Pamela Fonju
William Paterson University of New Jersey, United States
Abstract Title: Transforming the Pedagogy: A Strategic Integration of Artificial Intelligence in Nursing Education
Biography: Pamela Fonju, DNP, MSN, APN-BC, is a board-certified Family Nurse Practitioner and a distinguished member of the nursing faculty with a career spanning over thirty (30) years. She began her distinguished career with the New York City Health + Hospitals Corporation, where she served in diverse roles across the Emergency Department, ambulatory surgery, and the pediatric surgery clinic. Following the completion of her doctoral studies, Dr. Fonju served as the Regional Administrator for the Child Health Program—a collaborative, nurse-led initiative focusing on the physical, mental, and behavioral health needs of children in foster care. A passionate advocate for health education, she believes it serves as the foundation for illness prevention and is committed to empowering her patients through informed wellness. Dr. Fonju earned her Bachelor’s degree from the City University of New York, her Master’s from the University of Medicine and Dentistry/Rutgers, and her Doctorate from William Paterson University of New Jersey. With extensive experience in both higher education and clinical instruction, she has published numerous articles and presented at national and international conferences on nursing education, clinical practice, and chronic disease management.
Research Interest: Title: Transforming the Pedagogy: A Strategic Integration of Artificial Intelligence in Nursing Education Background: The rapid advancement of artificial intelligence (AI) is redefining healthcare delivery and creating an urgent mandate for nursing curriculum reform. As traditional nursing education continues to face challenges such as faculty shortages, limited sites for clinical placements, and the need for more personalized student support - AI is emerging as a transformative solution to bridge these gaps by enhancing clinical preparedness and optimizing educational workflows. Objective: This presentation aims to evaluate the current and emerging roles of AI in nursing education. The presentation will explore AI’s capacity to personalize learning, enhance simulation fidelity, and alleviate administrative burdens for faculty. Methods/Approach: An integrative review of recent implementations including virtual reality (VR) simulations, adaptive learning platforms, and AI-driven skill assessments was conducted to identify best practices for academic integration. Results: The data suggests that AI-powered tools impact outcomes in two primary domains: Student learning and faculty efficiency. Conclusion: While AI promises to revolutionize nursing education, its implementation must be guided by ethical frameworks that address data privacy, algorithmic bias, and the preservation of human interactions in nursing care. Keywords: Pedagogy, Adaptive learning, Artificial Intelligence, Simulation, Nursing Education, Faculty Efficiency.