摘要
针对课堂授课中实习教师和初任老师容易忽略学生情绪的问题,通过研究YOLOv5框架、关键帧提取、人脸识别、表情识别等技术,探究了数字化的教学评价方法,提出了一种基于表情识别的数字智能化的课堂评价方案,并且构建了基于YOLOv5技术框架的数字化课堂教学评价系统。系统注重于分析学生的面部表情信息,对学生的课堂情绪进行统计、分析以及可视化,方便授课教师课后分析授课过程,反思教学思路,提高教学技能,可有效地帮助教师提高课堂教学水平和授课质量,具有很好的价值和意义。
In view of the problem that intern teachers and first-time teachers tend to ignore students’ emotions in classroom teaching,this paper explores digital teaching evaluation methods by studying YOLOv5 framework,key frame extraction,face recognition,expression recognition and other technologies,and proposes a digital and intelligent classroom evaluation scheme based on expression recognition,and constructs a digital classroom teaching evaluation system based on the YOLOv5 technology framework.The system focuses on analyzing students’ facial expression information,and conducts statistics,analysis and visualization of students’ classroom emotions,which is convenient for teachers to analyze the teaching process after class,reflect on teaching ideas,and improve teaching skills.It can effectively help teachers improve classroom teaching level and teaching quality,which is of great value and significance.
作者
唐强
张璐平
夏志远
彭俊
符子扬
TANG Qiang;ZHANG Luping;XIA Zhiyuan;PENG Jun;FU Ziyang(Hunan Normal University,Changsha 410081,China)
出处
《现代信息科技》
2022年第20期191-195,共5页
Modern Information Technology
基金
湖南省普通高等学校教学改革研究项目(HNJG-2022-0522)
湖南师范大学教师教育改革研究实践项目(202105)。
关键词
YOLOv5
关键帧
表情识别
课堂教学评价
YOLOv5
key frame
expression recognition
classroom teaching evaluation
