Intelligent teaching comprehensive analysis method and system based on big data

Abstract

The invention discloses an intelligent teaching comprehensive analysis method and system based on big data, and the method comprises the steps: analyzing the sitting posture of a student in class, detecting the concentration degree of the student, positioning the available learning resources of the student, monitoring the learning process of the student for the available learning resources, and carrying out the analysis of the learning process. Whether the students in the learning process can follow the teaching rhythm under the current concentration degree is analyzed, and the teaching speed is adjusted according to the average learning process of the students in the classroom. According to the invention, the learning process of available learning resources is monitored, the class rhythm is monitored in real time, and whether the attention of the student is concentrated is analyzed in the note recording process of the student, so that the attention of the individual student is enhanced, the attention detection precision is improved, and the possibility that the individual student does not change the learning progress is reduced. The credibility of comprehensive analysis of intelligent teaching is improved, and teachers can further improve the teaching control of individual students. The system has the characteristics of high teaching detection capability and high humanization degree.

Description

Technical Field

[0001] The present invention relates to the field of teaching management technology, and specifically to a smart teaching comprehensive analysis method and system based on big data. Background Art

[0002] Smart classrooms focus on the application of intelligent teaching monitoring equipment. How to improve classroom teaching effectiveness with the support of big data is one of the development directions of teaching. Combining with teaching practice, we can find the main problems currently existing, find better strategies to apply big data resources to achieve the effective construction of smart classrooms, use data to confirm students' mastery of knowledge, and generate corresponding teaching plans based on the inquiry model.

[0003] In existing technologies, smart teaching systems monitor students' attention spans and analyze their learning status in real time. However, when students are taking notes, the monitoring system has low visual correlation with the students, making it difficult to monitor their attendance. Furthermore, as students are struggling to understand the lecture content, the monitoring system often struggles to effectively identify their learning progress. Therefore, it is essential to design a comprehensive smart teaching analysis method and system based on big data that offers robust teaching detection capabilities and a high degree of user-friendliness. Summary of the Invention

[0004] The purpose of the present invention is to provide a comprehensive analysis method and system for intelligent teaching based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a comprehensive analysis method and system for smart teaching based on big data, comprising:

[0006] Obtain students' concentration level during class based on their sitting posture;

[0007] Monitor students' progress in learning the available learning resources and analyze whether students can keep up with the lecture pace at their current level of concentration.

[0008] Record students who have not kept up with the teaching pace and adjust the teaching speed according to the average learning progress of students in the class.

[0009] According to the above technical solution, the method of obtaining the student's concentration level during class based on the student's sitting posture includes:

[0010] The first force sensor on the bottom of the current student's seat obtains an area value S where the force exceeds the limit value, and the second force sensor on the backrest obtains a force value f1, and a sitting posture model of the student in the seat is established in the database based on the area value S and the force value f1;

[0011] Check students' concentration during class Where K is the total concentration level of the students during the class. is the unit conversion factor.

[0012] According to the above technical solution, monitoring the student's learning progress of available learning resources and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress include:

[0013] Locate students' book locations and book data during the teaching process, and record students' available learning resources.

[0014] Sequentially obtain the distance values between the center points of multiple books on the desk and the center point of the desk and arrange them in ascending order, determine the center point of the book closest to the center point of the desk, and mark it as the first target book;

[0015] Locating the first target book frame, marking the page number of the book in the book frame, photographing content information of the page number in the book frame, and extracting text content in the content information;

[0016] Comparing the text content in the content information with the text content preset in the current teaching database, where the text content preset in the current teaching database is recorded based on the student's available learning resources, obtaining a first overlap between the text content in the content information and the text content in the teaching database as w1%, and if w1<w0, locating a second target book according to the ascending order, obtaining a second overlap as w2%, and if w1+w2<w0, repeating this step until the total overlap value is higher than w0, recording the target book position and corresponding target book data corresponding to the overlap;

[0017] Taking an image of the book position corresponding to the overlap of the records, and marking it as a difficult point marking event;

[0018] Frame the playback screen of the remote tutoring platform and obtain the focus point of the student's eyes on the playback screen of the remote tutoring platform;

[0019] Extracting the appearance position area of the teaching knowledge point in the playback picture, where the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point;

[0020] Match the corresponding book data with the focus point, obtain the closest distance between the focus point and the location of the teaching knowledge point as L, and obtain the distance between the focus point and the location where the teacher writes notes on the teaching knowledge point as C. Then, the matching degree between the student's current concentration level and the teaching rhythm in the learning process is calculated. Among them, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, when the focusing point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focusing point is outside the appearance position area of the teaching knowledge point, L is a positive number.

[0021] According to the above technical solution, monitoring the student's learning progress with available learning resources and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress also includes:

[0022] Relocating a new knowledge point note-taking location after a student turns a page in a book during a lecture. The knowledge point note-taking location is used to predict and locate in real time the note location recorded by the student after turning a page in the book;

[0023] Based on the feature of turning pages of the book, locating book features in the available learning resources includes:

[0024] Acquire a cross-section image of the book;

[0025] Performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book;

[0026] After detecting that a feature of a teaching knowledge point recorded in a playback screen of the remote tutoring platform has changed, repeatedly recording an appearance location area of the teaching knowledge point in the playback screen;

[0027] Based on the number of pages turned in the book, the knowledge point features between the appearance location areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, and the knowledge point note writing location points corresponding to the text content after association are marked, and the new knowledge point note writing location points are located.

[0028] According to the above technical solution, obtaining the matching results further includes:

[0029] Obtain the area value of the appearance position area of the teaching knowledge point in the playback screen, associate the importance Q of the current teaching knowledge point with the area value S of the appearance position area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q into the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

[0030] According to the above technical solution, recording students who have not kept up with the teaching pace and adjusting the teaching speed according to the average learning progress of students in the class include:

[0031] The camera will locate students whose matching degree with the teaching rhythm is below the limit value, and the student's position will be sent to the teacher through the indicator, and corresponding teaching speed adjustment suggestions will be provided.

[0032] According to the above technical solution, the big data-based smart teaching comprehensive analysis system includes:

[0033] A collection module, which obtains the student's concentration level during class based on the student's sitting posture;

[0034] An analysis module, the analysis module is used to monitor the student's learning progress of the available learning resources and analyze whether the student can keep up with the teaching pace at the current level of concentration;

[0035] The adjustment module is used to record students who have not kept up with the teaching pace and adjust the teaching speed according to the average learning progress of students in the class.

[0036] According to the above technical solution, the acquisition module includes:

[0037] a detection module configured to obtain an area value S of the current student's seat under which a force is above a limit value based on a first force sensor on the bottom surface of the seat, and to obtain a force value f1 through a second force sensor on the back surface, and to establish a sitting posture model of the student in the seat in a database based on the area value S and the force value f1;

[0038] The concentration acquisition module is used to detect the concentration of students during class. Where K is the total concentration level of the students during the class. is the unit conversion factor.

[0039] According to the above technical solution, the analysis module includes:

[0040] A matching degree analysis module is used to locate the student's book position and book data during the teaching process, record the student's available learning resources, obtain the distance values between the position center points of multiple books on the desk and the center point of the desk in sequence and arrange them in ascending order, determine the position center point of the book closest to the center point of the desk, and mark it as the first target book; locate the first target book frame, mark the page number of the book in the book frame, photograph the content information of the page number in the book frame, and extract the text content in the content information; compare the text content in the content information with the text content preset in the current teaching database, the text content preset in the current teaching database is recorded based on the student's available learning resources, obtain the first overlap degree of the text content in the content information with the text content in the teaching database as w1%, if w1<w0, then locate it in the ascending order For the second target book, obtain a second overlap of w2%. If w1+w2<w0, repeat this step until the total value of the overlap is higher than w0, then record the target book position and corresponding target book data corresponding to the overlap; take the book position image corresponding to the recorded overlap, and mark it as a difficult point marking event; frame the playback screen of the remote tutoring platform, and obtain the focus point of the student's eyeball on the playback screen of the remote tutoring platform; extract the appearance position area of the teaching knowledge point in the playback screen, and the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point; match the corresponding book data with the focus point, and obtain the closest distance between the focus point and the appearance position area of the teaching knowledge point as L, and obtain the distance between the focus point and the position point where the teacher writes notes on the teaching knowledge point as C, then the matching degree between the student's current concentration level and the teaching rhythm in the learning process is Wherein, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, when the focus point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focus point is outside the appearance position area of the teaching knowledge point, L is a positive number;

[0041] A positioning module, the positioning module is used to re-position the new knowledge point note-writing position point after the student turns the book page during the lecture, the knowledge point note-writing position point is used to predict and locate in real time the note position recorded by the student after turning the book page; based on the characteristics of turning the book page, locate the book characteristics in the available learning resources, including: obtaining a cross-sectional image of the book; performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book; after detecting that the characteristics of the teaching knowledge points recorded in the playback screen of the remote tutoring platform have changed, repeatedly recording the appearance position area of the teaching knowledge points in the playback screen; based on the number of book pages turned, the knowledge point features between the appearance position areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, marking the knowledge point note-writing position points corresponding to the text content after association, and locating the new knowledge point note-writing position point.

[0042] According to the above technical solution, the matching analysis module includes:

[0043] An area acquisition submodule, the area acquisition submodule is used to obtain the area value of the location where the teaching knowledge point appears in the playback picture;

[0044] An input module is used to associate the importance Q of the current teaching knowledge point with the area value S of the appearance area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q to determine the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

[0045] Compared with the existing technology, the beneficial effects achieved by the present invention are: the present invention detects the students' concentration level during class, locates the students' available learning resources, monitors the learning process of available learning resources, monitors the class rhythm in real time, and analyzes whether the students are focused while taking notes. This enhances the attention to individual students, improves the accuracy of attention detection, reduces the possibility of individual students failing to keep up with their learning progress, and improves the credibility of the comprehensive analysis of smart teaching. Teachers can further improve their control over the teaching of individual students. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 This is a flow chart of a comprehensive analysis method for smart teaching based on big data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] See also Figure 1 , which is a flow chart of a comprehensive analysis method for smart teaching based on big data provided by an embodiment of the present invention, such as Figure 1 It can be seen that the comprehensive analysis method of smart teaching based on big data includes:

[0050] Step S1: Obtain the student's concentration level during class based on the student's sitting posture;

[0051] Step S2: monitoring the student's learning progress on the available learning resources, and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress;

[0052] Step S3: Record students who have not kept up with the teaching pace, and adjust the teaching speed according to the average learning progress of students in the class.

[0053] The embodiments of the present invention detect the concentration level of students during class, locate the students' available learning resources, monitor the learning process of the available learning resources, monitor the class rhythm in real time, and analyze whether the students are focused while they are taking notes. This enhances the focus on individual students, improves the accuracy of attention detection, reduces the possibility of individual students falling behind in their learning progress, and improves the credibility of the comprehensive analysis of smart teaching. Teachers can further improve their control over the teaching of individual students.

[0054] In certain preferred embodiments, obtaining the student's concentration level during class based on the student's sitting posture during class includes:

[0055] Step S11: obtaining an area S where the force is higher than a limit value through a first force sensor on the bottom surface of the current student's seat, and obtaining a force value f1 through a second force sensor on the back surface, and establishing a sitting posture model of the student in the seat in a database based on the area value S and the force value f1;

[0056] Step S12: Detecting the student's concentration during class Where K is the total concentration level of the student during the class, which is the total value that the student can use to maintain the current concentration level. The total value can be used to allocate the concentration level. It is the unit conversion coefficient, which is used to convert the units of the area value S and the force value f1 into the same unit of concentration.

[0057] The sitting posture model can reflect the degree to which the student's body leans forward or backward while studying in a seat. When the student's body leans forward, the visual distance between the student's eyes and the book or the blackboard is short, the student's field of vision is small, and the line of sight is not easily deviated. Therefore, the student's concentration during class is high; conversely, when the student's body leans backward, the visual distance between the student's eyes and the book or the blackboard is long, the student's field of vision is large, and the line of sight is easily deviated. Therefore, the student's concentration during class is low. In addition, when the student's body leans back to a high degree while studying in a seat, the student's learning state is relatively relaxed, and it is more likely that the student will have a low concentration during class.

[0058] In certain preferred embodiments, monitoring the student's learning progress on available learning resources and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress includes:

[0059] Step S211: Locate the student's book location and book data during the teaching process, and record the student's available learning resources.

[0060] Step S212: sequentially obtaining the distances between the center points of the multiple books on the desk and the center point of the desk and arranging them in ascending order, determining the center point of the book closest to the center point of the desk and marking it as the first target book;

[0061] Step S213: locating the first target book frame, marking the page number of the book in the book frame, photographing the content information of the page number in the book frame, and extracting text content in the content information;

[0062] Step S214: Compare the text content in the content information with the text content preset in the current teaching database, where the text content preset in the current teaching database is recorded based on the student's available learning resources, and obtain a first overlap between the text content in the content information and the text content in the teaching database, which is w1%. If w1<w0, locate the second target book according to the ascending order, and obtain a second overlap of w2%. If w1+w2<w0, repeat this step until the total overlap value is higher than w0, then record the target book position and corresponding target book data corresponding to the overlap, specifically the Sth target book position and corresponding Sth target book data, where S is the number of target books located when the total overlap value is higher than w0.

[0063] The text content in the content information is obtained based on the student's available learning resources, and the text content preset in the current teaching database is recorded based on the student's available learning resources. The difference between the two is that the text content preset in the current teaching database is located in real time to the specific location of the student's available learning resources, while the text content in the content information is the location of the student's current learning book and is random. Comparing the text content in the content information with the text content preset in the current teaching database can effectively monitor the difference between the current student's learning content and the current teaching content.

[0064] Step S215: photographing an image of the book position corresponding to the overlap of the records, and marking it as a difficult point marking event;

[0065] Step S216: framing the playback screen of the remote tutoring platform, and obtaining the focus point of the student's eyes on the playback screen of the remote tutoring platform;

[0066] Step S217: extracting the appearance position area of the teaching knowledge point in the playback image, where the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point;

[0067] Step S218: Match the corresponding book data with the focus point, obtain the closest distance between the focus point and the location of the teaching knowledge point as L, obtain the distance between the focus point and the location where the teacher writes notes on the teaching knowledge point as C, and then the matching degree between the student's current concentration level and the teaching rhythm in the learning process is obtained. Among them, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, used to convert the unit of Q into the unit of length, the unit of αQ is the same as L, when the focusing point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focusing point is outside the appearance position area of the teaching knowledge point, L is a positive number.

[0068] In certain preferred embodiments, monitoring the student's learning progress on available learning resources and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress further includes:

[0069] Step S221: relocating a new knowledge point note-taking location after a student turns a page in a book during a lecture, wherein the knowledge point note-taking location is used to predict and locate in real time the note location recorded by the student after turning a page in the book;

[0070] Step S222: Based on the feature of turning the book page, locate the book feature in the available learning resources, including:

[0071] Acquire a cross-section image of the book;

[0072] Performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book;

[0073] After detecting that a feature of a teaching knowledge point recorded in a playback screen of the remote tutoring platform has changed, repeatedly recording an appearance location area of the teaching knowledge point in the playback screen;

[0074] Step S223: Based on the number of pages turned in the book, the knowledge point features between the appearance location areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, and the knowledge point note writing location points corresponding to the text content after association are marked, and the new knowledge point note writing location points are located.

[0075] In some preferred embodiments, obtaining the matching result further includes:

[0076] Step S2131: obtaining the area value of the appearance position region of the teaching knowledge point in the playback image;

[0077] Step S2132: Associate the importance Q of the current teaching knowledge point with the area value S of the appearance area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q to determine the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

[0078] The larger the area value S of the location where the teaching knowledge points appear in the playback image, the more teaching knowledge points there are, and the lower the student's acceptance level;

[0079] If the importance of the current teaching knowledge point matches the student's acceptance of the knowledge point, the remote teaching auxiliary platform prompts the teacher to adjust the teaching speed according to the real-time detection result. That is, when the importance of the current teaching knowledge point is high and the student's acceptance of the knowledge point is low, the teacher needs to be instructed to significantly reduce the teaching speed.

[0080] If the importance of the current teaching knowledge point and the student's acceptance level of the knowledge point have a low match, the remote teaching assistance platform prompts the teacher to adjust the teaching speed according to the real-time detection result. The difference requirement is low, that is, when the importance of the current teaching knowledge point is high and the student's acceptance level of the knowledge point is low, the teacher needs to be instructed to significantly reduce the teaching speed.

[0081] In certain preferred embodiments, recording students who have not kept up with the teaching pace and adjusting the teaching speed according to the average learning progress of students in the class includes:

[0082] Step S31: The camera locates students whose matching degree with the teaching rhythm is lower than the threshold value, sends the student's position to the teacher through the indicator, and provides corresponding teaching speed adjustment suggestions.

[0083] Based on the same concept as the above embodiment, the embodiment of the present invention further provides a comprehensive analysis system for intelligent teaching based on big data, including:

[0084] A collection module, which obtains the student's concentration level during class based on the student's sitting posture;

[0085] An analysis module, the analysis module is used to monitor the student's learning progress of the available learning resources and analyze whether the student can keep up with the teaching pace at the current level of concentration;

[0086] The adjustment module is used to record students who have not kept up with the teaching pace and adjust the teaching speed according to the average learning progress of students in the class.

[0087] In this embodiment, the acquisition module includes:

[0088] a detection module configured to obtain an area value S of the current student's seat under which a force is above a limit value based on a first force sensor on the bottom surface of the seat, and to obtain a force value f1 through a second force sensor on the back surface, and to establish a sitting posture model of the student in the seat in a database based on the area value S and the force value f1;

[0089] The concentration acquisition module is used to detect the concentration of students during class. Where K is the total concentration level of the students during the class. is the unit conversion factor.

[0090] In this embodiment, the analysis module includes:

[0091] A matching degree analysis module is used to locate the student's book position and book data during the teaching process, record the student's available learning resources, obtain the distance values between the position center points of multiple books on the desk and the center point of the desk in sequence and arrange them in ascending order, determine the position center point of the book closest to the center point of the desk, and mark it as the first target book; locate the first target book frame, mark the page number of the book in the book frame, photograph the content information of the page number in the book frame, and extract the text content in the content information; compare the text content in the content information with the text content preset in the current teaching database, the text content preset in the current teaching database is recorded based on the student's available learning resources, obtain the first overlap degree of the text content in the content information with the text content in the teaching database as w1%, if w1<w0, then locate it in the ascending order For the second target book, obtain a second overlap of w2%. If w1+w2<w0, repeat this step until the total value of the overlap is higher than w0, then record the target book position and corresponding target book data corresponding to the overlap; take the book position image corresponding to the recorded overlap, and mark it as a difficult point marking event; frame the playback screen of the remote tutoring platform, and obtain the focus point of the student's eyeball on the playback screen of the remote tutoring platform; extract the appearance position area of the teaching knowledge point in the playback screen, and the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point; match the corresponding book data with the focus point, and obtain the closest distance between the focus point and the appearance position area of the teaching knowledge point as L, and obtain the distance between the focus point and the position point where the teacher writes notes on the teaching knowledge point as C, then the matching degree between the student's current concentration level and the teaching rhythm in the learning process is Wherein, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, when the focus point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focus point is outside the appearance position area of the teaching knowledge point, L is a positive number;

[0092] A positioning module, the positioning module is used to re-position the new knowledge point note-writing position point after the student turns the book page during the lecture, the knowledge point note-writing position point is used to predict and locate in real time the note position recorded by the student after turning the book page; based on the characteristics of turning the book page, locate the book characteristics in the available learning resources, including: obtaining a cross-sectional image of the book; performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book; after detecting that the characteristics of the teaching knowledge points recorded in the playback screen of the remote tutoring platform have changed, repeatedly recording the appearance position area of the teaching knowledge points in the playback screen; based on the number of book pages turned, the knowledge point features between the appearance position areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, marking the knowledge point note-writing position points corresponding to the text content after association, and locating the new knowledge point note-writing position point.

[0093] In this embodiment, the matching analysis module includes:

[0094] An area acquisition submodule, the area acquisition submodule is used to obtain the area value of the location where the teaching knowledge point appears in the playback picture;

[0095] An input module is used to associate the importance Q of the current teaching knowledge point with the area value S of the appearance area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q to determine the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

[0096] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0097] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A comprehensive analysis method for smart teaching based on big data, characterized by: include: Obtain students' concentration level during class based on their sitting posture; Monitor students' progress in learning the available learning resources and analyze whether students can keep up with the lecture pace at their current level of concentration. Record students who have not kept up with the teaching pace and adjust the teaching speed according to the average learning progress of students in the class.

2. The method for comprehensive analysis of intelligent teaching based on big data according to claim 1, characterized in that: The method of obtaining the student's concentration level during class based on the student's sitting posture includes: The first force sensor on the bottom of the current student's seat obtains an area value S where the force exceeds the limit value, and the second force sensor on the backrest obtains a force value f1, and a sitting posture model of the student in the seat is established in the database based on the area value S and the force value f1; Check students' concentration during class Where K is the total concentration level of the students during the class. is the unit conversion factor.

3. The method for comprehensive analysis of intelligent teaching based on big data according to claim 2, characterized in that: The monitoring of students' learning progress on available learning resources and analyzing whether students can keep up with the teaching pace at their current level of concentration under the learning progress include: Locate students' book locations and book data during the teaching process, and record students' available learning resources. Sequentially obtain the distance values between the center points of multiple books on the desk and the center point of the desk and arrange them in ascending order, determine the center point of the book closest to the center point of the desk, and mark it as the first target book; Locating the first target book frame, marking the page number of the book in the book frame, photographing content information of the page number in the book frame, and extracting text content in the content information; Comparing the text content in the content information with the text content preset in the current teaching database, where the text content preset in the current teaching database is recorded based on the student's available learning resources, obtaining a first overlap between the text content in the content information and the text content in the teaching database as w1%, and if w1<w0, locating a second target book according to the ascending order, obtaining a second overlap as w2%, and if w1+w2<w0, repeating this step until the total overlap value is higher than w0, recording the target book position and corresponding target book data corresponding to the overlap; Taking an image of the book position corresponding to the overlap of the records, and marking it as a difficult point marking event; Frame the playback screen of the remote tutoring platform and obtain the focus point of the student's eyes on the playback screen of the remote tutoring platform; Extracting the appearance position area of the teaching knowledge point in the playback picture, where the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point; Match the corresponding book data with the focus point, obtain the closest distance between the focus point and the location of the teaching knowledge point as L, and obtain the distance between the focus point and the location where the teacher writes notes on the teaching knowledge point as C. Then, the matching degree between the student's current concentration level and the teaching rhythm in the learning process is calculated. Among them, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, when the focusing point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focusing point is outside the appearance position area of the teaching knowledge point, L is a positive number.

4. The method for comprehensive analysis of intelligent teaching based on big data according to claim 2, characterized in that: The monitoring of the student's learning progress on the available learning resources and analyzing whether the student can keep up with the teaching pace at the current level of concentration under the learning progress also includes: Relocating a new knowledge point note-taking location after a student turns a page in a book during a lecture. The knowledge point note-taking location is used to predict and locate in real time the note location recorded by the student after turning a page in the book; Based on the feature of turning pages of the book, locating book features in the available learning resources includes: Acquire a cross-section image of the book; Performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book; After detecting that a feature of a teaching knowledge point recorded in a playback screen of the remote tutoring platform has changed, repeatedly recording an appearance location area of the teaching knowledge point in the playback screen; Based on the number of pages turned in the book, the knowledge point features between the appearance location areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, and the knowledge point note writing location points corresponding to the text content after association are marked, and the new knowledge point note writing location points are located.

5. The method for comprehensive analysis of intelligent teaching based on big data according to claim 3 is characterized by: Obtaining the matching results further includes: Obtain the area value of the appearance position area of the teaching knowledge point in the playback screen, associate the importance Q of the current teaching knowledge point with the area value S of the appearance position area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q into the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

6. The method for comprehensive analysis of intelligent teaching based on big data according to claim 1, characterized in that: For students who have not kept up with the teaching pace, the teaching speed will be adjusted according to the average learning progress of students in the class, including: The camera will locate students whose matching degree with the teaching rhythm is below the limit value, and the student's position will be sent to the teacher through the indicator, and corresponding teaching speed adjustment suggestions will be provided.

7. The intelligent teaching comprehensive analysis system based on big data is characterized by: include: A collection module, which obtains the student's concentration level during class based on the student's sitting posture; An analysis module, the analysis module is used to monitor the student's learning progress of the available learning resources and analyze whether the student can keep up with the teaching pace at the current level of concentration; The adjustment module is used to record students who have not kept up with the teaching rhythm and adjust the teaching speed according to the average learning progress of students in the class.

8. The big data-based intelligent teaching comprehensive analysis system according to claim 7 is characterized by: The acquisition module includes: a detection module configured to obtain an area value S of the current student's seat under which a force is above a limit value based on a first force sensor on the bottom surface of the seat, and to obtain a force value f1 through a second force sensor on the back surface, and to establish a sitting posture model of the student in the seat in a database based on the area value S and the force value f1; The concentration acquisition module is used to detect the concentration of students during class. Where K is the total concentration level of the students during the class. is the unit conversion factor.

9. The big data-based intelligent teaching comprehensive analysis system according to claim 8, characterized in that: The analysis module includes: A matching degree analysis module is used to locate the student's book position and book data during the teaching process, record the student's available learning resources, obtain the distance values between the position center points of multiple books on the desk and the center point of the desk in sequence and arrange them in ascending order, determine the position center point of the book closest to the center point of the desk, and mark it as the first target book; locate the first target book frame, mark the page number of the book in the book frame, photograph the content information of the page number in the book frame, and extract the text content in the content information; compare the text content in the content information with the text content preset in the current teaching database, the text content preset in the current teaching database is recorded based on the student's available learning resources, obtain the first overlap degree of the text content in the content information with the text content in the teaching database as w1%, if w1<w0, then locate it in the ascending order For the second target book, obtain a second overlap of w2%. If w1+w2<w0, repeat this step until the total value of the overlap is higher than w0, then record the target book position and corresponding target book data corresponding to the overlap; take the book position image corresponding to the recorded overlap, and mark it as a difficult point marking event; frame the playback screen of the remote tutoring platform, and obtain the focus point of the student's eyeball on the playback screen of the remote tutoring platform; extract the appearance position area of the teaching knowledge point in the playback screen, and the appearance position area of the teaching knowledge point is the corresponding position range of the teacher's current teaching knowledge point; match the corresponding book data with the focus point, and obtain the closest distance between the focus point and the appearance position area of the teaching knowledge point as L, and obtain the distance between the focus point and the position point where the teacher writes notes on the teaching knowledge point as C, then the matching degree between the student's current concentration level and the teaching rhythm in the learning process is Wherein, Q is the preset importance of the current teaching knowledge point, Q is a variable value used to monitor the importance of the current teaching knowledge point, α is the unit conversion coefficient, when the focus point is within the appearance position area of the teaching knowledge point, L is a negative number, and when the focus point is outside the appearance position area of the teaching knowledge point, L is a positive number; A positioning module, the positioning module is used to re-position the new knowledge point note-writing position point after the student turns the book page during the lecture, the knowledge point note-writing position point is used to predict and locate in real time the note position recorded by the student after turning the book page; based on the characteristics of turning the book page, locate the book characteristics in the available learning resources, including: obtaining a cross-sectional image of the book; performing feature extraction on the cross-sectional image of the book to obtain the number of pages turned in the book; after detecting that the characteristics of the teaching knowledge points recorded in the playback screen of the remote tutoring platform have changed, repeatedly recording the appearance position area of the teaching knowledge points in the playback screen; based on the number of book pages turned, the knowledge point features between the appearance position areas of the teaching knowledge points are associated according to the coherence of the text content preset in the teaching database, marking the knowledge point note-writing position points corresponding to the text content after association, and locating the new knowledge point note-writing position point.

10. The big data-based intelligent teaching comprehensive analysis system according to claim 9, characterized in that: The matching degree analysis module includes: An area acquisition submodule, the area acquisition submodule is used to obtain the area value of the location where the teaching knowledge point appears in the playback picture; An input module is used to associate the importance Q of the current teaching knowledge point with the area value S of the appearance area of the teaching knowledge point in the playback screen, and input the area value S as the specific value of Q to determine the matching degree between the student's current concentration level and the teaching rhythm in the learning process.

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