WO2019223543A1

WO2019223543A1 - Teaching analysis method and server, and computer-readable storage medium

Info

Publication number: WO2019223543A1
Application number: PCT/CN2019/086191
Authority: WO
Inventors: 韩璧丞; 杨钊祎; 刘晨皓; 萧凯中; 郑辉; 单思聪; 阿迪斯; 于翔; 程交; 程翼
Original assignee: 深圳市心流科技有限公司
Priority date: 2018-05-23
Filing date: 2019-05-09
Publication date: 2019-11-28
Also published as: CN108805762A

Abstract

Disclosed is a teaching analysis method. The method comprises: acquiring attention indexes and synchronization rates of all students in one class, wherein the attention index represents the average attention of the students during a whole lesson, and the synchronization rate represents a synchronization degree between the attention of a student during the whole lesson and the average attention of the whole class; according to the attention index and the synchronization rate of each student, correspondingly evaluating the attention level and the synchronization rate level of each student; respectively counting the number of students with the same attention level and the same synchronization rate level to obtain a whole-class attention level distribution condition and a whole-class synchronization rate level distribution condition; and generating a teaching analysis report of the whole class according to the whole-class attention level distribution condition and the whole-class synchronization rate level distribution condition. Further disclosed are a teaching analysis server and a computer-readable storage medium. The present application can quantitatively and visually display the lesson-listening effect of students in one class.

Description

Teaching analysis method, server and computer-readable storage medium Ranch

This application claims priority from a Chinese patent application filed on May 23, 2018 with the Chinese Patent Office, application number 201810504361.8, and application name "Teaching Analysis Method, Server, and Computer-readable Storage Medium", the entire contents of which are incorporated by reference. In the application.

Technical field

The present application relates to the field of data analysis technology, and in particular, to a teaching analysis method, a server, and a computer-readable storage medium.

Background technique

At present, the teacher's evaluation of the lecture effect can only be assessed by means of staged assessment exams or questioning during the class. It is not possible to have a more quantitative and intuitive understanding of the effect of the lectures of the entire class, such as how many students are listening carefully in the classroom. How many students have not listened very carefully, and how many students have been constantly waiting, which is not conducive to the teacher's timely and accurate grasp of the effect of the class's students.

Summary of the Invention

The main purpose of this application is to propose a teaching analysis method, a server, and a computer-readable storage medium, which are intended to quantify and intuitively show the effect of the lectures of the entire class.

In order to achieve the above objective, the present application provides a teaching analysis method. The teaching analysis method includes the following steps:

Obtain the attention index and synchronization rate of each student in the entire class. The attention index indicates the average attention of the student during the entire class, and the synchronization rate indicates the concentration of the student's attention during the entire class and the average attention of the entire class. Degree of synchronization

According to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level;

Count the number of students at the same attention level and the same synchronization rate level to get the distribution of the attention level and the synchronization rate of the whole class;

According to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class, a teaching analysis report of the entire class is generated.

Optionally, the step of obtaining the attention index and synchronization rate of each student in the entire class includes:

Obtain and analyze the EEG data of each student in the class during the class, and obtain the attention index and the change curve of each student's attention, as well as the average change curve of the entire class;

For each student, analyze the degree of coincidence between the attention change curve and the average attention change curve of the whole class, and use the degree of agreement as its synchronization rate.

Optionally, the steps of obtaining and analyzing the EEG data of each student in the class during the class, obtaining the attention index and the attention change curve of each student, and the average attention change curve of the class include:

Receive the EEG data of each student in the class sent by the EEG data acquisition device during the class;

Converting the received EEG data into a corresponding attention index according to a preset correspondence between the EEG data and the attention index;

For each student, find the average value of their attention index at each time point during the class, and use it as their attention index. At the same time, draw the curve of the change of their attention index with time during the class as their attention. Force curve

Draw the curve of the class's average attention index as a function of time during the class, as the curve of the class's average attention.

Optionally, the teaching analysis method further includes:

Provide corresponding teaching suggestions according to the whole class average attention change curve;

The average class attention curve and the teaching suggestions are displayed in the teaching analysis report.

Optionally, the step of correspondingly evaluating the attention level and the synchronization rate level of each student according to the attention index and the synchronization rate of each student includes:

Determine the preset interval for each student's attention index and synchronization rate to correspondingly evaluate each student's attention level and synchronization rate level.

Calculate the average attention index and average synchronization rate of the entire class according to each student's attention index and synchronization rate;

Compare each student's attention index and synchronization rate with the class's average attention index and average synchronization rate to evaluate each student's attention level and synchronization rate.

Optionally, the step of counting the number of students at the same attention level and the same synchronization rate level to obtain the distribution of the attention level and the synchronization rate of the entire class includes:

Count the number of students at the same level of attention and the same synchronization rate, and the proportion of said students to the total number of the class;

Based on the statistical results, draw a pie chart of the distribution of the attention level of the entire class and a pie chart of the distribution of the synchronization rate of the entire class.

Optionally, the teaching analysis method further includes:

Obtaining course attribute information, which includes the instructor, class time, class and class name;

Displaying the course attribute information in the teaching analysis report.

In addition, in order to achieve the above purpose, the present application also provides a teaching analysis server, the teaching analysis server includes: a memory, a processor, and a teaching analysis program stored on the memory and executable on the processor. The steps of the teaching analysis method described above when the teaching analysis program is executed by the processor are described.

In addition, in order to achieve the above object, the present application also provides a computer-readable storage medium, where the computer-readable storage medium stores a teaching analysis program, and the teaching analysis program implements the teaching analysis as described above when executed by a processor. Method steps.

The teaching analysis method provided in this application obtains the attention index and synchronization rate of each student in the entire class, and then counts the number of students at the same attention level and the same synchronization rate level. The distribution of the class synchronization rate and the corresponding teaching analysis report were generated, which realized the quantification and intuitive display of the effect of the whole class.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic structural diagram of a teaching analysis server involved in a solution according to an embodiment of the present application;

2 is a schematic flowchart of a first embodiment of a teaching analysis method of the present application;

FIG. 3 is a detailed schematic diagram of the attention of the students in the class in the embodiment of the present application; FIG.

4 is a schematic flowchart of a second embodiment of a teaching analysis method of this application;

FIG. 5 is a schematic diagram of the detailed steps of step S11 in FIG. 4; FIG.

6 is a schematic flowchart of a third embodiment of a teaching analysis method of the present application;

FIG. 7 is a schematic diagram showing a teaching analysis report in the embodiment of the present application.

The implementation, functional characteristics and advantages of the purpose of this application will be further described with reference to the embodiments and the drawings.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application.

The main solution of the embodiment of the present application is to obtain the attention index and synchronization rate of each student in the entire class, where the attention index indicates the average attention of the students during the entire class, and the synchronization rate indicates the entire class. The degree of synchronization between the student's attention and the average attention of the class; according to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level; statistics are collected at the same attention level and the same synchronization rate, respectively The number of students at different levels obtains the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class; and generates a teaching analysis report for the entire class according to the distribution of the attention of the class and the synchronization rate of the entire class.

As shown in FIG. 1, FIG. 1 is a schematic structural diagram of a teaching analysis server according to a solution of an embodiment of the present application.

The teaching analysis server of the embodiment of the present application is deployed in a teaching analysis system. The teaching analysis system further includes an EEG data acquisition device and a wireless gateway. The EEG data collected by the EEG data acquisition device is sent to the teaching analysis server through the wireless gateway so that The teaching analysis server performs teaching analysis based on the EEG data.

As shown in FIG. 1, the teaching analysis server may include a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to implement connection and communication between these components. The user interface 1003 may include a display, an input unit such as a keyboard, and the optional user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory. memory), such as disk storage. The memory 1005 may optionally be a storage device independent of the foregoing processor 1001.

Those skilled in the art can understand that the structure shown in FIG. 1 does not constitute a limitation on the teaching analysis server, and may include more or fewer components than shown in the figure, or combine certain components, or arrange different components.

As shown in FIG. 1, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a teaching analysis program.

In the terminal shown in FIG. 1, the network interface 1004 is mainly used to connect to the background server and perform data communication with the background server; the user interface 1003 is mainly used to connect to the client (user) and perform data communication with the client; and the processor 1001 may be used to call a teaching analysis program stored in the memory 1005, and perform operations in the following embodiments of the teaching analysis method.

The specific embodiments of the teaching analysis server of the present application are basically the same as the specific embodiments of the teaching analysis method described below, and are not repeated here.

Based on the above hardware structure, an embodiment of the teaching analysis method of the present application is proposed.

Referring to FIG. 2, FIG. 2 is a schematic flowchart of a first embodiment of a teaching analysis method of the present application. The method includes:

Step S10: Obtain an attention index and a synchronization rate of each student in the entire class. The attention index indicates the average attention of the student during the entire class, and the synchronization rate indicates the student's attention and the average of the entire class during the entire class. The degree of synchronization of attention;

In this embodiment, the attention index and synchronization rate of each student in the class are first obtained. Among them, the attention index indicates the average attention of the students in the entire class. The higher the attention index, the more concentrated the students are, and the better the effect of the lecture; the synchronization rate indicates that the students' attention and the whole class are average during the entire class. The degree of attention synchronization, the higher the synchronization rate, the more the students can keep up with the teacher's rhythm.

When obtaining the attention index of each student in the class, first collect the EEG data of each student in the class during the class, and then convert the EEG data into the corresponding attention index according to a preset algorithm; According to the collected EEG data, you can draw a curve of the student's attention over time and a curve of the class's average attention over time based on the collected EEG data, and then calculate the degree of agreement between the two curves to obtain the student and the class. Synchronization rate.

Referring to FIG. 3, FIG. 3 is a schematic diagram of the attention details of the students in the class in the embodiment of the present application. The figure shows the attention index and synchronization rate of each student in the class, and the average attention index and average synchronization of the class. The rate, through this form, can quantify and intuitively reflect the students' attention during the class.

Step S20: According to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level;

As an implementation manner, step S20 may include: determining a preset interval in which each student's attention index and synchronization rate are located, so as to correspondingly evaluate each student's attention level and synchronization rate level.

Specifically, as an evaluation method of the attention level and the synchronization rate level, different evaluation intervals can be set for the target student's attention index and synchronization rate respectively, so by determining where each student's attention index and synchronization rate are located, , You can evaluate the attention level of each student. For example, when the attention index ≥80, the corresponding attention level is high, when 60≤attention index ≤80, the corresponding attention level is medium, and when the attention index ≤60, the corresponding attention level is Low; when the synchronization rate ≥ 80, the corresponding synchronization rate level is high; when 50 ≤ synchronization rate ≤ 80, the corresponding synchronization rate level is medium; when the synchronization rate ≤ 50, the corresponding synchronization rate level is low.

As another implementation manner, the above step S20 may include: calculating the average attention index and the average synchronization rate of the entire class according to the attention index and the synchronization rate of each student; Compare with the class's average attention index and average synchronization rate to evaluate each student's level of attention and synchronization rate.

Specifically, when evaluating the attention level of each student, the attention index of each student in the entire class during the entire class can be obtained first, and then the average value of the attention index of the entire student in the entire class can be obtained. , As the attention index of the whole class, and then compare the attention index of a target student with the attention index of the entire class to evaluate the attention level of the target student. For example, when the target student's attention index is higher than the class's attention index, the target student's attention level is evaluated to be high. When the target student's attention index is equal to the class's attention index, the target student's attention is evaluated. The power level is medium. When the target student's attention index is lower than the class's attention index, the target student's attention level is evaluated to be low. In this way, it is possible to evaluate the attention level of each student.

When evaluating the synchronization rate of each student, you can first obtain the synchronization rate of each student in the class, and then find the average of the synchronization rate of the students in the class as the synchronization rate of the entire class, and then set a target The synchronization rate of the students is compared with the synchronization rate of the entire class to evaluate the synchronization rate level of the target student. For example, when the synchronization rate of the target students is higher than the synchronization rate of the entire class, the synchronization rate of the target students is evaluated as high. When the synchronization rate of the target students is equal to the synchronization rate of the entire class, the synchronization rate of the target students is evaluated as medium. When the synchronization rate of the target students is lower than the synchronization rate of the whole class, the evaluation of the synchronization rate of the target students is low. In this way, the synchronization rate of each student can be evaluated.

Step S30: Count the number of students at the same attention level and the same synchronization rate level to obtain the distribution of the attention level and the synchronization rate of the entire class;

In this step, the number of students at the same attention level and the same synchronization rate level are respectively counted, so as to obtain the distribution of the attention level and the synchronization rate of the entire class. For example, for a class consisting of 50 students, the distribution of the attention level of the whole class can be expressed as: 26 students with a high level of attention, 20 students with a medium level of attention, and an attention level of The number of students with a low synchronization rate is 4; the distribution of the synchronization rate of the whole class can be expressed as follows: the number of students with a high synchronization rate is 16; the number of students with a medium synchronization rate is 24; the number of students with a high synchronization rate is 10 people.

Further, step S30 may further include: counting the number of students at the same attention level and the same synchronization rate level, and the ratio of the number of students to the total number of the class; and drawing a pie chart of the distribution of the class's attention level according to the statistical results. Graph and pie chart of horizontal distribution of class-wide synchronization rate. In this way, a more intuitive display of the distribution of attention levels and the synchronization rate distribution of the entire class is achieved.

Step S40: Generate a teaching analysis report of the entire class according to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class.

In this step, according to the distribution of the attention level of the whole class and the distribution rate of the synchronization rate of the whole class, a teaching analysis report of the entire class is generated, and the distribution of the attention level and the synchronization rate of the whole class are distributed Shown in the teaching analysis report.

Further, after step S40, it may further include the steps of: providing corresponding teaching suggestions according to the average attention change curve of the whole class; and displaying the average attention change curve of the whole class and the teaching suggestion in the teaching Analysis report.

In this embodiment, in addition to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class, the above-mentioned curve of the average attention of the entire class over time can also be displayed in a teaching analysis report. The curve of the class's average attention over time can be found in the period when the class's average attention is high and the period when the class's average attention is low. According to different time periods, teachers can provide different teaching suggestions, such as in During the period when the class's average attention is low, teachers are advised to combine teaching content to remind students to consolidate what they have learned during this period.

In addition, in order to facilitate students to review the teaching content, the teacher's teaching recordings and teaching courseware can also be obtained and stored in the teaching analysis server, so that students can review the lessons with the teacher's teaching recordings and teaching courseware.

The teaching analysis method provided in this embodiment obtains the attention index and synchronization rate of each student in the entire class, and then counts the number of students at the same attention level and the same synchronization rate level. The distribution of the synchronization rate of the entire class and the corresponding teaching analysis report are generated to quantify and intuitively display the lecture effect of the whole class, so that the teacher can grasp the lecture effect of the class in a timely and accurate manner.

Further, referring to FIG. 4, FIG. 4 is a schematic flowchart of a second embodiment of a teaching analysis method of the present application. Based on the embodiment shown in FIG. 2 above, step S10 may include:

Step S11: Obtain and analyze the EEG data of each student in the class during the class, and obtain the attention index and the change curve of the attention of each student, as well as the average change curve of the entire class;

In step S12, for each student, the degree of coincidence between the attention change curve and the average attention change curve of the whole class is analyzed, and the degree of coincidence is used as the synchronization rate.

In this embodiment, first, the EEG data of each student in the class during the class is acquired. In specific implementation, EEG data acquisition equipment can be worn for each student in the class, and a wireless connection between each EEG data acquisition equipment and the teaching analysis server is established through a wireless gateway. During the class, the EEG data acquisition equipment collects in real time The EEG data of the students in the class are sent to the teaching analysis server through the wireless gateway, so that the teaching analysis server receives the EEG data of the students in the class. Of course, the teaching analysis server can also receive the teaching analysis instructions from itself. The storage unit or external storage device obtains pre-saved EEG data. After that, the teaching analysis server analyzes the EEG data to obtain each student's attention index and attention change curve, as well as the class's average attention change curve. Among them, each student's attention change curve is used to represent the student. The relationship between the change in the attention index over time and the average attention curve of the whole class is used to represent the change in the average attention of the class students over time.

Then, for each student, analyze how well the concentration change curve matches the class's average concentration change curve. In this step, it is better to set the curve of attention of a certain student as curve 1 and the curve of average attention of the whole class as curve 2. The degree of agreement between the two curves can be calculated as follows: First calculate curve 1 respectively And the standard deviation of curve 2 and the covariance of curve 1 and curve 2, and then calculate the correlation coefficient according to the standard deviations of curve 1 and curve 2 and the covariance of the two, and then use the correlation coefficient as the standard to obtain the synchronization rate, the correlation coefficient The closer it is to 1, the higher the synchronization rate of the student with the whole class, it also means that the student keeps up with the teacher's rhythm. The specific calculation formula can refer to the existing technology, and will not be repeated here.

Referring to FIG. 5, FIG. 5 is a schematic diagram of the detailed steps of step S11 in FIG. 4. The above step S11 may include:

Step S111: Receive the EEG data of each student in the class sent by the EEG data acquisition device during the class;

Step S112: convert the received EEG data into a corresponding attention index according to a preset correspondence between the EEG data and the attention index;

In step S113, for each student, the average value of the attention index at each time point during the class is obtained as the attention index, and at the same time, the curve of the change of the attention index with time during the class is drawn. As its attention curve;

In step S114, a curve of the average attention index of the whole class during the class as a function of time is plotted as a change curve of the average attention of the entire class.

During the specific implementation, the EEG data of the students in different mental states (including relaxed state and concentrated state) can be collected, and then FFT (Fast Fourier Transformation (Fast Algorithm of Discrete Fourier Transform) to obtain the frequency domain information of the EEG data, and then classify the frequency domain information by a deep learning algorithm (such as what kind of frequency domain information is the student in a relaxed state, what kind of frequency (The student is in a centralized state when the domain information is in the state), so as to obtain a deep learning model. In this way, after receiving the EEG data of the entire class, the received EEG data is input into the deep learning model, and the EEG data can be converted. Is the corresponding attention index, and the higher the attention index, the more concentrated the students are.

For a student, the teaching analysis server converts its EEG data into the corresponding attention index according to the above-mentioned deep learning model. At this time, a curve of the student's attention index during the course of time can be drawn. The curve is For the student's attention curve during the entire lesson, average the student's attention index at each time point during the class. The average value is used as the student's attention index during the entire class. . In this way, each student's attention index and attention change curve can be obtained.

At each time point during the class, obtain the average attention index of each student in the class and average it to obtain the average attention index of the entire class at each time point. At this time, you can The average attention index of the entire class, draw a curve of the average attention index of the entire class as a function of time, and this curve is used as the average attention change curve of the entire class.

In this embodiment, by acquiring the attention index and the attention change curve of each student, and the average attention change curve of the entire class, and then analyzing that the concentration change curve of each student is consistent with the average attention change curve of the entire class Degree, get the synchronization rate of each student and the whole class, and realize a quantitative and intuitive reflection of the effect of each student in the class.

Further, referring to FIG. 6, FIG. 6 is a schematic flowchart of a third embodiment of a teaching analysis method of the present application. Based on the above embodiment, after step S40, the method may further include:

Step S50: Obtain course attribute information, where the course attribute information includes the instructor, class time, class and class name;

Step S60: Display the course attribute information in the teaching analysis report.

In this embodiment, when the teaching analysis server generates a teaching analysis report, it can receive a user's input instruction to obtain course attribute information. The course attribute information includes the instructor, class time, class and class name, and is used to: Distinguish different teaching analysis reports. After that, the acquired course attribute information is displayed in the teaching analysis report for the convenience of users.

Referring to FIG. 7, FIG. 7 is a schematic diagram showing a teaching analysis report in an embodiment of the present application. The teaching analysis report is a teaching analysis report for the history class of teacher Zhang Dazhuang in the third grade class on September 13, 2017, from 10:00 to 10:40 am. The report shows the distribution curve of the attention level of the whole class. The pie chart, the pie chart of the synchronization rate distribution of the whole class, the average attention change curve of the whole class, and the corresponding teaching suggestions, thus realizing the quantification and intuitive display of the effect of the entire class, so that users can evaluate the teaching effect. .

The present application also provides a computer-readable storage medium.

The computer-readable storage medium of the present application stores a teaching analysis program, and when the teaching analysis program is executed by a processor, the steps of the teaching analysis method described above are implemented.

For a method implemented when a teaching analysis program running on the processor is executed, reference may be made to various embodiments of the teaching analysis method of the present application, and details are not described herein again.

It should be noted that in this article, the terms "including", "including" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, It also includes other elements that are not explicitly listed, or elements that are inherent to such a process, method, article, or system. Without more restrictions, an element limited by the sentence "including a ..." does not exclude the existence of other identical elements in the process, method, article, or system that includes the element.

The above-mentioned serial numbers of the embodiments of the present application are merely for description, and do not represent the superiority or inferiority of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the methods in the above embodiments can be implemented by means of software plus a necessary universal hardware platform, and of course, also by hardware, but in many cases the former is better. Implementation. Based on such an understanding, the technical solution of the present application, in essence, or a part that contributes to the existing technology, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM) as described above. , Magnetic disk, optical disc), including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the embodiments of this application.

The above are only preferred embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of the application, or directly or indirectly used in other related technical fields Are included in the scope of patent protection of this application.

Claims

A teaching analysis method, wherein the teaching analysis method includes the following steps:

Obtain the attention index and synchronization rate of each student in the entire class. The attention index indicates the average attention of the student during the entire class, and the synchronization rate indicates the concentration of the student's attention during the entire class and the average attention of the entire class. Degree of synchronization

According to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level;

Count the number of students at the same attention level and the same synchronization rate level to get the distribution of the attention level and the synchronization rate of the whole class;

According to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class, a teaching analysis report of the entire class is generated.
The teaching analysis method according to claim 1, wherein the step of obtaining the attention index and synchronization rate of each student in the entire class comprises:

Obtain and analyze the EEG data of each student in the class during the class, and obtain the attention index and the change curve of each student's attention, as well as the average change curve of the entire class;

For each student, analyze the degree of coincidence between the attention change curve and the average attention change curve of the whole class, and use the degree of agreement as its synchronization rate.
The teaching analysis method according to claim 2, wherein the acquisition and analysis of the EEG data of each student in the class during the class, the attention index and the attention change curve of each student, and the average attention of the class The steps of the force curve include:

Receive the EEG data of each student in the class sent by the EEG data acquisition device during the class;

Converting the received EEG data into a corresponding attention index according to a preset correspondence between the EEG data and the attention index;

For each student, find the average value of their attention index at each time point during the class, and use it as their attention index. At the same time, draw the curve of the change of their attention index with time during the class as their attention. Force curve

Draw the curve of the class's average attention index as a function of time during the class, as the curve of the class's average attention.
The teaching analysis method according to claim 3, wherein the teaching analysis method further comprises:

Provide corresponding teaching suggestions according to the whole class average attention change curve;

The average class attention curve and the teaching suggestions are displayed in the teaching analysis report.
The teaching analysis method according to claim 1, wherein the step of correspondingly evaluating each student's attention level and synchronization rate level according to each student's attention index and synchronization rate comprises:

Determine the preset interval for each student's attention index and synchronization rate to correspondingly evaluate each student's attention level and synchronization rate level.
The teaching analysis method according to claim 1, wherein the step of correspondingly evaluating each student's attention level and synchronization rate level according to each student's attention index and synchronization rate comprises:

Calculate the average attention index and average synchronization rate of the entire class according to each student's attention index and synchronization rate;

Compare each student's attention index and synchronization rate with the class's average attention index and average synchronization rate to evaluate each student's attention level and synchronization rate.
The teaching analysis method according to claim 1, wherein the step of counting the number of students at the same attention level and the same synchronization rate level to obtain the distribution of the attention level of the whole class and the synchronization rate distribution of the whole class includes :

Count the number of students at the same level of attention and the same synchronization rate, and the proportion of said students to the total number of the class;

Based on the statistical results, draw a pie chart of the distribution of the attention level of the entire class and a pie chart of the distribution of the synchronization rate of the entire class.
The teaching analysis method according to claim 7, wherein the teaching analysis method further comprises:

Obtaining course attribute information, which includes the instructor, class time, class and class name;

Displaying the course attribute information in the teaching analysis report.
A teaching analysis server, wherein the teaching analysis server includes a memory, a processor, and a teaching analysis program stored on the memory and operable on the processor, and the teaching analysis program is used by the processor Implement the following steps during execution:

Obtain the attention index and synchronization rate of each student in the entire class. The attention index indicates the average attention of the student during the entire class, and the synchronization rate indicates the concentration of the student's attention during the entire class and the average attention of the entire class. Degree of synchronization

According to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level;

Count the number of students at the same attention level and the same synchronization rate level to get the distribution of the attention level and the synchronization rate of the whole class;

According to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class, a teaching analysis report of the entire class is generated.
The teaching analysis server according to claim 9, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Obtain and analyze the EEG data of each student in the class during the class, and obtain the attention index and the change curve of each student's attention, as well as the average change curve of the entire class;

For each student, analyze the degree of coincidence between the attention change curve and the average attention change curve of the whole class, and use the degree of agreement as its synchronization rate.
The teaching analysis server according to claim 10, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Receive the EEG data of each student in the class sent by the EEG data acquisition device during the class;

Converting the received EEG data into a corresponding attention index according to a preset correspondence between the EEG data and the attention index;

For each student, find the average value of their attention index at each time point during the class, and use it as their attention index. At the same time, draw the curve of the change of their attention index with time during the class as their attention. Force curve

Draw the curve of the class's average attention index as a function of time during the class, as the curve of the class's average attention.
The teaching analysis server according to claim 11, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Provide corresponding teaching suggestions according to the whole class average attention change curve;

The average class attention curve and the teaching suggestions are displayed in the teaching analysis report.
The teaching analysis server according to claim 9, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Determine the preset interval for each student's attention index and synchronization rate to correspondingly evaluate each student's attention level and synchronization rate level.
The teaching analysis server according to claim 9, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Calculate the average attention index and average synchronization rate of the entire class according to each student's attention index and synchronization rate;

Compare each student's attention index and synchronization rate with the class's average attention index and average synchronization rate to evaluate each student's attention level and synchronization rate.
The teaching analysis server according to claim 9, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Count the number of students at the same level of attention and the same synchronization rate, and the proportion of said students to the total number of the class;

Based on the statistical results, draw a pie chart of the distribution of the attention level of the entire class and a pie chart of the distribution of the synchronization rate of the entire class.
The teaching analysis server according to claim 15, wherein when the teaching analysis program is executed by the processor, the following steps are further implemented:

Obtaining course attribute information, which includes the instructor, class time, class and class name;

Displaying the course attribute information in the teaching analysis report.
A computer-readable storage medium, wherein the computer-readable storage medium stores a teaching analysis program, and when the teaching analysis program is executed by a processor, the following steps are implemented:

Obtain the attention index and synchronization rate of each student in the entire class. The attention index indicates the average attention of the student during the entire class, and the synchronization rate indicates the concentration of the student's attention during the entire class and the average attention of the entire class. Degree of synchronization

According to each student's attention index and synchronization rate, correspondingly evaluate each student's attention level and synchronization rate level;

Count the number of students at the same attention level and the same synchronization rate level to get the distribution of the attention level and the synchronization rate of the whole class;

According to the distribution of the attention level of the entire class and the distribution of the synchronization rate of the entire class, a teaching analysis report of the entire class is generated.
The computer-readable storage medium of claim 17, wherein the teaching analysis program further implements the following steps when executed by a processor:

Obtain and analyze the EEG data of each student in the class during the class, and obtain the attention index and the change curve of each student's attention, as well as the average change curve of the entire class;

For each student, analyze the degree of coincidence between the attention change curve and the average attention change curve of the whole class, and use the degree of agreement as its synchronization rate.
The computer-readable storage medium of claim 18, wherein the teaching analysis program further implements the following steps when executed by a processor:

Receive the EEG data of each student in the class sent by the EEG data acquisition device during the class;

Converting the received EEG data into a corresponding attention index according to a preset correspondence between the EEG data and the attention index;

For each student, find the average value of their attention index at each time point during the class, and use it as their attention index. At the same time, draw the curve of the change of their attention index with time during the class as their attention. Force curve

Draw the curve of the class's average attention index as a function of time during the class, as the curve of the class's average attention.
The computer-readable storage medium of claim 19, wherein the teaching analysis program further implements the following steps when executed by a processor:

Provide corresponding teaching suggestions according to the whole class average attention change curve;

The average class attention curve and the teaching suggestions are displayed in the teaching analysis report.