Practice and application of "artificial intelligence + big data" in the construction of thoracic surgery golden course
10.3760/cma.j.cn116021-20201122-00822
- VernacularTitle:"人工智能+大数据"在胸外科金课建设中的实践和应用
- Author:
Changjun HE
1
;
Yingbin LI
;
Bicheng FU
;
Xianglong KONG
;
Boxiong NI
;
Xue BAI
Author Information
1. 哈尔滨医科大学附属第三临床医学院,哈尔滨 150086
- Keywords:
Golden course construction;
Artificial intelligence;
Big data;
Education;
Learning ability of medical student
- From:
Chinese Journal of Medical Education Research
2022;21(4):442-446
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To discuss the practice and application of "artificial intelligence + big data" in the construction of thoracic surgery golden course.Methods:The intern students of the Department of Thoracic Surgery in Harbin Medical University Cancer Hospital were selected as the research objects, and they were randomly divided into 2 groups with 36 cases in each group. The control group was taught with regular courses, and the observation group was taught by the golden course system under "artificial intelligence + big data". After the course, self-made assessment forms were used to assess the academic performance (theoretical knowledge assessment results and skill operation assessment results) of the two groups of medical students. The excellent and good rate of knowledge mastery and the mastery of clinical operation techniques were scored by the teachers, and the evaluation was made from the aspects of learning attitude, the mastery degree of theoretical knowledge and clinical operational techniques, etc. In addition, self-made innovative thinking ability scale was used to assess the medical students. SPSS 22.0 was used for independent samples t test and chi-square test. Results:There was no statistically significant difference between the two groups of theoretical knowledge assessment scores and skill operation assessment scores before the teaching; after the course, the theoretical knowledge assessment scores and skill operation assessment scores of the control group were higher than those before the teaching, with statistically significant differences ( t=5.37, 4.17, P<0.05). After the course, the theoretical knowledge assessment scores and skill operation assessment scores of the observation group were higher than those before the teaching, with significant differences ( t=10.93, 8.24, P<0.05). The results of theoretical knowledge assessment and skill operation assessment in the observation group were significantly higher than those in the control group after the course ( t=7.10, 5.77, P<0.05). In the control group, 17 cases were excellent in knowledge mastery, accounting for 47.22%, and the rate of knowledge mastery was 83.33% (30/36); in the observation group, 26 cases were excellent in knowledge mastery, accounting for 72.22%, and the excellent and good rate of knowledge mastery was 100% (36/36), and the difference was statistically significant ( χ2=4.55, P=0.033). After the course, the innovative thinking ability of the control group was higher than that before the teaching, the innovative thinking ability of the observation group was higher than that before the teaching, and the innovative thinking ability of the observation group was higher than that of the control group, and the difference was statistically significant ( t=7.07, P<0.001). Conclusion:The use of the "artificial intelligence + big data" golden course to build a teaching system can improve the academic performance, knowledge mastery and innovative thinking ability of medical students.
