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Systematic review of AI chatbots in nursing education finds limited evidence for learning gains

Systematic review of AI chatbots in nursing education finds limited evidence for learning gains
Photo by Julia Taubitz / Unsplash
Key Takeaway
Consider the limited and inconclusive evidence when evaluating AI chatbots for nursing education learning gains.

This is a systematic review examining the use of AI chatbots in nursing education. The review synthesized findings from 25 studies with individual sample sizes ranging from 16 to 457 learners. The authors found that evidence for cognitive learning gains, such as learning achievement and critical thinking, was most dominant, though several studies reported no statistically significant improvement in knowledge acquisition or clinical reasoning competency. Evidence for affective and behavioral learning gains, such as improvements in confidence and satisfaction, was limited.

The review noted that reported digital affordances included assistance provision, personalization, human-like conversing, distilling information, and fostering familiarity. However, facilitation, enriching information, context identification, and ensuring privacy lacked empirical support. Key limitations acknowledged by the authors include a geographical distribution mainly in Asia, short study durations (follow-up from few hours to 3 months), and small sample sizes.

The authors conclude that the overall evidence remains inconclusive. Practice relevance was not reported, and the review does not establish causal effects of AI chatbots on learning outcomes.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedApr 2026
View Original Abstract ↓
BackgroundDigital affordances refer to the possibilities provided by digital environments for learners. In the context of nursing education, artificial intelligence (AI) chatbots currently offer multimodal learning approaches and demonstrate various possibilities for digital actions. Therefore, exploring the digital affordances of AI chatbots in nursing education is crucial for the continuous advancement of the field.ObjectiveTo evaluate the digital affordances of AI chatbots in nursing education, focusing on the relationship between digital affordances and learning gains.MethodsWe employed affordance theory to conceptualize the potential actions of AI chatbots and utilized a taxonomy of affective, behavioral and cognitive learning gains to conduct a systematic review in nursing education.Results and conclusionsA total of 25 studies were identified in this systematic review. The geographical distribution of the studies is mainly in Asia. The most used study designs were quantitative designs (n = 12) with sample sizes between 16 and 457. The duration of these studies is usually short, ranging from a few hours to 3 months. The included studies reported several digital affordances of AI chatbots in nursing education, including assistance provision, personalization, human-like conversing, distilling information, and fostering familiarity. However, four digital affordances-facilitation, enriching information, context identification, and ensuring privacy-still lack empirical support. The evidence for the digital affordances of AI chatbots in nursing education was dominated by cognitive learning gains (such as learning achievement, critical thinking, and problem solving) and followed by affective (such as learning interest, self-efficacy, and enjoyment) and behavioral learning gains (such as engagement, diagnostic skills and clinical practice). However, several studies reported no statistically significant improvement in certain cognitive learning gains, particularly knowledge acquisition and clinical reasoning competency. Similarly, limited evidence was found for improvements in learners’ confidence and satisfaction. These findings suggest that the current evidence remains inconclusive. Future research should employ longer study durations and larger sample sizes to further examine the educational impact of AI chatbots.
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