Trial reportBMC medical education2025
Development and effects of a chatbot education program for self-directed learning in nursing students.
Trial report in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Nurse educators' experiences and perceptions using generative artificial intelligence: a systematic review.BMC medical education · 2026Pooled it
- The Effectiveness of Artificial Intelligence in Undergraduate Health Professions Education: Systematic Review and Meta-Analysis of Randomized Controlled Trials.JMIR medical education · 2026Pooled it
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Effect of using artificial intelligence chatbot about electronic fetal monitoring on maternity nursing students' performance.BMC medical education · 2025Trial
- AI-Based Learning Experiences of Nursing Students: A Qualitative Study.Journal of evaluation in clinical practice · 2026Article
- Enhancing perceived clinical competence of nursing students in the AI era: the role of AI acceptance and self-directed learning.BMC medical education · 2026Article
- Evolution of Chatbots as an Educational and Supportive Digital Intervention for Family Caregivers of People With Dementia: Protocol for a Systematic Integrative Review.JMIR research protocols · 2026Article
- Comparative performance of artificial intelligence models in intensive care nursing questions: an evaluation of ChatGPT, DeepSeek, and Google Gemini.BMC nursing · 2026Article
- The effect of artificial intelligence-supported applications on critical thinking motivation and clinical decision making in nursing students: path analysis.BMC medical education · 2026Article
- Educational Applications of AI-Based Chatbots in Nursing: A Scoping Review.Nursing reports (Pavia, Italy) · 2026Review
- Effects of Artificial Intelligence-Supported Education on Critical Thinking, Problem-Solving, Clinical Reasoning, and Decision-Making in Health Science Education: A Systematic Review of Interventional Studies.Advances in medical education and practice · 2026Review
- Advancing Nursing Through Artificial Intelligence: A Systematic Literature Review of Current Evidence.Cureus · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundCritical care nurses require adequate thinking skills to assess the condition of acutely-ill patients, make decisions, and implement appropriate interventions. Specifically, precise knowledge and swift response to mechanical ventilation-related nursing are of utmost importance. Educational needs of clinical nurses revealed a high demand for education in mechanical ventilation nursing. This study aims to develop a chatbot educational program for self-directed learning to enhance nursing students' skills and assess its impact on clinical reasoning competency, mechanical ventilation nursing-related knowledge, self-confidence, and education satisfaction.
methodsThis study employed a randomized controlled trial with a pretest-posttest parallel group design. The participants included fourth-year nursing students from the Department of Nursing at a university in the "G" province in South Korea, with 31 participants in the experimental group and 29 in the control group. The experimental group had access to the Uniform Resource Locator or URL of the mechanical ventilation nursing chatbot educational program and video lectures, while the control group received only the video lectures.
resultsThe experimental group demonstrated statistically significantly higher clinical reasoning competency (t=-5.00, p <.001), self-confidence (t=-2.62, p =.011), and satisfaction in education (t=-3.51, p <.001) compared to the control group. However, there was no statistically significant difference in knowledge (t=-0.09, p =.926).
conclusionsThe chatbot educational program could be an effective educational method to positively influence nursing students' clinical reasoning competency, self-confidence, and education satisfaction. It can enhance self-directed learning among nursing students and effectively improve nursing competency. CLINICAL TRIAL NUMBER: Not applicable.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.