AI-Assisted World Café Teaching Model Pilot Study in Clinical Pharmacology

Ying Guo's dataset contains results from a pilot study evaluating an AI-assisted World Café teaching model for graduate clinical pharmacology. The study involved 56 first-year master's students at Kunming Medical University and assessed teaching effectiveness through questionnaires, knowledge tests, and AI-generated scoring. The data was last updated on 2026-04-24.

Use Cases

• Compare AI-generated and instructor-generated assessment scores based on case discussion records mentioned in the description.
• Analyze changes in student knowledge test accuracy before and after the teaching intervention based on the described pre- and post-test results.
• Evaluate student perceptions of a novel teaching model based on the described teaching effectiveness perception questionnaire.
• Assess the distribution of student performance across different assessment dimensions based on the AI-based scoring described.

Strengths

• Dataset includes multi-method assessment results from 56 students, providing a basis for comparative analysis.
• Results show a statistically significant median improvement in post-test knowledge accuracy from 60.71% to 78.43%.
• Student agreement rates for the teaching model exceeded 90% across all evaluated items.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 11.2 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Data was collected as part of a pilot study involving questionnaires, knowledge tests, and comparative scoring analysis.

Freshness

Last updated 2026-04-24 05:40:27; freshness should be verified.

Geography

Study conducted at Kunming Medical University.