Automatic S-T teaching analysis method based on intelligent recording and broadcasting system

Abstract

The invention discloses an automatic S-T teaching analysis method based on an intelligent recording and broadcasting system. Systems applied to the method include an audio and video on-site collection and recording and broadcasting system, a network transmission system and a remote broadcasting system. The method includes the steps: 1, acquiring switching modes of signal sources in a recording process of the audio and video on-site collection and recording and broadcasting system; 2, performing conversion processing on the switching modes and generating xml files; 3, defining parameters, which are behaviors of teachers and students, in video source files in the xml files; 4, calculating teacher behavior percentage, student behavior percentage and conversion ratio; and 5, utilizing a web interface for displaying S-T behavior diagrams. A recording and broadcasting host computer can convert intelligent switching information of video source placements into a teacher behavior information sequence table and a student behavior information sequence table while teachers record lessons, after video recording is finished, visual S-T histograms can be generated directly via automatic encoding, and conversion ratio of the lessons is calculated, and teaching types are judged according to norms.

Description

technical field [0001] The invention relates to the field of intelligent recording and broadcasting systems, in particular to an automatic analysis method for S-T teaching based on the intelligent recording and broadcasting system. Background technique [0002] American scholar Posner believes that: teacher growth = experience + reflection 。 How to support teachers to carry out case study and reflection has become a difficult problem to better promote teachers' professional development. In order to effectively record, analyze and study the teaching process, and realize the evaluation and improvement of the teaching process, it is necessary to conduct an in-depth discussion on the analysis methods of the teaching process. [0003] In order to study teaching more vividly and intuitively, reduce the ambiguity of behavior classification in the teaching process, and increase objectivity, at first, the evaluation experts listened to the class (or watched the class video), and the...

AI Technical Summary

Problems solved by technology

In the description of teaching behavior analysis, the recorder inevitably has the ambiguity of subjective experience, and the manual recording of S-T data by the analyst is not only cumbersome but also has a heavy workload. The above factors reduce the objectivity and reliability of the analysis process and recording results, and cannot be obtained immediately. Analyze results and provide timely feedback

[0009] The shortcomings of the existing analysis methods are: first, the video must be manually analyzed after the course recording is completed, and there is no way to automatically describe the video teaching information while recording the video; The work of sampling and calculating S-T data is cumbersome and heavy. Third, the behavior of teachers or students recorded by the evaluators when watching the lesson video has ambiguity of subjective experience. Fourth, it takes a certain amount of time to evaluate and analyze the data. It is impossible to give timely feedback to the teaching process based on the analysis results

Sampling, making S-T instructional analysis difficult to use in large quantities

[0010] The shortcomings of the above-mentioned existing technologies are due to the lack of a solution for automatically recording teaching behavior from the video recording signal source, and the analysis of teaching behavior can only be separated from the recording and analysis process.

Moreover, the current S-T analysis software can only draw the S-T diagram and judge the Rt-Ch diagram for the recorded data, and there is no way to realize the position analysis and judgment of the analysis points corresponding to the video while recording the video, so as to carry out intelligent automatic sampling and Record S, T data

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