Data Sheet 1_Application of the artificial intelligence-assisted World Café teaching model

Ying Guo's pilot study assesses an AI-assisted World Café teaching model applied to a graduate clinical pharmacology course at Kunming Medical University. The dataset likely contains results from a multi-method assessment involving 56 first-year master's students, including questionnaire responses, knowledge test scores, and AI-generated versus instructor-generated scores on case discussions. The study was published on figshare in April 2026.

Use Cases

• Evaluating teaching effectiveness based on student perception questionnaire data
• Analyzing improvements in clinical decision-making competencies based on self-rated scores
• Comparing AI-generated and instructor-generated assessment scores for formative evaluation
• Studying knowledge acquisition outcomes based on pre- and post-test accuracy on depression etiology

Strengths

• Multi-method assessment strategy integrating questionnaire, knowledge test, and comparative scoring
• Results show significant improvement in post-test accuracy (median increase from 60.71% to 78.43%)
• High student agreement rates exceeding 90% across all items assessing the learning experience

Limitations

• Dataset size is 88.0 KB, indicating a very limited scope and likely small number of records
• Row count and column-level documentation are unknown, requiring manual inspection after download
• Data is specific to a single pilot study involving 56 students at one university, limiting generalizability

Provenance

Source

figshare

Collection Method

A pilot study involving 56 first-year master's students enrolled in a clinical pharmacology course, using a structured five-stage seminar with AI tools.

Freshness

Last updated 2026-04-24 05:40:25

Geography

Kunming Medical University