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Survey on the current status of statistical cognition and teaching needs of Chinese medical students
Hui Ouyang1, Siyang Wang2, Lingyun Huang3
1Department of Neurology, Peking University People's Hospital, Beijing, China.
Purpose:
To assess medical students' needs regarding statistics education and inform potential reforms in medical statistics teaching.
Method:
A self-administered questionnaire survey was conducted among 274 medical students from five Chinese institutions. The survey evaluated students' attitudes toward statistics, their perceived mastery of statistical knowledge, and their perspectives on current teaching methods and desired improvements.
Result:
Main findings: (1) only 10.22% of students reported strong interest in statistics and 8.76% are hard-working, while 75.18% perceived it as difficult and 64.23% spend less than 3 h per week studying statistics. (2) Most statistics courses were delivered in large-class settings (70.07%) or via lecture-based learning (53.28%). The average practical course duration is 10.86 ± 12.85 h. For 42.34% of students, their schools or majors do not offer practical courses in statistics. (3) 83.21% reported difficulties in selecting the correct statistical methods and 68.61% of students use Excel for analysis. 71.53% of medical students expressed difficulties in interpreting statistical analysis results. Although most students can pass the statistic exam, but 34.31% have misused statistical methods in scientific research, and 28.47% affected by statistical misuse in scientific research. (4) A high proportion (88.32%) emphasized the need for statistical guidance in medical research projects and advocated for integrating clinical and research cases into coursework, 79.56% willing to accept blended learning and 78.1% considered case-based learning an effective teaching approach.
Conclusion:
Medical students are weak in both theory and practical statistical skills. Current teaching methods cannot stimulate students' interest in learning statistics, and lack sufficient alignment with real-world applications due to excessive reliance on lecture-based instruction over case-based learning (CBL), necessitating reforms in medical statistics education.
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