摘要
随着信息时代的到来,智慧校园建设为创新高等教育模式奠定了基础。笔者结合高校需求,设计了一个基于智慧教室环境的学情监测及感知可视化系统。学情监测子系统采用深度残差网络模型,实现基于学生课堂面部行为的学情监测。感知可视化子系统通过Flask框架将结果以可视化方式呈现给用户。实验结果表明,该系统不仅可以实时监测课堂学习行为和投入度等学情,还能够捕捉异常行为并预警。
With the arrival of the information age,the construction of smart campus has laid the foundation for the innovation of higher education mode.According to the demand,a learning situation monitoring and perception visualization system based on smart classroom environment is designed and implemented.The learning situation monitoring subsystem adopts the deep residual network model to realize the learning situation monitoring based on students’ facial behavior.The perceptual visualization subsystem presents the results to users visually through the flask frame.The results show that the system can monitor the classroom learning behavior and engagement in real time,capture abnormal behavior and give early warning.
作者
李长运
刘涛
张钰晶
谌君泽
万佳
LI Changyun;LIU Tao;ZHANG Yujing;CHEN Junze;WAN Jia(Jiujiang University,Jiujiang Jiangxi 332005,China)
出处
《信息与电脑》
2022年第10期97-101,共5页
Information & Computer
基金
国家级大学生创新创业训练项目“智慧教室环境下的学情监测及感知可视化系统”(项目编号:202111843025)。
关键词
智慧教室
人脸识别
面部行为
学情监测
smart classroom
face recognition
facial behavior
learning situation monitoring
作者简介
李长运(2000-),男,山东枣庄人,本科。研究方向:物联网工程、网络安全。
