摘要
目的探讨"人工智能+大数据"在胸外科金课建设中的实践和应用。方法选择哈尔滨医科大学附属肿瘤医院胸外科实习学生作为研究对象,分为两组,各36例。对照组进行常规课程学习,观察组采用"人工智能+大数据"下的金课体系教学。课程结束后,采用自制考核测评表对两组医学生学习成绩(理论知识考核成绩及技能操作考核成绩)进行考核评估。由带教教师对两组知识掌握优良率进行评价,从学习态度、理论知识掌握程度、临床操作技术掌握程度等方面进行评分。采用自制创新思维能力测量量表对医学生进行考核评估。采用SPSS 22.0进行独立样本t检验和卡方检验。结果教学前两组理论知识考核成绩、技能操作考核成绩比较,差异无统计学意义;课程结束后,对照组理论知识考核成绩、技能操作考核成绩均高于教学前,差异有统计学意义(t=5.37、4.17,P<0.05);课程结束后,观察组理论知识考核成绩、技能操作考核成绩均高于教学前,差异有统计学意义(t=10.93、8.24,P<0.05);课程结束后,观察组理论知识考核成绩、技能操作考核成绩均高于对照组,差异有统计学意义(t=7.10、5.77,P<0.05)。对照组知识掌握优秀17例,占比47.22%,知识掌握优良率83.33%(30/36);观察组知识掌握优秀26例,占比72.22%,知识掌握优良率100%(36/36),差异有统计学意义(χ^(2)=4.55,P=0.033)。课程结束后,对照组创新思维能力高于教学前,观察组创新思维能力高于教学前,观察组创新思维能力高于对照组,差异有统计学意义(t=7.07,P<0.001)。结论采用"人工智能+大数据"金课建设教学体系,可提高医学生学习成绩、知识掌握情况以及创新思维能力。
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(χ^(2)=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.
作者
贺长军
李英滨
傅毕成
孔祥龙
倪博雄
白雪
He Changjun;Li Yingbin;Fu Bicheng;Kong Xianglong;Ni Boxiong;Bai Xue(The Third Affiliated Clinical Medical College of Harbin Medical University,Harbin 150086,China;The First Affiliated Clinical Medical College of Harbin Medical University,Harbin 150010,China)
出处
《中华医学教育探索杂志》
2022年第4期442-446,共5页
Chinese Journal of Medical Education Research
基金
黑龙江省教育科学规划重点课题(GJE1421007)
关键词
金课建设
人工智能
大数据
教育
医学生学习能力
Golden course construction
Artificial intelligence
Big data
Education
Learning ability of medical student
