Integrated ideological and political lesson teaching effect dynamic evaluation system

Abstract

The invention discloses an integrated ideological and political course teaching effect dynamic evaluation system, and belongs to the technical field of teaching evaluation. Comprising a camera and an arranged campus local area network, and the camera is arranged at the top of a classroom and collects images of all students in class time; the local area network comprises a front end, a rear end and a memory which are connected in sequence; the front end comprises personal data, pre-class preparation, class pages, after-class conditions and student evaluation; the rear end comprises an information authentication module, an administrator module, a pre-class module, an in-class module and an after-class module; and data contents used by the front end and the rear end and image data acquired by the camera are recorded in the memory. By adopting the system, the teaching effect of the classroom is dynamically evaluated through the behavior analysis network and the attention calculation network, and a teacher can be helped to quickly know the conditions of students through various congruent data, so that the attention of the students is quickly improved in the classroom, and an improved means is provided for teaching after the classroom.

Description

Technical Field

[0001] The present invention relates to the technical field of teaching evaluation, and in particular to an integrated dynamic evaluation system for the teaching effect of ideological and political courses. Background Art

[0002] The study of ideological and political courses belongs to political courses and is an important link in cultivating students' ideological qualities and social responsibilities. Therefore, various universities have offered a series of ideological and political related courses. However, in the existing evaluation criteria, teachers often have difficulty clearly understanding the performance of students because they are in charge of learning tasks. If they invest too much energy in students, it will affect teaching tasks. But in the current classroom form, one-way teaching makes it difficult for teachers to estimate their own classroom content, and it is impossible to establish the scanning factors related to students' attention performance and teaching effect. Often, they can only correct it by the way of outsiders attending classes. Therefore, it is not good to adjust the content of the courseware. Summary of the Invention

[0003] The purpose of the present invention is to provide an integrated dynamic evaluation system for the teaching effect of ideological and political courses, which calculates the unity of students' behaviors through a behavior network to judge the real-time score of the current teaching, facilitates teachers to control the teaching direction and the overall situation of students in a timely manner, calculates the attention performance of students through face recognition, evaluates the teaching effect based on the attention performance and the analysis of homework, and teachers can review their teaching process, so as to make reasonable improvements and better meet the teaching requirements.

[0004] To achieve the above purpose, the present invention provides an integrated dynamic evaluation system for the teaching effect of ideological and political courses, including a camera and an in-school local area network arranged. The camera is arranged on the top of the classroom to collect images of all students during class time; the local area network includes a front end, a back end, and a memory connected in sequence;

[0005] The front end includes personal information, pre-class preparation, in-class page, after-class situation, and student evaluation;

[0006] The back end includes an information authentication module, an administrator module, a pre-class module, an in-class module, and an after-class module;

[0007] The memory stores the data content used by the front end and the back end, as well as the image data collected by the camera.

[0008] Preferably, the specific content of the front end is as follows:

[0009] Personal information includes name, gender, age, teacher's photo, and the class managed;

[0010] Pre-class preparation includes showing the knowledge chain, ability chain, and value chain of the current teaching progress, which are filled in by the teacher;

[0011] The class page includes the courseware page, real-time scores, attention average curve graph, attention area graph, and images captured by the camera;

[0012] The after-class situation includes a homework situation module, in-class statistics module, and courseware prediction module classified by class;

[0013] Student evaluations include students' self-evaluations and peer evaluations.

[0014] Preferably, the specific content of the backend is as follows:

[0015] The information authentication module records the login information of teachers. Teachers authenticate and log in through the web page on the computers in the classroom within the school;

[0016] The administrator module allows administrators to adjust teacher information, the classes managed by teachers, and system maintenance;

[0017] The pre-class module records the content of the knowledge chain, ability chain, and value chain filled in by teachers in sequence according to the time axis;

[0018] The knowledge chain includes the ideological and political information knowledge that students in different academic stages need to learn accordingly;

[0019] The ability chain records the ideological and political knowledge mastered by students in different academic stages accordingly;

[0020] The value chain records the ideological and political value knowledge that students in different academic stages need to learn accordingly;

[0021] The in-class module provides the data content of the front-end class page, specifically as follows:

[0022] The courseware page is the courseware used by teachers during class, and records the time that different contents in the courseware stay according to time;

[0023] The real-time score calculates the real-time score by comprehensively analyzing the students' behavior situations based on the images captured by the camera, and provides it to the front-end accordingly, facilitating teachers to judge whether to boost the classroom order to improve the real-time score based on the real-time score;

[0024] The attention average curve graph selects pictures at intervals of 60 frames based on the images captured by the camera, calculates the attention of students in each picture, and calculates the attention average curve graph and provides it to the front-end accordingly, facilitating teachers to understand the class status of the entire class in real time;

[0025] The attention area graph draws the attention area graph of each student according to the position of the students based on the calculation results of the attention of students in each picture calculated previously, and provides it to the front-end after integration, facilitating teachers to find students with inattentive attention through the attention area graph and take corresponding measures;

[0026] The image captured by the camera is directly transmitted to the front end, facilitating teachers to observe students from another perspective;

[0027] The after-class module provides data content on the after-class situation in the front end, specifically as follows:

[0028] The homework situation module calculates the error rate of the questions for students' homework through the statistics module, arranges them from high to low, and feeds them back to the front end accordingly, facilitating teachers to identify students' problems and correct them in the next class;

[0029] The in-class statistics module records the content displayed in the in-class module for each class in chronological order, facilitating teachers to find the corresponding situation during class based on the error rate and make corresponding teaching improvements;

[0030] The courseware prediction module is used to detect problems in the courseware. Based on the error rate reflected by the homework situation module, it records the arrangement of corresponding knowledge points in the courseware. When the same content arrangement appears in the courseware to be detected, the courseware prediction module prompts the user of the courseware to be detected, facilitating teachers to make improvements.

[0031] Preferably, the implementation process of the backend is as follows:

[0032] For real-time scores, YoloV5 combined with Openpose is used to calculate the real-time scores by calculating the behavioral unity of students; for the average attention curve graph, a face detection algorithm is used to calculate the attention based on students' head movements and facial expressions and perform mathematical statistics to obtain the average attention curve graph; for the attention area graph, a corresponding area graph is formed according to the attention of each student.

[0033] Therefore, the present invention adopts the above-mentioned integrated ideological and political education teaching effect dynamic evaluation system, which has the following advantages:

[0034] In the present invention, by analyzing the unity of students' behaviors, the classroom order and teaching effect can be quickly and accurately judged, and then real-time scores can be given, enabling teachers to quickly grasp the classroom situation. The attention of the pictures captured by the camera is calculated through a neural network, thereby recording the classroom state accordingly, facilitating teachers to conduct after-class analysis and summary, and continuously improving the teaching effect.

[0035] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a structural diagram of the front end of an integrated ideological and political education teaching effect dynamic evaluation system of the present invention;

[0037] Figure 2 This is the structure diagram of the backend of an integrated ideological and political education course teaching effect dynamic evaluation system of the present invention. Detailed implementation manners

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the accompanying drawings here can be arranged and designed in various different configurations. The specific model specifications need to be selected and determined according to the actual specifications of the device, etc. The specific selection calculation system adopts the existing technologies in the art, so it will not be elaborated in detail.

[0039] Embodiment

[0040] As Figure 1 shown, the present invention provides an integrated ideological and political education course teaching effect dynamic evaluation system, including a camera and an arranged campus local area network. The camera is arranged on the top of the classroom to collect images of all students during class time. The local area network includes a front end, a backend, and a memory connected in sequence;

[0041] The front end includes personal information, pre-class preparation, in-class page, after-class situation, and student evaluation;

[0042] The backend includes an information authentication module, an administrator module, a pre-class module, an in-class module, and an after-class module;

[0043] The memory records the data content used by the front end and the backend, as well as the image data collected by the camera.

[0044] The specific content of the front end is as follows: Personal information includes name, gender, age, teacher's photo, and the managed class. The managed class is divided through the administrator module to determine the class managed by the teacher

[0045] The in-class page includes a courseware page, real-time scores, an average attention curve graph, an attention area graph, and the image collected by the camera. When the in-class page is opened during class, the system will provide all the above-mentioned content on the screen correspondingly, facilitating the teacher to intuitively understand the in-class status of the students and the students who do not attend class well;

[0046] The after-class situation includes a homework situation module, an in-class statistics module, and a courseware prediction module classified by class; The after-class situation is used by the teacher after class, which can review the status of the students during class, analyze the homework situation, and combine the homework situation and the student status to locate the problems in the courseware, so as to improve the courseware and record the problems to avoid repeating mistakes next time;

[0047] Student evaluations, including students' self-evaluations and peer evaluations, enable teachers to better understand the internal situation of students and facilitate management.

[0048] The specific content of the backend is as follows: an information authentication module that records the login information of teachers. Teachers can authenticate and log in through the web page on the computers in the classrooms within the school, and different classes can also log in quickly for convenient use.

[0049] An administrator module where administrators can adjust teacher information, the classes managed by teachers, and system maintenance to ensure the proper operation of the system.

[0050] The pre-class module records the content of the knowledge chain, ability chain, and value chain filled in by teachers in sequence according to the time axis;

[0051] The knowledge chain includes the ideological and political information knowledge that students in different academic stages need to learn. It is set according to the time axis and, under the guidance of the value chain, the ideological and political information knowledge is arranged accordingly;

[0052] The ability chain records the ideological and political knowledge mastered by students in different academic stages. It mainly records that the value chain in the past learning was the knowledge chain, thereby realizing the recording of the abilities mastered by students;

[0053] The value chain records the ideological and political value knowledge that students in different academic stages need to learn, including the mainstream ideological viewpoints of ideological and political courses, such as environmental protection values, national values, etc., which are used to guide the arrangement of knowledge content in the knowledge chain;

[0054] The in-class module provides the data content of the front-end class page, specifically as follows:

[0055] The courseware page shows the courseware used by teachers during class. The time that different contents in the courseware stay is recorded according to time. Through time recording, the specific time for explaining knowledge points can be confirmed.

[0056] Real-time scores are calculated by comprehensively analyzing students' behaviors based on the images collected by the camera using a behavior network and provided to the front-end accordingly. This enables teachers to determine whether to boost classroom order to improve real-time scores based on the real-time scores. For real-time scores, YoloV5 combined with Openpose is used to calculate the real-time scores by calculating the behavioral unity of students;

[0057] Attention average curve graph. Based on the images collected by the camera, pictures are selected at intervals of 60 frames, the attention of students in each picture is calculated, and the attention average curve graph is calculated accordingly and provided to the front end to facilitate teachers to understand the class status of the entire class in real time. For the attention average curve graph, a face detection algorithm is adopted to calculate the attention based on the head movements and facial expressions of students, and mathematical statistics are performed to obtain the attention average curve graph.

[0058] Attention area graph. Based on the calculation results of the attention of students in each picture calculated previously, according to the positions of the students, the attention area graph of each student is drawn according to the seat map, and after integration, it is provided to the front end accordingly to facilitate teachers to find students with inattentive attention through the attention area graph and take corresponding measures. For the attention area graph, corresponding area graphs are formed according to the attention of each student, so as to facilitate teachers to quickly find students with low attention.

[0059] Images collected by the camera. The images collected by the camera are directly transmitted to the front end to facilitate teachers to observe students from another angle.

[0060] After-class module. It provides the data content of the after-class situation in the front end, specifically as follows:

[0061] Homework situation module. For the homework of students, the error rate of the questions is calculated through the statistics module and arranged from high to low, and the corresponding feedback is sent to the front end to facilitate teachers to find the problems of students and correct them in the next class.

[0062] In-class statistics module. For each class, the content shown in the in-class module is recorded in chronological order to facilitate teachers to find the corresponding situations during class according to the error rate and make corresponding teaching improvements.

[0063] Courseware prediction module. It is used to detect problems in the courseware. Based on the error rate reflected by the homework situation module, the arrangement of corresponding knowledge points in the courseware is recorded. When the same content arrangement appears in the detected courseware, the courseware prediction module prompts the user of the detected courseware to facilitate teachers to make improvements.

[0064] Therefore, the present invention adopts an integrated dynamic evaluation system for the teaching effect of ideological and political courses. By analyzing the unity of students' behaviors, it can quickly and accurately judge the classroom order and teaching effect, and then give real-time scores, enabling teachers to quickly grasp the classroom situation. And through the neural network, the attention of the pictures collected by the camera is calculated, so as to record the state of the classroom accordingly, facilitating teachers to conduct after-class analysis and summary, and continuously improving the teaching effect.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An integrated ideological and political teaching effect dynamic evaluation system, characterized by: It includes a camera and a school local area network, wherein the camera is arranged on the top of the classroom to collect images of all students during class time; the local area network includes a front end, a back end, and a storage device connected in sequence; The front end includes personal information, pre-class preparation, class page, post-class situation and student evaluation; The backend includes information authentication module, administrator module, pre-class module, in-class module, and after-class module; The memory records the data content used by the front-end and back-end as well as the image data collected by the camera.

2. According to claim 1, the integrated ideological and political teaching effect dynamic evaluation system is characterized by: The specific contents of the front end are as follows: Personal information includes name, gender, age, teacher photo and classes managed; Preparation before class includes showing the knowledge chain, ability chain and value chain of the current teaching progress, and teachers fill in the corresponding information; The class page includes the courseware page, real-time scores, attention average curve graph, attention area graph, and images collected by the camera; After-class status includes homework status module classified by class, class statistics module and courseware prediction module; Student evaluation, including students' self-evaluation and peer evaluation.

3. According to claim 2, the integrated ideological and political teaching effect dynamic evaluation system is characterized by: The specific contents of the backend are as follows: The information authentication module records the login information of teachers. Teachers can log in through the web page on the computer in the classroom. Administrator module, where administrators adjust teacher information, teacher-managed classes, and system maintenance; In the pre-class module, the contents of the knowledge chain, competence chain and value chain filled in by the teacher are recorded accordingly in the order of the timeline; The knowledge chain includes the ideological and political information knowledge that students at different stages of education need to learn; The competency chain records the ideological and political knowledge that students at different stages of study have mastered; The value chain records the ideological and political values ​​knowledge that students at different stages of education need to learn; The in-class module provides the data content of the front-end class page, as follows: Courseware page, the courseware used by the teacher in class, records the time spent on different contents in the courseware; Real-time scores: Based on the images captured by the camera, the behavioral network is used to analyze the students' behaviors and calculate the real-time scores. The scores are then provided to the front end, so that teachers can judge whether to improve the classroom order to improve the real-time scores. The average attention curve is based on the images collected by the camera, and pictures are selected at intervals of 60 frames. The attention of students in each picture is calculated, and the average attention curve is calculated accordingly and provided to the front end, so that teachers can understand the class status of the entire class in real time; Attention area map: Based on the calculation results of the students’ attention in each picture, the attention area map of each student is drawn according to the students’ positions and the seating map. After integration, it is provided to the front end accordingly, so that teachers can find the students who are not paying attention through the attention area map and take corresponding measures; The images collected by the camera are directly transmitted to the front end, which is convenient for teachers to observe students from another angle; The after-school module provides data content about after-school situations in the front end, as follows: Homework status module: For students' homework, the error rate of questions is calculated through the statistics module, and the questions are arranged from high to low. The corresponding feedback is sent to the front end, which makes it easier for teachers to find students' problems and correct them in the next class; The class statistics module records the contents of each class in chronological order, which is convenient for teachers to find the corresponding situations in class according to the error rate and make corresponding teaching improvements. The courseware prediction module is used to detect problems in the courseware. According to the error rate reflected by the homework status module, the arrangement of corresponding knowledge points in the courseware is recorded. When the same content arrangement appears in the tested courseware, the courseware prediction module prompts the users of the tested courseware to facilitate teachers to make improvements.

4. According to claim 3, the integrated ideological and political teaching effect dynamic evaluation system is characterized by: The backend implementation process is as follows: For real-time scores, YoloV5 combined with Openpose is used to calculate the real-time scores by calculating the uniformity of students' behaviors; for the average attention curve, a face detection algorithm is used based on The students’ head movements and facial expressions are used to calculate their attention, and mathematical statistics are performed to obtain an average attention curve. For the attention area map, a corresponding area map is formed according to the attention of each student.

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