TITLE:
Exploration and Analysis of AI in Cardiovascular Module Practical Teaching
AUTHORS:
Yanhua Zhang, Xiaochun Peng, Xueyuan Li
KEYWORDS:
Cardiovascular Module, Experimental Teaching, Education Reform, Artificial Intelligence, Intelligence Assisted Teaching
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.16 No.8,
August
17,
2026
ABSTRACT: Objective: This paper aims to explore the application effect of AI hybrid experimental teaching. Method: 53 clinical medicine students from the 2023 cohort were selected as the control group, and 59 clinical medicine students from the 2024 cohort were selected as the experimental group. The control group used traditional teaching mode, while the experimental group used AI blended teaching mode. After the teaching is completed, the theoretical level and skill operation of the two groups of students will be assessed, and their performance in various skills will be compared. The satisfaction of the two groups of students with the teaching methods will also be investigated. After the course ended, the theoretical and skill operation scores of the experimental group students were significantly higher than those of the control group. In the experimental group, the success rate of shock experiment, mechanism of shock description, clinical symptoms of right heart failure, and clinical pathological correlation scores of the experimental group were higher than those of the control group, and the differences were statistically significant (P Conclusion: By integrating AI software into a hybrid experimental teaching model that combines online and offline methods, this approach solved the problem of lack of deep learning in traditional blended learning experimental teaching, and improved students’ initiative and efficiency in self-directed learning.