For a field as hands-on and human-centered as nursing, artificial intelligence (AI), particularly large language models (LLMs), present both a huge opportunity and a complex challenge. While LLMs are rapidly entering nursing classrooms, their fundamental concepts remain largely unexplored.
Julia Harrington, a master's student in the nursing department at Western University, and her team are leading the way in clarifying this new frontier. In their paper, “Large Language Models in Nursing Education: Concept Analysis,” published in JMIR Nursing, they applied a rigorous concept analysis method to 41 recent publications to understand how LLMs are being defined and used in nursing education.
The team's analysis revealed that LLMs possess several key attributes. They are accessible, providing an easy way for students to engage with vast amounts of information. They are personalized and interactive, capable of tailoring learning experiences to an individual student's needs and pace. As an innovative technology, they have the potential to transform how nursing is taught and learned, enhancing students' skills and cognitive abilities.
This transformative potential, however, comes with a responsibility to address ethical considerations. The study highlights the importance of ensuring that the integration of LLMs aligns with core nursing values, such as data privacy, transparency, and patient safety. It's not enough for a tool to be useful; it must also be used safely and ethically to ensure the integrity of the profession.
This research is important because it provides a foundational definition of LLMs within the context of nursing education. It moves the discussion beyond simple adoption to a deeper understanding of the technology's potential and its limitations. The analysis suggests that while LLMs can significantly enhance access to resources and support individualized learning, their use must be carefully managed, especially in specialized areas like graduate nursing programs. This work is a crucial first step toward developing a framework for safe, ethical, and meaningful integration of AI into nursing education.
The research was published in JMIR Nursing because of the journal's reputation as a high-quality, peer-reviewed, open-access publication. With its inaugural impact factor of 4.0, the journal is a leader in the nursing field, with a scope that explicitly includes research on nursing education, technology, and innovation. This ensures the study will reach a wide audience interested in the very topics at its core, benefiting from a rigorous review process and broad accessibility.
Curious to learn more about how AI is shaping the future of nursing education? Watch the video to hear Julia Harrington discuss her team's findings, and read the full research article to explore the complete concept analysis.
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