Management method and system of teacher training management platform

Abstract

The invention relates to the technical field of teacher training management, and relates to a management method and system for a teacher training management platform, and the method comprises the steps: determining basic information corresponding to a user when the user is detected to log in the teacher training management platform; performing grade evaluation on professional knowledge of the user according to the basic information to obtain an evaluation result; mapping a training grade according to an evaluation result, and matching a grade association sub-database in a training information database according to the training grade; historical search information of the user is learned and mined, and training materials meeting the integrating degree are matched in the grade correlation sub-database according to the learning and mining result; and pushing the training data to the user. According to the management method and system of the teacher training management platform, the professional knowledge evaluation level of the user and the historical search information of the learning mining user are combined to obtain the training content which the user is interested in and push the training data, and the effectiveness of teacher training and the enthusiasm of teacher training learning are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of teacher training management, and in particular to a management method and system for a teacher training management platform. Background Art

[0002] With the continuous development of vocational education, teachers' professional quality and teaching ability are becoming increasingly important. In order to improve teachers' teaching level and comprehensive skills, vocational colleges have established teacher management platforms, combining modules such as teacher assessment, training and learning, aiming to achieve comprehensive and systematic capacity improvement. However, most current platforms still have many problems in matching learning and training materials, which restricts the comprehensive improvement of teachers' professional knowledge and soft skills: (1) Teachers can see all the training content related to their teaching grade and research group, but before clicking to learn the selected training content, they do not know the difficulty and professional matching of the current training content, resulting in the inability to match training materials in a targeted manner. This lack of evaluation makes teachers confused when choosing learning content, thus affecting the effectiveness of learning; (2) The current platform lacks dynamic evaluation and effective feedback in the teacher training process, making it difficult for teachers to understand their progress and shortcomings in real time during the learning process. This lack makes it difficult for teachers to clearly understand their own learning outcomes after the training, thus affecting their subsequent learning enthusiasm. Summary of the invention

[0003] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the content of teachers' training and learning through a teacher training management platform lacks pertinence and low fit, and to provide a management method and system for a teacher training management platform, which combines the user's professional knowledge assessment level and learning to mine the user's historical search information to obtain training content that the user is interested in and push training materials, thereby improving the effectiveness of teacher training and the enthusiasm of teacher training and learning.

[0004] In the first aspect, in order to solve the above technical problems, the present invention provides a management method of a teacher training management platform, comprising the following steps: When it is detected that a user logs into the teacher training management platform, basic information corresponding to the user is determined; the basic information includes the subject group and teaching subject of the user; Performing a level evaluation on the user's professional knowledge according to the basic information to obtain an evaluation result; Mapping a training grade according to the evaluation results, and matching a grade-associated sub-database in a training data database according to the training grade; Learning and mining the historical search information of the user, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results; The training material is pushed to the user.

[0005] In one embodiment of the present invention, the user's professional knowledge is evaluated based on the basic information, and the evaluation result is obtained, including: Acquire the content to be evaluated corresponding to the user, and extract at least one keyword from the content to be evaluated; the content to be evaluated includes at least one of a teaching case, a teaching courseware, and a competition project; Creating an assessment question database, wherein the assessment question database includes multiple levels to be assessed, each of which includes multiple subjects to be assessed; each of which includes multiple chapters to be assessed; each of which includes multiple knowledge points to be assessed, and each of which includes multiple assessment questions; Matching all evaluation questions related to the keyword in the evaluation question database according to the keyword; The questions to be evaluated that are relevant to the user are screened out from the matched evaluation questions according to the basic information, and the level of the user is evaluated according to the questions to be evaluated.

[0006] In one embodiment of the present invention, obtaining the content to be evaluated corresponding to the user includes receiving video data uploaded by the user in the teacher training management platform, and converting the video data into the content to be evaluated corresponding to the user.

[0007] In one embodiment of the present invention, mapping the training level according to the evaluation result includes constructing an evaluation-training mapping table, in which each evaluation level in the evaluation-training mapping table corresponds to a training level.

[0008] In one embodiment of the present invention, learning and mining the user's search information, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results include: Acquire the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information; Clustering the cleaned historical search information according to knowledge points to generate a number of knowledge point cluster sets, and performing deep learning on the knowledge point cluster sets to obtain the influence values ​​of the knowledge points on the fit degree; Comparing the influence value of the degree of fit with an influence value threshold, selecting a knowledge point whose influence value of the degree of fit is greater than or equal to the influence value threshold as a target knowledge point, and matching training materials that meet the degree of fit in the hierarchical association sub-database according to the target knowledge point; Among them, the deep learning includes first-direction learning and second-direction learning. The first-direction learning compares the several knowledge point cluster sets and deeply learns the influence values ​​of different knowledge points on the fit; the second-direction learning compares several fit items within a single knowledge point cluster set and deeply learns the influence values ​​of the same knowledge point on the fit.

[0009] In one embodiment of the present invention, learning and mining the user's search information, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results include: Acquire the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information; Clustering the cleaned historical search information according to the teaching method to generate a number of teaching method cluster sets, and performing deep learning on the teaching method cluster sets to obtain the impact value of the teaching method on the fit degree; Comparing the influence value of the degree of fit with an influence value threshold, selecting a teaching method whose influence value of the degree of fit is greater than or equal to the influence value threshold as a target teaching method, and matching training materials that meet the degree of fit in the level-related sub-database according to the target teaching method; Among them, the deep learning includes first direction learning and second direction learning. The first direction learning compares the several teaching method cluster sets and deeply learns the impact values ​​of different teaching methods on the fit; the second direction learning compares several fit items within a single teaching method cluster set and deeply learns the impact value of the same teaching method on the fit.

[0010] In one embodiment of the present invention, it also includes creating a training material database, which includes multiple training levels, each of the training levels includes multiple training subjects; each of the training subjects includes multiple training chapters; each of the training chapters includes multiple knowledge points, and each of the knowledge points includes multiple teaching methods.

[0011] In one embodiment of the present invention, the training material is pushed to the user in at least one of email push, DingTalk push, WeChat push and SMS push.

[0012] In one embodiment of the present invention, after pushing the training material to the user, the method further includes: Collect post-training feedback information from the user, and adjust the training materials according to the post-training feedback information.

[0013] In a second aspect, in order to solve the above technical problems, the present invention also provides a management system for a teacher training management platform, including: An information collection module, which is used to obtain basic information corresponding to the user when it is detected that the user logs in to the teacher training management platform; the basic information includes the subject group and teaching subject of the user; A level evaluation module, which is used to evaluate the level of the user's professional knowledge according to the basic information and obtain an evaluation result; A training mapping module, which is used to map out a training grade according to the evaluation results, and match a grade-associated sub-database in a training data database according to the training grade; A learning and mining module, which is used to learn and mine the historical search information of the user, and match the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results; A push module is used to push the training materials to the user.

[0014] The above technical solution of the present invention has the following beneficial effects compared with the prior art: The management method and system of the teacher training management platform described in the present invention evaluate the professional knowledge of users according to their research groups and teaching subjects; ensure that the training materials are closely connected with the teaching background and professional field of teachers, and enhance the relevance of learning content; and introduce a professional knowledge level evaluation mechanism, which can accurately evaluate the current knowledge level of teachers. This evaluation provides a data basis for personalized training, so that the platform can provide appropriate training content according to the actual ability of teachers, and effectively avoid the mismatch between learning materials and teachers' knowledge levels; match the level-related sub-database in the training material database according to the level evaluation results; and can quickly locate the level-related sub-database in the data database. Sub-databases ensure that the materials teachers obtain are consistent with their current level. This precise matching significantly improves the fit of training materials and enhances the effectiveness and pertinence of learning; learning mines users' historical search information, and matches training materials that meet the fit in the hierarchical associated sub-databases based on the results of learning mining; and finally pushes training materials that meet the fit requirements to users; it can further understand teachers' learning preferences and needs. Based on these data, it can match training materials that are more in line with teachers' interests in the hierarchical associated sub-databases, so that the teacher training management platform not only improves the convenience of teachers finding materials again, but also stimulates the teachers' intrinsic motivation to learn and increases teachers' dependence on the platform.

[0015] In summary, the management method and system of the teacher training management platform described in the present invention application combine the user's professional knowledge assessment level and learn to mine the user's historical search information to obtain the training content that the user is interested in and push training materials, thereby improving the effectiveness of teacher training and the enthusiasm of teacher training learning. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein: Figure 1 It is a flow chart of a management method of a teacher training management platform in a preferred embodiment of the present invention; Figure 2 It is a structural block diagram of the management system of the teacher training management platform in the preferred embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0018] With the continuous development of vocational education, the professional quality and teaching ability of teachers in vocational colleges have become increasingly important. In order to improve teachers' teaching level and comprehensive skills, vocational colleges have established teacher management platforms, combining teacher evaluation, training and learning, aiming to achieve comprehensive and systematic capacity improvement. Example

[0019] Reference Figure 1 As shown, the present invention discloses a management method for a teacher training management platform, including the following steps: when a user is detected to log in to the teacher training management platform, the basic information corresponding to the user is determined; the basic information includes the subject group and teaching subject to which the user belongs; the user's professional knowledge is graded and evaluated according to the basic information to obtain the evaluation result; the training level is mapped according to the evaluation result, and the level-related sub-database is matched in the training material database according to the training level; the historical search information of the user is learned and mined, and the training materials that meet the fit degree are matched in the level-related sub-database according to the result of the learning and mining; the training materials are pushed to the user; wherein the method of pushing the training materials to the user includes at least one of email push, DingTalk push, WeChat push and SMS push. The management method for the teacher training management platform described in the present invention application combines the user's professional knowledge evaluation level and the learning and mining of the user's historical search information to obtain the training content that the user is interested in and push the training materials, thereby improving the effectiveness of teacher training and the enthusiasm of teacher training learning.

[0020] In specific application scenarios, users (teachers) obtain an account to log in to the teacher training management platform by registering. When registering, the user's basic information including name, teaching experience, courses taken, research group, teaching subjects and teaching development direction is entered, and the basic information is updated regularly; after registration, the user uses the account to log in to the teacher training management platform, and the user's basic information is directly obtained when logging in.

[0021] After the user logs in to the teacher training management platform and before starting training, the teacher training management platform will assess the user's professional knowledge level based on basic information, obtain the assessment results, and select training materials closely related to the teacher's teaching background and professional field based on the assessment results, thereby enhancing the relevance of the learning content; and introduce a professional knowledge level assessment mechanism that can accurately evaluate the teacher's current knowledge level. This assessment provides a data basis for personalized training, enabling the platform to provide appropriate training content based on the teacher's actual ability, effectively avoiding the mismatch between learning materials and the teacher's knowledge level.

[0022] In a specific application scenario, before the user's professional knowledge is evaluated, the content to be evaluated corresponding to the user is first obtained, and the content to be evaluated includes at least one of teaching cases, teaching courseware and competition projects; specifically, the content to be evaluated can be obtained in the following ways: one solution is that the user actively uploads video data on the teacher training management platform, and converts the video data into the content to be evaluated corresponding to the user; including video data of teaching cases; video data of online and offline teaching courseware with classroom interaction or classroom feedback; or video data of competition projects, etc.

[0023] While obtaining the user's corresponding content to be evaluated, the user's corresponding objectives to be evaluated are obtained, such as professional evaluation objectives including knowledge points and teaching methods of various subjects, and soft skill evaluation objectives including classroom management, communication skills, etc.

[0024] At least one keyword is extracted from the content to be evaluated; for example, the keyword may be a specific knowledge point or a soft skill related term; and a basis is provided for the subsequent matching of the evaluation question bank.

[0025] An evaluation question database is created, and all evaluation questions related to the keyword are matched in the evaluation question database according to the keyword; questions to be evaluated related to the user are screened out from the matched evaluation questions according to the basic information, and the level of the user is evaluated according to the questions to be evaluated.

[0026] Among them, the evaluation question database includes multiple levels to be evaluated, each of which includes multiple subjects to be evaluated; each subject to be evaluated includes multiple chapters to be evaluated; each chapter to be evaluated includes multiple knowledge points to be evaluated, and each knowledge point to be evaluated includes multiple evaluation questions. Creating a comprehensive evaluation question database can identify knowledge points related to the content to be evaluated by teachers and generate keyword matching results. According to the keyword matching results of the previous step, the knowledge points associated with the teacher at the evaluation level of a specific knowledge point are screened out from the knowledge points to be evaluated. For soft skills, the learning needs filled in by the teacher can be matched with the preset soft skill knowledge points to obtain relevant evaluation content. These evaluation knowledge points will form the focus of subsequent learning and evaluation for teachers, and effectively guide the learning direction of teachers.

[0027] The management method of the teacher training management platform described in the application of the present invention matches the level-related sub-database in the training material database according to the level assessment results, and can quickly locate the level-related sub-database in the material database to ensure that the materials obtained by the teacher are consistent with their current level. This precise matching significantly improves the fit of the materials and enhances the effectiveness and pertinence of learning.

[0028] Furthermore, an assessment-training mapping table is pre-constructed, in which each assessment level corresponds to a training level; after obtaining the assessment results of the professional knowledge level assessment (for example, basic, advanced, enhanced, advanced, etc., each level can also be subdivided into different branches, for example, level 1, level 2, level 3, etc.), the training level is obtained according to the assessment-training mapping table.

[0029] According to the results of learning mining, the training materials that meet the fit requirements are matched in the hierarchical associated sub-database; finally, the training materials that meet the fit requirements are pushed to the users; the learning preferences and needs of teachers can be further understood, and based on these data, the training materials that are more in line with the teachers' interests can be matched in the hierarchical associated sub-database, so that the teacher training management platform not only improves the convenience of teachers to find materials again, but also stimulates the teachers' intrinsic motivation to learn and increases the teachers' dependence on the platform.

[0030] In a specific application scenario, learning and mining the user's search information, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results include: Obtain the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information; cluster the cleaned historical search information according to knowledge points to generate a number of knowledge point cluster sets, and perform deep learning on the knowledge point cluster sets to obtain the influence value of the knowledge point on the fit; compare the influence value of the fit with the influence value threshold, select the knowledge point whose influence value of the fit is greater than or equal to the influence value threshold as the target knowledge point, and match the training materials that meet the fit in the hierarchical association sub-database according to the target knowledge point; this solution ensures that only knowledge points that are highly consistent with user needs are selected, thereby improving the success rate of subsequent material matching.

[0031] Among them, the deep learning includes first-direction learning and second-direction learning. The first-direction learning compares the several knowledge point cluster sets and deeply learns the influence values ​​of different knowledge points on the fit; the second-direction learning compares several fit items within a single knowledge point cluster set and deeply learns the influence values ​​of the same knowledge point on the fit.

[0032] On the basis of the above embodiments, the first direction of learning is the influence of different knowledge points on the degree of fit for the deep learning model, such as which knowledge points are more suitable for what degree of fit; the second direction of learning is the influence of the same knowledge points on different degree of fit for the deep learning model, such as learning that a certain knowledge point is more important or has a greater impact on the fit of skill improvement. In the deep learning process, the model will learn and capture the influence of different knowledge points on the degree of fit, where the knowledge points include but are not limited to mechanical knowledge points, optical knowledge points, thermal knowledge points, fluid mechanics knowledge points, electromagnetic knowledge points, acoustic knowledge points, ion physics and nuclear physics knowledge points; basic mathematics knowledge points, algebra knowledge points, trigonometric function knowledge points, calculus knowledge points, discrete mathematics knowledge points, etc. These knowledge points will affect the final degree of fit. Combined with the deep learning results of the first direction of learning and the second direction of learning, training materials that meet the requirements of fit are finally obtained. Deep learning technology is used to cluster and learn historical search information, so as to achieve personalized matching and select the best training materials.

[0033] Furthermore, learning and mining the search information of the user, and matching the training materials that meet the fit in the hierarchical association sub-database according to the results of the learning and mining, includes: obtaining the historical search information of the user on the teacher training management platform, and performing data cleaning on the historical search information; clustering the cleaned historical search information according to the teaching method to generate a number of teaching method cluster sets, and performing deep learning on the teaching method cluster sets to obtain the influence value of the teaching method on the fit; comparing the influence value of the fit with an influence value threshold, selecting the teaching method whose influence value of the fit is greater than or equal to the influence value threshold as the target teaching method, and matching the training materials that meet the fit in the hierarchical association sub-database according to the target teaching method.

[0034] Among them, the deep learning includes first direction learning and second direction learning. The first direction learning compares the several teaching method cluster sets and deeply learns the impact values ​​of different teaching methods on the fit; the second direction learning compares several fit items within a single teaching method cluster set and deeply learns the impact value of the same teaching method on the fit.

[0035] On the basis of the above embodiments, the first direction of learning is that the deep learning model learns the impact of different teaching methods on the degree of fit, such as learning which teaching methods are more suitable for what degree of fit; the second direction of learning is that the deep learning model learns the impact of the same teaching method on different fit items, such as a certain teaching method is more important or has a greater impact on the fit of classroom management. In the deep learning process, the model will learn and capture the degree of influence of different teaching methods on the fit, where teaching methods include but are not limited to lectures, discussions, demonstrations, inquiry-based learning, cooperative learning, practical teaching, reversed classrooms, gamification, role-playing, etc. These teaching methods will affect the final fit, and the deep learning results of the first and second direction learning are combined to finally obtain training materials that meet the fit requirements. Deep learning technology is used to cluster and learn historical search information, so as to achieve personalized matching and select the best training materials.

[0036] The management method of the teacher training management platform described in the present invention application is a training material matching scheme based on data cleaning, clustering and deep learning of user historical search information to improve the fit of the matched training materials. Among them, through the cleaning and clustering of historical search information, it is ensured that the matched training materials are more in line with the real needs of users; based on the user's past learning behavior and needs, personalized training materials are provided to reduce information overload; and learning materials with high fit are recommended to stimulate teachers' learning interest and improve learning participation and enthusiasm.

[0037] In addition, it also includes creating a training material database, which includes multiple training levels, each of which includes multiple training subjects; each of which includes multiple training chapters; each of which includes multiple knowledge points, and each of which includes multiple teaching methods.

[0038] In the specific application scenario, the training data database structure is as follows: 1. Training level Level 1 training Secondary training Level 3 training … 2. Training subjects There are different disciplines within each training level. For example: Level 1 training Subject A Subject B Subject C Secondary training Subject D Subject E … 3. Training Section Each training subject is divided into several chapters. For example: Subject A Chapter 1: Basics Chapter 2: Advanced Knowledge Chapter 3: Application Examples Subject B Chapter 1: Theoretical Background Chapter 2: Practical Tips … 4. Knowledge Points Each training chapter contains multiple knowledge points. For example: Chapter 1: Basics Knowledge point 1: Definition and basic concepts Knowledge point 2: Important formulas Knowledge point 3: Typical applications Chapter 2: Advanced Knowledge Knowledge point 1: Advanced concepts Knowledge point 2: Complex problem solving … 5. Teaching methods There are multiple teaching methods attached to each knowledge point. For example: Knowledge point 1: Definition and basic concepts Teaching method 1: Lecture method Teaching method 2: Discussion method Teaching method 3: Demonstration Knowledge point 2: Important formulas Teaching method 1: Exploratory learning Teaching method 2: case analysis.

[0039] In other embodiments of the present invention, after the training materials are pushed to the user, the post-training feedback information of the user is collected, and the training materials are adjusted according to the post-training feedback information. The training materials are updated or modified according to the user's feedback to ensure that the content better meets the user's needs. If the user has difficulty understanding a certain knowledge point, relevant supplementary materials or case analysis can be added. The effectiveness of the teaching methods in the feedback is analyzed. If some methods are found to be unpopular, they can be replaced with other teaching methods. Through closed-loop feedback, the fit of the training content can be effectively improved, the user's learning experience and satisfaction can be enhanced, and the overall effect of the training can be enhanced to achieve continuous improvement. Example

[0040] Reference Figure 2 As shown, the embodiment of the present invention also discloses a management system of a teacher training management platform, including: An information collection module, which is used to obtain basic information corresponding to the user when it is detected that the user logs in to the teacher training management platform; the basic information includes the subject group and teaching subject of the user; A level evaluation module, which is used to evaluate the level of the user's professional knowledge according to the basic information and obtain an evaluation result; A training mapping module, which is used to map out a training grade according to the evaluation results, and match a grade-associated sub-database in a training data database according to the training grade; A learning and mining module, which is used to learn and mine the historical search information of the user, and match the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results; A push module is used to push the training materials to the user.

[0041] The management system of the teacher training management platform disclosed in the embodiment of the present invention can effectively realize the management system of the teacher training management platform, and the technical effects that can be achieved are as described in the above embodiment, which will not be repeated here.

[0042] In summary, the management method and system of the teacher training management platform described in the present invention application combine the user's professional knowledge assessment level and learn to mine the user's historical search information to obtain the training content that the user is interested in and push training materials, thereby improving the effectiveness of teacher training and the enthusiasm of teacher training learning.

[0043] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0044] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0045] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0046] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0047] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. A management method for a teacher training management platform, characterized in that: The following steps are included: When it is detected that a user logs into the teacher training management platform, basic information corresponding to the user is determined; the basic information includes the subject group and teaching subject of the user; Performing a level evaluation on the user's professional knowledge according to the basic information to obtain an evaluation result; Mapping a training grade according to the evaluation results, and matching a grade-associated sub-database in a training data database according to the training grade; Learning and mining the historical search information of the user, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results; The training material is pushed to the user.

2. The management method of the teacher training management platform according to claim 1, characterized in that: The user's professional knowledge is evaluated based on the basic information, and the evaluation results obtained include: Acquire the content to be evaluated corresponding to the user, and extract at least one keyword from the content to be evaluated; the content to be evaluated includes at least one of a teaching case, a teaching courseware, and a competition project; Creating an assessment question database, wherein the assessment question database includes multiple levels to be assessed, each of which includes multiple subjects to be assessed; each of which includes multiple chapters to be assessed; each of which includes multiple knowledge points to be assessed, and each of which includes multiple assessment questions; Matching all evaluation questions related to the keyword in the evaluation question database according to the keyword; The questions to be evaluated that are relevant to the user are screened out from the matched evaluation questions according to the basic information, and the level of the user is evaluated according to the questions to be evaluated.

3. The management method of the teacher training management platform according to claim 2 is characterized by: Acquiring the content to be evaluated corresponding to the user includes receiving video data uploaded by the user in the teacher training management platform, and converting the video data into the content to be evaluated corresponding to the user.

4. The management method of the teacher training management platform according to claim 1 or 2, characterized in that: Mapping the training level according to the evaluation results includes constructing an evaluation-training mapping table, in which each evaluation level corresponds to a training level.

5. The management method of the teacher training management platform according to claim 1, characterized in that: Learning and mining the user's search information, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results include: Acquire the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information; Clustering the cleaned historical search information according to knowledge points to generate a number of knowledge point cluster sets, and performing deep learning on the knowledge point cluster sets to obtain the influence values ​​of the knowledge points on the fit degree; Comparing the influence value of the degree of fit with an influence value threshold, selecting a knowledge point whose influence value of the degree of fit is greater than or equal to the influence value threshold as a target knowledge point, and matching training materials that meet the degree of fit in the hierarchical association sub-database according to the target knowledge point; Among them, the deep learning includes first-direction learning and second-direction learning. The first-direction learning compares the several knowledge point cluster sets and deeply learns the influence values ​​of different knowledge points on the fit; the second-direction learning compares several fit items within a single knowledge point cluster set and deeply learns the influence values ​​of the same knowledge point on the fit.

6. The management method of the teacher training management platform according to claim 1 or 5, characterized in that: Learning and mining the user's search information, and matching the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results include: Acquire the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information; Clustering the cleaned historical search information according to the teaching method to generate a number of teaching method cluster sets, and performing deep learning on the teaching method cluster sets to obtain the impact value of the teaching method on the fit degree; Comparing the influence value of the degree of fit with an influence value threshold, selecting a teaching method whose influence value of the degree of fit is greater than or equal to the influence value threshold as a target teaching method, and matching training materials that meet the degree of fit in the level-related sub-database according to the target teaching method; Among them, the deep learning includes first direction learning and second direction learning. The first direction learning compares the several teaching method cluster sets and deeply learns the impact values ​​of different teaching methods on the fit; the second direction learning compares several fit items within a single teaching method cluster set and deeply learns the impact value of the same teaching method on the fit.

7. The management method of the teacher training management platform according to claim 6 is characterized by: It also includes creating a training material database, which includes multiple training levels, each of which includes multiple training subjects; each of which includes multiple training chapters; each of which includes multiple knowledge points, and each of which includes multiple teaching methods.

8. The management method of the teacher training management platform according to claim 1, characterized in that: The training material is pushed to the user in at least one of email push, DingTalk push, WeChat push and SMS push.

9. The management method of the teacher training management platform according to claim 1, characterized in that: After pushing the training materials to the user, it also includes: Collect post-training feedback information from the user, and adjust the training materials according to the post-training feedback information.

10. A management system for a teacher training management platform, characterized in that: include, An information collection module, which is used to obtain basic information corresponding to the user when it is detected that the user logs in to the teacher training management platform; the basic information includes the subject group and teaching subject of the user; A level evaluation module, which is used to evaluate the level of the user's professional knowledge according to the basic information and obtain an evaluation result; A training mapping module, which is used to map out a training grade according to the evaluation results, and match a grade-associated sub-database in a training data database according to the training grade; A learning and mining module, which is used to learn and mine the search information of the user, and match the training materials that meet the fit in the hierarchical association sub-database according to the learning and mining results; A push module is used to push the training materials to the user.

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