Management Method and System of Teacher Training Management Platform

Abstract

The present invention relates to the technical field of teacher training management, and relates to a management method and system for a teacher training management platform, including when detecting that a user logs in to the teacher training management platform, determining the basic information corresponding to the user; performing a level evaluation on the professional knowledge of the user according to the basic information to obtain an evaluation result; mapping a training level according to the evaluation result, and matching a level-associated sub-database in the training material database according to the training level; learning and mining the historical search information of the user, and matching training materials that meet the degree of fit in the level-associated sub-database according to the result of the learning and mining; and pushing the training materials to the user. The management method and system for the teacher training management platform according to the present invention combine the professional knowledge evaluation level of the user and the historical search information of the learning and mining user to obtain the training content that the user is interested in and push the training materials, improving the effectiveness of teacher training and the enthusiasm of teachers for training and learning.

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, the professional qualities and teaching abilities of teachers have become increasingly important. In order to improve the teaching level and comprehensive skills of teachers, vocational colleges have successively established teacher management platforms, combining modules such as teacher evaluation, training, and learning, aiming to achieve comprehensive and systematic capacity improvement. However, there are still many problems in the current most platforms 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 contents related to their teaching grades and research groups, but they do not know the difficulty level and professional matching degree of the current training content before clicking to select the training content for learning, resulting in the inability to match training materials targeted. This lack of evaluation makes teachers confused when choosing learning contents, thus affecting the effectiveness of learning; (2) The current platforms lack dynamic evaluation and effective feedback during the teacher training process, and it is difficult for teachers to understand their progress and deficiencies in real time during the learning process. This lack leads to the difficulty for teachers to clarify their learning achievements after the training, thus affecting their subsequent learning enthusiasm. Summary of the Invention

[0003] Therefore, the technical problem to be solved by the present invention is to overcome the problems of lack of pertinence and low matching degree in the content of teacher training and learning through the teacher training management platform in the prior art, and provide a management method and system for a teacher training management platform, which combines the professional knowledge evaluation level of users and learns the historical search information of users to obtain the training contents that users are interested in and push training materials, so as to improve the effectiveness of teacher training and the enthusiasm of teachers for training and learning.

[0004] In the first aspect, to solve the above technical problem, the present invention provides a management method for a teacher training management platform, including the following steps,

[0005] When it is detected that a user logs in to the teacher training management platform, determine the basic information corresponding to the user; the basic information includes the research group where the user is located and the teaching subject;

[0006] Evaluate the professional knowledge of the user according to the basic information to obtain an evaluation result;

[0007] Map a training level according to the evaluation result, and match a level-related sub-database in the training material database according to the training level;

[0008] Learn to mine the historical search information of the user, and match training materials that meet the fit in the level-associated sub-database according to the results of the learning and mining;

[0009] Push the training materials to the user.

[0010] In an embodiment of the present invention, the professional knowledge of the user is evaluated according to the basic information, and the evaluation results include,

[0011] Obtain 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 teaching cases, teaching courseware, and competition projects;

[0012] Create an evaluation question database, the evaluation question database includes multiple levels to be evaluated, and each level to be evaluated includes multiple disciplines to be evaluated; each discipline 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;

[0013] Match all evaluation questions related to the keyword in the evaluation question database according to the keyword;

[0014] Screen out the evaluation questions related to the user from the matched evaluation questions according to the basic information, and perform the level evaluation of the user according to the evaluation questions to be evaluated.

[0015] In an embodiment of the present invention, obtaining the content to be evaluated corresponding to the user includes receiving the 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.

[0016] In an embodiment of the present invention, mapping the training level according to the evaluation result includes constructing an evaluation-training mapping table, and each evaluation level in the evaluation-training mapping table corresponds to a training level.

[0017] In an embodiment of the present invention, learning to mine the search information of the user, and matching training materials that meet the fit in the level-associated sub-database according to the results of the learning and mining includes,

[0018] Obtain the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information;

[0019] Cluster the cleaned historical search information according to knowledge points, generate several knowledge point clustering sets, and perform deep learning on the knowledge point clustering sets to obtain the influence value of the knowledge points on the fit;

[0020] Compare the influence value of the fit degree with the influence value threshold, select the knowledge points whose influence value of the fit degree is greater than or equal to the influence value threshold as the target knowledge points, and match the training materials that meet the fit degree in the hierarchical association sub-database according to the target knowledge points;

[0021] Among them, the deep learning includes first-direction learning and second-direction learning. The first-direction learning compares between the several knowledge point clustering sets and deeply learns the influence value of different knowledge points on the fit degree; the second-direction learning compares several fit degree items within a single knowledge point clustering set and deeply learns the influence value of the same knowledge point on the fit degree.

[0022] In an embodiment of the present invention, learning and mining the user's search information, and matching the training materials that meet the fit degree in the hierarchical association sub-database according to the results of the learning and mining includes,

[0023] Obtain the historical search information of the user on the teacher training management platform, and perform data cleaning on the historical search information;

[0024] Cluster the cleaned historical search information according to teaching methods, generate several teaching method clustering sets, and perform deep learning on the teaching method clustering sets to obtain the influence value of the teaching method on the fit degree;

[0025] Compare the influence value of the fit degree with the influence value threshold, select the teaching methods whose influence value of the fit degree is greater than or equal to the influence value threshold as the target teaching methods, and match the training materials that meet the fit degree in the hierarchical association sub-database according to the target teaching methods;

[0026] Among them, the deep learning includes first-direction learning and second-direction learning. The first-direction learning compares between the several teaching method clustering sets and deeply learns the influence value of different teaching methods on the fit degree; the second-direction learning compares several fit degree items within a single teaching method clustering set and deeply learns the influence value of the same teaching method on the fit degree.

[0027] In an embodiment of the present invention, it further includes creating a training material database. The training material database includes multiple training levels, and each training level includes multiple training disciplines; each training discipline includes multiple training chapters; each training chapter includes multiple knowledge points, and each knowledge point includes multiple teaching methods.

[0028] In an embodiment of the present invention, the manner of pushing the training materials to the user includes at least one of email push, DingTalk push, WeChat push, and SMS push.

[0029] In one embodiment of the present invention, after pushing the training materials to the user, it further includes

[0030] collecting the post-training feedback information of the user, and adjusting the training materials according to the post-training feedback information.

[0031] In a second aspect, to solve the above technical problems, the present invention also provides a management system for a teacher training management platform, including

[0032] an information collection module, which is used to obtain the basic information corresponding to the user when detecting that the user logs in to the teacher training management platform; the basic information includes the research group where the user is located and the teaching subject;

[0033] a level evaluation module, which is used to evaluate the professional knowledge of the user according to the basic information and obtain an evaluation result;

[0034] a training mapping module, which is used to map a training level according to the evaluation result, and match a level-related sub-database in the training material database according to the training level;

[0035] a learning mining module, which is used to learn and mine the historical search information of the user, and match training materials that meet the fit degree in the level-related sub-database according to the results of learning and mining;

[0036] a pushing module, which is used to push the training materials to the user.

[0037] The above technical solutions of the present invention have the following beneficial effects compared with the prior art:

[0038] The management method and system of the teacher training management platform described in the present invention conduct a level evaluation of the user's professional knowledge based on the user's research group and teaching subject; ensure that the training materials are closely linked to the teacher's teaching background and professional field, enhancing the relevance of the learning content; and introduce a professional knowledge level evaluation mechanism, which can accurately evaluate the teacher's current knowledge level. This evaluation provides a data basis for personalized training, enabling the platform to provide appropriate training content according to the teacher's true ability, effectively avoiding the mismatch between the learning materials and the teacher's knowledge level; match the level-related sub-database in the training material database according to the level evaluation results; can quickly locate the level-related sub-database in the material database to ensure that the materials obtained by the teacher match their current level. This precise matching significantly improves the fitness of the training materials and enhances the effectiveness and pertinence of learning; learn and excavate the user's historical search information, and match the training materials that meet the fitness in the level-related sub-database according to the results of the learning excavation; finally, push the training materials that meet the fitness requirements to the user; can further understand the teacher's learning preferences and needs. Based on these data, it is possible to match more training materials that meet the teacher's interests in the level-related sub-database, making the teacher training management platform not only improve the convenience for teachers to search for materials again, but also stimulate the internal motivation of teachers to learn and increase the teacher's dependence on the platform.

[0039] In summary, the management method and system of the teacher training management platform described in the present invention apply the user's professional knowledge evaluation level and learn and excavate the user's historical search information to obtain the training content that the user is interested in and push the training materials, improving the effectiveness of teacher training and the enthusiasm of teachers for training and learning. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to the specific embodiments of the present invention in combination with the drawings, wherein,

[0041] Figure 1 is the flowchart of the management method of the teacher training management platform in the preferred embodiment of the present invention;

[0042] Figure 2 is the structural block diagram of the management system of the teacher training management platform in the preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following further illustrates the present invention in combination with the drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the embodiments cited do not limit the present invention.

[0044] With the continuous development of vocational education, the professional qualities and teaching abilities of vocational college teachers have become increasingly important; to improve teachers' teaching levels and comprehensive skills, vocational colleges have successively established teacher management platforms, combining sections such as teacher evaluation, training, and learning, aiming to achieve comprehensive and systematic capacity improvement. Embodiment

[0045] Refer to Figure 1 As shown, the present invention discloses a management method for a teacher training management platform, including the following steps: when it is detected that a user logs in to the teacher training management platform, determine the basic information corresponding to the user; the basic information includes the research group and teaching subject where the user is located; perform a level evaluation on the user's professional knowledge according to the basic information to obtain an evaluation result; map a training level according to the evaluation result, and match a level-associated sub-database in the training material database according to the training level; learn and mine the user's historical search information, and match training materials that meet the degree of fit in the level-associated sub-database according to the result of the learning and mining; push the training materials to the user; wherein, the manner 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 of the teacher training management platform described in the present invention application combines the professional knowledge evaluation level of the user and the historical search information of the learning and mining user to obtain the training content that the user is interested in and push the training materials, improving the effectiveness of teacher training and the enthusiasm of teachers for training and learning.

[0046] In a specific application scenario, a user (teacher) obtains an account to log in to the teacher training management platform through registration. When registering, the user enters basic information including name, teaching age, completed courses, research group where the user is located, teaching subject, and teaching development direction, and updates the basic information regularly; after registration, the user uses the account to log in to the teacher training management platform, and directly obtains the user's basic information when logging in.

[0047] Before the user logs in to the teacher training management platform and conducts training and learning, the teacher training management platform performs a level evaluation on the user's professional knowledge according to the basic information to obtain an evaluation result, selects training materials closely related to the teacher's teaching background and professional field according to the evaluation result, enhancing the relevance of the learning content; and introduces a professional knowledge level evaluation mechanism, which can accurately evaluate the teacher's current knowledge level. This evaluation provides a data basis for personalized training, enabling the platform to provide appropriate training content according to the teacher's true ability, effectively avoiding the mismatch between the learning materials and the teacher's knowledge level.

[0048] In a specific application scenario, before evaluating the professional knowledge level of a user, the content to be evaluated corresponding to the user is obtained first. 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 through the following several methods: 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 or offline teaching courseware with classroom interaction or classroom feedback, or video data of competition projects, etc.

[0049] While obtaining the content to be evaluated corresponding to the user, the evaluation objectives to be evaluated corresponding to the user are obtained, such as professional evaluation objectives including knowledge points and teaching methods in various subjects, and soft skill evaluation objectives including classroom management, communication skills, etc.

[0050] And at least one keyword is extracted from the content to be evaluated. For example, the keyword can be a specific knowledge point or a term related to soft skills, providing a basis for the subsequent matching of the evaluation question bank.

[0051] 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. The evaluation questions related to the user are screened out from the matched evaluation questions according to the basic information, and the level evaluation of the user is carried out according to the evaluation questions to be evaluated.

[0052] Among them, the evaluation question database includes multiple levels to be evaluated, and each level to be evaluated includes multiple disciplines to be evaluated. Each discipline 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 the 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 a specific knowledge point evaluation level are screened out from the knowledge points to be evaluated. For soft skills, according to the learning needs filled in by the teacher, they can be matched with the preset soft skill knowledge points to obtain relevant evaluation content. These evaluation knowledge points will form the subsequent learning and evaluation focus of teachers, effectively guiding the learning direction of teachers.

[0053] For the management method of the teacher training management platform described in this invention application, according to the level evaluation results, the level-associated sub-databases are matched in the training material database, which can quickly locate the level-associated sub-databases in the material database, ensuring that the materials obtained by teachers match their current level. This precise matching significantly improves the fit of the materials and enhances the effectiveness and pertinence of learning.

[0054] Furthermore, a evaluation-training mapping table is pre-constructed, in which each evaluation level corresponds to a training level; after obtaining the evaluation results of professional knowledge level evaluation (such as basic, advanced, improved, advanced, etc., and each level can be further divided into different branches below, such as level 1, level 2, level 3, etc.), the training level is obtained according to the evaluation-training mapping table.

[0055] According to the results of learning and mining, training materials that meet the fit degree are matched in the level-related sub-database; finally, training materials that meet the fit degree requirements are pushed to the user; it is possible to further understand the learning preferences and needs of teachers. Based on these data, training materials that are more in line with the interests of teachers can be matched in the level-related sub-database, which not only improves the convenience of teachers to search for materials again, but also stimulates the internal motivation of teachers to learn and increases teachers' dependence on the platform.

[0056] In a specific application scenario, learning and mining the user's search information, and matching training materials that meet the fit degree in the level-related sub-database according to the results of learning and mining includes

[0057] 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 knowledge points to generate several knowledge point clustering sets, and performing in-depth learning on the knowledge point clustering sets to obtain the influence value of the knowledge points on the fit degree; comparing the influence value of the fit degree with the influence value threshold, and selecting the knowledge points whose influence value of the fit degree is greater than or equal to the influence value threshold as target knowledge points, and matching training materials that meet the fit degree in the level-related sub-database according to the target knowledge points; this solution ensures that only knowledge points that highly match the user's needs are selected, improving the success rate of subsequent material matching.

[0058] Among them, the in-depth learning includes first-direction learning and second-direction learning. The first-direction learning compares between the several knowledge point clustering sets and deeply learns the influence value of different knowledge points on the fit degree; the second-direction learning compares several fit items within a single knowledge point clustering set and deeply learns the influence value of the same knowledge point on the fit degree.

[0059] On the basis of the above embodiments, the first - direction learning is for the deep - learning model to learn the influence of different knowledge points on the fit degree, for example, to learn which knowledge points are more in line with what degree of fit; the second - direction learning is for the deep - learning model to learn the influence of the same knowledge points on different fit - degree items, for example, to learn that a certain knowledge point is more important or has a greater impact on the fit degree of skill improvement. During the deep - learning process, the model will learn and capture the influence degree of different knowledge points on the fit degree, where the knowledge points include but are not limited to mechanics knowledge points, optics knowledge points, thermology knowledge points, fluid mechanics knowledge points, electromagnetics knowledge points, acoustics 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 fit degree. Combining the deep - learning results of the first - direction learning and the second - direction learning, training materials that meet the fit - degree requirements are finally obtained. Deep - learning technology is used to cluster and learn historical search information, so as to achieve personalized matching and select the optimal training materials.

[0060] Further, learning to mine the user's search information and matching training materials that meet the fit degree in the hierarchical - related sub - database according to the learning - mining results includes: obtaining the user's historical search information on the teacher training management platform and performing data cleaning on the historical search information; clustering the cleaned historical search information according to teaching methods to generate several teaching - method clustering sets, and performing deep learning on the teaching - method clustering sets to obtain the influence value of teaching methods on the fit degree; comparing the influence value of the fit degree with the influence - value threshold, and selecting the teaching methods whose influence value of the fit degree is greater than or equal to the influence - value threshold as target teaching methods, and matching training materials that meet the fit degree in the hierarchical - related sub - database according to the target teaching methods.

[0061] Among them, the deep learning includes the first - direction learning and the second - direction learning. The first - direction learning compares between the several teaching - method clustering sets and deeply learns the influence value of different teaching methods on the fit degree; the second - direction learning compares several fit - degree items within a single teaching - method clustering set and deeply learns the influence value of the same teaching method on the fit degree.

[0062] Based on the above embodiments, the first - direction learning enables the deep - learning model to learn the impact of different teaching methods on the fit, for example, learning which teaching methods are more in line with what degree of fit; the second - direction learning enables the deep - learning model to learn the impact of the same teaching method on different fit items, for example, a certain teaching method is more important or has a greater impact on the fit of classroom management. During the deep - learning process, the model will learn and capture the degree of impact of different teaching methods on the fit. Among them, teaching methods include but are not limited to the lecture method, discussion method, demonstration method, inquiry - based learning method, cooperative learning method, practice - teaching method, flipped classroom method, gamification learning method, role - playing method, etc. These teaching methods will affect the final fit. Combining the deep - learning results of the first - direction learning and the second - direction learning, training materials that meet the fit requirements are finally obtained. Deep - learning technology is used to cluster and learn historical search information, so as to achieve personalized matching and select the optimal training materials.

[0063] The management method of the teacher training management platform described in this 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 behaviors and needs, personalized training materials are provided to reduce the situation of information overload; learning materials with high fit are recommended to stimulate teachers' learning interests and improve their learning participation and enthusiasm.

[0064] In addition, it also includes creating a training - material database. The training - material database includes multiple training levels, and each training level includes multiple training disciplines; each training discipline includes multiple training chapters; each training chapter includes multiple knowledge points, and each knowledge point includes multiple teaching methods.

[0065] In a specific application scenario, the structure of the training - material database is as follows:

[0066] 1. Training level

[0067] Level - 1 training

[0068] Level - 2 training

[0069] Level - 3 training

[0070] ……

[0071] 2. Training discipline

[0072] There are different disciplines under each training level. For example:

[0073] Level - 1 training

[0074] Discipline A

[0075] Subject B

[0076] Subject C

[0077] Secondary training

[0078] Subject D

[0079] Subject E

[0080] ……

[0081] 3. Training chapters

[0082] Each training subject is divided into multiple chapters. For example:

[0083] Subject A

[0084] Chapter 1: Basic knowledge

[0085] Chapter 2: Advanced knowledge

[0086] Chapter 3: Application examples

[0087] Subject B

[0088] Chapter 1: Theoretical background

[0089] Chapter 2: Practical skills

[0090] ……

[0091] 4. Knowledge points

[0092] Each training chapter contains multiple knowledge points. For example:

[0093] Chapter 1: Basic knowledge

[0094] Knowledge point 1: Definitions and basic concepts

[0095] Knowledge point 2: Important formulas

[0096] Knowledge point 3: Typical applications

[0097] Chapter 2: Advanced knowledge

[0098] Knowledge point 1: Advanced concepts

[0099] Knowledge point 2: Solving complex problems

[0100] ……

[0101] 5. Teaching methods

[0102] Multiple teaching methods are attached to each knowledge point. For example:

[0103] Knowledge point 1: Definitions and basic concepts

[0104] Teaching Method 1: Lecturing Method

[0105] Teaching Method 2: Discussion Method

[0106] Teaching Method 3: Demonstration Method

[0107] Knowledge Point 2: Important Formulas

[0108] Teaching Method 1: Exploratory Learning

[0109] Teaching Method 2: Case Analysis.

[0110] In other embodiments of the present invention, after pushing the training materials to the user, it further includes collecting the post-training feedback information of the user, and adjusting the training materials according to the post-training feedback information. According to the user's feedback, update or modify the training materials to ensure that the content better meets the user's needs. For example, if the user has difficulty understanding a certain knowledge point, relevant supplementary materials or case analyses can be added. Analyze the effectiveness of the teaching methods in the feedback. If it is found that some methods are not popular, consider replacing them with other teaching forms. Through the closed-loop feedback, the fit of the training content can be effectively improved, the user's learning experience and satisfaction can be enhanced, and thus the overall effect of the training can be strengthened to achieve continuous improvement. Embodiment

[0111] Refer to Figure 2 As shown, the present invention also discloses a management system of a teacher training management platform, including,[[]]

[0112] An information collection module, which is used to obtain the basic information corresponding to the user when detecting that the user logs in to the teacher training management platform; the basic information includes the research group where the user is located and the teaching subject;

[0113] A level evaluation module, which is used to evaluate the professional knowledge of the user according to the basic information and obtain an evaluation result;

[0114] A training mapping module, which is used to map a training level according to the evaluation result and match a level-associated sub-database in the training material database according to the training level;

[0115] A learning mining module, which is used to learn and mine the historical search information of the user and match training materials that meet the fit degree in the level-associated sub-database according to the results of the learning and mining;

[0116] A push module, which is used to push the training materials to the user.

[0117] The management system of the teacher training management platform disclosed in the embodiments of the present invention can effectively implement the management system of the teacher training management platform, and the technical effects that can be achieved are as described in the above embodiments, which will not be elaborated here.

[0118] In summary, for the management method and system of the teacher training management platform described in this invention application, by combining the professional knowledge evaluation level of users and mining the historical search information of users to obtain training content that users are interested in and pushing training materials, the effectiveness of teacher training and the enthusiasm of teachers for training and learning are improved.

[0119] Those skilled in the art should understand that the embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take 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.) that contain computer-usable program code.

[0120] This application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0121] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0122] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0123] Obviously, the above embodiments are merely examples given for clear illustration and are not limitations on the implementation manners. For those of ordinary skill 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 implementation manners here. And the obvious changes or modifications derived therefrom are still within the protection scope of the present 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 results of the learning and mining, including: 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 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 value of the knowledge point on the fit; comparing the influence value of the fit with the influence value threshold, selecting 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 matching the training materials that meet the fit in the hierarchical association sub-database according to the target knowledge point; 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 in a single knowledge point cluster set and deeply learns the influence value of the same knowledge point on the fit; 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 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.

6. The management method of the teacher training management platform according to claim 5 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.

7. 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.

8. 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.

9. 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 results of the learning and mining, including: 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 knowledge points to generate a plurality of knowledge point cluster sets, and performing deep learning on the knowledge point cluster sets to obtain the influence value of the knowledge point on the fit; comparing the influence value of the fit with the influence value threshold, selecting 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 matching the training materials that meet the fit in the hierarchical association sub-database according to the target knowledge point; wherein the deep learning includes first-direction learning and second-direction learning, the first-direction learning compares the plurality of knowledge point cluster sets and deeply learns the influence values ​​of different knowledge points on the fit; the second-direction learning compares a plurality of fit items in a single knowledge point cluster set and deeply learns the influence value of the same knowledge point on the fit; A push module is used to push the training materials to the user.

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