Internet-based teaching management system

Abstract

The invention discloses a teaching management system based on the Internet, and relates to the field of teaching management. The teaching management system based on the Internet comprises a data acquisition module, a data analysis module, a user identification module, a comprehensive analysis module and a management module, acquiring historical behavior data and current behavior data of each student registered user and each teacher registered user of the teaching system, and performing data analysis to obtain a state parameter set of each student registered user and each teacher registered user; and performing comprehensive analysis on the current behavior data of each student registered user and the current behavior data of each teacher registered user in combination with the state parameter set to obtain a corresponding quality evaluation value, and analyzing the quality evaluation value of each student registered user and the quality evaluation value of each teacher registered user with a preset corresponding quality evaluation threshold value. And corresponding management measures are taken according to the analysis result, so that more reasonable and effective management measures are provided, and targeted improvement suggestions and support are further provided.

Description

Technical Field

[0001] The present invention relates to the field of teaching management, and in particular to an Internet-based teaching management system. Background Art

[0002] The Internet-based teaching management system aims to solve the problems of low efficiency, lack of real-time performance and insufficient resource utilization in traditional teaching management through the application of modern information technology. Traditional teaching management relies on manual records and paper archives, with low management efficiency and difficulty in adapting to the needs of large-scale student groups. Cloud computing provides cross-platform resource sharing and collaboration, and big data helps teachers develop personalized teaching plans by analyzing students' learning behaviors and grades. Artificial intelligence is used for automatic homework correction and intelligent evaluation, which greatly reduces teachers' repetitive work. In addition, the application of Internet of Things technology enables the teaching management system to monitor and optimize the classroom environment in real time, and improve interactivity and participation. Through the Internet platform, teachers and students can interact in real time, share online resources and monitor learning dynamics, thereby comprehensively improving teaching quality and management efficiency.

[0003] Prior art, such as the invention patent application with announcement number: CN113487458B, discloses an Internet-based medical chain teaching management system, which comprises the following steps: a cloud platform for storing and recording various information data; a management control module for intelligently controlling various functions of the entire management system; and a user terminal for medical staff to log in to the management system for operation. The management control module outputs learning resource data to the cloud platform and the user terminal, and the cloud platform outputs learning resource data to the user terminal, and the user terminal outputs login information to the management control module. The present invention is scientific and reasonable, safe and convenient to use. The present invention shares the internal educational resources of medical institutions through the cloud platform, so that medical staff can improve their professional skills on the Internet, thereby improving the medical level and the professional quality of medical staff.

[0004] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems. First, although the live broadcast management module in the existing technology provides functions such as question annotation library and barrage recognition, the processing and feedback mechanism of interactive barrage is relatively simple. The processing of barrage relies on static word comparison, and it is difficult to process user questions or feedback in real time and accurately, affecting the user's interactive experience and satisfaction. Secondly, the existing technology mainly focuses on the independent operation of individual functional modules, lacks comprehensive analysis and application of system-wide data, and data analysis is more limited to specific functions, such as barrage analysis or exam management, and fails to form a systematic and comprehensive data utilization. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an Internet-based teaching management system, which solves the problem that although the live broadcast management module in the prior art provides functions such as a question annotation library and barrage recognition, the processing and feedback mechanism for interactive barrage is relatively simple, and the processing of barrage relies on static word comparison, which makes it difficult to process users' questions or feedback in real time and accurately, affecting users' interactive experience and satisfaction. Secondly, the prior art mainly focuses on the independent operation of individual functional modules, lacks comprehensive analysis and application of system-wide data, and data analysis is more limited to specific functions, such as barrage analysis or exam management, and fails to form a systematic comprehensive data utilization problem.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an Internet-based teaching management system, comprising: a data acquisition module, a data analysis module, a comprehensive analysis module, and a management module; the data acquisition module is used to obtain the historical behavior data and current behavior data of each student registered user and teacher registered user of the teaching system; the data analysis module is used to perform data analysis on the historical behavior data of each student registered user and teacher registered user, and obtain a state parameter set of each student registered user and teacher registered user; the comprehensive analysis module is used to perform comprehensive analysis on the current behavior data of each student registered user and teacher registered user in combination with the state parameter set, and obtain a quality evaluation value of each student registered user and teacher registered user; the management module is used to perform analysis based on the quality evaluation value of each student registered user and teacher registered user and a preset quality evaluation threshold, and take teaching management measures according to the corresponding analysis results.

[0007] Furthermore, the historical behavior data of the student registered user specifically includes the historical homework score, historical homework completion time, historical homework estimated completion time, historical test score, historical test total score and historical investment time of each historical homework for each subject; the historical behavior data of the teacher registered user specifically includes the historical satisfaction score, history class participation and history class test average score and history test difficulty coefficient of each student in each history class; the current behavior data of the student registered user specifically includes the current homework corrected score, current test corrected score and current learning efficiency of each subject; the current behavior data of the teacher registered user specifically includes the current satisfaction score, current class participation and current class grade improvement; the status parameter set of the student registered user specifically includes the historical homework corrected score, historical test corrected score and historical learning efficiency of each subject; the status parameter set of the teacher registered user specifically includes the mean historical satisfaction score, the mean history class participation and the mean history class grade improvement.

[0008] Furthermore, the specific steps for obtaining the status parameter set of each student registered user are as follows: respectively analyze the historical homework completion time, the historical homework estimated completion time, the historical test scores, and the historical test total scores of each historical homework of each subject of each student registered user to obtain the homework difficulty factor of each historical homework and the test difficulty factor of each historical test of each subject of each student registered user; respectively analyze the historical homework scores of each historical homework and the historical test scores of each test of each subject of each student registered user with the homework difficulty factor and the test difficulty factor to obtain the historical homework corrected score of each historical homework and the historical test corrected score of each historical test of each subject of each student registered user; analyze the historical investment time and historical test scores of each historical test of each subject of each student registered user to obtain the historical learning efficiency of each subject of each student registered user.

[0009] Furthermore, the historical homework correction score of each historical homework of each subject of each student registered user, the historical test correction score of each historical test, and the specific calculation formula of historical learning efficiency are as follows: ;in, For the Student registered user History of the subject The historical difficulty factor of the task, For the Student registered user History of the subject The historical completion time of the job, For the Student registered user History of the subject The estimated completion time of the historical jobs of the job. For the Student registered user History of the subject The test difficulty factor of the test, For the Student registered user History of the subject Historical scores of tests, For the Student registered user History of the subject Total historical scores of the tests, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered user History of the subject The historical scores of the assignments. For the Student user's History of the subject Historical test difficulty adjusted scores for this test, For the Student registered user History of the subject Historical learning efficiency of the test, For the Student registered user History of the subject The historical time spent on the test, , The number of registered users for students. , is the number of subjects, , is the number of operations, , Number of user quizzes registered for history students.

[0010] Furthermore, the specific steps for obtaining the status parameter set of the registered teacher user are as follows: analyzing the average score of the history class test and the difficulty coefficient of the history test for each historical test of each registered teacher user, and obtaining the improvement rate of the history class grade for each historical test of each registered teacher user; performing a mean analysis on the history satisfaction score, history class participation and history class grade improvement rate of each student in each historical class taught by each registered teacher user, and obtaining the mean history satisfaction score, class participation and history class grade improvement rate of each registered teacher user's history classes.

[0011] Furthermore, the specific steps for obtaining the quality evaluation value of each student registered user are as follows: read the current homework correction score, current test correction score, current learning efficiency of each subject of each student registered user and the historical homework correction score, historical test correction score, and historical learning efficiency of each subject in the corresponding state parameter set; perform statistical analysis on the historical homework correction score, historical test correction score, and historical learning efficiency of each subject of each student registered user to obtain the maximum historical homework correction score, the maximum historical test correction score, the maximum historical learning efficiency, the minimum historical homework correction score, the minimum historical test correction score, and the minimum historical learning efficiency of each subject of each student registered user; combine the mean method to analyze the historical homework correction score, historical test correction score, and historical learning efficiency of each subject of each student registered user to obtain the value of each student. The mean historical homework corrected scores, the mean historical test corrected scores, and the mean historical learning efficiency of each subject of each registered user; analyze the current homework corrected score, current test corrected score, and current learning efficiency of each subject of each student registered user with the mean historical homework corrected score, the mean historical test corrected score, the mean historical learning efficiency, the maximum historical homework corrected score, the maximum historical test corrected score, the maximum historical learning efficiency, the minimum historical homework corrected score, the minimum historical test corrected score, and the minimum historical learning efficiency to obtain the current homework score index, current test score index, and current learning efficiency index of each subject of each student registered user; comprehensively analyze the current homework score index, current test score index, and current learning efficiency index of each subject of each student registered user to obtain the quality assessment value of each student registered user.

[0012] Furthermore, the specific calculation formula for calculating the average of the historical homework corrected scores, the current homework score index and the learning quality evaluation value of each subject of each student registered user is as follows: ;in, For the Student registered user Corrected mean scores for history assignments in each subject, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered users The current assignment score index for each subject, For the Student registered users The corrected score of the current assignment for each subject. For the Student registered user The maximum corrected score for history assignments in each subject. For the Student registered users Minimum corrected score for history assignments in each subject, For the The quality evaluation value of student registered users, The first Student registered user The homework adjustment factor for the current homework score index of the subject, For the Student registered user The current test score index for each subject, The first Student registered user The test adjustment factor for the current test score index for the subject, For the Student registered user Current learning efficiency index of each subject, The first Student registered user The efficiency coefficient of the current learning efficiency index of the subject, and , , The number of registered users for students. , is the number of subjects, , The number of operations.

[0013] Furthermore, the specific steps for obtaining the quality assessment value of each registered teacher user are as follows: read the current satisfaction score, current class participation, current class grade improvement range and the historical satisfaction score average, class participation average, and historical class grade improvement range in the corresponding state parameter set of each registered teacher user; analyze the current satisfaction score, current class participation, current class grade improvement range and the historical satisfaction score average, class participation average, and historical class grade improvement range in the corresponding state parameter set of each registered teacher user to obtain the current satisfaction score index, current class participation index, and current class grade improvement index of each registered teacher user; use the weighted method to conduct a comprehensive analysis of the current satisfaction score index, current class participation index, and current class grade improvement index of each registered teacher user to obtain the quality assessment value of each registered teacher user.

[0014] Furthermore, the specific formulas for calculating the current satisfaction score index, current class participation index, current class performance improvement index, and teaching quality evaluation value of each teacher registered user are as follows: ;in, For the The current satisfaction index of registered teacher users, For the The average historical satisfaction rating of registered teacher users, For the The current satisfaction rating of registered teacher users, For the The current class participation index of registered teacher users, For the The average historical classroom participation of registered teacher users, For the The current class participation rate of teacher registered users, For the The current class performance improvement index of the teacher registered user, For the The average improvement of the historical class scores of the registered teachers, For the The improvement rate of the current class scores of the teacher registered users, For the The quality evaluation value of registered teacher users, The first The satisfaction coefficient of registered teacher users, The first The participation coefficient of teacher registered users, The first The performance coefficient of the teacher registered user, and , , The number of registered teachers. is a natural constant.

[0015] Furthermore, the specific steps of analyzing the quality assessment values ​​of each student registered user and teacher registered user against the preset quality assessment threshold and taking teaching management measures based on the corresponding analysis results are as follows: performing a ratio analysis on the quality assessment value of each student registered user and the preset quality assessment threshold, converting the ratio analysis result into a percentage, generating a quality assessment range for each student registered user, and taking corresponding management measures based on the quality assessment range of each student registered user; performing a ratio analysis on the quality assessment value of each teacher registered user and the preset quality assessment threshold, converting the ratio analysis result into a percentage, generating a quality assessment range for each teacher registered user, and taking corresponding management measures based on the quality assessment range of each teacher registered user.

[0016] The present invention has the following beneficial effects: (1) The Internet-based teaching management system can accurately acquire and analyze the historical behavior data of each student registered user and teacher registered user through the data acquisition module, data analysis module and comprehensive analysis module, and obtain the status parameter set of each student registered user and teacher registered user respectively, so as to more accurately evaluate the actual performance and needs of each user, and generate personalized evaluation values ​​based on the current behavior data and corresponding status parameter set of each student registered user and teacher registered user. At the same time, based on these evaluation values, the quality evaluation range of each student registered user and teacher registered user is generated, thereby ensuring the accuracy and personalization of the evaluation, thereby providing more reasonable and effective management measures, and helping to discover the strengths and weaknesses of users, and then providing targeted improvement suggestions and support.

[0017] (2) The Internet-based teaching management system can monitor and analyze changes in user data in real time through the comprehensive analysis module and management module. It can quickly reflect the current status of students' learning quality and teachers' teaching quality evaluation, and take dynamic adjustment measures. It can make real-time adjustments based on students' current performance and historical data, automatically optimize test questions and teaching content, thereby improving the system's response speed and enhancing the system's adaptability, enabling the system to quickly adapt to different teaching and management needs.

[0018] (3) This Internet-based teaching management system can generate evaluation values ​​for the refined data of student registered users and teacher registered users through a detailed data acquisition and analysis process. This can not only accurately reflect the real performance of users, but also help managers make more scientific management decisions. In addition, through statistical analysis of historical data such as the mean and standard deviation, it can reveal the patterns and trends of user behavior, thereby providing a basis for personalized education and management.

[0019] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of an Internet-based teaching management system of the present invention.

[0021] Figure 2 The present invention is a flowchart of the steps of obtaining a state parameter set of each student registered user in an Internet-based teaching management system.

[0022] Figure 3 The present invention is a flowchart of the steps of obtaining the teaching quality evaluation value of each registered teacher user in an Internet-based teaching management system. DETAILED DESCRIPTION

[0023] The embodiment of the present application solves the problem that although the live broadcast management module in the prior art provides functions such as a question annotation library and barrage recognition, the processing and feedback mechanism for interactive barrage is relatively simple, and the processing of barrage relies on static word comparison, which makes it difficult to process users' questions or feedback in real time and accurately, affecting users' interactive experience and satisfaction. Secondly, the prior art mainly focuses on the independent operation of individual functional modules, lacks comprehensive analysis and application of system-wide data, and data analysis is more limited to specific functions, such as barrage analysis or exam management, and fails to form a systematic and comprehensive data utilization problem.

[0024] The overall idea for solving the problem in the embodiments of the present application is as follows: first, the historical behavior data and current behavior data of each student registered user and teacher registered user of the teaching system are obtained, and then the data analysis module is used to obtain the status parameter set of each student registered user and teacher registered user; secondly, the current behavior data of each student registered user and teacher registered user are combined with the status parameter set for comprehensive analysis to obtain the quality assessment value of each student registered user and teacher registered user; finally, the management module is used to analyze the quality assessment value of each student registered user and teacher registered user with the preset corresponding quality assessment threshold, and teaching management measures are taken according to the corresponding analysis results.

[0025] See also Figure 1The embodiment of the present invention provides a technical solution: a teaching management system based on the Internet, comprising: a data acquisition module, a data analysis module, a comprehensive analysis module, and a management module; the data acquisition module is used to acquire the historical behavior data and current behavior data of each student registered user and teacher registered user of the teaching system; the data analysis module is used to perform data analysis on the historical behavior data of each student registered user and teacher registered user respectively, and obtain the state parameter set of each student registered user and teacher registered user; the comprehensive analysis module is used to perform comprehensive analysis on the current behavior data of each student registered user and teacher registered user in combination with the state parameter set, and obtain the quality evaluation value of each student registered user and teacher registered user; the management module is used to perform analysis based on the quality evaluation value of each student registered user and teacher registered user and the preset quality evaluation threshold, and take teaching management measures according to the corresponding analysis results.

[0026] The historical behavior data of student registered users specifically include the historical homework scores, historical homework completion time, historical homework estimated completion time, historical test scores, total historical test scores and historical investment time for each history homework of each subject. The historical behavior data of teacher registered users specifically include the historical satisfaction score, history class participation and history class test average score and history test difficulty coefficient of each student in each history class. The current behavior data of student registered users specifically include the current homework corrected score, current test corrected score and current learning efficiency of each subject. The current behavior data of teacher registered users specifically include the current satisfaction score, current class participation and current class grade improvement. The status parameter set of student registered users specifically includes the historical homework corrected score, historical test corrected score and historical learning efficiency of each subject. The status parameter set of teacher registered users specifically includes the average historical satisfaction score, the average history class participation and the average history class grade improvement.

[0027] Among them, the historical investment time is the time spent by the student registered user in preparing for each test and taking the test, and the preparation time before each test is calculated through the student registered user's online learning record and the behavior log before the test.

[0028] The current class score improvement is the score improvement between two adjacent test scores.

[0029] The historical satisfaction score is the student satisfaction score of the teacher after each class, which is obtained through the student evaluation data in the teaching feedback system.

[0030] The participation in history class is expressed as the number of comments, questions, and discussions participated in, which is obtained based on the interactive recording system of the learning platform.

[0031] The corrected score of historical assignments is the score after the original assignment score has been adjusted for difficulty. The score is corrected, and the difficulty adjustment is to standardize the scores of assignments of different difficulty levels so that the scores of different assignments can be compared under the same standards.

[0032] The corrected score of a historical test is the score after the original test score has been adjusted for difficulty. The score is corrected, and the difficulty adjustment is to standardize the scores of tests of different difficulty levels so that the scores of different tests can be compared under the same standards.

[0033] The mean improvement in history class grades is the average of the improvement in the overall grades of students in a class during a certain period of history.

[0034] The history test difficulty coefficient is an indicator to measure the relative difficulty of the test paper. The history test difficulty coefficient = (total score of the history test paper - average score of the history class) / total score of the history test paper.

[0035] Specifically, Figure 2 As shown, the specific steps for obtaining the status parameter set of each student registered user are as follows: the historical homework completion time, the historical homework estimated completion time, the historical test scores, and the historical test total scores of each historical homework of each subject of each student registered user are analyzed respectively to obtain the homework difficulty factor of each historical homework and the test difficulty factor of each historical test of each subject of each student registered user; the historical homework scores of each historical homework and the historical test scores of each test of each subject of each student registered user are analyzed with the homework difficulty factor and the test difficulty factor respectively to obtain the historical homework corrected score of each historical homework and the historical test corrected score of each historical test of each subject of each student registered user; the historical investment time and historical test scores of each historical test of each subject of each student registered user are analyzed to obtain the historical learning efficiency of each subject of each student registered user.

[0036] In this implementation scheme, by analyzing data such as homework completion time and test scores, the homework difficulty factor and test difficulty factor of each subject can be obtained, which helps to understand the actual difficulty level of each subject and provide data support for subsequent adjustments to learning strategies. The difficulty adjustment scores of historical homework and tests can help understand the performance of student registered users at different difficulty levels, and help provide personalized learning suggestions for student registered users, thereby improving the quality of learning. At the same time, by analyzing the time and scores invested in tests, the learning efficiency of each subject can be evaluated, which can help student registered users and teacher registered users identify learning strengths and weaknesses, thereby optimizing learning time allocation and teaching methods.

[0037] Specifically, the historical homework correction score of each historical homework of each subject of each student registered user, the historical test correction score of each historical test, and the specific calculation formula of historical learning efficiency are as follows: ;in, For the Student registered user History of the subject The historical difficulty factor of the task, For the Student registered user History of the subject The historical completion time of the job, For the Student registered user History of the subject The estimated completion time of the historical jobs of the job. For the Student registered user History of the subject The test difficulty factor of the test, For the Student registered user History of the subject Historical scores of tests, For the Student registered user History of the subject Total historical scores of the tests, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered user History of the subject The historical scores of the assignments. For the Student user's History of the subject Historical test difficulty adjusted scores for this test, For the Student registered user History of the subject Historical learning efficiency of the test, For the Student registered user History of the subject The historical time spent on the test, , The number of registered users for students. , is the number of subjects, , is the number of operations, , Number of user quizzes registered for history students.

[0038] Among them, the calculation logic of the historical test corrected score of each test of each subject of each student registered user and the historical homework corrected score of each homework are consistent, and the calculation formula is also consistent.

[0039] In this implementation scheme, firstly, by calculating the historical homework corrected scores and historical test corrected scores of each student registered user, the student's performance in different subjects and tasks can be evaluated more comprehensively, and the difficulty and completion time of the task are taken into consideration, which can more accurately reflect the student's true learning level. Secondly, according to the student's performance in different homework and tests, the teacher can better provide personalized support and guidance to the students, and the teacher can timely discover the student's learning progress and dynamically adjust the student's learning plan. At the same time, the students can obtain real-time feedback on the learning process, which helps to improve their ability of self-management and learning strategy adjustment. Finally, through the calculation of the difficulty adjustment score, the simple comparison of tasks of different difficulty levels is avoided, making the evaluation criteria more fair and reasonable.

[0040] Specifically, the specific steps for obtaining the status parameter set of teacher registered users are as follows: analyze the average score of history class tests and the difficulty coefficient of history tests for each historical test of each teacher registered user, and obtain the improvement rate of history class grades for each historical test of each teacher registered user; perform mean analysis on the history satisfaction score, history class participation and history class grade improvement rate of each student in each historical class taught by each teacher registered user, and obtain the mean history satisfaction score, class participation mean and history class grade improvement rate of each teacher registered user's history classes.

[0041] Among them, the specific formula for calculating the historical class score improvement rate, the historical class score improvement rate average, and the historical satisfaction score average of each teacher registered user is as follows: ;in, For the Teacher registered users in history The improvement in the history class scores for the 10-test period was For the Teacher registered users in history The average score of the history class test for the test, For the Teacher registered users in history The average score of the history class test for the test, For the Teacher registered users in history The historical difficulty coefficient of the test, For the Teacher registered users in history The historical difficulty coefficient of the test, For the The average improvement of the historical class scores of the registered teachers, For the The average historical satisfaction rating of registered teacher users, For the The first registered teacher user The first lesson The student satisfaction ratings , The number of registered teachers. , Number of quizzes registered for history teachers, , Number of history lessons, , The number of students taught history.

[0042] It needs to be explained that the calculation logic of the average participation in history classes of each teacher’s registered users is consistent with the average improvement in history class grades, and the calculation formula is also the same.

[0043] In this implementation scheme, by calculating the improvement in class grades, satisfaction scores and classroom participation of registered users of teachers in history classes, the performance of teachers in different teaching environments can be comprehensively evaluated, thereby avoiding the limitation of relying on a single indicator and being able to more comprehensively reflect the teaching effectiveness of teachers. Secondly, the teacher's performance improvement index can be obtained to quantify the teacher's teaching improvement, which is helpful to judge the changes in the teacher's teaching quality in each class, so as to discover effective teaching strategies and promote them. At the same time, through the analysis of the current satisfaction score and the current classroom participation, real-time feedback can be provided to teachers to help them better understand students' feedback and participation in the course. Moreover, the dynamic feedback mechanism can motivate teachers to reflect on themselves and optimize after each class to improve their teaching level. Finally, through the mean calculation of historical data, teachers can adjust their teaching strategies based on the long-term accumulated performance. For example, if the class grade improvement is high, it means that the teacher's teaching method is effective and can be maintained and further optimized.

[0044] Specifically, the specific steps for obtaining the (learning) quality evaluation value of each student registered user are as follows: read the current homework correction score, current test correction score, current learning efficiency of each subject of each student registered user and the historical homework correction score, historical test correction score, and historical learning efficiency of each subject in the corresponding state parameter set; perform statistical analysis on the historical homework correction score, historical test correction score, and historical learning efficiency of each subject of each student registered user to obtain the maximum historical homework correction score, the maximum historical test correction score, the maximum historical learning efficiency, the minimum historical homework correction score, the minimum historical test correction score, and the minimum historical learning efficiency of each subject of each student registered user; combine the mean method to analyze the historical homework correction score, historical test correction score, and historical learning efficiency of each subject of each student registered user to obtain the value of each student. The mean historical homework corrected score, the mean historical test corrected score, and the mean historical learning efficiency of each subject of each registered user; analyze the current homework corrected score, current test corrected score, and current learning efficiency of each subject of each student registered user with the mean historical homework corrected score, the mean historical test corrected score, the mean historical learning efficiency, the maximum historical homework corrected score, the maximum historical test corrected score, the maximum historical learning efficiency, the minimum historical homework corrected score, the minimum historical test corrected score, and the minimum historical learning efficiency respectively to obtain the current homework score index, current test score index, and current learning efficiency index of each subject of each student registered user; comprehensively analyze the current homework score index, current test score index, and current learning efficiency index of each subject of each student registered user to obtain the (learning) quality assessment value of each student registered user.

[0045] Among them, the current homework corrected score, current test corrected score, current learning efficiency of each subject of each student registered user are obtained in the same steps as the historical homework corrected score, historical test corrected score, and historical learning efficiency.

[0046] In this implementation scheme, by comparing the current behavior data with the historical data, the student's performance changes can be comprehensively considered to provide a more accurate learning quality assessment. The historical data provides a benchmark, and the current behavior data reflects the student's latest status. The combination of the two can fully understand the student's learning situation. Secondly, combined with the maximum, minimum and mean analysis methods, the student's current performance can be dynamically adjusted and fed back, and the latest progress made by the student in the learning process can be reflected in real time, motivating students to continue their efforts or helping them find directions for improvement. Through the comprehensive analysis of homework correction scores, test correction scores and learning efficiency, the assessment not only focuses on the student's final grades, but also considers their learning process, so as to more comprehensively understand the student's learning status and avoid the overall assessment results being affected by fluctuations in one-time test scores. Then, by comparing the current and historical data, the strengths and weaknesses of students in homework and tests can be identified. Finally, the provided learning quality assessment value can be used as the basis for teachers and students to discuss learning progress and goal setting, promote a common understanding of the learning situation between both parties, and students can set specific learning goals based on the comprehensive analysis results and obtain appropriate incentives to improve learning motivation and effectiveness.

[0047] Specifically, the specific calculation formula for calculating the average of the historical homework corrected scores, the current homework score index and the quality evaluation value of each subject of each student registered user is as follows: ;in, For the Student registered user Corrected mean scores for history assignments in each subject, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered users The current assignment score index for each subject, For the Student registered users The corrected score of the current assignment for each subject. For the Student registered user The maximum corrected score for history assignments in each subject. For the Student registered users Minimum corrected score for history assignments in each subject, For the The (learning) quality evaluation value of student registered users, The first Student registered user The homework adjustment factor for the current homework score index of the subject, For the Student registered user The current test score index for each subject, The first Student registered user The test adjustment factor for the current test score index for the subject, For the Student registered user Current learning efficiency index of each subject, The first Student registered user The efficiency coefficient of the current learning efficiency index of the subject, and , , The number of registered users for students. , is the number of subjects, , The number of operations.

[0048] It needs to be explained that , , The specific acquisition process is: read the mean historical homework corrected score, the mean historical test corrected score, and the mean historical learning efficiency of each subject of each student registered user and perform sum analysis to obtain the (learning) quality evaluation and value of each subject of each student registered user; perform proportion analysis on the mean historical homework corrected score, the mean historical test corrected score, and the mean historical learning efficiency of each subject of each student registered user and the (learning) quality evaluation and value, and the proportion analysis result is the corresponding weighting coefficient.

[0049] The calculation logic and formula of the mean corrected historical test scores, the mean historical learning efficiency and the mean corrected historical homework scores of each subject for each registered student user are consistent. At the same time, the calculation logic and formula of the current test score index, current learning efficiency index and current homework score index of each subject for each registered student user are consistent.

[0050] In this implementation plan, by combining the student's current homework score index, current test score index and current learning efficiency index, the student's learning quality is comprehensively evaluated. Compared with the evaluation of a single indicator, this multi-dimensional comprehensive evaluation method can more accurately reflect the student's overall learning status and ensure that the evaluation is more comprehensive and objective. Secondly, by comparing and analyzing the student's historical behavior data with the current behavior data, it can effectively track the student's progress or regression, help identify the weak links in their learning, and then reflect the student's long-term learning effect. It can also discover changes in recent performance and make timely adjustments. At the same time, by analyzing the proportion of the historical score mean and the current index, the weighting coefficient is dynamically adjusted to flexibly reflect the student's current learning status, which helps to discover fluctuations in learning efficiency, homework and test performance in real time, and then provide timely feedback and suggestions. Finally, through precise formulas and weighted analysis, the evaluation results are more scientific and transparent. Data-driven decision-making can not only reduce subjective bias, but also provide students and teachers with improvement suggestions based on objective data, thereby improving the fairness and credibility of the evaluation.

[0051] Specifically, Figure 3 As shown in the figure, the specific steps to obtain the (teaching) quality evaluation value of each registered teacher user are as follows: read the current satisfaction score, current class participation, current class grade improvement range of each registered teacher user and the historical satisfaction score average, class participation average, and historical class grade improvement range average in the corresponding state parameter set; analyze the current satisfaction score, current class participation, current class grade improvement range of each registered teacher user and the historical satisfaction score average, class participation average, and historical class grade improvement range average in the corresponding state parameter set to obtain the current satisfaction score index, current class participation index, and current class grade improvement index of each registered teacher user; use the weighted method to conduct a comprehensive analysis of the current satisfaction score index, current class participation index, and current class grade improvement index of each registered teacher user to obtain the (teaching) quality evaluation value of each registered teacher user.

[0052] Among them, the steps for obtaining the current class grade improvement of each teacher registered user and the historical class grade improvement are consistent.

[0053] In this implementation plan, the teaching quality of registered teacher users is comprehensively evaluated through three key dimensions (satisfaction score, class participation, and class grade improvement). It not only focuses on student satisfaction, but also combines class participation and actual teaching effects (such as class grade improvement) to ensure that the evaluation results are more comprehensive and objective. Secondly, by comparing and analyzing current data with historical data, we can better understand the changing trend of teachers' teaching status, so as to accurately identify teachers' progress or regression, and make corresponding adjustments or intervention measures to ensure that teachers can continuously improve their teaching quality. At the same time, by comparing teachers' current performance with historical averages, we can provide teachers with personalized feedback and provide feedback through specific quantitative indicators (satisfaction score, class participation, and class grade improvement). The evaluation value of teachers' teaching quality is generated by using the weighted method, which reduces subjective bias, provides a more scientific and transparent basis for teaching quality evaluation, and enhances the credibility of the evaluation process. Finally, combined with the comparative analysis of current and historical data, it can dynamically monitor teachers' teaching performance and identify performance fluctuations in a timely manner. Schools or education management agencies can provide teachers with timely training, support or incentives based on the results of dynamic monitoring to ensure continuous improvement of teaching quality, provide advanced development opportunities for teachers with outstanding performance in a targeted manner, and provide additional training and guidance for teachers who need improvement to ensure the rational allocation of educational resources.

[0054] Specifically, the specific formula for calculating the current satisfaction score index, current class participation index, current class performance improvement index, and teaching quality evaluation value of each teacher registered user is as follows: ;in, For the The current satisfaction index of registered teacher users, For the The average historical satisfaction rating of registered teacher users, For the The current satisfaction rating of registered teacher users, For the The current class participation index of registered teacher users, For the The average historical classroom participation of registered teacher users, For the The current class participation rate of teacher registered users, For the The current class performance improvement index of the teacher registered user, For the The average improvement of the historical class scores of the registered teachers, For the The improvement rate of the current class scores of the teacher registered users, For the The (teaching) quality evaluation value of each registered teacher user, The first The satisfaction coefficient of registered teacher users, The first The participation coefficient of teacher registered users, The first The performance coefficient of the teacher registered user, and , , The number of registered teachers. It is a natural constant, usually taken as 2.71.

[0055] It needs to be explained that , , The specific acquisition process is: obtain the current satisfaction score index, current classroom participation index, and current class grade improvement index of each registered teacher user and perform sum analysis to obtain the (teaching) quality evaluation and value of each registered teacher user, and perform proportion analysis on the current satisfaction score index, current classroom participation index, and current class grade improvement index of each registered teacher user and the (teaching) quality evaluation and value respectively, and the proportion analysis result is the corresponding weighting coefficient.

[0056] Among them, The following table shows an example of the calculation data of the (teaching) quality evaluation value of each registered teacher user: Table 1 Example of calculation data of the (teaching) quality evaluation value of registered teacher users

[0057] In the table, For the The average historical satisfaction rating of registered teacher users, in points. For the The current satisfaction rating of registered teacher users, in points. For the The current satisfaction index of registered teacher users, For the The average historical classroom participation of registered teacher users, For the The current class participation rate of teacher registered users, For the The current class participation index of registered teacher users, For the The average improvement of the historical class scores of the registered teachers, For the The improvement rate of the current class scores of the teacher registered users, For the The current class performance improvement index of the teacher registered user, The first The satisfaction coefficient of registered teacher users, The first The participation coefficient of teacher registered users, The first The performance coefficient of each teacher registered user, For the The (teaching) quality evaluation value of each registered teacher user.

[0058] The first set of data: The average historical satisfaction rating of users is: 4.00; The current satisfaction rating of registered teacher users is: 4.20; The current satisfaction index of the registered teacher users is about: 0.05; The average participation rate of history classes among registered teachers is: 0.80; The current classroom participation rate of the teacher registered user is: 0.85; The current classroom participation index of the teacher registered users is approximately: 0.06; The average improvement in the history class scores of the teacher registered users is: 0.15; The improvement of the current class score of the teacher registered user is: 0.18; The current class score improvement index of the teacher registered user is: 0.17; the first The satisfaction coefficient of the teacher registered user is about: 0.18; the first The participation coefficient of each teacher registered user is approximately: 0.21; the first The performance coefficient of each teacher registered user is approximately: 0.61; The (teaching) quality evaluation value of registered teacher users is approximately: 5.61.

[0059] The second set of data: The average historical satisfaction rating of teacher registered users is: 4.00; The current satisfaction rating of registered teacher users is: 3.80; The current satisfaction index of the registered teacher users is about: 0.05; The average participation rate of history classes among registered teachers is: 0.80; The current classroom participation rate of the teacher registered users is: 0.82; The current classroom participation index of the teacher registered users is approximately: 0.03; The average improvement in the history class scores of the teacher registered users is: 0.15; The current class score improvement of the teacher registered user is: 0.15; The current class score improvement index of the teacher registered user is: 0.15; the first The satisfaction coefficient of the teacher registered user is about: 0.22; the first The participation coefficient of each teacher registered user is approximately: 0.13; the first The performance coefficient of each teacher registered user is approximately: 0.65; The (teaching) quality evaluation value of registered teacher users is approximately: 5.42.

[0060] The third set of data: The average historical satisfaction rating of teacher registered users is: 4.00; The current satisfaction rating of registered teacher users is: 3.70; The current satisfaction index of registered teacher users is approximately: 0.08; The average participation rate of history classes among registered teachers is: 0.80; The current classroom participation rate of the teacher registered users is: 0.87; The current classroom participation index of registered teacher users is approximately: 0.09; The average improvement in the history class scores of the teacher registered users is: 0.15; The current class score improvement of the teacher registered user is: 0.20; The current class score improvement index of the teacher registered user is: 0.18; the first The satisfaction coefficient of the teacher registered user is about: 0.24; the first The participation coefficient of each teacher registered user is approximately: 0.25; the first The performance coefficient of each teacher registered user is approximately: 0.51; The (teaching) quality evaluation value of registered teacher users is approximately: 5.43.

[0061] The fourth set of data: The average historical satisfaction rating of teacher registered users is: 4.00; The current satisfaction rating of registered teacher users is: 4.30; The current satisfaction index of registered teacher users is approximately: 0.08; The average participation rate of history classes among registered teachers is: 0.80; The current classroom participation rate of the teacher registered user is: 0.85; The current classroom participation index of the teacher registered users is approximately: 0.06; The average improvement in the history class scores of the teacher registered users is: 0.15; The improvement of the current class score of the teacher registered user is: 0.12; The current class score improvement index of the teacher registered user is: 0.14; the first The satisfaction coefficient of the teacher registered user is about: 0.28; the first The participation coefficient of each teacher registered user is approximately: 0.22; the first The performance coefficient of each teacher registered user is approximately: 0.50; The (teaching) quality evaluation value of registered teacher users is approximately: 5.62.

[0062] The fifth set of data: The average historical satisfaction rating of teacher registered users is: 4.00; The current satisfaction rating of registered teacher users is: 4.10; The current satisfaction index of registered teacher users is approximately: 0.03; The average participation rate of history classes among registered teachers is: 0.80; The current classroom participation rate of the teacher registered users is: 0.83; The current classroom participation index of the teacher registered users is approximately: 0.04; The average improvement in the history class scores of the teacher registered users is: 0.15; The improvement of the current class score of the teacher registered user is: 0.11; The current class score improvement index of the teacher registered user is: 0.13; the first The satisfaction coefficient of the teacher registered user is about: 0.15; the first The participation coefficient of each teacher registered user is approximately: 0.20; the first The performance coefficient of each teacher registered user is approximately: 0.65; The (teaching) quality evaluation value of registered teacher users is approximately: 6.03.

[0063] In this implementation plan, by comprehensively analyzing the data of three aspects, namely, current satisfaction score, classroom participation and class grade improvement, the teaching quality of each registered teacher user can be comprehensively evaluated, and the actual teaching effect of the registered teacher user can be more accurately reflected, avoiding the deviation that may be caused by a single indicator. By comparing the current behavior data with the historical data, the registered teacher user can see the changes in his or her performance in various aspects. Secondly, according to the evaluation results, the registered teacher user can obtain specific feedback, which is helpful to formulate personalized improvement plans. For example, by providing clear teaching quality evaluation standards, teachers can clearly understand their own performance, thereby helping teachers to identify their own strengths and weaknesses, and then motivating teachers to invest more energy and effort in teaching to improve the quality of teaching. Then, weighted coefficients such as satisfaction coefficient, participation coefficient and grade coefficient are used to make the evaluation results more scientific and objective, ensure the reliability and fairness of the evaluation results, and help registered teacher users make reasonable improvement decisions based on data. Finally, through a scientific evaluation and feedback mechanism, the allocation of teaching resources can be optimized and the overall teaching quality can be improved.

[0064] Specifically, the quality evaluation values ​​of each student registered user and teacher registered user are analyzed with the preset quality evaluation thresholds, and the specific steps of taking teaching management measures according to the corresponding analysis results are as follows: Perform a ratio analysis on the (learning) quality assessment value of each registered student user and the preset (learning) quality assessment threshold, convert the ratio analysis result into a percentage, generate the (learning) quality assessment range of each registered student user, and take corresponding management measures based on the (learning) quality assessment range of each registered student user; The specific process is as follows: The formula for generating the (learning) quality assessment range for each student registered user is as follows: ,in, For the The (learning) quality evaluation value of student registered users, For the preset The (learning) quality assessment threshold for student registered users, , The number of registered students.

[0065] Jordi If the (learning) quality assessment range of a student registered user is between 0 and 20%, it is considered to be at a low level, and a detailed reinforcement learning plan is automatically generated for the student registered user, multiple rounds of tests and exercises are arranged to help the student improve his or her grades, and progress tracking is set up, and a learning progress report is generated every week to remind teachers and parents to continue to pay attention to the student's progress; Jordi If the (learning) quality assessment range of a student registered user is between 21% and 40%, it is considered to be below average, and the teacher is recommended to provide individual tutoring for the student registered user to help him / her solve the difficulties in learning. A detailed learning report is generated to analyze the student's problems and automatically pushed to the teacher; Jordi If the (learning) quality assessment range of a student registered user is between 41% and 60%, it is considered to be at a medium level, and the student registered user will be prompted with the learning content that needs to be strengthened, and a personalized tutoring plan will be automatically generated to provide more exercises and guidance for the student's weak areas. At the same time, the teacher will be notified to pay more attention to the student and provide guidance; Jordi If the (learning) quality assessment of a student user is between 61% and 80%, it is considered to be at a good level, and additional learning materials or exercises are recommended for the student user, and teachers are notified and encouraged to communicate with students to discuss strategies for improvement; Jordi If the (learning) quality assessment range of a student registered user is between 81% and 100%, it is considered to be at an excellent level, and the student registered user will be included in the list of outstanding students, and an electronic award or certificate will be automatically generated. Based on the student's excellent performance, more difficult learning resources or challenging tasks will be recommended to help him / her further improve. A proportion analysis is performed between the (teaching) quality assessment value of each registered teacher user and the preset (teaching) quality assessment threshold, and the result of the proportion analysis is converted into a percentage to generate the (teaching) quality assessment range of each registered teacher user. Corresponding management measures are then taken based on the (teaching) quality assessment range of each registered teacher user.

[0066] The specific process is as follows: The formula for generating the (teaching) quality assessment range for each teacher registered user is as follows: ,in, For the The (teaching) quality evaluation value of each registered teacher user, For the preset The (teaching) quality evaluation threshold for registered teacher users, , The number of registered teachers.

[0067] Jordi If the (teaching) quality evaluation range of a registered teacher user is between 0 and 20%, it is considered to be at a low level, and the registered teacher user will be subject to emergency teaching intervention, and teaching guidance experts will be recommended to help improve teaching methods. A regular teaching progress tracking mechanism will be set up to generate periodic teaching reports and timely evaluate the teacher's improvement progress; Jordi If the (teaching) quality evaluation range of a registered teacher user is between 21% and 40%, it is considered to be at a lower-middle level, and a teaching problem analysis report is automatically generated for the registered teacher user, and a series of improvement measures are provided for the teacher's reference, and training and tutoring courses are recommended for the teacher; Jordi If the (teaching) quality assessment range of a teacher registered user is between 41% and 60%, it is considered to be at a medium level, and a teaching improvement plan will be automatically generated for the teacher registered user to optimize the weak links, and detailed teaching feedback will be automatically generated to provide improvement suggestions for the teacher's reference and adjustment; Jordi If the (teaching) quality evaluation range of a registered teacher user is between 61% and 80%, it is considered to be at a good level, and teaching feedback is automatically generated for the registered teacher user to help the teacher maintain and further improve the teaching quality, and recommend corresponding teaching tools, methods and materials to improve classroom effects. At the same time, detailed teaching improvement suggestions are generated based on data analysis and sent to the registered teacher user; Jordi If the (teaching) quality assessment range of a registered teacher user is between 81% and 100%, it is considered to be at an excellent level, and a commendation notice will be automatically generated and sent to the registered teacher user to reward the teacher's excellent performance, and recommend the teacher to participate in demonstration teaching activities and share teaching experience.

[0068] The quality assessment threshold is the standardized highest quality assessment value that a user can achieve.

[0069] In this implementation plan, by taking corresponding management measures for different evaluation scopes of different registered users (students and teachers), we ensure that the needs of different registered users (students and teachers) receive customized attention, thereby helping students improve their learning outcomes and helping teachers improve their teaching quality. Secondly, each evaluation scope corresponds to specific improvements or incentives. At the same time, we not only focus on registered users with poor performance, but also on those with medium or excellent performance, and provide positive feedback and incentives to maintain the enthusiasm of users and encourage them to continue to maintain or improve their current levels in the future. Finally, the system provides different levels of support and resources for users of different levels. Differentiated support can effectively allocate resources and improve overall efficiency. Through timely feedback and incentives, users can feel their progress and achievements in a timely manner, enhance their self-confidence and sense of accomplishment, and thus be more engaged in learning or work. From evaluation and comparison to taking measures, we ensure that all users are in an orderly management system, so that the progress of different registered users can be tracked and adjusted in a timely manner.

[0070] In summary, this application has at least the following effects: Through the data acquisition module, data analysis module and comprehensive analysis module, the historical behavior data of each user can be accurately acquired and analyzed, and the status parameter sets of student registered users and teacher registered users can be obtained respectively, so as to more accurately evaluate the actual performance and needs of each user. A comprehensive analysis is performed based on each user's current behavior data and status parameter set to generate personalized evaluation values. At the same time, the user's quality evaluation range is generated based on these evaluation values, ensuring the accuracy and personalization of the evaluation, thereby providing more reasonable and effective management measures, helping to discover the strengths and weaknesses of users, and then providing targeted improvement suggestions and support.

[0071] Through the comprehensive analysis module and management module, it is possible to monitor and analyze changes in user data in real time, evaluate students' learning quality and teachers' teaching quality, quickly reflect the current status, and take dynamic adjustment measures. It makes real-time adjustments based on students' current performance and historical data, and automatically optimizes test questions and teaching content, thereby improving the system's response speed and enhancing its adaptability, enabling the system to quickly adapt to different teaching and management needs.

[0072] Through a detailed data acquisition and analysis process, the evaluation values ​​generated for the refined data of student registered users and teacher registered users can not only accurately reflect the user's true performance, but also help managers make more scientific management decisions. In addition, through statistical analysis of historical data such as the mean and standard deviation, the patterns and trends of user behavior can be revealed, thus providing a basis for personalized education and management.

[0073] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0074] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An Internet-based teaching management system, characterized in that: include: Data acquisition module, data analysis module, comprehensive analysis module, management module; The data acquisition module is used to acquire the historical behavior data and current behavior data of each student registered user and teacher registered user of the teaching system; The data analysis module is used to analyze the historical behavior data of each student registered user and teacher registered user to obtain a state parameter set of each student registered user and teacher registered user; The comprehensive analysis module is used to comprehensively analyze the current behavior data of each student registered user and teacher registered user in combination with the state parameter set to obtain the quality evaluation value of each student registered user and teacher registered user; The management module is used to analyze the quality evaluation value of each student registered user and teacher registered user respectively with the preset quality evaluation threshold, and take teaching management measures according to the corresponding analysis results.

2. The Internet-based teaching management system according to claim 1, characterized in that: The historical behavior data of the student registered user specifically include the historical homework score, historical homework completion time, historical homework estimated completion time, historical test score, historical test total score and historical investment time of each historical homework for each subject; the historical behavior data of the teacher registered user specifically include the historical satisfaction score, history class participation and history class test average score and history test difficulty coefficient of each student in each history class; the current behavior data of the student registered user specifically include the current homework corrected score, current test corrected score and current learning efficiency of each subject; the current behavior data of the teacher registered user specifically include the current satisfaction score, current class participation and current class grade improvement; the status parameter set of the student registered user specifically include the historical homework corrected score, historical test corrected score and historical learning efficiency of each subject; the status parameter set of the teacher registered user specifically include the mean historical satisfaction score, the mean history class participation and the mean history class grade improvement.

3. The Internet-based teaching management system according to claim 2, characterized in that: The specific steps to obtain the status parameter set of each student registered user are as follows: Analyze the completion time of each historical homework, the estimated completion time of each historical homework, the historical test score of each historical test, and the total score of each historical test for each subject of each student registered user, and obtain the homework difficulty factor of each historical homework and the test difficulty factor of each historical test for each subject of each student registered user; Analyze the historical homework scores of each historical homework and the historical test scores of each test of each subject of each student registered user with the homework difficulty factor and the test difficulty factor respectively, and obtain the historical homework corrected scores of each historical homework and the historical test corrected scores of each historical test of each subject of each student registered user; The historical investment time and historical test scores of each subject of each student registered user are analyzed to obtain the historical learning efficiency of each subject of each student registered user.

4. The Internet-based teaching management system according to claim 3 is characterized in that: The specific calculation formula for calculating the historical homework correction score of each historical homework of each subject of each student registered user, the historical test correction score of each historical test, and the historical learning efficiency is as follows: ； in, For the Student registered user History of the subject The historical difficulty factor of the task, For the Student registered user History of the subject The historical completion time of the job, For the Student registered user History of the subject The estimated completion time of the historical jobs of the job. For the Student registered user History of the subject The test difficulty factor of the test, For the Student registered user History of the subject Historical scores of tests, For the Student registered user History of the subject Total historical scores of the tests, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered user History of the subject The historical scores of the assignments. For the Student user's History of the subject Historical test difficulty adjusted scores for this test, For the Student registered user History of the subject Historical learning efficiency of the test, For the Student registered user History of the subject The historical time spent on the test, , The number of registered users for students. , is the number of subjects, , is the number of operations, , Number of user quizzes registered for history students.

5. The Internet-based teaching management system according to claim 2, characterized in that: The specific steps to obtain the status parameter set of each teacher registered user are as follows: Analyze the average score of the history class test and the difficulty coefficient of the history test for each teacher registered user in each test, and obtain the improvement of the history class score for each teacher registered user in each test; A mean analysis was conducted on the history satisfaction score, history class participation, and history class grade improvement of each student in each history class taught by each teacher’s registered user, and the mean history satisfaction score, class participation, and history class grade improvement of each teacher’s registered user’s history classes were obtained.

6. The Internet-based teaching management system according to claim 2, characterized in that: The specific steps to obtain the quality evaluation value of each student registered user are as follows: Read the current homework correction score, current test correction score, current learning efficiency of each subject of each student registered user and the historical homework correction score, historical test correction score, and historical learning efficiency of each subject in the corresponding state parameter set; Perform statistical analysis on the corrected historical homework scores, corrected historical test scores, and historical learning efficiency of each subject of each registered student user, and obtain the maximum corrected historical homework scores, the maximum corrected historical test scores, the maximum historical learning efficiency, the minimum corrected historical homework scores, the minimum corrected historical test scores, and the minimum historical learning efficiency of each subject of each registered student user; Combined with the mean method, the corrected scores of historical homework, corrected scores of historical tests, and historical learning efficiency of each subject of each registered student user are analyzed to obtain the mean corrected scores of historical homework, the mean corrected scores of historical tests, and the mean historical learning efficiency of each subject of each registered student user; Analyze the current homework corrected score, current test corrected score, and current learning efficiency of each subject of each registered student user with the mean of historical homework corrected scores, the mean of historical test corrected scores, the mean of historical learning efficiency, the maximum value of historical homework corrected scores, the maximum value of historical test corrected scores, the maximum value of historical learning efficiency, the minimum value of historical homework corrected scores, the minimum value of historical test corrected scores, and the minimum value of historical learning efficiency, to obtain the current homework score index, current test score index, and current learning efficiency index of each subject of each registered student user; A comprehensive analysis is performed on the current homework score index, current test score index, and current learning efficiency index of each subject of each student registered user to obtain a quality assessment value for each student registered user.

7. The Internet-based teaching management system according to claim 6, characterized in that: The specific calculation formula for calculating the average corrected score of historical homework, the current homework score index and the quality assessment value of each subject for each student registered user is as follows: ； in, For the Student registered user Corrected mean scores for history assignments in each subject, For the Student registered user History of the subject The historical homework correction score of the homework, For the Student registered users The current assignment score index for each subject, For the Student registered users The corrected score of the current assignment for each subject. For the Student registered user The maximum corrected score for history assignments in each subject. For the Student registered users Minimum corrected score for history assignments in each subject, For the The quality evaluation value of student registered users, The first Student registered user The homework adjustment factor for the current homework score index of the subject, For the Student registered user The current test score index for each subject, The first Student registered user The test adjustment factor for the current test score index for the subject, For the Student registered user Current learning efficiency index of each subject, The first Student registered user The efficiency coefficient of the current learning efficiency index of the subject, and , , The number of registered users for students. , is the number of subjects, , The number of operations.

8. The Internet-based teaching management system according to claim 2, characterized in that: The specific steps to obtain the quality evaluation value of each teacher registered user are as follows: Read the current satisfaction score, current class participation, current class grade improvement of each teacher registered user and the historical average satisfaction score, average class participation, and historical average class grade improvement in the corresponding state parameter set; Analyze the current satisfaction score, current class participation, current class grade improvement of each teacher registered user and the historical satisfaction score mean, class participation mean, and historical class grade improvement mean in the corresponding state parameter set to obtain the current satisfaction score index, current class participation index, and current class grade improvement index of each teacher registered user; Combined with the weighted method, a comprehensive analysis is conducted on the current satisfaction score index, current classroom participation index, and current class performance improvement index of each registered teacher user to obtain the quality assessment value of each registered teacher user.

9. The Internet-based teaching management system according to claim 8, characterized in that: The specific formula for calculating the current satisfaction score index, current class participation index, current class performance improvement index, and teaching quality evaluation value of each teacher registered user is as follows: ； in, For the The current satisfaction index of registered teacher users, For the The average historical satisfaction rating of registered teacher users, For the The current satisfaction rating of registered teacher users, For the The current class participation index of registered teacher users, For the The average historical classroom participation of registered teacher users, For the The current class participation rate of teacher registered users, For the The current class performance improvement index of the teacher registered user, For the The average improvement of the historical class scores of the registered teachers, For the The improvement rate of the current class scores of the teacher registered users, For the The quality evaluation value of registered teacher users, The first The satisfaction coefficient of registered teacher users, The first The participation coefficient of teacher registered users, The first The performance coefficient of the teacher registered user, and , , The number of registered users for teachers, is a natural constant.

10. The Internet-based teaching management system according to claim 1, characterized in that: The specific steps for analyzing the quality assessment values ​​of each student registered user and teacher registered user with the preset quality assessment threshold and taking teaching management measures according to the corresponding analysis results are as follows: Perform a ratio analysis on the quality assessment value of each student registered user and the preset quality assessment threshold, convert the ratio analysis result into a percentage, generate the quality assessment range of each student registered user, and take corresponding management measures based on the quality assessment range of each student registered user; The quality assessment value of each registered teacher user is analyzed in proportion to the preset quality assessment threshold, and the result of the proportion analysis is converted into a percentage to generate the quality assessment range of each registered teacher user. Corresponding management measures are then taken based on the quality assessment range of each registered teacher user.

Images