Artificial intelligence tools utilized in nursing education: Incidence and associated factors
| dc.contributor.author | Samar Thabet Jallad | |
| dc.contributor.author | Khitam Alsaqer | |
| dc.contributor.author | Baker Ishaq Albadareen | |
| dc.contributor.author | Duaa Al-maghaireh | |
| dc.date.accessioned | 2026-01-31T12:24:28Z | |
| dc.date.available | 2026-01-31T12:24:28Z | |
| dc.date.issued | 2024-11-01 | |
| dc.description.abstract | Background: Artificial intelligence technology is among the most significant advancements that provide students with effective learning opportunities in this digital era. Therefore, the National League for Nursing states that it is necessary to reframe the nursing education process. Objective: This study aimed to determine the factors that affect the usefulness and sustainability of artificial intelligence tools used in nursing education. Design: A descriptive cross-sectional study was conducted among. Three models, including the Technological Acceptance Model (TAM), the Information System Success Model (ISSM), and the Online Learning Self-Efficacy (OLSE), were used. Participant: All of fourth- year undergraduate nursing students who were enrolled in nursing department regu larly (N = 420), and who respond (n = 204). Setting: In the nursing department of the health professions faculty at AL-Quds University, in Palestine. Results: Among the 204 students who responded, 9.80 % employed simulation, 5.40 % utilized virtual reality, 19.10 % used Chat GPT, 42.20 % used mobile applications, and 23.50 % utilized PowerPoint AI as part of their learning process. The mean and standard deviation (SD) were computed for key parameters related to the in formation system success model (AI) (ISSM) (M = 4.52, SD = 1.17). Technology Acceptance Model (TAM) (M = 4.61, SD = 1.16). Online Learning Self-Efficacy (OLSE) (M = 4.55, SD = 1.28). Conclusion: There is a need to adapt teaching strategies and integrate AI tools as useful learning tools, which have become essential for students to complete their learning activities through enhancing knowledge of the multi modal technological factors that should be taken into consideration while creating AI tools across several do mains for universities and developers. Keywords: Artificial intelligence (AI); Nursing education; Nursing students; TAM model | |
| dc.identifier.citation | Jallad, S. T., Alsaqer, K., Albadareen, B. I., & Al-Maghaireh, D. (2024). Artificial intelligence tools utilized in nursing education: Incidence and associated factors. Nurse education today, 142, 106355. | |
| dc.identifier.uri | https://dspace.alquds.edu/handle/20.500.12213/10500 | |
| dc.language.iso | en_US | |
| dc.publisher | Churchill Livingstone | |
| dc.title | Artificial intelligence tools utilized in nursing education: Incidence and associated factors | |
| dc.type | Article |