Effects of AI on Nursing Education: Protocol for a Systematic Review and Meta-Analysis

Area of Science:

• Nursing Education
• Artificial Intelligence
• Educational Technology

Background:

• Artificial intelligence (AI) shows promise in nursing education, but its effects on key learning outcomes are not well-defined.
• Specific impacts on knowledge acquisition, practical skills, student satisfaction, competence, and confidence require further characterization.

Purpose of the Study:

• To systematically assess the effects of AI on nursing students' educational experiences and outcomes.
• To quantify the impact of AI-assisted teaching methodologies compared to traditional approaches.

Main Methods:

• Adherence to PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) guidelines.
• Systematic literature searches across six databases (PubMed, Web of Science, Embase, CINAHL, MEDLINE, Cochrane Library) up to February 2026.
• Inclusion of randomized controlled trials and quasi-experimental studies focusing on nursing students, comparing AI interventions with traditional methods; outcomes include knowledge, practical ability, satisfaction, competence, and confidence.

Main Results:

• Literature retrieval concluded in February 2026; abstract screening and full-text evaluation are in progress.
• Data extraction, risk-of-bias assessment (using Cochrane and ROBINS-I tools), and meta-analysis are scheduled from January 2026.
• Manuscript submission is planned for June 2026.

Conclusions:

• This meta-analysis will systematically quantify the effects of AI-assisted teaching on nursing students' knowledge, practical skills, satisfaction, competence, and confidence.
• The synthesized evidence aims to support the standardized implementation of AI in nursing education and inform future research directions.