Published on July 2025 | Artificial Intelligence, Higher Education, Nursing Students

Level of student attitudes towards artificial intelligence: Perspectives from nursing students

Artificial intelligence in the healthcare field, especially in the academic community, is making its name and relevance. Hence, knowing how to navigate and deal with Artificial intelligence in the learning process as well as in the healthcare service is a must to keep abreast with the trends. This study aimed to understand nursing students' attitudes toward artificial intelligence from a tertiary educational institution in Olongapo City, Philippines. The investigators employed a descriptive-correlational research design with the help of an online survey as the primary data-gathering tool. Three hundred twenty-four nursing students, via purposive sampling, partook in the said online survey from September to October 2023. The study also used a standardized instrument to gather data on the attitude of student nurses toward Artificial intelligence. For the statistical analysis, the study employed both descriptive (frequency, percentage, and mean) and inferential statistics (Mann-Whitney U, Kruskal-Wallis H, Spearman rho) with the help of statistical software SPSS 23. Results from the demographics of the students mainly included females, first year in level, less than 20 years of age, with smartphones, and have a GPA between 85-89%, and have already used Artificial intelligence in their study or learning. At the same time, the respondents moderately agree with the survey's cognitive, affective, and behavioral aspects regarding the student nurses' attitudes toward Artificial intelligence. Significant differences also occurred among student nurses when the investigators grouped them according to the use of Artificial intelligence in study/ learning, year level, age bracket, and GPA. Finally, moderate to strong relationships occurred between the survey's cognitive, affective, and behavioral aspects. The study then provided pertinent recommendations at the end of the study, which focused on training, faculty development, and student advocacy towards Artificial intelligence learning and adoption.