AI Classroom Recording Analysis and Supervision Solution
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| Real-time observation of AI classrooms | AI Classroom Recording Analysis |
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Leveraging AI technology to achieve real-time analysis of classroom teaching processes, covering live-streamed class analysis, distribution of teaching time, teacher trajectory tracking, student behavior recognition, and dynamically generating classroom insights.
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Conduct an in-depth analysis of recorded courses, supporting S-T analysis of teaching behaviors, in-depth assessment of cognitive development, visualization of the learning pyramid model, and other features that empower teaching reflection and optimization.
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| Intelligent Supervision and Classroom Observation | Scientific Online Lesson Evaluation |
| A normalized, panoramic classroom observation system that supports real-time classroom monitoring, historical review, and customizable observation templates, enabling flexible and efficient classroom supervision and task management. | By integrating AI-based classroom evaluation with expert evaluations, we provide a multi-dimensional and diversified assessment model that enables renowned teachers from both inside and outside the school to participate in classroom evaluations—either online or after class—thereby enhancing the scientific rigor and authority of the evaluations. |
Classroom Observation
AI classroom observation analyzes live-streamed classes in real time, covering aspects such as speech-to-text transcription, distribution of teaching time, analysis of teaching trajectories, student behavior analysis, and the student learning pyramid.
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・Analysis of teaching time allocation: Automatically identify and tally the duration and proportion of various teaching activities, such as teacher lectures, students’ independent study, group discussions, and teacher-student Q&A sessions, thereby quantifying the teaching model. ・Teacher Teaching Trajectory Analysis: Generate the duration of teachers’ presence at the podium, their patrol routes, and a heat map of their patrols to assess teachers’ engagement and attention distribution in the classroom. ・Real-time analysis of student behavior: Accurately detects key behaviors such as raising hands, standing up, resting on the desk, and writing, and outputs a real-time concentration curve that dynamically reflects the overall learning state in the classroom. ・Learning Pyramid: Student classroom behavior data, such as the proportions of active learning and passive learning. |
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Class Report
The AI Classroom Recording Analysis Service analyzes classroom videos uploaded by users or classroom videos recorded by recording hosts and cameras, covering aspects such as classroom teaching behaviors, classroom thinking training, and student learning behaviors. The system automatically generates an “AI Classroom Analysis Report,” which includes analysis content such as basic classroom information, analysis of classroom teaching behaviors, analysis of classroom thinking training, and analysis of student learning behaviors.
・S-T Analysis of Classroom Teaching Behavior: Generate a temporal sequence diagram of teaching behaviors, quantify the proportions of “teacher-led (T)” and “student-led (S)” behaviors, and objectively determine the type of course.
・Cultivating deep analytical thinking in the classroom: Includes transcribed text of classroom audio recordings, analysis of classroom questions (including Bloom’s Taxonomy of Educational Objectives and McCarthy’s 4MAX Model), analysis of student responses, and feedback from teacher-student interactions.
· Student Behavior Analysis: Includes student classroom behavior data, analysis of student attention levels, analysis of student engagement, and the learning pyramid—among other student classroom behavior data.
Supervisory classroom observation
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・Panoramic Data Dashboard and Real-Time Perception: Aggregating multi-dimensional annual data from classroom observations, supervision, and teaching research, this system visually presents real-time insights into school-wide indicators such as student engagement and participation rates, providing intuitive, quantifiable data support for instructional management decision-making. ・Multi-modal online classroom observation: Supports multiple classroom monitoring views, including lists and carousels, to display in real time the attendance status of all classes, device statuses, and monitoring progress, while accommodating different supervisory staff’s operational preferences. ・Flexible historical class review and retrospective: It supports precise multi-dimensional queries and retrieval of historical classroom records by campus, grade, subject, teacher, time, and other dimensions. It also supports multi-screen splicing, behavioral data analysis, and the capture and retention of screenshots of inappropriate behaviors. ・In-depth class observation statistics and trend analysis: Provides daily, monthly, and yearly statistics on classroom observation data, integrates an overview of class status and supervision alerts, and visually displays the development trends of classroom observation and evaluation through trend charts. • Scientific Online Course Evaluation System: We offer multi-dimensional classroom evaluation templates that support various evaluation modes, including task-driven approaches, self-scheduled appointments, and online sessions with renowned teachers. Additionally, we integrate AI-generated classroom reports as objective references to enhance the efficiency and scientific rigor of classroom evaluations. |
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