Bridging the Generational Gap in Nursing Education with Generative AI
I have a unique experience of the world when it comes to technology. I grew up in a time when music was enjoyed on 8-tracks, vinyl, cassette tapes, and CDs. Making mixtapes involved tuning into your favorite radio station and being quick with the buttons to record your favorite songs.
This was also a time when you would argue with your siblings to get off the phone so you could connect to the internet. Hearing that iconic door openening on AOL instant messenger, telling you that your best friend was online. The only gaming experience many of us had was trying not to die of dysentery on the Oregon Trail.
Within my journey with technology, I've observed a stark contrast: the majority of people I teach today have had an iPhone in their hands since they were toddlers. They've always had access to iPads and the internet, and Googling everything is second nature.
I think this perspective is important because, in part, I’m a Xennial. I understand both life experiences of the introduction of the internet and computers to the world, a life without them, and now a life experience where I have technology in my face everyday. This places me in a unique position as an educator, fitting right in the middle of the students we teach today and the educators who are teaching them.
Understanding the Generational Divide in Nursing Education
The majority of current nurse educators belong to the Baby Boomer generation, where technology was not as integral to everyday life as it is today. According to the National League of Nursing (2019), a significant percentage of nursing faculty are from the Baby Boomer (ages 55–73) and Generation X (ages 40–54) cohorts. Meanwhile, today's nursing students primarily belong to Generation Y (Millennials) and Generation Z, who have grown up with technology and are inherently more comfortable with digital tools.
This generational gap in technology familiarity can lead to resistance among educators when it comes to adopting new, complex digital tools like Generative AI. A survey revealed that while 69% of Baby Boomers show interest in new technologies, a higher percentage of Gen Zers (88%) and Millennials (89%) are more eager to embrace them. These statistics highlight the need for solutions that can bridge this gap and make technological tools accessible and effective for both educators and students.
Why does this matter?
Most nursing education still relies heavily on antiquated ideologies, such as Benner's competency model. While Benner’s work on nursing competency was groundbreaking in the 1980s, it did not account for the advances in technology we see today.
The brains of this new generation have developed differently, shaped by constant interaction with digital devices and instant access to information. As a result, technology must play a key role in their education. Modern nursing students benefit greatly from delivery systems and educational modalities that integrate technology, such as gamification and interactive simulations. These methods provide the necessary dopamine hits that reinforce good learning habits, a stark contrast to the traditional teaching methods still prevalent in many nursing programs.
So the question then remains: what can be done in nursing education to help promote the use of Generative AI in improving adoption amongst educators while meeting the needs of students?
The Role of Generative AI in Nursing Education
Generative AI presents an exciting opportunity to address the challenges posed by this generational gap. In my own practice, I use a three tiered approach to nearly everything (mostly because it forces me to find the most impactful, high yield options or context statements).
When it comes to GenAI, I’ve found that these three solutions share the greatest overlap between both educators and students:
1. Personalized Content Generation
Generative AI can create personalized learning experiences by tailoring educational content to individual learning styles and needs. For example, AI-driven training videos can be assigned for pre-class learning, significantly reducing in-person class time by up to 20%. In my experience, using generative AI for video production has decreased production time by 89%, demonstrating its efficiency and effectiveness in educational settings.
2. Data-Driven Insights for Gap Analysis
AI can analyze educational data to identify gaps in students' knowledge and performance. By pinpointing areas where students need more support, educators can adjust their teaching strategies to be more effective. One way to use this is to employ GenAI to assess data, to identify p-values and point biserials that may indicate that question integrity is compromised. One can then modify, and then redeploy the assessment information to users, and see if the adjustments were correct. This data-driven approach ensures that students are better prepared for their roles, leading to higher retention rates and better educational outcomes.
3. Enhancing Quality Assurance and Efficiency
Generative AI can automate repetitive tasks such as grading, scheduling, and managing student data. This automation frees up educators to focus more on teaching and engaging with students - the same mantra we tell practicing nurses with the implementation of AI in the healthcare setting. That is, free up your time from the EHR and technology and spend more time with patients. By streamlining administrative tasks, AI contributes to more efficient and cost-effective educational processes.
Bridging the Generational Gap with AI
As we move further into the digital age, the importance of technology in education cannot be overstated. The COVID-19 pandemic accelerated the adoption of digital learning tools, but disparities remain, particularly regarding access and quality across different socioeconomic groups. Generative AI has the potential to bridge these gaps by providing equitable and effective technological solutions in nursing education.
I do think that this is important to note…
While generative AI is a groundbreaking tool with the potential to revolutionize nursing education, it's important to remember that the human element cannot be entirely replaced. GenAI can handle mundane, repetitive tasks with minimal oversight, significantly increasing efficiency. However, when it comes to high-stakes information—such as clinical decision-making, patient care protocols, or nuanced educational content—human review is irreplacable. AI, particularly large language models, can sometimes produce hallucinations or misinterpret data, leading to inaccuracies. Because of this potential complication, we must always review critical information meticulously and validate it.
Implementing these AI-driven solutions can help educators from all generations to embrace the changes that technology brings. Leveraging Generative AI can create a more connected, efficient, and personalized learning environment that meets the needs of today's students and prepares them for the challenges of tomorrow.
References:
McCarthy, J. (2022, April 12). Better technology produced better learning outcomes during the pandemic. Gallup. https://news.gallup.com/opinion/gallup/388502/better-technology-produced-better-learning-outcomes-during-pandemic.aspx
Yu, Z., Sun, Y., Li, P., & Wu, X. (2023). Overall perception of Gen AI and other AI tools across different age ranges. ResearchGate. https://www.researchgate.net/figure/Overall-perception-of-Gen-AI-and-other-AI-tools-across-different-age-ranges-Gen-AI_fig1_380750836
U.S. National Library of Medicine. (2012). The introduction of new technologies and decision-making for neonatal screening programs: Experiences in the United States and Europe. National Center for Biotechnology Information (NCBI). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3370300/
