Quality Assessment and Teaching Optimization Strategies for the Clinical Surgery Theoretical Examination Based on Knowledge-Point Analysis
- VernacularTitle:基于知识点分析的临床医学外科学理论考试质量评估与教学优化策略研究
- Author:
Ru YAO
1
;
Zenan XIA
2
;
Changjun WANG
1
;
Yidong ZHOU
1
;
Qiang SUN
1
Author Information
- Publication Type:Journal Article
- Keywords: knowledge-point analysis; theoretical examination; difficulty coefficient; discrimination index; surgical education; teaching-assessment coordination
- From: Medical Journal of Peking Union Medical College Hospital 2025;17(5):1477-1482
- CountryChina
- Language:Chinese
-
Abstract:
Objective To conduct a systematic analysis of a clinical surgery theoretical examination based on knowledge points, thereby providing a reference for establishing a scientific and comprehensive test paper analysis system.
Methods Using the difficulty coefficient (P-value) and discrimination index (D-value) as indicators, a detailed evaluation was performed on 6 question types and 40 knowledge points from the
Clinical Comprehensive Course: Surgery examination for the 2023 clinical medicine pilot class at Peking Union Medical College. Data were visualized using frequency distribution charts, radar charts, and scatter plots.Results A total of 23 examination papers were collected. The students' average score was 78.63±7.58, with a pass rate of 100%. The overall examination difficulty was relatively low (P=0.79), and the overall discrimination was poor (D=0.15). Among the 40 knowledge points, 2 (5.0%) were difficult, 9 (22.5%) were moderately difficult, and 29 (72.5%) were relatively easy. Regarding discrimination, 3 (7.5%) knowledge points showed excellent discrimination, 8 (20.0%) demonstrated good or acceptable discrimination, and 29 (72.5%) had relatively poor discrimination. Some knowledge points [e.g., "Benign Prostatic Hyperplasia" (P=0.26, D=-0.17)] presented issues of high difficulty coupled with poor discrimination. A considerable number of knowledge points require corresponding adjustments.
Conclusion Knowledge-point-based test paper analysis can provide references for optimizing question type design, thereby enhancing the scientific nature of assessments and offering a basis for teaching improvements.
