Teaching evaluation method, device and equipment and readable storage medium

Abstract

The embodiment of the invention provides a teaching evaluation method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining a video analysis result, an audio analysis result and configuration parameters of a target classroom through a server, and generating intermediate data according to the video analysis result, the audio analysis result and the configuration parameters of the target classroom, and teaching evaluation is carried out on the target classroom according to the intermediate data, the video file obtained by recording the target classroom and the configuration parameters. By adopting the scheme, the target classroom is evaluated by combining the configuration parameters for indicating the evaluation requirements of the target classroom, the audio and video analysis result of the target classroom, the intermediate data obtained by analyzing and understanding the target classroom and other multivariate data, the data source is more comprehensive, the overall evaluation of teachers in teaching can be better given, and the teaching efficiency is improved. More accurate and more comprehensive teaching feedback is provided for teaching of teachers, and the purpose of adapting to different teaching scenes is achieved while the teaching evaluation quality is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of audio and video analysis or processing, and in particular to a teaching evaluation method, device, equipment and readable storage medium. Background Art

[0002] At present, in order to improve the teaching level, it is often necessary to evaluate classroom teaching.

[0003] In traditional teaching evaluation methods, audio and video data of the classroom are collected and analyzed to achieve teaching evaluation.

[0004] However, the above teaching evaluation methods have a single data source and lack the ability to understand, resulting in poor quality of teaching evaluation. Summary of the invention

[0005] The embodiments of the present application provide a teaching evaluation method, device, equipment and readable storage medium, which perform teaching evaluation by combining data from multiple channels to achieve the purpose of improving the quality of teaching evaluation.

[0006] In a first aspect, an embodiment of the present application provides a teaching evaluation method, which is applied to a server, and the method includes:

[0007] Obtaining the video analysis results, audio analysis results, and configuration parameters of the target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analyzing the audio collected from the target classroom, and the configuration parameters are used to indicate the evaluation requirements of the target classroom;

[0008] Generate intermediate data according to the video analysis result, the audio analysis result and the configuration parameters;

[0009] A teaching evaluation is performed on the target classroom according to the intermediate data, the video file and the configuration parameters, and the video file is recorded from the target classroom.

[0010] In a second aspect, an embodiment of the present application provides a teaching evaluation method, which is applied to a management platform, and the method includes:

[0011] Displaying a configuration interface of a target classroom, wherein the configuration interface is used to configure evaluation requirements of the target classroom;

[0012] In response to an operation on the configuration interface, generating configuration parameters of the target classroom, the configuration parameters being used to indicate evaluation requirements of the target classroom;

[0013] The configuration parameters are sent to a server so that the server performs a teaching evaluation on the target classroom according to the configuration parameters.

[0014] In a third aspect, an embodiment of the present application provides a teaching evaluation device, which is integrated on a server and includes:

[0015] An acquisition module, used to acquire video analysis results, audio analysis results and configuration parameters of a target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analysis of the audio collected from the target classroom, and the configuration parameters are used to indicate the evaluation requirements of the target classroom;

[0016] A processing module, used to generate intermediate data according to the video analysis result, the audio analysis result and the configuration parameters;

[0017] An evaluation module is used to perform teaching evaluation on the target classroom based on the intermediate data, the video file and the configuration parameters, and the video file is recorded from the target classroom.

[0018] In a fourth aspect, an embodiment of the present application provides a teaching evaluation device, which is integrated on a management platform and includes:

[0019] A display module, used to display a configuration interface of a target classroom, wherein the configuration interface is used to configure evaluation requirements of the target classroom;

[0020] A processing module, for generating configuration parameters of the target classroom in response to an operation on the configuration interface, wherein the configuration parameters are used to indicate evaluation requirements of the target classroom;

[0021] The transceiver module is used to send the configuration parameters to the server so that the server can perform teaching evaluation on the target classroom according to the configuration parameters.

[0022] In a fifth aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the electronic device implements the method described in the first aspect or various possible implementations of the first aspect; or, when the processor executes the computer program, the electronic device implements the method described in the second aspect or various possible implementations of the second aspect.

[0023] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed by a processor, they are used to implement the method described in the first aspect or various possible implementations of the first aspect, or, when the computer instructions are executed by a processor, they are used to implement the method described in the second aspect or various possible implementations of the second aspect.

[0024] In the seventh aspect, an embodiment of the present application provides a computer program product comprising a computing program, wherein the computer program, when executed by a processor, implements the method described in the first aspect or various possible implementations of the first aspect, or, when executed by a processor, implements the method described in the second aspect or various possible implementations of the second aspect.

[0025] The teaching evaluation method, device, equipment and readable storage medium provided in the embodiment of the present application, the server obtains the video analysis results, audio analysis results and configuration parameters of the target classroom, generates intermediate data according to the video analysis results, audio analysis results and configuration parameters of the target classroom, and then performs teaching evaluation on the target classroom according to the intermediate data, the video file obtained by recording the target classroom and the configuration parameters. With this scheme, the target classroom is evaluated by combining the configuration parameters used to indicate the evaluation requirements of the target classroom, the audio and video analysis results of the target classroom, the intermediate data obtained by analyzing and understanding the target classroom, and other multivariate data. The data source is more comprehensive, and the overall evaluation of the teacher in teaching can be better given, providing more accurate and comprehensive teaching feedback to the teacher's teaching, achieving the purpose of adapting to different teaching scenarios while improving the quality of teaching evaluation. Moreover, the configuration parameters of different classrooms are different, and the configuration parameters reflect the actual evaluation requirements of different schools, different majors, and different subjects, so that the configuration parameters and the target classroom are more adapted, further achieving the purpose of improving the quality of teaching evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 Schematic diagram of a network architecture applicable to the teaching evaluation method provided in the embodiment of the present application;

[0028] Figure 2 is a flow chart of the teaching evaluation method provided in the embodiment of the present application;

[0029] Figure 3 is another flow chart of the teaching evaluation method provided in the embodiment of the present application;

[0030] Figure 4 is a schematic diagram of a teaching evaluation system provided in an embodiment of the present application;

[0031] Figure 5 A schematic diagram of a teaching evaluation device provided in an embodiment of the present application;

[0032] Figure 6 Another schematic diagram of the teaching evaluation device provided in an embodiment of the present application;

[0033] Figure 7 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] Traditional teaching evaluation methods include pure computer vision (CV) algorithms or neural network plus data methods. Among them, the pure CV algorithm analyzes the video data of the class to be evaluated. The data in the neural network plus data includes video data and audio data, which are input into the neural network model so that the neural network model outputs the evaluation results.

[0035] The above teaching evaluation methods are based only on video data, audio data, etc., with a single data source and lack of comprehension, which makes it impossible to accurately and comprehensively evaluate teaching. For example, there are misjudgments of teacher emotions, teacher behaviors, and knowledge point analysis.

[0036] Moreover, the traditional teaching evaluation scheme has an opaque evaluation dimension mechanism, and the evaluation dimensions of different classrooms are fixed, making it difficult to adapt to different teaching scenarios, such as theoretical teaching and practical training teaching.

[0037] Based on this, the embodiments of the present application provide a teaching evaluation method, device, equipment and readable storage medium, which evaluates the target classroom by combining multiple data such as configuration parameters used to indicate the evaluation requirements of the target classroom, the audio and video analysis results of the target classroom, and the intermediate data obtained by analyzing and understanding the target classroom, so as to improve the quality of teaching evaluation while achieving the purpose of adapting to different teaching scenarios.

[0038] Figure 1 This is a schematic diagram of the network architecture applicable to the teaching evaluation method provided in the embodiment of this application. Figure 1 The network architecture includes a server 11, a collection terminal 12, a computing terminal 13, and a management platform 14. The server 11 establishes a network connection with the computing terminal 13 and the management platform 14. The computing terminal 13 also establishes a network connection with the collection terminal 12, and the management platform 14 also establishes a network connection with the collection terminal 12.

[0039] The server 11 can be deployed in the cloud or at the edge, for example, the server 11 is an edge server in a school. The teaching big model is deployed on the server 11, and the big model can be a self-developed big model or an open source model. The server 11 uses the teaching big model to perform reasoning analysis on the audio and video analysis results, configuration parameters, etc., so as to obtain intermediate data.

[0040] The acquisition terminal 12 is, for example, a recording and broadcasting host, etc. The acquisition terminal 12 establishes a network connection with the teacher's panoramic camera, student panoramic camera, microphone array, blackboard camera, smart interactive tablet, and computers in the corresponding classroom of the target classroom. The acquisition terminal 12 is used to pull the teacher's panoramic stream from the teacher's panoramic camera, pull the student's panoramic stream from the student's panoramic camera, and pull the audio from the microphone array. The teacher's panoramic stream and the student's panoramic stream are collectively referred to as the video collected for the target classroom. After the acquisition terminal 12 pulls the video and audio of the target classroom, it extracts frames of the video and audio, and sends the extracted video frames and audio frames to the computing power terminal 13.

[0041] The acquisition terminal 12 also records the course based on the video, audio, etc. of the target classroom to obtain a video file, and uploads the video file to the server 11.

[0042] Various visual algorithms and audio algorithms are deployed on the computing terminal 13. The video of the target classroom is analyzed by the visual algorithm to obtain the video analysis result, and the audio of the target classroom is analyzed by the audio algorithm to obtain the audio analysis result. After that, the audio analysis result and the video analysis result are sent to the server 11.

[0043] The management platform 14 is also called the teaching quality management platform, which is used to provide customized services. Multiple databases are deployed on the management platform 14, such as an indicator library, a configuration table library, a class evaluation table library, and a report library. Different schools and majors select evaluation dimensions from the indicator library and the weights and conditions of each evaluation dimension from the configuration table library according to their own evaluation needs, thereby generating configuration parameters for the target classroom, and the configuration parameters of different classrooms are different. The evaluation dimension includes the main dimension and the sub-dimensions described below.

[0044] When teaching evaluation is required, the server 11 obtains the configuration parameters of the target classroom from the management platform 14, and inputs the configuration parameters, audio and video analysis results, etc. into the teaching model, so that the teaching model outputs intermediate data.

[0045] The management platform 14 also records all course information of the school, and sends instruction information to the collection terminal 12 at a timely manner to notify the collection terminal 12 to collect data and record videos according to the start time and end time of the target class.

[0046] Figure 1 In the network architecture shown, the collection terminal 12 and the computing power terminal 13 are independently configured. However, the embodiment of the present application is not limited thereto, and in other feasible implementations, the collection terminal 12 and the computing power terminal 13 may also be integrated.

[0047] It should be understood that Figure 1The number of servers 11, collection terminals 12, computing terminals 13, and management platforms 14 is only for illustration. In actual implementation, any number of servers 11, collection terminals 12, computing terminals 13, and management platforms 14 may be deployed according to actual needs.

[0048] Figure 2 This is a flow chart of the teaching evaluation method provided by the embodiment of the present application. This embodiment is described from the perspective of the server. This embodiment includes:

[0049] 201. Obtain video analysis results, audio analysis results, and configuration parameters of a target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analysis of the audio collected from the target classroom, and the configuration parameters are used to indicate evaluation requirements of the target classroom.

[0050] In the embodiment of the present application, the target classroom is the classroom for which teaching evaluation is to be conducted, and can be a classroom of any subject taught by any lecturer.

[0051] The embodiment of the present application can flexibly trigger teaching evaluation. For example, after receiving an evaluation instruction carrying the identification (ID) of the target class, the server performs a teaching evaluation on the target class. For another example, a timer is set on the server, and when the timer times out after the target class is over, the server automatically performs a teaching evaluation on the target class. During the teaching evaluation process, the server obtains the video analysis results and audio analysis results of the target class from the computing power terminal, and obtains the configuration parameters of the target class from the management platform.

[0052] The video analysis results refer to the data obtained by the computing terminal through analyzing the video of the target classroom through visual algorithms, such as teacher behavior, clothing, posture, position tracking, student behavior, standing up and raising hands, looking up and lowering heads, position tracking, face recognition, etc.

[0053] Audio analysis results refer to the data obtained by the computing terminal through the audio algorithm to analyze the audio of the target classroom, such as the content of the speaker's speech, who the specific speaker is, sound events, etc. Sound events refer to a sound, such as noise, human speech, or reading aloud.

[0054] Configuration parameters are used to indicate the evaluation requirements of the target classroom, and the evaluation requirements of different classrooms are different. For example, if the target classroom is a theoretical class, the evaluation dimensions indicated by the configuration parameters include teaching attitude, teaching content, and classroom literacy. For another example, if the target classroom is a practical training class, the evaluation dimensions indicated by the configuration parameters include teaching design and teaching methods. The sub-dimensions of teaching design include course review, course objectives, course assignments, extracurricular resources, etc.; the sub-dimensions of teaching methods include whether teachers and students interact, whether students actively ask questions, etc.

[0055] 202. Generate intermediate data based on the video analysis result, the audio analysis result and the configuration parameters, where the intermediate data is used to indicate data obtained by analyzing and understanding the target classroom.

[0056] The teaching model is deployed on the server, and the server inputs the obtained video analysis results, audio analysis results, configuration parameters, course information, etc. into the teaching model, so that the teaching model can understand the target classroom in combination with the course information, accurately identify the semantics and teaching behavior of the target classroom, and thus obtain intermediate data. Intermediate data includes but is not limited to the proportion of teachers' teaching behaviors, speech speed statistics, improvement suggestions, question and answer type analysis, Flanders interaction analysis, student-teacher teaching analysis, teacher behavior occupancy rate-student behavior occupancy rate (ST / Rt-Ch), etc.

[0057] 203. Conduct a teaching evaluation on the target classroom according to the intermediate data, the video file and the configuration parameters, wherein the video file is recorded from the target classroom.

[0058] Please refer to Figure 1 The acquisition terminal pulls the teacher's panoramic stream from the teacher's panoramic camera, pulls the student's panoramic stream from the student's panoramic camera, pulls the audio from the microphone array, and records the course for the pulled video, audio, etc. to obtain a video file, and uploads the video file to the server.

[0059] The teaching evaluation service is deployed on the server, and the teaching evaluation server is used to combine the intermediate data, video files and configuration parameters to obtain the teaching evaluation report. In this way, the server combines multi-dimensional information such as cameras, computer input, microphones, teaching models, and management platforms to evaluate teaching, giving full play to the effective information in the classroom and school, and can identify teaching behaviors and conduct teaching evaluation in more dimensions, more effectively and more accurately. Among them, computer input refers to screenshots of the computer playing PPT, etc.

[0060] Afterwards, the server can send the teaching evaluation report to the management platform, and the visualization module of the management platform will display the teaching evaluation report of the target class.

[0061] The teaching evaluation method provided in the embodiment of the present application is that the server obtains the video analysis results, audio analysis results and configuration parameters of the target classroom, generates intermediate data based on the video analysis results, audio analysis results and configuration parameters of the target classroom, and then performs teaching evaluation on the target classroom based on the intermediate data, the video file obtained by recording the target classroom and the configuration parameters. With this scheme, the target classroom is evaluated by combining multiple data such as configuration parameters indicating the evaluation requirements of the target classroom, the audio and video analysis results of the target classroom, and the intermediate data obtained by analyzing and understanding the target classroom. The data source is more comprehensive, and the overall evaluation of the teacher's teaching can be better given, providing more accurate and comprehensive teaching feedback to the teacher's teaching, achieving the purpose of adapting to different teaching scenarios while improving the quality of teaching evaluation. Moreover, the configuration parameters of different classrooms are different, and the configuration parameters reflect the actual evaluation requirements of different schools, different majors, and different subjects, so that the configuration parameters and the target classroom are more adapted, further achieving the purpose of improving the quality of teaching evaluation.

[0062] Figure 3 This is another flow chart of the teaching evaluation method provided in the embodiment of the present application. This embodiment is described from the perspective of the management platform. This embodiment includes:

[0063] 301. Display a configuration interface of a target classroom, where the configuration interface is used to configure evaluation requirements of the target classroom.

[0064] In the embodiment of the present application, the management platform is a customized platform for schools and majors with different needs to customize configuration parameters for target classrooms. The configuration parameters of the target classroom include evaluation dimensions, sub-dimensions of the evaluation dimensions, weights and / or conditions of each evaluation dimension, etc. The configuration parameters of different target classrooms are different. For example, the evaluation dimensions of the fluid mechanics class include main dimension A, main dimension B, and main dimension C; the evaluation dimensions of the electronic engineering principles class include main dimension D and main dimension E.

[0065] When the management platform is a device with a display screen, the user calls up the configuration interface of the target classroom through the display screen, and customizes the configuration parameters for the target classroom through the configuration interface. When the management platform is a remote server, the user logs in to the management platform through a terminal device such as a desktop computer or a laptop, and the management platform sends a data stream for displaying the configuration interface to the terminal device. The terminal device renders and displays the configuration interface according to the data stream, and customizes the configuration parameters for the target classroom through the configuration interface.

[0066] 302. In response to an operation on the configuration interface, generate configuration parameters of the target classroom, where the configuration parameters are used to indicate evaluation requirements of the target classroom.

[0067] The user customizes the evaluation dimensions and evaluation sub-dimensions for the target classroom through the configuration interface, and the management platform generates the configuration parameters of the target classroom according to the user's selection operation. Alternatively, the user modifies the evaluation dimensions, evaluation sub-dimensions, and weights of each evaluation dimension of the target classroom through the configuration interface. For example, the evaluation dimensions of the target classroom include main dimension A, main dimension B, and main dimension C. The management platform modifies the evaluation dimensions of the target classroom to main dimension B, main dimension C, and main dimension E according to the user's operation in the configuration interface. The management platform generates the configuration parameters of the target classroom according to the user's modification operation.

[0068] 303. Send the configuration parameters to the server, so that the server performs teaching evaluation on the target classroom according to the configuration parameters.

[0069] After the management platform generates configuration parameters for the target classroom, it sends the configuration parameters to the server so that the server can evaluate the target classroom based on the configuration parameters, the video analysis results of the target classroom, the audio analysis results, etc. For example, when the server is about to conduct a teaching evaluation on the target classroom, it sends an acquisition instruction to the management platform. After receiving the acquisition instruction sent by the server, the management platform sends the configuration parameters to the server. For another example, after the management platform generates configuration parameters based on the user's operation on the configuration interface, it actively sends the configuration parameters to the server.

[0070] In the teaching evaluation method provided in the embodiment of the present application, the management platform displays a configuration interface for configuring the evaluation requirements of the target classroom, generates configuration parameters of the target classroom in response to the operation of the configuration interface, and sends the configuration parameters of the target classroom to the server. With this solution, by providing customized services, different schools, different majors, and different subjects can customize configuration parameters for the target classroom according to actual needs. Different classrooms have different configuration parameters, which makes the configuration parameters more compatible with the target classroom, that is, adapting to the evaluation focus of different schools and different majors, and achieving the purpose of improving the quality of teaching evaluation.

[0071] Optionally, in the above embodiment, the management platform stores multiple databases, including the indicator library, the configuration table library, the class evaluation table library, and the report library. The class evaluation table library stores multiple class evaluation tables, and different class evaluation tables are used to indicate the evaluation of different classes by the evaluator. The report library stores multiple teaching evaluation reports. In the process of generating the configuration parameters of the target classroom in response to the operation of the configuration interface, the management platform first determines the evaluation dimension of the target classroom from the indicator library according to the operation of the configuration interface. The evaluation dimension includes the main dimension and the sub-dimension under the main dimension, and the indicator library stores multiple evaluation dimensions for selection; the weight and / or condition of each sub-dimension is determined from the configuration table library, and the configuration table library stores multiple weights and conditions for selection of the sub-dimensions under each main dimension. Afterwards, the management platform generates the configuration parameters of the target classroom according to the weight and / or condition of the main dimension of the target classroom and the sub-dimension under the main dimension.

[0072] Exemplarily, the management platform is a customized platform for schools and majors with different needs to customize configuration parameters for target classrooms. The configuration parameters of the target classroom include evaluation dimensions. The evaluation dimensions include main dimensions and sub-dimensions under each main dimension. The configuration parameters also include weights and / or conditions of each sub-dimension. The indicator library stores multiple evaluation dimensions for selection. The evaluation dimensions include multiple main dimensions for selection. For each main dimension, the indicator library also stores multiple sub-dimensions for selection. When customizing configuration parameters for the target classroom, the user selects the required main dimension from multiple main dimensions through the configuration interface. For each selected main dimension, the required sub-dimension is selected from multiple sub-dimensions, thereby customizing the evaluation dimension for the target classroom, which includes the main dimension and the sub-dimension.

[0073] Afterwards, for each sub-dimension, the user selects weights and / or conditions for each sub-dimension from the configuration table library through the location interface, and then generates the configuration parameters of the target classroom based on the weights and / or conditions of the main dimension and the sub-dimensions under each main dimension.

[0074] With this solution, users can configure the main dimensions, sub-dimensions, weights and conditions of each sub-dimension for the target classroom according to needs through the configuration interface provided by the management platform, so that the configuration parameters reflect the actual needs of different schools, different majors, and different subjects, making the configuration parameters more adaptable to the target classroom and achieving the goal of improving the quality of teaching evaluation.

[0075] Optionally, in the above embodiment, when the server performs teaching evaluation on the target classroom according to the intermediate data, the video file and the configuration parameters, first, the evaluation dimension of the target classroom is determined according to the configuration parameters, and the evaluation dimension includes a main dimension and a sub-dimension under the main dimension. After that, the server determines the weight and / or condition of the sub-dimension according to the configuration parameters, and then performs teaching evaluation on the target classroom according to the main dimension of the target classroom, the weight and / or condition of the sub-dimension under the main dimension, the intermediate data and the video file.

[0076] The main dimensions in the indicator library in the embodiment of the present application include but are not limited to teaching attitude, teaching design, teaching content, teaching methods, classroom literacy, etc., and multiple sub-dimensions are set under each main dimension. For example, the main dimension is teaching attitude, and the sub-dimensions include lateness and early departure, teacher mood, demeanor and dress, classroom order, etc. The evaluation dimensions of the target classroom are some or all of the main dimensions in the indicator library and the sub-dimensions under the main dimensions. After the server obtains the configuration parameters, the evaluation dimensions (including the main dimensions and the following sub-dimensions) are parsed from the configuration parameters, and the weights, conditions, etc. of each sub-dimension are parsed from the configuration parameters, and then the teaching evaluation report of the target classroom is generated according to the main dimensions, sub-dimensions, weights and / or conditions of the sub-dimensions, intermediate data and video files of the target classroom, thereby completing the teaching evaluation of the target classroom.

[0077] In the above teaching evaluation process, different target classrooms have different configuration parameters. Accordingly, the main dimensions, sub-dimensions, and weights and / or conditions of each sub-dimension are different. For example, the main dimensions of the fluid mechanics course include main dimension A, main dimension B, and main dimension C; the main dimensions of the electronic engineering principle course include main dimension D and main dimension E. In this way, the teaching evaluation dimensions are no longer fixed, but adapt to the current target classroom.

[0078] By adopting this solution, the configuration parameters reflect the actual evaluation needs of the target classroom. The configuration parameters and the target classroom are more adaptable and can be adapted to different schools, different majors, and different subjects, thereby achieving the goal of improving the quality of teaching evaluation.

[0079] Figure 4 This is a schematic diagram of the teaching evaluation system provided in the embodiment of the present application. Figure 4 ,The teaching evaluation system includes classroom information collection part, computing ,terminal, cloud / edge and management platform. ,Below, each part of the teaching evaluation system is described in detail.

[0080] First, the classroom information collection part.

[0081] Classroom information collection part: mainly used to collect images and audio of teachers and students in class, blackboard content, record video files, and provide images and audio to computing terminals. The classroom information collection part includes teacher panoramic camera, student panoramic camera, blackboard acquisition component, microphone array, collection terminal, upload module, etc.

[0082] The teacher / student panoramic cameras are installed at the front and back of the classroom respectively. The teacher panoramic camera is used to shoot the podium area, and the student panoramic camera is used to shoot the student area, the front row area of ​​the students, etc., to support early deployment.

[0083] During the initial deployment, the camera images are manually annotated, and the annotated area information is used as the input of the computing terminal. For example, the student panoramic camera has a relatively large shooting range and captures the entire student area. If only the front row area is needed, the images captured by the student panoramic camera are annotated during the initial deployment, and the front row area is annotated from the entire shooting image. The front row area is part of the student area. During subsequent course recording or teaching evaluation, the acquisition terminal pulls the student panoramic stream from the student panoramic camera, annotates the front row area from each frame of the student panoramic stream, and sends the annotation information and the extracted image frames to the computing terminal.

[0084] Blackboard acquisition components: including blackboard camera, four-sided infrared blackboard, screenshot software, etc. There are two types of blackboards. One is the blackboard written on the blackboard. This type of blackboard can be photographed by a blackboard camera, or the blackboard handwriting can be collected by a four-sided infrared blackboard. The other type of blackboard is a screenshot. The slide presentation (Power Point, PPT) played on the computer is projected onto the smart interactive tablet or projector through the High Definition Multimedia Interface (HDMI), DisplayPort (DP), etc. The screenshot of the computer, smart interactive tablet, etc. is taken through the screenshot software to obtain a screenshot of the blackboard.

[0085] Microphone array: Through different audio collection schemes and multi-microphone collection methods, various sounds of teachers and students in the target classroom can be collected.

[0086] Capture terminal: For example, a recording and broadcasting host, etc., is used to pull the teacher's panoramic stream from the teacher's panoramic camera and the student's panoramic stream from the student's panoramic camera. The teacher's panoramic stream and the student's panoramic stream are collectively referred to as the target classroom video. The capture terminal also pulls the target classroom's audio from the microphone array. The blackboard acquisition component collects the target classroom's blackboard. The capture terminal extracts frames from the above audio and video from the panoramic camera, blackboard acquisition component and microphone array and sends them to the computing power terminal. At the same time, the capture terminal records the course based on the pulled audio and video, so as to obtain the video file of the target classroom.

[0087] Upload module: The upload module is, for example, a node such as a router in the network, which is used to upload the video file recorded by the acquisition module for the target classroom to a server located in the cloud or at the edge.

[0088] Secondly, the computing power terminal.

[0089] The computing power terminal is used to perform visual analysis on the video of the target classroom to obtain video analysis results, and to perform auditory analysis on the audio of the target classroom to obtain audio analysis results.

[0090] The computing terminal uses various visual algorithms to perform visual analysis on the target classroom video to obtain specific algorithm results. Among them, visual algorithms include but are not limited to human detection algorithms, stand-up and sit-down recognition algorithms, and multi-target tracking algorithms. Face detection algorithms and optical character recognition (OCR) algorithms, etc. The OCR algorithm is mainly used to recognize the text in the blackboard taken by the blackboard camera, screenshots taken by the screenshot software, etc. to obtain the blackboard information. The algorithm results include teacher behavior, dress, posture, position tracking, student behavior, standing up and raising hands, looking up and down, position tracking, face recognition, etc.

[0091] In addition, the visual analysis algorithm can also be used to obtain student events, such as group discussions, classroom exercises, and other student events.

[0092] The computing power terminal uses the algorithm result as the video analysis result, or outputs the structured data in a certain format and uses the structured data as the video analysis result.

[0093] The computing terminal uses various audio algorithms to perform auditory analysis on the audio of the target classroom to obtain audio analysis results. Among them, audio algorithms include but are not limited to automatic speech recognition (ASR) algorithms, sound event recognition algorithms, voiceprint recognition algorithms, etc. Audio analysis results include but are not limited to text, sound events, who the specific speaker is, etc. Sound events refer to a sound that is noise, human speech, or reading aloud.

[0094] The computing power terminal provides the audio and video analysis results to the teaching model on the server side, so that the model can perform semantic analysis to obtain intermediate data.

[0095] In the embodiment of the present application, the computing power terminal is mainly used to provide analysis results, that is, mainly used to provide video analysis results and audio analysis results. As business needs change, the visual algorithm and audio algorithm can be expanded. At the same time, the rules for how to use the video analysis results and audio analysis results are determined by the cloud or edge teaching and evaluation services, the configuration parameters of the management platform, etc.

[0096] It should be noted that the computing terminal, as the hardware entity for audio analysis and video analysis, can be the same hardware as the acquisition terminal, or it can be a different hardware.

[0097] Again, cloud / edge.

[0098] In the embodiment of the present application, the teaching model, teaching evaluation service, and storage service are deployed on the server, and the server can be deployed in the cloud or at the edge. When the server is deployed at the edge, the teaching model is also called the edge model; when the server is deployed in the cloud, the teaching model is also called the cloud model.

[0099] The teaching big model is used to combine course information, blackboard information obtained by OCR, and student events obtained by CV, and conduct big model analysis on audio analysis results and video analysis results, so as to better combine the knowledge points and teaching scenarios of the course, more accurately identify semantics and teaching behaviors, and infer intermediate data. Intermediate data includes but is not limited to: the proportion of teachers' teaching behaviors, speech speed statistics, improvement suggestions, question and answer type analysis, Flanders interaction analysis, student-teacher teaching analysis, teacher behavior occupancy rate-student behavior occupancy rate (ST / Rt-Ch), etc.

[0100] The resource storage service is used to store video files recorded by the acquisition module.

[0101] The teaching evaluation service mainly has the following functions:

[0102] a. Generate teaching evaluation report.

[0103] Based on this function, the teaching evaluation service obtains video analysis results and audio analysis results from the computing power terminal; reads the configuration parameters of the target classroom from the management platform, and uses these data as the input of the teaching model so that the teaching model can infer intermediate data. Among them, the configuration parameters include the main dimension, sub-dimension, and weight of the sub-dimension of the target classroom. In addition, the input of the teaching model also includes course information.

[0104] Afterwards, the teaching evaluation service conducts teaching evaluation on the target class based on the intermediate data, video files, and configuration parameters indicating the evaluation requirements of the target class. For example, the teaching evaluation service combines the intermediate data obtained from the teaching big model, the video files of the target class obtained from the storage service, the weights and scoring rules obtained from the configuration parameters, etc. to obtain a teaching evaluation report, and sends the teaching evaluation report to the management platform for display by the visualization module of the management platform.

[0105] In the embodiment of the present application, the teaching evaluation report includes teaching scores, video files, scores and basis of each main dimension, growth suggestions, opinions in the course evaluation form, etc. Below, the evaluation system for calculating teaching scores is described in detail.

[0106] Exemplarily, the evaluation dimensions in the indicator library include main dimension A to main dimension N, the sub-dimensions of main dimension A include A1 to An, and the sub-dimensions of main dimension N include N1 to Nn. Each sub-dimension is set with several levels, such as excellent, good, and medium. The configuration table in the configuration table library defines the bonus points, weights, and conditions for each level of the indicator sub-dimension, that is, score X, score Y, score Z are set for each level, and weight coefficients x, y, z and basic scores are set for each level. In the process of determining the teaching score, the administrator can choose to adopt a bonus mechanism or a subtraction mechanism, and the total score is the teaching score.

[0107] The bonus mechanism is as follows:

[0108] The score of dimension A = (A1 rating score X + A2 evaluation score Y + ······ +An rating score Z) × weight coefficient x.

[0109] Total score = basic score + additional points in each dimension.

[0110] The deduction mechanism is as follows:

[0111] The deduction for dimension A = (A1 rating deduction X + A2 evaluation deduction Y + ······ +An rating deduction Z) × weight coefficient x.

[0112] Total score = total score - deduction points in each dimension.

[0113] In the embodiment of the present application, the default main dimensions include: teaching attitude, teaching design, teaching content, teaching methods, classroom literacy, etc.

[0114] The sub-dimensions of teaching evaluation include: lateness and early departure, teacher's mood, demeanor and dress, classroom order, etc.

[0115] Lateness and early departure: Through visual recognition, whether the teacher is on time for get out of class or not, the teacher will be graded according to the degree of lateness or early departure. The grading conditions are provided by the configuration table.

[0116] Teaching attitude: Visually identify the teacher's posture, movement frequency, facial expression, etc., and make graded judgments based on different levels of performance.

[0117] Demeanor and attire: Visual algorithms are used to identify teachers’ clothing types and demeanor, and to determine whether they are formally dressed, whether the length is appropriate, etc., and to make graded judgments.

[0118] Classroom order: The system uses visual algorithms to identify students’ attendance rate, head-up rate, front-row seating rate, lateness and early departure, etc., and then judges the classroom order. Classification is based on the percentage data of attendance rate, head-up rate, seating rate, and the number of latecomers and early leavers.

[0119] The sub-dimensions of teaching design include course review, course objectives, course summary, homework, setting questions, providing extracurricular resources, etc. The server identifies these sub-dimensions based on automatic speech recognition algorithms and large language models (LLM), combined with course information and courseware information.

[0120] The sub-dimensions of teaching content include whether the semantics contain disciplinary thinking, disciplinary history, interdisciplinary connections, disciplinary frontiers, case references, etc. The server identifies these sub-dimensions based on automatic speech recognition algorithms, LLM, etc., combined with course information, courseware information, etc.

[0121] The sub-dimensions of teaching methods include teacher questions, interactive behaviors, classroom inquiries, feedback evaluation, reminder difficulty, etc. The server identifies these sub-dimensions based on automatic speech recognition algorithms, LLM, etc.

[0122] The sub-dimensions of classroom literacy include critical thinking, providing opportunities for students to exercise their expression skills, and ideological and political education in the curriculum. Critical thinking refers to teachers asking open questions and encouraging students to analyze or answer different viewpoints. The server identifies these sub-dimensions based on automatic speech recognition algorithms, LLM, etc.

[0123] b. Self-study evaluation.

[0124] The configuration parameters obtained by the server from the management platform include not only the main dimension, sub-dimension, and weight of each sub-dimension of the target class, but also, optionally, the evaluation form of the target class, which is used to indicate the evaluator's evaluation of the target class. The teaching evaluation service generates first information based on the evaluation form, and the first information is used to indicate the modification of the weight and / or condition of the main dimension and sub-dimension of the target class.

[0125] Exemplarily, the evaluator is also called a supervisor, etc., and several evaluation dimensions are provided to the evaluator in advance, and the evaluator evaluates and scores the content of the target class according to these evaluation dimensions. In addition, the evaluator can also customize other evaluation dimensions and conduct evaluations. The management platform generates a class evaluation form for the target class based on the evaluator's evaluation content of several evaluation dimensions provided in advance and the evaluation content of the customized evaluation dimensions. The server obtains the class evaluation form of the target class from the management platform, summarizes and organizes the evaluation content of the evaluator in the class evaluation form, especially the evaluation content of the customized evaluation dimension, and generates first information through big data analysis, etc. The first information is used to indicate improvement suggestions for the main dimensions, sub-dimensions, and weights of sub-dimensions in the configuration parameters, for the administrator to refer to whether it is necessary to adjust the main dimensions, sub-dimensions, and weights of sub-dimensions of the target class, so as to make the configuration parameters more in line with the actual target class.

[0126] By adopting this solution, the first information for indicating modification of the evaluation dimensions, weights and / or conditions of the target classroom is automatically generated according to the course evaluation form, so that the administrator can adjust the configuration parameters of the target classroom to make the configuration parameters and the target classroom more adapted, thereby achieving the purpose of improving the quality of teaching evaluation.

[0127] c. Teacher growth evaluation.

[0128] The configuration parameters obtained by the server from the management platform include not only the main dimension, sub-dimension, and weight of the sub-dimension of the target classroom, but may also optionally include multiple teaching evaluation reports.

[0129] In one embodiment, the plurality of teaching evaluation reports are a plurality of teaching evaluation reports of a target teacher within a preset time period, and the target teacher is a lecturer of the target class. The teaching service generates second information according to the plurality of teaching evaluation reports, and the second information is used to indicate teaching suggestions for the target teacher.

[0130] Exemplarily, the preset time period is, for example, a school year, a semester, a month, a week, etc. The teaching evaluation database of the management platform stores the teaching evaluation reports for each semester and each class. Taking the preset time period as a semester as an example, the server reads all the teaching evaluation reports of the target teacher in this semester from the teaching evaluation database of the management platform. These teaching evaluation reports reflect the performance and growth of the target teacher in this semester. The teaching evaluation service on the server generates second information for the target teacher from the teacher dimension. The second information is used for improvement suggestions so that the target teacher can improve the teaching according to the second information.

[0131] In addition, by adjusting the preset time period, target teachers, evaluators, etc. can examine the target teachers' teaching level, performance appraisal, etc. from different time dimensions.

[0132] By adopting this solution, the second information is generated with teachers as the dimension, and the target teachers improve their teaching according to the second information, thereby achieving the purpose of improving teaching quality.

[0133] In another embodiment, the multiple evaluation reports are multiple teaching evaluation reports of target subjects within a preset time period. The target subject is the subject corresponding to the target class, and the teaching evaluation reports are obtained by evaluating the classes of multiple teachers who teach the target subject. The teaching evaluation service on the server generates third information based on the teaching evaluation report, and the third information is used to indicate teaching suggestions for the target subject.

[0134] Exemplarily, the preset time period is, for example, a school year, a semester, a month, a week, etc. The teaching evaluation report for each semester and each class is stored in the teaching evaluation database of the management platform. Taking the preset time period as a semester as an example, the server reads all the teaching evaluation reports of the target subject in this semester from the teaching evaluation database of the management platform. For example, there are a total of 5 teachers teaching the target subject, and these 5 teachers only teach the target subject, then the server reads all the teaching evaluation reports of these 5 teachers. If a teacher teaches other subjects in addition to the target subject, the server only reads the teaching evaluation report of the target subject.

[0135] After the server obtains all teaching evaluation reports of the target subject, it counts the outstanding performances of each lecturer based on these teaching evaluation reports, and generates third information based on the outstanding performances for teachers in the subject to learn from each other and improve.

[0136] By adopting this solution, the third information is generated based on the subject dimension, and each teacher improves the teaching of the target subject based on the third information to achieve the goal of improving teaching quality.

[0137] Finally, the management platform.

[0138] The management platform is also called the teaching quality management platform, which is used to provide customized services to customize configuration parameters for target classes, visualize teaching evaluation reports, and manage class schedules. For details, please refer to I~III below.

[0139] I. Customized service.

[0140] Different schools, different majors, and different subjects have different teaching and evaluation needs. Some subjects are more theoretical, while others are more practical. The management platform provides customized services, allowing different schools and majors to customize the configuration parameters of the target classroom according to their own needs.

[0141] Multiple databases are deployed on the management platform, such as the indicator library, configuration table library, course evaluation table library, report library, etc. Schools and majors with different needs select the main dimension and sub-dimensions of each main dimension from the indicator library according to their own evaluation needs, and select the weight and conditions of each sub-dimension from the configuration table library.

[0142] Below, these databases are described in detail.

[0143] 1) Indicator library.

[0144] The indicator library defines multiple evaluation dimensions. The default evaluation dimensions include: teaching attitude, teaching design, teaching content, teaching methods, classroom literacy and other dimensions and their sub-dimensions. For example, the evaluation dimensions in the indicator library include main dimension A~main dimension N, the sub-dimensions of main dimension A include A1~An, and the sub-dimensions of main dimension N include N1~Nn. Each sub-dimension is set with several levels, such as excellent, good, and medium.

[0145] 2) Configure the table library.

[0146] The configuration table library is used to store configuration tables, which indicate the optional extra score weights and conditions for each sub-dimension, and are used to configure the weights and conditions of each sub-dimension. By configuring the weights and conditions of each sub-dimension, it is possible to adapt to the teaching characteristics and assessment requirements of different schools and majors.

[0147] 3) Course evaluation form library.

[0148] The school supervisor will regularly inspect the courses, evaluate the target classroom according to several preset evaluation dimensions and custom evaluation dimensions, and obtain the evaluation form of the target classroom, which is stored in the evaluation form library. The purpose of improving the efficiency of the supervisor's inspection is achieved through the evaluation form.

[0149] In order to obtain the evaluation form of the target class, on the one hand, several evaluation dimensions are provided for supervisors to evaluate and score the content of the target class; on the other hand, custom evaluation dimensions are added for supervisors to customize the evaluation dimensions and evaluate the target class. The management platform evaluates the target class according to several preset evaluation dimensions and custom evaluation dimensions to obtain the evaluation form of the target class.

[0150] In the embodiment of the present application, the evaluation form of each semester, each subject, and each teacher's class is stored on the management platform to form an evaluation form library. The server reads the evaluation form of the target class to generate first information, which is used to indicate the modification of the evaluation dimension, the weight and / or condition of the evaluation dimension of the target class.

[0151] 4) Report library.

[0152] The teaching evaluation report of each class is stored as the school's asset, and the teaching evaluation report is summarized according to teacher dimensions, subject dimensions, etc. The development trends and trajectories of teachers are observed over the long term in units of semesters, academic years, etc.

[0153] II. Visual display of teaching evaluation report.

[0154] The management platform can visually display the teaching evaluation report, making it easier for users to view the teaching evaluation report by intuitively displaying the teaching evaluation report.

[0155] When it is necessary to display the teaching evaluation report of the target classroom, the management platform obtains the teaching evaluation report of the target classroom from the application database based on the ID of the target classroom, and displays at least one of the following information based on the teaching evaluation report: video file, comprehensive evaluation of the target classroom, scores of each evaluation dimension, growth suggestions, and opinions in the course evaluation form.

[0156] Exemplarily, the management platform displays the teaching evaluation report through a visualization module. The visualization module includes several sections: a video browsing section, an evaluation score section, a section for displaying the scores of each evaluation dimension and the basis, growth suggestions, supervisory evaluation, etc. The management platform plays video files through the video browsing section; displays the comprehensive evaluation of the target class through the evaluation score section, and the comprehensive evaluation is reflected, for example, through the teaching score; the score of each evaluation dimension is based on the event in the video file, based on the time period of the event, etc., through which the video file can be quickly located to the time when the event occurred. Supervisory evaluation is, for example, the evaluation content of the supervisor in the class evaluation form, etc.

[0157] With this solution, the management platform displays a variety of information such as video files, comprehensive evaluations, and growth suggestions when displaying teaching evaluation reports, thereby quickly and comprehensively displaying the teaching evaluation reports of the target classroom.

[0158] III. Timetable management.

[0159] Based on the timetable management function, the management platform records all the course information of the school and sends it to the collection terminal at the right time, thereby triggering the collection terminal to record the course and collect audio and video according to the start and end time of the target course.

[0160] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0161] Figure 5 A schematic diagram of a teaching evaluation device provided in an embodiment of the present application. The teaching evaluation device 500 is integrated on a server, and includes: an acquisition module 51 , a processing module 52 , and an evaluation module 53 .

[0162] An acquisition module 51 is used to acquire video analysis results, audio analysis results, and configuration parameters of a target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analyzing the audio collected from the target classroom, and the configuration parameters are used to indicate the evaluation requirements of the target classroom;

[0163] A processing module 52, configured to generate intermediate data according to the video analysis result, the audio analysis result and the configuration parameters;

[0164] The evaluation module 53 is used to perform teaching evaluation on the target classroom according to the intermediate data, the video file and the configuration parameters, and the video file is recorded from the target classroom.

[0165] In a feasible implementation, the evaluation module 53 is used to determine the evaluation dimensions of the target classroom according to the configuration parameters, the evaluation dimensions including the main dimension and the sub-dimensions under the main dimension; determine the weights and / or conditions of the sub-dimensions according to the configuration parameters; and perform teaching evaluation on the target classroom according to the main dimension of the target classroom, the weights and / or conditions of the sub-dimensions under the main dimension, the intermediate data and the video file.

[0166] In a feasible implementation, the processing module 52 is also used to generate first information based on the course evaluation form in the configuration parameters, the course evaluation form is used to indicate the evaluator's evaluation of the target class, and the first information is used to indicate the modification of the evaluation dimension of the target class.

[0167] In a feasible implementation, the processing module 52 is also used to obtain multiple teaching evaluation reports of a target teacher within a preset time period based on the target classroom, and the target teacher is the lecturer of the target classroom; and generate second information based on the multiple teaching evaluation reports, and the second information is used to indicate teaching suggestions for the target teacher.

[0168] In a feasible implementation, the processing module 52 is also used to obtain multiple teaching evaluation reports of the target subject within a preset time period based on the target classroom, the target subject is the subject corresponding to the target classroom, and the multiple teaching evaluation reports are obtained by conducting teaching evaluations on classes of multiple teachers who teach the target subject; third information is generated based on the multiple teaching evaluation reports, and the third information is used to indicate teaching suggestions for the target subject.

[0169] The teaching evaluation device provided in the embodiment of the present application can execute the actions of the server in the above embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0170] Figure 6 Another schematic diagram of the teaching evaluation device provided in the embodiment of the present application. The teaching evaluation device 600 is integrated on the management platform, and the teaching evaluation device 600 includes: a display module 61 , a processing module 62 , and a transceiver module 63 .

[0171] A display module 61, used to display a configuration interface of a target classroom, where the configuration interface is used to configure evaluation requirements of the target classroom;

[0172] A processing module 62, for generating configuration parameters of the target classroom in response to an operation on the configuration interface, wherein the configuration parameters are used to indicate evaluation requirements of the target classroom;

[0173] The transceiver module 63 is used to send the configuration parameters to the server so that the server can perform teaching evaluation on the target classroom according to the configuration parameters.

[0174] In a feasible implementation, the processing module 62 is used to determine the evaluation dimension of the target classroom from the indicator library according to the operation of the configuration interface, the indicator library stores multiple evaluation dimensions for selection, and the evaluation dimension includes a main dimension and a sub-dimension under the main dimension; determine the weight and / or condition of the sub-dimension from the configuration table library, and the configuration table library stores multiple weights and conditions for selection of each sub-dimension; generate the configuration parameters of the target classroom according to the main dimension of the target classroom and the weight and / or conditions of the sub-dimension under the main dimension; wherein the management platform stores multiple databases, and the multiple databases include the indicator library, the configuration table library, the course evaluation table library, and the report library, the course evaluation table library stores multiple course evaluation tables, and different course evaluation tables are used to indicate the evaluator's evaluation of different classes, and the report library stores multiple teaching evaluation reports.

[0175] In a feasible implementation, the processing module 62 is further used to obtain a teaching evaluation report of the target classroom;

[0176] The display module 61 is also used to display at least one of the following information according to the teaching evaluation report: video files, comprehensive evaluation of the target class, scores of each evaluation dimension, growth suggestions, and opinions in the course evaluation form.

[0177] The teaching evaluation device provided in the embodiment of the present application can execute the actions of the management platform in the above-mentioned embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0178] Figure 7 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, the electronic device is, for example, the above-mentioned server or management platform. Figure 7The electronic device 700 described in the embodiment of the present application includes: at least one processor 71, at least one communication bus 72, a user interface 73, at least one network interface 74 and a memory 75.

[0179] The communication bus 72 is used to realize the connection and communication between these components.

[0180] The user interface 73 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 73 may also include a standard wired interface and a wireless interface. The display screen is used to display an editing interface, a roaming interface, and the like.

[0181] The network interface 74 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0182] Among them, the processor 71 may include one or more processing cores. The processor 71 uses various interfaces and lines to connect various parts of the entire electronic device 700, and executes various functions and processes data of the electronic device 700 by running or executing instructions, programs, code sets or instruction sets stored in the memory 75, and calling data stored in the memory 75. Optionally, the processor 71 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 71 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the panoramic ball required to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 71, and can be implemented separately through a chip.

[0183] Among them, the memory 75 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 75 includes a non-transitory computer-readable storage medium. The memory 75 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 75 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 75 may also be optionally at least one storage device located away from the aforementioned processor 71. As Figure 7 As shown, the memory 75 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an operating application of the electronic device.

[0184] An embodiment of the present application also provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed by a processor, they are used to implement the teaching evaluation method as described above.

[0185] An embodiment of the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the teaching evaluation method as described above is implemented.

[0186] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0187] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of the processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0188] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0189] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0190] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0191] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0192] Computer readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0193] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0194] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A teaching evaluation method, characterized in that: Applied to a server, the method comprises: Obtaining the video analysis results, audio analysis results, and configuration parameters of the target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analyzing the audio collected from the target classroom, and the configuration parameters are used to indicate the evaluation requirements of the target classroom; Generate intermediate data according to the video analysis result, the audio analysis result and the configuration parameters; A teaching evaluation is performed on the target classroom according to the intermediate data, the video file and the configuration parameters, and the video file is recorded from the target classroom.

2. The method according to claim 1, characterized in that The performing teaching evaluation on the target classroom according to the intermediate data, the video file and the configuration parameters comprises: Determine the evaluation dimension of the target classroom according to the configuration parameters, wherein the evaluation dimension includes a main dimension and a sub-dimension under the main dimension; Determining the weight and / or condition of the sub-dimension according to the configuration parameters; A teaching evaluation is performed on the target classroom according to the main dimension of the target classroom, the weights and / or conditions of the sub-dimensions under the main dimension, the intermediate data and the video file.

3. The method according to claim 1, characterized in that Also includes: The first information is generated according to the lesson evaluation form in the configuration parameters, the lesson evaluation form is used to indicate the evaluator's evaluation of the target class, and the first information is used to indicate the modification of the evaluation dimension of the target class.

4. The method according to any one of claims 1 to 3, characterized in that Also includes: Acquiring multiple teaching evaluation reports of a target teacher within a preset time period according to the target classroom, the target teacher being a lecturer of the target classroom; Second information is generated based on the multiple teaching evaluation reports, and the second information is used to indicate teaching suggestions for the target teacher.

5. The method according to any one of claims 1 to 3, characterized in that: Also includes: Acquire multiple teaching evaluation reports of a target subject within a preset time period according to the target classroom, wherein the target subject is a subject corresponding to the target classroom, and the multiple teaching evaluation reports are obtained by conducting teaching evaluations on classes of multiple teachers who teach the target subject; The third information is generated according to the plurality of teaching evaluation reports, and the third information is used to indicate teaching suggestions for the target subject.

6. A teaching evaluation method, characterized in that: Applied to a management platform, the method includes: Displaying a configuration interface of a target classroom, wherein the configuration interface is used to configure evaluation requirements of the target classroom; In response to an operation on the configuration interface, generating configuration parameters of the target classroom, the configuration parameters being used to indicate evaluation requirements of the target classroom; The configuration parameters are sent to a server so that the server performs a teaching evaluation on the target classroom according to the configuration parameters.

7. The method according to claim 6, characterized in that The generating of the configuration parameters of the target classroom in response to the operation on the configuration interface includes: According to the operation on the configuration interface, the evaluation dimension of the target classroom is determined from an indicator library, wherein the indicator library stores a plurality of evaluation dimensions for selection, and the evaluation dimension includes a main dimension and sub-dimensions under the main dimension; Determine the weight and / or condition of the sub-dimension from a configuration table library, wherein the configuration table library stores a plurality of weights and conditions for selection of each sub-dimension; Generate configuration parameters of the target classroom according to the weights and / or conditions of the main dimension of the target classroom and the sub-dimensions under the main dimension; Among them, the management platform stores multiple databases, and the multiple databases include the indicator library, the configuration table library, the course evaluation table library, and the report library. The course evaluation table library stores multiple course evaluation tables, and different course evaluation tables are used to indicate the evaluator's evaluation of different classes. The report library stores multiple teaching evaluation reports.

8. The method according to claim 6 or 7, characterized in that: Also includes: Obtaining a teaching evaluation report of the target classroom; At least one of the following information is displayed according to the teaching evaluation report: video files, comprehensive evaluation of the target class, scores of each evaluation dimension, growth suggestions, and opinions in the course evaluation form.

9. A teaching evaluation device, characterized in that: The device is integrated on a server, and comprises: An acquisition module, used to acquire video analysis results, audio analysis results and configuration parameters of a target classroom, wherein the video analysis results refer to data obtained by visually analyzing the video collected from the target classroom, the audio analysis results refer to data obtained by auditory analysis of the audio collected from the target classroom, and the configuration parameters are used to indicate the evaluation requirements of the target classroom; A processing module, used to generate intermediate data according to the video analysis result, the audio analysis result and the configuration parameters; An evaluation module is used to perform teaching evaluation on the target classroom based on the intermediate data, the video file and the configuration parameters, and the video file is recorded from the target classroom.

10. A teaching evaluation device, characterized in that: The device is integrated on a management platform, and comprises: A display module, used to display a configuration interface of a target classroom, wherein the configuration interface is used to configure evaluation requirements of the target classroom; A processing module, for generating configuration parameters of the target classroom in response to an operation on the configuration interface, wherein the configuration parameters are used to indicate evaluation requirements of the target classroom; The transceiver module is used to send the configuration parameters to the server so that the server can perform teaching evaluation on the target classroom according to the configuration parameters.

11. An electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the electronic device implements the method according to any one of claims 1 to 8.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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