Nurse Educators' Concerns of GenAI in Education
Scoping Review of Technical Factors
Bibliographic Data
| ID | 21456384 |
|---|---|
| Authors | Ragi George (0009-0007-4882-2547, Azusa Pacific University), Sharon K Titu (0000-0002-5148-9366), Sharon K Titus, Denise R Gehring (0000-0003-1178-4712) |
| Year | 2025 |
| Volume | 64 |
| Issue | 8 |
| Pages | 503-510 |
| Publication date | 2025-08-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Nursing Education (JOURNAL) |
| Journal identifiers | ISSN: 0148-4834 • E-ISSN: 1938-2421 |
| Publisher | SLACK, Inc (PUBLISHER) |
| DOI | 10.3928/01484834-20250519-02 |
| PMID | 40801509 |
| OpenAlex | W4413110897 |
| Language | EN |
| References cited | 33 |
BACKGROUND: Generative artificial intelligence (GenAI) has greatly affected higher education since its release in 2022. Academic nurse educators are being called to implement GenAI; however, some have concerns. This article sought to identify and describe the existing evidence on nurse educators' perceived concerns regarding the use of GenAI in nurse education. METHOD: This scoping review was conducted using the Joanna Briggs Institute Methodology and reported using PRISMA-ScR guidelines; a total of736 articles from eight databases were reviewed. Thirty articles met the inclusion criteria. Data were extracted using an author-created Data Extraction Instrument, and thematic analysis was performed. RESULTS: Included are 25 sources on the theme of technical factors and subthemes of data inaccuracy, data bias, access inequity, privacy and confidentiality breach, lack of policies and guidelines, and faculty workload. CONCLUSION: As nursing education continues to become more technology-driven, educators need to receive professional development training on its use in nursing programs
Confidentiality · Data extraction · Inclusion (mineral) · Medical education · MEDLINE · Nurse education · Nurse educator · Political science · Professional development · Qualitative research · Registered nurse · Sociology · Thematic analysis · Workload · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Computer Science · Medicine · Nursing · Psychology · Simulation-Based Education in Healthcare
Scoping reviews
Recommendations for the extraction, analysis, and presentation of results in scoping reviews
The PRISMA 2020 statement
Are Nursing Faculty Future-Ready? The Effects of Emerging Technologies on Nursing Education
The ChatGPT Effect
The Use of AI Powered ChatGPT for Nursing Education
Scoping studies
| Highly cited | No |
|---|