Readiness of AI (Artificial Intelligence) strategies Used in Nursing Education among Undergraduate Nursing Students “A Cross Sectional Descriptive Survey”

Abstract

The aim of this quantitative cross sectional survey is to describe the frequencies of readiness of AI (Artificial Intelligence) in nursing education among undergraduate nursing students. Methodology of this research included, the design of this research is cross sectional descriptive study, sample size was N=50 undergraduate nursing students of first year first semester. Sampling technique was simple random sampling and setting was a Nursing College in private University. The data was analyzing by SPSS AMOS-23 software. The TAM (Technology Acceptance Model) was used to collect the data basically this tool was adopted from a Pakistani research article the validity and reliability of the tool has been mentioned in methodology section in chapter 3. A total of 50 undergraduate nursing students participated in the study examining readiness for the use of artificial intelligence (AI) strategies in nursing education. The demographic findings showed an equal distribution of male and female participants, with 25 (50%) students in each group. Regarding age, the majority of participants, 47 (94%), were aged 21–23 years, while 3 (6%) were aged 24–26 years. Regarding the perceived usefulness of AI strategies in nursing education, all participants reported negative responses to the statement that AI strategies improved their learning outcomes, with 26 (52%) strongly disagreeing and 24 (48%) disagreeing. For the statement that AI tools could help students understand complex nursing concepts, 18 (36%) strongly disagreed, 11 (22%) disagreed, 11 (22%) remained neutral, and 10 (20%) strongly agreed. Similarly, 42 (84%) participants disagreed or strongly disagreed that AI-based learning resources could improve their clinical decision-making skills, while 4 (8%) were neutral and 4 (8%) strongly agreed. Regarding whether AI strategies could make nursing studies more productive, 17 (34%) strongly disagreed, 12 (24%) disagreed, 11 (22%) were neutral, and 10 (20%) strongly agreed. All participants (100%) disagreed with the statement that AI tools could help them prepare more effectively for nursing examinations.

The study revealed low readiness among undergraduate nursing students towards the use of AI strategies in nursing education. Most participants reported negative perceptions regarding AI usefulness, ease of use and integration into academic activities. The findings highlight the need for structured AI literacy training, practical guidance and education on the responsible use of AI. Further research with larger sample is recommended to explore student’s readiness for AI integration in nursing education.