions to a hospital, and it sends you down a road that was closed last year. The students also noticed that the AI can't show them videos or pictures of medical procedures, which is a big deal for learning how to actually do things in a hospital. Furthermore, the best versions of these tools often cost money or require tricky technical setups, which creates a barrier for students who don't have much cash.
Perhaps the most interesting part of the story is how the students think about academic integrity. They aren't confused; they have a clear line in the sand. They see using AI to understand a concept or polish a sentence as a smart study hack, but copying an answer word-for-word or using it during a test is considered a violation of academic standards. They worry, though, that if they get too used to having the AI do the heavy lifting, their own cognitive engagement might decrease. They fear that if they rely on the robot too much, they might lose their ability to think critically or feel the empathy needed to care for patients.
The students have a clear wish list for the future. They want AI tools that are built specifically for nursing, with up-to-date textbooks and real sources they can check. They want to see videos and diagrams, not just walls of text. And most importantly, they want schools to teach them how to use these tools properly, so they can be the masters of the technology rather than the other way around. The study suggests that while AI is a powerful tool that can make learning more efficient, nursing schools need to set clear rules and create better, specialized tools to ensure students stay sharp, critical, and ready to care for real people.
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