Classroom behavior analysis method and system, and electronic equipment

Abstract

The invention discloses a classroom behavior analysis method which is applied to multimedia classroom teaching. Classroom recording and broadcasting, non-inductive human face attendance checking and classroom behavior analysis are realized through an artificial intelligence technology and a big data technology. The method comprises the following steps of S10, collecting biological information of teachers and students in a teaching process in real time while classroom videos are recorded, wherein the biological information includes behavior data, position data, expression data and body movementdata; S20, performing multi-dimensional analysis according to the biological information and generating a classroom quality report; and S30, sending a recorded classroom video and a generated classroom quality report to cloud for storage. Compared with the prior art, the classroom behavior analysis method provided by the invention has the advantages that time and labor are saved, a obtained sample size is large, and discovery of a general teaching rule is facilitated. The invention further provides a classroom behavior analysis system and electronic equipment.

Description

technical field [0001] The present invention relates to the technical field of educational informatization, in particular to a classroom behavior analysis method, system and electronic equipment. Background technique [0002] With the construction and popularization of the intelligent teaching environment, the research on the corresponding education and teaching mode and classroom teaching behavior analysis has become the focus of attention. Classroom behavior analysis, by exploring the internal mechanism of classroom teaching activities to promote students' development, helps teachers reflect on the acquisition of practical knowledge, which is conducive to promoting the improvement of classroom teaching quality. [0003] However, traditional classroom teaching behavior analysis methods mostly collect and analyze data through self-reporting, manual observation, and manual coding, which have the disadvantages of strong subjectivity, time-consuming and labor-intensive coding, ...

AI Technical Summary

Problems solved by technology

[0003] However, traditional classroom teaching behavior analysis methods mostly collect and analyze data through self-reporting, manual observation, and manual coding, which have the disadvantages of strong subjectivity, time-consuming and labor-intensive coding, and small sample size, which is not conducive to the discovery of common teaching rules

At the same time, the detection and analysis of human faces in the existing technology often adopts the general model of security and the static analysis method of frame extraction analysis, which is not suitable for teaching scenes with a large number of body movements and interactions.

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