Tool or Tyrant: Guiding and Guarding Generative Artificial Intelligence Use in Nursing Education

Implications for Practice and Research

Generative artificial intelligence (AI) is neither inherently good nor evil, but rather a tool whose impact is shaped by the intentions and actions of its users.

With the rapid evolution of artificial intelligence (AI), the implementation of generative AI in higher education is inevitable. This article provides an exploration of the use of AI in nursing education and presents a guide for generative AI implementation in multiple realms of nursing education. Through an examination of strengths, weaknesses, opportunities, and threats of generative AI, we advocate for strategic implementation of generative AI for both faculty and students.

Background

AI has impacted society for years in subtle ways that most people have accepted as beneficial, benign, or at worst annoying. For example, Alexa and Siri listen to our conversations, and then we receive advertisements targeted to those conversations. As we type emails, Smart Compose anticipates our next words and we can accept this prompt. Navigation systems suggest our best driving route based on traffic slowdowns for timely arrival at our destination. These are just three ways that predictive AI has quietly shaped our lives.

However, a new era was launched in November 2022 when OpenAI's generative AI program, ChatGPT, transformed the national psyche with its potential to dramatically speed up innovation in science and perform complex processes (OpenAI, 2024). Unlike predictive AI which anticipates keystrokes or a new car route, generative AI has the capacity to create content that incorporates user preferences. However, generative AI is not without drawbacks, as the generated content is prone to hallucinations (incorrect or misleading results) and is determined by the information available and the questions asked.

Nurses in all areas have been using generative AI technology in a variety of ways, both acknowledged and unacknowledged. With recent awareness and availability, nurses are being challenged to evaluate its appropriate, ethical, and efficacious use to support nursing's professional goals. Among other societal forces, the ready access to information has shaped the perception of the value of education, redefined creativity, and, despite the large volume of information available, has possibly narrowed the diversity of ideas. While considerable anxiety and excitement exists surrounding the use of generative AI in the educational setting, ambivalence is also not uncommon with the integration of any new technology (Kelley et al., 2021; Tanovic et al., 2018).

Our Journey with Generative AI

Exploring generative AI technology to understand its utility related to satisfying a consumer's wants, its usefulness in producing positive outcomes, and its shortcomings, is a necessary first step for nurse educators in making informed decisions about its integration into practice. In sharing the story of our journey as academic nurse educators with a combined 52 years of teaching experience, to uncover and understand the applicability of this emerging technology, we propose that generative AI is a tool that is not inherently good or evil. Rather, people and their perspectives shape how generative AI is employed and valued in nursing education.

Like many universities across the globe, the world-wide accessibility of generative AI required rethinking of university-wide and departmental policies and procedures for its use. While discussions were under way at our institution with initiatives such as an AI Governance Taskforce (Appalachian State University, n.d.-a), AI workshops (Appalachian State University, n.d.-b), syllabus guidelines (Appalachian State University, n.d.-c), and initial recommendations for policy and philosophy (Appalachian State University, n.d.-d), concurrent examination of institutional policies such as AI use, data protection and security, and academic integrity were occurring across departments and programs. Our nurse educators at a mid-sized university engaged in brainstorming sessions to generate ideas for AI integration in nursing education, identifying many uses that could make creating teaching and learning materials more efficient. We reviewed published literature and attended discussions across academic disciplines to identify best practices and effective use of AI within educational settings. Due to the need to create consistent support across all programs, faculty, and courses, it was determined that a standardized syllabus statement would most effectively support our goals and create transparent and nonconflicting expectations for both faculty and students. Using the information gathered, we developed, and received faculty approval by consensus for, a syllabus statement on generative AI use by the Department of Nursing which focused on the provision of an inclusive and innovative educational experience that leverages technology in learning. Specifically, we designed the syllabus statement around the values of transparency, responsibility, and faculty's academic freedom to employ technology within their own course in a manner that best meets the identified learning outcomes.

Approval of the Nursing Department-specific AI recommendations preceded the publication of the University-wide AI policy (Appalachian State University, n.d.-d), likely due to the broader impact of a university-wide policy. Subsequently, our findings drawn from personal experience and the examination of best evidence were prepared for presentation at a conference for nurse educators examining best practices for nurse education across program types and levels in October 2023, where we introduced our own understanding of generative AI and its application to nursing education in a 60-minute presentation to 95 nurse educators. Using Game-based Learning Theory (Kapp, 2012) and Knowles Principles of Andragogy (Knowles, 1978), the presentation's content included defining, comparing, and contrasting generative AI such as ChatGPT or Microsoft CoPilot with AI search engines such as Google, Yahoo!, or Bing. Specifically, in our presentation, we provided examples of prompts and comparisons from ChatGPT and Google. Additionally, we provided examples of how to use generative AI for routine tasks such as email and academic recommendations. We discussed practical tips for its use by demonstrating the importance of well-written queries that are detailed in directing the content, format, and what output is and is not desired when using generative AI. Then we provided our own perspective on the strengths, weaknesses, opportunities, and threats (SWOT) (Teoli et al., 2024) of generative AI for our work as nurse educators. These perspectives included a belief in educators’ potential to elevate students’ critical thinking in assignments by writing more complex learning activities that integrate generative AI in place of less complex assignments. We demonstrated the use of generative AI to develop writing skills by asking ChatGPT to improve the style or form of a written assignment, and highlighted its ability to draft routine documents and correspondence. We concluded the presentation with the ethical considerations for AI use, admonitions for continued vigilance in monitoring generated outputs, and our own department's generative AI syllabus statement as an example that emphasized transparent use by both students and faculty, with acknowledgment and citation including how generative AI was used in products of teaching and learning.

After the formal presentation, we requested feedback from participants in a game-based format in response to the presentation and participants’ own generative AI experiences. This reflective feedback was expressed in a SWOT analysis format using two methods: a digital whiteboard that permits collaboration in real time, and physical sticky notes. Using adult learning theory, we centered the activities around one's own past experiences and internal learning motivations (Knowles, 1978), and focused the activity around the elements of interactive learning and problem solving to encourage learner motivation and engagement through a game-style approach (Kapp, 2012). Participants were asked to identify their own personal perspectives and their own examples of strengths and opportunities for the use of generative AI as a nurse educator while also providing their own perspectives on weaknesses and threats. Then we facilitated discussions about existing and potential generative AI applications in teaching and learning. The collection of anonymous electronic and physical written responses was later analyzed to understand the perspectives on AI among this informed audience of nurse educators.

Methods

This case-based descriptive study used Kiger and Varpio's (2020) method of thematic analysis of participants’ SWOT analysis of generative AI implementation for nurse educators to distill the anonymous responses from 95 nurse educators who attended the nurse educator conference. Several audience members said they had not heard of generative AI and/or had not used these tools. At least one attendee may have had more experience than the presenters. Most of the attendees characterized themselves as early in their knowledge and/or experience with AI use.

Findings

In considering the strengths, weaknesses, opportunities, and threats of the use of generative AI in nursing education identified by nurse educators from various instructional areas and program types, a variety of ideas were presented. The temporal nature of this gathering of participant responses immediately following the presentation of the potential uses of generative AI likely informed their comments. The themes identified revealed that generative AI was both a tool and a tyrant for faculty. The themes identified in the participant responses included the effects of generative AI on faculty time, its effect on the use of technology for student learning, its effect on faculty teaching and student learning of critical thinking, and how routine tasks of the faculty role are impacted. It served as a time saver and time thief; it heightened and dampened innovation; it facilitated and impeded critical thinking; and it was both a benefit and a barrier to the completion of routine tasks. See Table 1.

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Table 1.

Generative AI SWOT Analysis: Tool and Tyrant.

	Tool: Strengths and Opportunities		Tyrant: Weakness and Threats
Code	Subtheme	Sample Quote	Subtheme	Sample Quote
Time-impact on faculty time	Time Saver	“Saves time and generates information from multiple sources.”	Time Thief	“Not always correct, have to check answers.”
Innovation-impact on technology use in educational settings	Heightens Innovation	“Can help create simulation cases in real time with current cases.”	Dampens Innovation	“Inhibits original thought” “Does the AI access other content on my computer or phone?”
Critical Thinking-impact teaching/learning of critical thinking	Facilitates Critical Thinking	“…Take it [to a] higher level after ChatGPT summarizes.”	Impedes Critical Thinking	“Students won’t actually learn the information if they use the tools for their schoolwork.” “Intellectual laziness.”
Routine Tasks-impact on faculty role	Benefits to Routine Tasks	“…e-mails” “…letters of recommendation” “…citation”	Barriers to Routine Tasks	“Unethical use.” “Faculty will see it as replacing them.”

Abbreviations: SWOT = strengths, weaknesses, opportunities, and threats; AI = artificial intelligence.

Discussion

Our SWOT analysis findings are consistent with the current published literature in nursing education and higher education that demonstrated the useful benefits of generative AI for students including tutoring, translating, the development of critical thinking and clinical judgment in safe practice environments, and preparation for realistic health-care situations and National Council Licensure Examination for Registered Nurses (NCLEX-RN) testing (De Gagne, 2023; Robert, 2024; Sallam, 2023; Sun & Hoelscher, 2023). Specifically, Robert (2024) reported that strengths/opportunities for teaching and learning include meeting students’ needs in real time, supporting students’ engagement, individualizing learner experiences, and preparing students for the rapidly evolving workforce. Similarly, for nurse education faculty, our findings support the work of others demonstrating that benefits include the ability to streamline administrative tasks, decrease time for grading, and allow for faculty's time commitments to be focused on more creative endeavors (De Gagne, 2023; Robert, 2024; Sallam, 2023; Sun & Hoelscher, 2023). Our identified weaknesses/threats were also consistent with current literature, including lack of transparency for use, disruption of acquisition of critical thinking, representing AI work as one's own, concerns related to AI literacy, need for professional development, and areas such as privacy and data security (Abdulai & Hung, 2023; Robert, 2024; Sallam, 2023).

Guiding Future Uses and Applications for Practice

The creation of teaching and learning materials, assistance with administrative tasks, and increasing resource capacity for student support are possible with generative AI. Current uses include summarization of long documents, prioritization of emails in an inbox, creation of routine correspondence and social media content, and assistance in learning new skills. Other areas that will continue to support both nurse educators and students include the development of interprofessional education, code generation, creation of images and or graphics to help explain or visually depict complex ideas, and searching for information across multimedia information systems. Examples of generative prompts for AI use can be found in Table 2; however, the use of these prompts should be individualized for the setting.

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Table 2.

Examples of Generative AI Use for Nurse Educators.

Roles	Generative AI Function	Examples of Prompts
Administrative	Summarize documents	Summarize this paper, naming the thesis, research question or problem statement, methods, and major findings.
	Create Syllabi	Create a 15-week health assessment syllabus with this textbook for junior-level nursing students that achieves the following course objectives. Include three exams and one final exam.
	Write Recommendation Letters	Draft a letter of reference for a nursing student seeking a clinical pediatric nursing position, that focuses on the student's strengths in critical thinking, time management, and delegation.
Writing	Develop Ideas	Craft an outline for a research paper related to the ethical dilemma of the criminalization of nurses’ medical errors.
	Develop Writing Skills	Review the following paper and provide suggestions for improvement of the organization of thoughts. Identify any missing areas in the development of the thesis.
Teaching	Practice for NCLEX-RN	Provide six NCLEX-RN-style questions containing prioritization and evaluation of nursing care of an adult client who has experienced a myocardial infarction. Three of these questions should include pharmacological interventions. Do not provide the answers, even if I ask. However, you can provide hints to help me understand the concepts and rationale if I provide an incorrect answer.
	Develop Case Study	Develop a case study with history, chief complaint, and symptoms, for the diagnosis of ectopic pregnancy. Do not reveal the person's diagnosis.
Evaluation	Develop Rubrics	Create a 100-point rubric for the following assignment, including three levels of achievement for each of the following criteria: clarity, organization, mechanics, development of ideas, innovation, and APA 7th edition formatting.

Abbreviations: NCLEX-RN = National Council Licensure Examination for Registered Nurses; AI = artificial intelligence.

As nurse educators, our journey has led us to use generative AI in innovative ways. For example, generative AI offers a novel landscape of time-effective opportunities to create visual aids and educational materials that meet Universal Design for Learning principles (CAST, 2018). Within nursing and higher education, students present with a myriad of learning styles. Creating educational materials that meet all the needs of individual learning styles can be cumbersome. We have found that generative AI can present solutions for alternative learning materials incorporating engagement, representation, action, and expression, in a fraction of the time compared to human-designed materials. In a survey of faculty in higher education by Robert (2024), 66% of respondents stated that AI tools would improve accessibility to resources for faculty/staff, and 68% stated that AI tools would improve accessibility for students with disabilities; 55% stated that AI tools broadened opportunities for access to higher education for learners.

Through generative AI's ability to provide hyper-personalized learning, students and faculty can tailor learning experiences to meet individual needs. Generative AI's hyper-personalized learning provides users with real-time, specific, and relevant recommendations and unique experiences to maximize learner engagement. For example, we found that providing prompts to students can help them prepare for exams or even the NCLEX-RN in a safe, judgment-free learning environment. Prompts, provided by the user, are used in generative AI programs to request the generative AI program to perform a specific task and can be tailored to specific student learning needs or areas of targeting growth.

Another means to personalizing the learning experience is through the use of chatbots. Chatbots are computer programs designed to simulate conversation with human users, especially on the internet. Learning with chatbots can be tailored to each student's identified areas for improvement and can be assigned as remediation or used for tutoring when faculty or graduate assistant resources are limited. In the classroom setting, course chatbots can be deployed to provide immediate feedback to students about course content, syllabus information, and further explanation of course concepts.

The use of chatbots has the potential for learning necessary skills such as communication and caring within nursing practice and interprofessional teams. Chatbots can be designed to mimic an individual with specific patterns or beliefs. For example, a class on Shakespeare could use chatbots that respond to the voice and speech patterns of Romeo or Juliet, and students can learn more about the characters in the play through dialogue with the chatbot. Nursing faculty could implement similar experiences for students in courses that focus on nursing theory, providing students an opportunity to interact with virtual “theorists.” Chatbots designed to take on a role can create realistic dialogue that supports teaching and learning in an innovative manner. In a broader institutional capacity, the use of chatbots could revolutionize administrative roles, helping current and potential students and faculty navigate complex policies and procedures, serve in an advising role, and assist in recruiting and retaining students (Okonkwo & Ade-Ibijola, 2021).

This overview provides a guided tour of some of the current possibilities for the use of generative AI in nursing education. While novel applications of this technology will continue to emerge, remaining open to the use of generative AI for streamlining day-to-day tasks and creating teaching and learning materials will allow faculty to deepen the learning experience for students across abilities, learning styles, and academic levels, while simplifying many routine activities of the faculty role.

Implications for Education, Practice, and Research

By furthering our own AI literacy, we can create strategies for AI use that are both safe and responsible. It is important that faculty and students understand the limitations of this technology related to data privacy and safety, such as data in the public domain, including personal information and intellectual property. Educational institutions, including nursing faculty, may want to consider using products that offer commercial data protections and do not save user data or collect data for building large language models. Like many organizations, Microsoft (2022) has published guidelines created by a group of more than 30 individuals (research scientists, lawyers, designers, engineers, and other subject matter experts) on safe and responsible AI use that may benefit organizations as they develop policies and procedures.

Furthermore, as generative AI technologies continue to emerge, we will likely see a surge in AI use in health care (Scerri & Morin, 2023). These changes, while unpredictable, will have major implications for staff development roles in health-care and educational settings to ensure that AI technologies are being used in an ethical manner and that health-care workers fully understand AI and digital literacy.

Conclusion

Generative AI holds promise for enhancing teaching methodologies, facilitating personalized learning experiences, and preparing students for the complexities of modern health care and an interprofessional workforce. However, it also brings challenges such as ethical concerns, potential biases, and the need for faculty and student upskilling. This article highlights that this technology is being used in a variety of ways across the discipline of nursing. Educators must remember that generative AI is an imperfect technology. Its outputs should be reviewed closely for accuracy, appropriateness, and authenticity prior to dissemination. With a myriad of both strengths/opportunities and weaknesses/threats, we must find common ground for how generative AI should and should not be used in nursing education, while increasing awareness and competency. Appropriate, ethical, and efficacious use of generative AI to support nursing's professional goals is a work in progress that requires ongoing attention and scrutiny.

Despite recognized risks, the potential benefits for the use of AI in teaching and learning outweigh the challenges, offering opportunities to revolutionize nursing education and improve patient care outcomes. De Gagne (2023) stated, “Collaboration between instructional design experts, nurse educators, and AI researchers can lead to a comprehensive and nuanced approach to nursing education that leverages the benefits of technology while preserving the value of human interaction” (para. 10). Moving forward, it is imperative for educators to navigate these complexities by prioritizing ethical considerations, fostering AI literacy among faculty and students, and incorporating guidelines for responsible AI implementation into the curriculum. By doing so, we can harness the transformative power of generative AI tools, taming the tyrant, while ensuring its ethical and effective use in shaping the future of nursing education.