Today’s nurse education programs are facing mounting, unprecedented challenges: underprepared students, faculty shortages, and the growing pressures of accelerated programs. To bridge these gaps and help get nursing education programs back on a successful track, schools are turning to artificial intelligence (AI)—not as a replacement for educators, but as a powerful tool to personalize learning, enhance engagement, and improve NCLEX outcomes. This requires educators to think differently and truly understand how and when to use AI, as well as how it can benefit both themselves and their students.
Data Nursing Schools Need for Effective AI Implementation
To effectively implement AI in nursing education, schools need access to comprehensive and high-quality data. This data can be categorized into several key areas: curriculum data, student performance data, and clinical practice data.
Detailed information about the curriculum, including course content, learning objectives, and assessment methods, is crucial. AI systems can use this data to tailor educational content and provide personalized learning experiences. This relieves the burden on faculty from needing to create original content, allowing them to focus instead on ensuring that the content students are accessing is evidence-based, current, and relevant to their learning.
Historical data on student performance, including grades, test scores, and clinical evaluations, can help AI systems identify patterns and predict future performance. This allows for early intervention and support for students who may be struggling. It takes the guesswork out for faculty and provides them with concrete data to support the success of their students.
Lastly, data from clinical practice settings, such as patient care scenarios and outcomes, can be used to create realistic simulations and case studies. This helps students apply theoretical knowledge in practical situations, keeping them connected with the clinical setting even when they cannot physically be there to hone skills. Clinical hours are often filled with time waiting for instructors, observing only, or connecting just one student per patient. Using real clinical practice data in simulations, case studies, and even in class will bring the focus back to the content students need to be practice-ready after graduation.
How AI Creates New Channels for Faculty-Student Engagement
AI technologies are revolutionizing faculty-student engagement by providing new and innovative channels for interaction in several ways. AI-powered virtual simulations allow students to practice clinical skills in a risk-free environment. Faculty can monitor student progress and provide real-time feedback, enhancing the learning experience. The technology also allows faculty to provide students with a standardized scenario while maintaining the flexibility for individualized decision-making and processing. These capabilities are made possible by adaptive learning platforms, which use AI to personalize learning paths based on individual student needs. That personalization, and the ability to share real-time feedback, helps foster a more supportive learning environment uniquely suited to each individual.
Students can also learn through AI-driven communication tools. Chatbots and virtual assistants can facilitate communication between students and faculty, answering common questions and providing resources in real-time, including after hours when students may be studying or working through assignments. This allows faculty to focus on more complex student needs rather than spending extra time on simple questions.
Finally, AI can analyze large volumes of data to provide insights into student performance and engagement. Faculty can see which questions come up a lot, or which lessons seem to be the most confusing, and use that information to tailor their teaching strategies and address specific student needs. This can inform faculty to ensure students get what they need to learn to pass the NCLEX, as well as be ready for the realities of practice.
Early Lessons from Schools Leveraging AI
Early adopters of AI have seen many ways the technology can benefit nursing education through increased efficacy, more accessible and more personal learning, increased student engagement and motivation, as well as augmenting faculty needs. The schools taking the right approach to AI implementation are:
- Starting with pilot programs to test AI tools and gather feedback before scaling
- Providing faculty training focused on practical use and instructional balance
- Balancing technology with human interaction to preserve meaningful faculty–student connections
- Addressing data privacy and bias with clear policies and ethical guidelines
These steps ensure that AI is benefiting students, faculty, and nursing programs overall, avoiding hasty implementations, ethical traps, and overuse of AI. By taking an iterative approach and establishing clear guidelines around how AI should be used, institutions can ensure the technology is a net positive.
Impact on NCLEX Outcomes
The integration of AI in nursing education has the potential to significantly impact NCLEX outcomes, an alluring possibility amid variable NCLEX scores nationwide. AI-driven adaptive learning platforms can identify areas where students need improvement and provide targeted resources. This personalized approach enhances student readiness for the NCLEX by tailoring their education to their personal needs and roadblocks. AI-powered simulations and case studies help students gain more experience and fully develop the clinical judgment and decision-making skills needed to pass the NCLEX.
Additionally, AI’s ability to continuously analyze student performance data, and provide relevant insights to instructors, is crucial in identifying those at risk of failing the NCLEX while there is still time to correct course. Early intervention and support, along with tailored, personalized resources, can enhance their chances of success.
The integration of AI in nursing education offers numerous benefits, from personalized learning experiences to improved faculty-student engagement. By leveraging comprehensive data and embracing innovative technologies, nursing schools can enhance the educational experience and improve NCLEX outcomes. However, successful implementation requires careful planning, faculty training, and ethical considerations. As more schools adopt AI, ongoing evaluation and adaptation will be essential to maximize its potential and ensure the best possible outcomes for nursing students.
About Dr. Beth Cusatis Phillips
Dr. Beth Cusatis Phillips is the Strategic Nursing Advisor and Senior Manager of Content Strategy at Ascend Learning and for its brand ATI. She is Faculty Emeritus at Duke University School of Nursing, where she served for 16 years as Associate Professor and Director of the Institute for Educational Excellence. Beth has taught across ABSN, MSN, and biomedical science programs and previously led ADN/LPN programs at Vance Granville Community College. Her clinical experience spans nearly two decades in med-surg and surgical/trauma ICU roles at UNC Hospitals and East Carolina University Health.
