Student Classroom Engagement Analysis | 学生课堂情绪参与度分析

Using a fixed classroom camera, the system analyzes students' facial expressions (focused, confused, happy, frustrated, bored, etc.), computes a class-level overall engagement score (0-100), and can identify low-engagement student positions (no identity stored — for real-time teacher reminders only). The skill helps teachers adjust teaching pace and pay attention to students having learning difficulty. Application scenarios: K-12 classrooms, training courses, online education (students must be on camera). Real-time analysis provides engagement heatmaps and abnormal alerts. Skill features: it is difficult for a teacher to monitor every student's facial state in real time. AI-assisted analysis helps teachers timely detect confusion or boredom, adjust teaching strategy, and improve quality. Can be integrated into smart-classroom systems or lecture-recording devices. | 通过教室固定摄像头，分析学生面部表情（专注、困惑、开心、沮丧、无聊等），计算班级整体参与度评分（0-100分），并可识别出参与度较低的学生个体（不存储身份，仅用于实时提醒）。该技能可辅助教师调整教学节奏，关注学习困难学生。应用场景：中小学教室、培训课堂、在线教育（需拍摄学生）。系统实时分析，为教师提供参与度热力图和异常提醒。技能特点：教师难以实时关注每个学生的表情状态。通过AI辅助分析，可帮助教师及时发现学生困惑或无聊，调整教学策略，提高教学质量。该技能可集成到智慧教室系统或录播设备中。

by @18072937735 (smyx-skills)·MIT-0