Page 60 - KNJIGA SAŽETAKA

INOVACIJE I IZAZOVI U OBRAZOVANJU I SESTRINSKOJ SKRBI - KNJIGA SAŽETAKA

Artificial Intelligence in Education and Nursing –

Hidden Potential of Interdisciplinary Cooperation

Artificial intelligence (AI) has great potential to transform education and the nursing profession.
After a brief insight into the technological principles of AI, concrete examples of the use of AI
in these sectors are presented, emphasizing the importance of interdisciplinary cooperation in
solving problems. Different types of AI are explained, including machine learning, deep
learning, and natural language processing. Tools and techniques used to develop AI systems
are discussed, emphasizing the importance of data in AI, including collection, preparation, and
ethical aspects. The paper will present the results of a test that will be conducted among the
teachers of the Vinogradska Nursing School to determine their familiarity with the possibilities
of using AI tools in teaching and education.

Some examples of the use of AI in education and nursing: Personalization of learning - AI can
be used to adapt lesson plans to students' individual needs by analyzing data on academic
progress, learning styles, and interests; Task automation - AI can automate repetitive tasks such
as grading tests and written papers, freeing teachers' time to support students one-on-one;
Intelligent tutors - AI-based tutors can provide students personalized feedback and real-time
support and encourage interactive learning through simulations and games; Decision support -
AI can analyze patient data from various sources, helping nurses quickly and accurately identify
potential problems and make informed decisions about patient care; Patient monitoring - AI can
be used to monitor patients' vital signs in real-time and send alerts to nurses when they deviate
from expected parameters; Virtual Assistants - AI-based assistants can provide nurses with
support in administrative tasks, freeing up their time to focus on nursing patient care.

In addition, the paper outlines a case study demonstrating how AI was used to analyze patient
data collected from a hospital system over several years to predict rehospitalization. The
emphasis is on interdisciplinary teamwork and the contribution of people's domain knowledge
to data modeling through AI algorithms.

AI has significant potential to improve education and nursing. However, it is essential that AI
systems are developed and used ethically and responsibly, with transparency, data privacy
protection, and inclusion. The future of AI in these sectors offers exciting opportunities to
transform these professions and improve student and patient experiences.

Key words: Artificial Intelligence (AI), education, nursing, interdisciplinary work

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