Digital Affordances of AI Chatbots in Nursing Education: Systematic Review Evidence

A systematic review document synthesizes evidence from 25 studies on the digital affordances of AI chatbots in nursing education. The document, authored by Shuling Wei, was last updated in April 2026. It analyzes the relationship between chatbot affordances and affective, behavioral, and cognitive learning gains.

Use Cases

• Identify supported digital affordances like assistance provision and personalization for curriculum design.
• Evaluate gaps in evidence for affordances like facilitation and ensuring privacy for future research planning.
• Analyze the distribution of reported learning gains (cognitive, affective, behavioral) to understand AI chatbot impact.
• Assess study characteristics like geographic distribution and duration to contextualize the evidence base.

Strengths

• Includes a defined scope of 25 studies, providing a concrete evidence base.
• Categorizes findings using a taxonomy of affective, behavioral, and cognitive learning gains.
• Identifies five specific digital affordances with empirical support from the reviewed literature.

Limitations

• The dataset is a single 56.3 KB document, offering limited scope for quantitative analysis.
• Row count and column-level documentation are absent; field semantics must be inferred from the text.
• The description notes the evidence for certain learning gains remains inconclusive.

Provenance

Source

figshare

Collection Method

Systematic review employing affordance theory and a taxonomy of learning gains.

Freshness

Last updated 2026-04-24 04:23:41

Geography

Studies are mainly in Asia, according to the description.