Aug 2026· Bandırma Onyedi Eylül Üniversitesi Sağlık Bilimleri ve Araştırmaları Dergisi· 0 citations· 45 references
TL;DR
A meta-analysis examined the effectiveness of artificial intelligence (AI)-based educational interventions on learning outcomes in nursing students and found that AI-based interventions significantly improved knowledge acquisition.
Abstract
Aim: This meta-analysis examined the effectiveness of artificial intelligence (AI)-based educational interventions on learning outcomes in nursing students.Material and Method: A systematic search of PubMed, Scopus, CINAHL, and Web of Science identified studies published between January 2021 and May 2025. Following PRISMA guidelines, 11 studies with 1,539 students were included, comprising randomized controlled trials and quasi-experimental designs. Outcomes assessed were knowledge, clinical reasoning, satisfaction, clinical performance, attitude, and self-efficacy. Risk of bias was evaluated with the RoB 2 tool, and random-effects models were used for meta-analysis.Results: AI-based interventions significantly improved knowledge acquisition (MD = 4.47, 95% CI [2.60, 6.34], p
The findings showed that AI can enhance clinical teaching, improve nursing students' self-efficacy, and support teaching and learning and that the use of AI in nursing education is instrumental in improving the acquisition of clinical skills and teaching and learning.
S. Khunou, Carine Prinsloo· Indonesian Contemporary Nurs...· 0 citations
Nursing students’ experiences with generative AI are shaped by both the opportunities and challenges associated with its use in learning, highlighting the need for nursing educators to strengthen students’ AI literacy, critical thinking, and ethical awareness.
Shanshan Du, Sha Wang, Feng-ming Yan et al.· Frontiers in Medicine· 0 citations
OBJECTIVES
This systematic review aimed to both determine whether educational interventions improve medical students' ability and/or confidence in Bad News Communication (BNC), as well as assess the relative efficacy of instructional formats.
METHODS
Performed according to the PRISMA guidelines, four databases were searched for articles describing education-based interventions to improve medical student's BNC ability and/or confidence, published in English between 2001 and 2024. Data on students' self-reported or observer-assessed level of competence/ability in BNC (primary outcome), and students' self-assessed confidence in BNC skills (secondary outcomes), were analysed. Meta regression explained the influence of several categorical moderators on heterogeneity in relation to intervention effects on competence/ability.
RESULTS
27 studies met the criteria for inclusion in the systematic review and 17 studies for the meta-analysis. Interventions described in controlled studies were associated with a moderate and significant increase in BNC ability (13 data sets; standardized mean difference [SMD] = 1.09, 95% CI = 0.52 - 1.66). Interventions detailed in pre-post design studies were associated with a significant increase in BNC ability (20 data sets; SMD = 0.92, 95% CI = 0.52 - 1.32), and student confidence/comfort in their BNC skills (12 data sets; SMD = 1.16, 95% CI = 0.57 - 1.75). Subgroup analysis demonstrated better skills/competence outcomes in studies that included simulation-based training (SBT).
CONCLUSIONS
Educational interventions improve the BNC ability and confidence of medical students. Interventions should include an SBT element as this leads to greater improvements in BNC ability. Further research is needed to determine to what extent these interventions translate to positive patient outcomes.
PRACTICE IMPLICATIONS
Diverse educational programme, especially those including simulation-based training, are effective in improving BNC skills, although the longetivity of these improvements is at present unclear. Therefore, we recommend that refresher courses or practice opportunities should be scheduled throughout students' medical education to ensure retention of BNC skills.
Alanna McMullin, C. O’Tuathaigh, E. Montagna· Patient Education and Counse...· 0 citations
Nursing academics appear to adopt AI selectively, prioritising preservation of core professional values while embracing applications perceived to enhance, rather than replace, educational practice, providing evidence for nursing education programs globally regarding faculty development, institutional policy frameworks, and curriculum design strategies integrating technological advancement whilst maintaining person-centred values.
Natasha Hawkins, Anthea Fagan, Yumiko Coffey et al.· Journal of Advanced Nursing· 0 citations
AIM
To evaluate the effectiveness of scenario-based simulation training in adult nursing education on nursing students' cognitive, affective and psychomotor domains.
DESIGN
Systematic review and meta-analysis.
BACKGROUND
The nursing curriculum consists of various courses, including adult, maternal, pediatric, psychiatric and community nursing. However, previous studies have often aggregated results across nursing courses, limiting the ability to identify subject-specific effects.
METHODS
The systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. An extensive search of domestic and international databases was conducted to identify RCTs that evaluated scenario-based simulation in adult nursing education. Effect sizes were calculated using standardized mean differences (SMDs) and 95% confidence intervals (CIs) based on a random-effects model.
RESULTS
The systematic review included 19 studies, while the meta-analysis included 14 studies. Scenario-based simulation showed a moderate effect in the cognitive domain (SMD = 0.79; 95% CI: 0.46-1.13) and a large effect in the affective domain (SMD = 0.98; 95% CI: 0.39-1.58). Within the cognitive domain, knowledge demonstrated a moderate effect size immediately following the intervention, but the effect was not maintained at subsequent follow-up assessments. In contrast, outcomes within the affective domain, such as confidence and self-efficacy, demonstrated sustained effects over time.
CONCLUSION
The results confirmed that scenario-based simulation training for nursing students produces short-term effects in the cognitive domain and sustained effects in the affective domain.
Hyun Ji Kim, Eun Kyung Lee, Eunju Mun· Nurse Education in Practice· 0 citations
Purpose: This study aimed to elucidate the concept of generative artificial intelligence (AI)-based learning support in nursing education using Walker and Avant’s concept analysis method.Methods: A comprehensive review of scholarly articles published between 2020 and 2025 from RISS (Research Information Sharing Service), DBpia, KISS (Korean studies Information Service System), PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Scopus was conducted. Following Walker and Avant’s framework, the concept’s attributes, model cases, antecedents, consequences, and empirical referents were identified.Results: Generative AI-based learning support was defined as “a reflective teaching-learning process in which learners reconstruct knowledge and refine clinical reasoning competencies through dynamic interaction with AI, reflecting individual needs and clinical contexts”. Five defining attributes were identified: adaptive personalization, contextual presence, cognitive facilitation, conversational interactivity, and reflective instrumentality. Antecedents comprised technological infrastructure and guidelines, learners’ AI and information literacy, ethical awareness and responsibility, and instructors’ educational design competency and willingness to adopt generative AI. Consequences included strengthened critical thinking and clinical reasoning, improved learning outcomes and self-directed learning, enhanced clinical practice readiness, internalized digital literacy and ethical attitudes, and the potential enhancement of nursing care quality and patient safety.Conclusion: This analysis provides a theoretical foundation for generative AI-based learning support in nursing education. It distinguishes this concept from conventional technological assistance by emphasizing cognitive facilitation and reflective learning. The findings can inform curriculum development, instructor training, and future research, with the potential to support nursing care quality and patient safety through clinical reasoning and responsible AI use.
Hyo Hoon Ku· The Journal of Korean Academ...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
