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Artificial intelligence tools utilized in nursing education: Incidence and associated factors.
Jallad, Samar Thabet; Alsaqer, Khitam; Albadareen, Baker Ishaq; Al-Maghaireh, Duaa.
Afiliación
  • Jallad ST; Department of Nursing, Faculty of Health Professions, Al-Quds University, Jerusalem, Palestine. Electronic address: sgalad@staff.alquds.edu.
  • Alsaqer K; Faculty of Nursing, Zarqa University, Zarqa, Jordan. Electronic address: majd61_2009@yahoo.com.
  • Albadareen BI; Department of Applied mathematics, Faculty of Applied Science, Palestine Technical University - Kadoorie, Tulkarem, Palestine. Electronic address: b.badarin@ptuk.edu.ps.
  • Al-Maghaireh D; Department of Nursing Sciences, Faculty of Nursing, Irbid National University, Irbid, Jordan. Electronic address: dfm_2013@yahoo.com.
Nurse Educ Today ; 142: 106355, 2024 11.
Article en En | MEDLINE | ID: mdl-39163690
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 regularly (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 information 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 multimodal technological factors that should be taken into consideration while creating AI tools across several domains for universities and developers.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estudiantes de Enfermería / Inteligencia Artificial / Bachillerato en Enfermería Límite: Adult / Female / Humans / Male Idioma: En Revista: Nurse Educ Today Asunto de la revista: EDUCACAO / ENFERMAGEM Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estudiantes de Enfermería / Inteligencia Artificial / Bachillerato en Enfermería Límite: Adult / Female / Humans / Male Idioma: En Revista: Nurse Educ Today Asunto de la revista: EDUCACAO / ENFERMAGEM Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido