A medical theory teaching quality assessment model based on classroom behavior analysis
10.3760/cma.j.cn116021-20240211-01994
- VernacularTitle:基于课堂行为分析的医学理论教学质量评估模型
- Author:
Yuchuan LIU
1
;
Jun YI
;
Zhihua QU
;
Chengmin WANG
;
Haibo YANG
Author Information
1. 重庆科技大学计算机科学与工程学院，重庆 401331
- Publication Type:Journal Article
- Keywords:
Teaching quality assessment;
Classroom behavior analysis;
Chain-like agent genetic algorithm;
Support vector regression machine
- From:
Chinese Journal of Medical Education Research
2025;24(3):320-324
- CountryChina
- Language:Chinese
-
Abstract:
Objective:In response to the subjectivity and poor real-time performance in methods for evaluating the quality of medical theory teaching, this study aims to develop an objective and real-time evaluation method for medical theory teaching quality.Methods:Classroom behavior data from both teachers and students in the course "medical image processing" were collected. An approach combining chain-like agent genetic algorithm with support vector regression machines was employed to analyze the collected classroom behavior data, and a classroom behavior-based evaluation model for medical theory teaching quality was established.Results:The predicted value generated by the model showed minimal error compared to students' actual answer accuracy, with an average absolute error of 4.84%. Additionally, the model demonstrated low time computation, with an average modeling time of 8.63 seconds and an average prediction time of 21.00 milliseconds.Conclusions:The constructed teaching quality assessment model shows high fitting precision and low time consumption.
