Georgian Med News. 2026 Jun;(375):96-99.
ABSTRACT
OBJECTIVE: To address the challenges of abstract theoretical concepts and low practical application in medical statistics teaching, this study proposes an innovative teaching model integrating Doubao AI and R software, focusing on the F-distribution with numerator degrees of freedom (df₁) =2 and denominator degrees of freedom (df₂) =27.
METHODS: A comparative teaching experiment was conducted among 52 medical students, divided into an experimental group (n=26) adopting the dual-software integrated model and a control group (n=26) using traditional teaching methods. The teaching process included AI-assisted theoretical interpretation, R-based data simulation, and case-driven practical application. Academic performance, task completion efficiency, and student satisfaction were evaluated. Task completion efficiency and student satisfaction were evaluated.
RESULTS: The average time for the experimental group to complete the teaching process of F-test was 10±2 minutes, shorter than the traditional instruction’s 30±5 minutes. The duration required for this teaching process is shorter than that of traditional instruction.100% of students in the experimental group believed that the dual-software integration helped them understand the application of F-distribution (df₁=2, df₂=27) in clinical research.
CONCLUSION: The integration of Doubao AI and R software effectively bridges the gap between theory and practice in F-distribution teaching, improves students’ statistical thinking and operational capabilities as well as learning efficiency and satisfaction, and provides a replicable solution for the digital reform of medical statistics courses.
PMID:42603322
