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TRUVACE RECORD VERSION
record: TRV-2026-1910
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-19T18:12:29.652436Z
status: published
lens: g_space
sector: education
headline: Artificial Intelligence Supported Teaching Approaches in Nursing Education: A Scoping Review
dek: Background The increasing integration of artificial intelligence (AI) has generated growing interest in its use to support teaching and learning in nursing education. This scoping review aimed to map the existing literature on AI-supported teaching approaches in nursing education, examine how learning outcome domains are addressed, and identify gaps in the current evidence base. Method A scoping review followed the Joanna Briggs Institute Framework and PRISMA-ScR (Preferred Reporting Items for Scoping Reviews) g…
gain_title: Across 38 reviewed studies, AI-supported teaching approaches appear to support knowledge and skill development among nursing students.
problem_title: (none)
trace_subject: (none)
gain_reading: Across 38 reviewed studies, AI-supported teaching approaches appear to support knowledge and skill development among nursing students.
gain_evidence: AI-supported teaching approaches show promise in nursing education by supporting knowledge and skill development
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers mapped the literature on AI-supported teaching in nursing education using the Joanna Briggs Institute framework and PRISMA-ScR guidelines. They searched eight databases and included thirty-eight studies, grouping the findings into three themes.

The review suggests AI tools may help nursing students build knowledge and skills, which matters for educators weighing whether to adopt them. The authors say stronger study designs and clear pedagogical frameworks are still needed before sustainable practice can be recommended.
limitation: The authors state that further research using robust designs and clear pedagogical frameworks is needed, which indicates the current evidence is not strong enough to guide sustainable practice.
tag: Evidence-backed gain
key_points: The review followed the Joanna Briggs Institute Framework and PRISMA-ScR reporting guidelines. | Eight databases were searched, including MEDLINE, Scopus, ERIC and PubMed. | Thirty-eight studies were included in the review. | Three themes emerged: AI tools and applications, learning outcome domains and assessment approaches, and current limitations and future directions.
rundown: The review aimed to map existing literature on AI-supported teaching approaches in nursing education and to examine how different learning outcome domains are addressed. It also sought to identify gaps in the current evidence base.

The search covered ProQuest Central, Scopus, ScienceDirect, Web of Science, MEDLINE, Cochrane Library, ERIC and PubMed. This breadth spans both health and education literature.

Its conclusion is cautious: the approaches show promise, but the authors call for robust designs and clear pedagogical frameworks to inform sustainable educational practice. The abstract gives no specific effect sizes or named tools.
sources:
- peer_reviewed | Journal of Nursing Education | https://doi.org/10.3928/01484834-20260827-04 | 2026-10-15
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