A teacher teaching ability promotion training method and system

Abstract

The application discloses a kind of teacher teaching ability promotion training method and system, its method includes: determining multiple evaluation dimensions of teacher teaching ability, obtaining the quantitative evaluation index of each evaluation dimension, obtain multiple high-quality training course resources according to quantitative evaluation index;The historical teaching state parameter of each teacher is input and the teaching ability of each teacher is evaluated;According to the evaluation result, the teaching short board index and short board state description of each teacher are analyzed and the ability promotion demand parameter is determined;According to the ability promotion demand parameter, the target training course resource is filtered from multiple high-quality training course resources, and the training plan is formulated based on the learning ability information of each teacher, and the teaching ability promotion training is carried out according to the training plan for each teacher.It can accurately aim at different teaching level teachers for accurate short board related ability training, which improves the efficiency and stability of training, and also guarantees the adaptability of training resources, improves the practicability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of personnel ability training, and in particular to a teacher teaching ability improvement training method and system. BACKGROUND

[0002] At present, with the increasing diversification of the educational environment, the challenges faced by teachers are also increasing, especially novice teachers often have difficulty in adapting to the variability of student behavior and teaching needs in the actual teaching process. The current teacher training methods are mainly divided into offline and online two kinds. Offline training mode can provide real classroom scene for teachers, on the one hand, the cost of offline training is high, it is difficult to apply and popularize at any time; on the other hand, although offline training is convenient for novice teachers to share teaching experience with experienced teachers, it is often difficult to combine into actual teaching scene to exercise the teaching ability of teachers, and it is also difficult to provide personalized feedback and support, so that teachers are difficult to adjust according to the diversified needs of students. Compared with offline training mode, online training realizes the connection training through watching video and theoretical explanation, greatly improves the convenience, but it has the following problems: due to the uneven teaching level of each teacher, the fixed online training mode cannot accurately train each teacher's teaching short board, which reduces the practicability, training efficiency and stability. SUMMARY

[0003] In view of the above problems, the present application provides a teacher teaching ability improvement training method and system to solve the problem of uneven teaching level of each teacher, fixed online training mode cannot accurately train each teacher's teaching short board, which reduces the practicability, training efficiency and stability mentioned in the background art.

[0004] A teacher teaching ability improvement training method, comprising the following steps:

[0005] Determine a plurality of evaluation dimensions of teacher teaching ability, obtain quantitative evaluation indexes of each evaluation dimension, and obtain a plurality of high-quality training course resources according to the quantitative evaluation indexes;

[0006] Obtain the historical teaching state parameters input by each teacher, and evaluate the teaching ability of each teacher according to the historical teaching state parameters;

[0007] According to the evaluation result, the teaching short board index and the short board state description of each teacher are analyzed, and the ability improvement demand parameter is determined according to the teaching short board index and the short board state description;

[0008] The target training course resource is selected from a plurality of high-quality training course resources according to the capacity improvement demand parameter, and a training plan is made based on the target training course resource and the learning capacity information of each teacher, and each teacher is trained for teaching capacity improvement according to the training plan.

[0009] Preferably, before obtaining the historical teaching state parameter input by each teacher and evaluating the teaching capacity of each teacher according to the historical teaching state parameter, the method further comprises:

[0010] determining the teaching subject of each teacher, obtaining the teaching scene parameter corresponding to the teaching subject, and determining the teaching emphasis label of the teaching subject according to the teaching scene parameter;

[0011] determining a plurality of necessary teaching indexes of each teacher based on the teaching emphasis label through the evaluation analysis data model;

[0012] obtaining the teaching form and teaching system corresponding to the teaching subject of each teacher, and giving weight to each necessary teaching index according to the teaching form and teaching system;

[0013] According to the given weight of each necessary teaching index, the key necessary teaching index and the non-key necessary teaching index are screened out.

[0014] Preferably, the method of determining a plurality of evaluation dimensions of the teaching capacity of the teacher, obtaining a quantitative evaluation index of each evaluation dimension, and obtaining a plurality of high-quality training course resources according to the quantitative evaluation index comprises:

[0015] determining a plurality of evaluation dimensions of the teaching capacity of the teacher according to the education standard, and determining the education data source of each evaluation dimension;

[0016] collecting teaching data of each evaluation dimension from the education data source, and extracting dynamic behavior data from the teaching data;

[0017] determining a quantitative evaluation index of each evaluation dimension according to the extracted dynamic behavior data and the behavior conclusion, and determining a course three-dimensional label demand according to the quantitative evaluation index;

[0018] obtaining a plurality of training course resources based on the course three-dimensional label demand, performing high-quality identification on each training course resource based on the historical teaching situation of the training course resource, and screening a plurality of high-quality training course resources of each quantitative evaluation index according to the identification result.

[0019] Preferably, the method of obtaining the historical teaching state parameter input by each teacher and evaluating the teaching capacity of each teacher according to the historical teaching state parameter comprises:

[0020] collecting the classroom basic data, student academic data, teaching behavior data and interactive feedback data input by each teacher as the historical teaching state parameter;

[0021] determining respective mapping teaching indexes of the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data respectively and determining analysis logic of the mapping teaching indexes;

[0022] selecting analysis models of the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data respectively according to the analysis logic;

[0023] performing teaching ability evaluation on each teacher according to the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data through the analysis models.

[0024] Preferably, the performing teaching ability evaluation on each teacher according to the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data through the analysis models comprises:

[0025] outputting growth evaluation parameters of the mapping teaching indexes based on time series according to the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data through the analysis models;

[0026] determining growth trends of the mapping teaching indexes according to the growth evaluation parameters of the mapping teaching indexes based on time series;

[0027] screening out first mapping teaching indexes of normal development and steady development and second mapping teaching indexes of declining trend according to the growth trends;

[0028] determining respective evaluation dimensions of the first mapping teaching indexes and the second mapping teaching indexes respectively, and constructing teaching ability histograms of each teacher according to the respective evaluation dimensions.

[0029] Preferably, after analyzing teaching short board indexes and short board state descriptions of each teacher according to the evaluation results, the method further comprises:

[0030] determining whether the teaching short board indexes of each teacher are non-key essential teaching indexes of the teachers, and if yes, obtaining qualified state parameters of the teaching short board indexes;

[0031] determining theoretical improvement amplitudes of each teacher on the teaching short board indexes according to the qualified state parameters, and determining training intensities of each teacher on the teaching short board indexes based on the theoretical improvement amplitudes;

[0032] determining training priorities of each teaching short board index according to the training intensities, and sorting the teaching short board indexes of each teacher according to the training priorities;

[0033] taking the sorting results as reference conditions for formulating training plans.

[0034] Preferably, the teaching short board index and the short board state description of each teacher are analyzed according to the evaluation result, and the ability improvement demand parameter is determined according to the teaching short board index and the short board state description, including:

[0035] According to the evaluation result, the short board teaching dimension of each teacher is determined, and the target quantitative evaluation index corresponding to the short board teaching dimension is determined as the teaching short board index;

[0036] The short board type of the teaching short board index is determined, and the interaction behavior parameter of each teacher with the students under the teaching short board index is obtained according to the short board type;

[0037] The related state description of the teaching short board index is extracted according to the interaction behavior parameter, and the optimization target is determined according to the related state description and the teaching short board index;

[0038] The optimization behavior parameter of each teacher on the teaching short board index is determined according to the optimization target, and the ability improvement demand parameter is determined according to the optimization behavior parameter.

[0039] Preferably, the target training course resource is selected from the plurality of high-quality training course resources according to the ability improvement demand parameter, including:

[0040] A plurality of intervention strategies corresponding to the ability improvement demand parameter are determined, and the time cost parameter and the energy cost parameter of each intervention strategy are obtained;

[0041] The best intervention strategy is selected according to the time cost parameter and the energy cost parameter, and the matching high-quality training course resource of the best intervention strategy is determined;

[0042] The matching degree score of each matching high-quality training course resource is calculated by a multi-dimensional matching algorithm, and the matching high-quality training course resource with the highest matching degree score is selected as the target training course resource.

[0043] Preferably, the training plan is formulated based on the target training course resource and the learning ability information of each teacher, and the teaching ability improvement training is carried out for each teacher according to the training plan, including:

[0044] The multi-dimensional historical learning data of each teacher is collected, and the learning ability index of each teacher is calculated based on the learning ability quantitative index and the multi-dimensional historical learning data;

[0045] The course outline and the content volume of the target training course resource are determined, and the course load coefficient is determined based on the course outline and the content volume;

[0046] A plurality of learning stages and stage targets of each learning stage are formulated according to the course load coefficient and the learning ability index of each teacher;

[0047] A training plan is formulated according to the multiple learning stages, the stage targets of each learning stage and the time arrangement parameters of each teacher, and each teacher is trained according to the training plan.

[0048] A teacher teaching ability improvement training system, comprising:

[0049] An acquisition module is configured to determine multiple evaluation dimensions of the teaching ability of a teacher, acquire quantitative evaluation indexes of each evaluation dimension, and acquire multiple high-quality training course resources according to the quantitative evaluation indexes;

[0050] An evaluation module is configured to acquire historical teaching state parameters input by each teacher, and evaluate the teaching ability of each teacher according to the historical teaching state parameters;

[0051] A determination module is configured to analyze teaching short board indicators and short board state descriptions of each teacher according to the evaluation results, and determine ability improvement demand parameters according to the teaching short board indicators and the short board state descriptions;

[0052] A training module is configured to filter target training course resources from the multiple high-quality training course resources according to the ability improvement demand parameters, formulate a training plan based on the target training course resources and learning ability information of each teacher, and train the teaching ability of each teacher according to the training plan.

[0053] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the application. The objects and other advantages of the present application will be realized and attained by the structure particularly pointed out in the written description and claims.

[0054] The technical solutions of the present application will be further described in detail below with the aid of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0055] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate the present application and explain the present application together with the embodiments of the present application, and do not constitute a limitation on the present application.

[0056] Figure 1 A work flow diagram of a teacher teaching ability improvement training method provided by the present application;

[0057] Figure 2 Another work flow diagram of a teacher teaching ability improvement training method provided by the present application;

[0058] Figure 3 Still another work flow diagram of a teacher teaching ability improvement training method provided by the present application;

[0059] Figure 4 A structural schematic diagram of a teacher teaching ability promotion training system provided by the present application. DETAILED DESCRIPTION

[0060] The exemplary embodiments will be described in detail hereinbelow with reference to the accompanying drawings. In the following description, the same numbers refer to the same or similar elements unless otherwise represented. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0061] At present, with the increasing diversification of the educational environment, the challenges faced by teachers are also increasing, especially novice teachers often have difficulty in quickly adapting to the variability of student behavior and teaching needs in the actual teaching process. The current teacher training methods are mainly divided into offline and online two kinds. Offline training mode can provide real classroom scene for teachers, on the one hand, the cost of offline training is high, it is difficult to apply and popularize at any time; on the other hand, although offline training is convenient for novice teachers to share teaching experience with experienced teachers, it is often difficult to combine into actual teaching scene to exercise the teaching ability of teachers, and it is also difficult to provide personalized feedback and support, so that teachers are difficult to adjust according to the diversified needs of students. Compared with offline training mode, online training realizes the connection training through watching video and theoretical explanation, greatly improves the convenience, but it has the following problems: due to the uneven teaching level of each teacher, the fixed online training mode cannot accurately train each teacher's teaching short board, which reduces the practicability, training efficiency and stability. In order to solve the above problems, the embodiment discloses a teacher teaching ability promotion training method.

[0062] A teacher teaching ability promotion training method, as shown in Figure 1 includes the following steps:

[0063] Step S101, determining a plurality of evaluation dimensions of the teaching ability of teachers, obtaining a quantitative evaluation index of each evaluation dimension, and obtaining a plurality of high-quality training course resources according to the quantitative evaluation index;

[0064] Step S102, obtaining the historical teaching state parameters input by each teacher, and evaluating the teaching ability of each teacher according to the historical teaching state parameters;

[0065] Step S103, analyzing the teaching short board index and short board state description of each teacher according to the evaluation result, and determining the ability promotion demand parameter according to the teaching short board index and short board state description;

[0066] In step S104, the target training course resource is selected from the plurality of high-quality training course resources according to the capacity improvement demand parameter, and a training plan is formulated based on the target training course resource and the learning capacity information of each teacher, and each teacher is trained for teaching capacity improvement according to the training plan.

[0067] In the embodiment, the plurality of evaluation dimensions represent evaluation dimensions for comprehensive evaluation of the teaching capacity of the teachers, and specifically include teaching skills, subject literacy, classroom management, knowledge application, student development, and teacher ethics, etc.

[0068] In the embodiment, the quantitative evaluation index represents a mapping quantitative index of each evaluation dimension, for example, the quantitative evaluation index of classroom management includes classroom discipline management, classroom atmosphere management, and classroom learning initiative management, etc.

[0069] The working principle of the above technical solution is that a plurality of evaluation dimensions of the teaching capacity of the teachers are determined, quantitative evaluation indexes of each evaluation dimension are obtained, and a plurality of high-quality training course resources are obtained according to the quantitative evaluation indexes; historical teaching state parameters input by each teacher are obtained, and the teaching capacity of each teacher is evaluated according to the historical teaching state parameters; teaching short board indicators and short board state descriptions of each teacher are analyzed according to the evaluation results, and capacity improvement demand parameters are determined according to the teaching short board indicators and the short board state descriptions; a target training course resource is selected from the plurality of high-quality training course resources according to the capacity improvement demand parameters, and a training plan is formulated based on the target training course resource and the learning capacity information of each teacher, and each teacher is trained for teaching capacity improvement according to the training plan.

[0070] The above technical solution has the beneficial effects that: by evaluating the teaching capacity of each teacher and then determining the short board teaching indicators and the capacity improvement demand to select the course resources with the adaptive degree for capacity improvement training, the teachers with different teaching levels can be precisely trained for the short board related capacity, which improves the efficiency and stability of the training, guarantees the adaptability of the training resources, improves the practicality, and solves the problem of the existing technology that the fixed online training mode cannot precisely train each teacher for the teaching short board due to the uneven teaching levels of the teachers, which reduces the practicality and the efficiency and stability of the training.

[0071] In the embodiment, after evaluating the teaching capacity of each teacher according to the historical teaching state parameters, the following steps are further included:

[0072] The historical teaching materials of each teacher are determined according to the historical teaching state parameters, and the classroom response parameters of the historical teaching materials are obtained;

[0073] The knowledge sequence demand distribution of the historical teaching materials is determined based on the teaching thinking of the classroom response parameters and the historical teaching materials.

[0074] screening the classroom active knowledge points according to the knowledge sequence demand distribution, and determining the target teaching mode of the classroom active knowledge points;

[0075] determining the teaching skill demand variation parameter of the teacher according to the target teaching mode, and determining the conversion adjustment mechanism of the quantitative evaluation index according to the teaching skill demand variation parameter;

[0076] determining the state adjustment ability demand of the teacher based on the conversion adjustment mechanism of the quantitative evaluation index, and determining the state adjustment adaptation factor of each teacher under the historical teaching state parameter according to the state adjustment ability demand;

[0077] determining the teaching ability fluctuation vector of each teacher under the historical teaching state parameter according to the state adjustment adaptation factor;

[0078] evaluating the teaching ability feedback gap of each teacher under the historical teaching state parameter according to the teaching ability fluctuation vector;

[0079] determining the teaching ability evaluation error of each teacher according to the teaching ability feedback gap, and determining the error interval of the teaching ability evaluation error;

[0080] selecting the teaching ability reference parameter based on the error interval, wherein the teaching ability reference parameter comprises: a problem corresponding problem solving time parameter, a correctness parameter, a problem solving thought parameter and a modification process parameter;

[0081] selecting the target teaching resource according to the teaching ability parameter, collecting the teaching process parameter of each teacher on the target teaching resource, and performing the secondary evaluation on the teaching ability of each teacher through the teaching process parameter;

[0082] correcting the teaching ability evaluation result of each teacher according to the secondary evaluation result.

[0083] The beneficial effects of the above technical solutions are that: by deeply mining the historical teaching materials of each teacher to determine the state conversion adjustment parameter of each evaluation index in the teaching process to evaluate the teaching ability error of each teacher, and then selecting the teaching resource for re-evaluation, the ability evaluation error of the teacher caused by poor on-site state adjustment can be overcome, thereby ensuring the stability and reliability of the teaching ability evaluation of each teacher, and laying a foundation for subsequent improvement training.

[0084] In one embodiment, before obtaining the historical teaching state parameter input by each teacher and evaluating the teaching ability of each teacher according to the historical teaching state parameter, the method further comprises:

[0085] determining the teaching subject of each teacher, obtaining the teaching scene parameter corresponding to the teaching subject, and determining the teaching emphasis label of the teaching subject according to the teaching scene parameter;

[0086] determining a plurality of necessary teaching indicators of each teacher based on the teaching emphasis label through the evaluation analysis data model;

[0087] obtaining a teaching form and a teaching system corresponding to a teaching subject of each teacher, and assigning weights to each necessary teaching indicator according to the teaching form and the teaching system;

[0088] According to the assigned weights of each necessary teaching indicator, a key necessary teaching indicator and a non-key necessary teaching indicator are screened out.

[0089] The beneficial effects of the above technical solutions are that by judging and classifying the key necessary teaching indicators and the non-key necessary teaching indicators of each teacher, the emphasis teaching indicators of each teacher can be understood from a general direction, and the objectivity and rationality of the evaluation of the teaching ability of each teacher are ensured.

[0090] In one embodiment, the determining a plurality of evaluation dimensions of the teaching ability of the teacher, obtaining a quantitative evaluation indicator of each evaluation dimension, and obtaining a plurality of high-quality training course resources according to the quantitative evaluation indicator, comprises:

[0091] determining a plurality of evaluation dimensions of the teaching ability of the teacher according to the education standard, and determining an education data source of each evaluation dimension;

[0092] collecting teaching data of each evaluation dimension from the education data source, and extracting dynamic behavior data from the teaching data;

[0093] determining a quantitative evaluation indicator of each evaluation dimension according to the extracted dynamic behavior data and the behavior conclusion, and determining a course three-dimensional label requirement according to the quantitative evaluation indicator;

[0094] obtaining a plurality of training course resources based on the course three-dimensional label requirement, performing high-quality identification on each training course resource based on the historical teaching situation of the training course resource, and screening out a plurality of high-quality training course resources of each quantitative evaluation indicator according to the identification result.

[0095] The beneficial effects of the above technical solutions are that by obtaining a plurality of training course resources based on the course three-dimensional label requirement, the course resources can be accurately adapted and screened according to the corresponding course labels of the quantitative evaluation indicators of each dimension, and high-quality identification is performed, so as to ensure the high quality and reliability of the course resources and improve the objectivity of the training effect.

[0096] In one embodiment, the obtaining a historical teaching state parameter input by each teacher, and evaluating the teaching ability of each teacher according to the historical teaching state parameter, comprises:

[0097] Collecting the classroom basic data, student academic data, teaching behavior data and interactive feedback data input by each teacher as historical teaching state parameters;

[0098] Determine the mapping teaching indicators of the classroom basic data, student academic data, teaching behavior data and interactive feedback data respectively and determine the analysis logic of the mapping teaching indicators;

[0099] Select the analysis model of the classroom basic data, student academic data, teaching behavior data and interactive feedback data according to the analysis logic;

[0100] Perform teaching ability evaluation on each teacher according to the classroom basic data, student academic data, teaching behavior data and interactive feedback data through the analysis model.

[0101] The beneficial effects of the above technical solutions are that the analysis model can be selected to comprehensively and intuitively evaluate the teaching ability of each teacher, thereby improving the reliability of the evaluation results.

[0102] In one embodiment, as shown in Figure 2 the teaching ability evaluation on each teacher according to the classroom basic data, student academic data, teaching behavior data and interactive feedback data through the analysis model includes:

[0103] Step S201, output the mapping teaching indicators based on time series growth evaluation parameters according to the classroom basic data, student academic data, teaching behavior data and interactive feedback data through the analysis model;

[0104] Step S202, determine the growth trend of the mapping teaching indicators based on the time series growth evaluation parameters;

[0105] Step S203, filter out the first mapping teaching indicators of normal development and steady development and the second mapping teaching indicators of downward trend according to the growth trend;

[0106] Step S204, determine the evaluation dimensions of the first mapping teaching indicators and the second mapping teaching indicators respectively, and construct the teaching ability histogram of each teacher according to the evaluation dimensions.

[0107] The beneficial effects of the above technical solutions are that the growth trend of each teacher on each teaching indicator can be quickly and intuitively determined, the teaching ability score of each teacher in each dimension is accurately determined, a reference condition for subsequent selection of short board teaching indicators is laid, and the practicability is further improved.

[0108] In one embodiment, after analyzing the teaching short board indicators and short board state descriptions of each teacher according to the evaluation results, it further includes:

[0109] determining whether the teaching short board index of each teacher is a non-key essential teaching index of the teacher, and if so, obtaining a qualified state parameter of the teaching short board index;

[0110] determining a theoretical improvement range of each teacher on the teaching short board index according to the qualified state parameter, and determining a training intensity of each teacher on the teaching short board index based on the theoretical improvement range;

[0111] determining a training priority of each teaching short board index according to the training intensity, and sorting the teaching short board index of each teacher according to the training priority;

[0112] using the sorting result as a reference condition for formulating a training plan.

[0113] The beneficial effects of the above technical solutions are that the priority sorting of the teaching short board index of each teacher can be based on the key determination attribute and the improvement range of each teaching short board index to perform the core teaching ability training identification, so as to avoid the waste of course training resources on the improvement of non-core ability and improve the training efficiency.

[0114] In one embodiment, as shown in Figure 3 the teaching short board index and the short board state description of each teacher are analyzed according to the evaluation result, and the ability improvement requirement parameter is determined according to the teaching short board index and the short board state description, including:

[0115] Step S301, determining the short board teaching dimension of each teacher according to the evaluation result, and determining the target quantitative evaluation index corresponding to the short board teaching dimension as the teaching short board index;

[0116] Step S302, determining the short board type of the teaching short board index, and obtaining the interaction behavior parameter of each teacher with students under the teaching short board index according to the short board type;

[0117] Step S303, extracting the related state description of the teaching short board index according to the interaction behavior parameter, and determining the optimization target according to the related state description and the teaching short board index;

[0118] Step S304, determining the optimization behavior parameter of each teacher on the teaching short board index according to the optimization target, and determining the ability improvement requirement parameter according to the optimization behavior parameter.

[0119] The beneficial effects of the above technical solutions are that the optimization behavior parameter of each teacher on the teaching short board index can be determined according to the mapping relationship between the behavior and the ability to accurately determine the ability improvement requirement parameter of each teacher, thereby improving the reliability and accuracy.

[0120] In one embodiment, the target training course resource is selected from a plurality of high-quality training course resources according to the ability improvement requirement parameter, including:

[0121] determine a plurality of intervention strategies corresponding to the capacity improvement requirement parameter, obtain a time cost parameter and an energy cost parameter of each intervention strategy;

[0122] screen out a best intervention strategy according to the time cost parameter and the energy cost parameter, and determine a matching high-quality training course resource of the best intervention strategy;

[0123] calculate a fit degree score of each matching high-quality training course resource through a multi-dimensional matching algorithm, and select a matching high-quality training course resource with the highest fit degree score as a target training course resource.

[0124] The above technical solution has the beneficial effect that: determining the best intervention strategy and then screening out the training course resource with the highest adaptation and fit degree can not only train from the capacity essence but also maximize the training effect, thereby further improving the practicality.

[0125] In one embodiment, the training plan is formulated based on the target training course resource and the learning capacity information of each teacher, and the teaching capacity improvement training is performed on each teacher according to the training plan, including:

[0126] collecting multi-dimensional historical learning data of each teacher, calculating a learning capacity index of each teacher based on the multi-dimensional historical learning data according to a learning capacity quantitative index;

[0127] determining a course outline and a content volume of the target training course resource, and determining a course load coefficient based on the course outline and the content volume;

[0128] formulating a plurality of learning stages and stage targets of each learning stage according to the course load coefficient and the learning capacity index of each teacher;

[0129] formulating a training plan according to the plurality of learning stages, the stage targets of each learning stage, and a time arrangement parameter of each teacher, and performing the teaching capacity improvement training on each teacher according to the training plan.

[0130] The above technical solution has the beneficial effect that: formulating the training plan according to the plurality of learning stages, the stage targets of each learning stage, and the time arrangement parameter of each teacher can sequentially and progressively improve the capacity of each teacher while ensuring the training acceptance degree under the learning capacity of each teacher, thereby maximizing the teaching efficiency.

[0131] In one embodiment, the present embodiment also discloses a teacher teaching capacity improvement training system, as shown in Figure 4 The system includes:

[0132] The acquisition module 401 is configured to determine a plurality of evaluation dimensions of the teaching ability of the teachers, acquire a quantitative evaluation index of each evaluation dimension, and acquire a plurality of high-quality training course resources according to the quantitative evaluation index.

[0133] The evaluation module 402 is configured to acquire historical teaching state parameters input by each teacher, and evaluate the teaching ability of each teacher according to the historical teaching state parameters.

[0134] The determination module 403 is configured to analyze a teaching short-board index and a short-board state description of each teacher according to the evaluation result, and determine a capability improvement demand parameter according to the teaching short-board index and the short-board state description.

[0135] The training module 404 is configured to filter out a target training course resource from the plurality of high-quality training course resources according to the capability improvement demand parameter, and formulate a training plan based on the target training course resource and learning ability information of each teacher, and perform teaching ability improvement training on each teacher according to the training plan.

[0136] The working principle and beneficial effects of the above technical solution have been described in the method embodiment, and will not be repeated here.

[0137] Other embodiments of the disclosure will be readily apparent to the skilled user in the art, having the benefit of the instant disclosure. The present application is intended to embrace all such alterations, modifications, and variations that fall within the scope of the present disclosure, which is defined solely by the claims appended hereto. The specification and examples are to be considered exemplary only, with the true scope and spirit of the disclosure indicated by the following claims.

[0138] It should be understood that the present disclosure is not limited to the precise construction that has been described above and illustrated in the accompanying drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the claims that follow.

Claims

1. A teacher teaching ability improvement training method, characterized by, The method comprises the following steps: determining a plurality of evaluation dimensions of the teaching ability of teachers, obtaining quantitative evaluation indicators of each evaluation dimension, and obtaining a plurality of high-quality training course resources according to the quantitative evaluation indicators; obtaining historical teaching state parameters input by each teacher, and evaluating the teaching ability of each teacher according to the historical teaching state parameters; analyzing teaching short board indicators and short board state descriptions of each teacher according to the evaluation results, and determining the ability improvement demand parameters according to the teaching short board indicators and the short board state descriptions; selecting target training course resources from the plurality of high-quality training course resources according to the ability improvement demand parameters, and formulating a training plan based on the target training course resources and learning ability information of each teacher, and training the teaching ability of each teacher according to the training plan; the obtaining of the historical teaching state parameters input by each teacher and the evaluation of the teaching ability of each teacher according to the historical teaching state parameters comprises: collecting classroom basic data, student academic data, teaching behavior data and interactive feedback data input by each teacher as historical teaching state parameters; determining respective mapping teaching indicators of the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data, and determining analysis logic of the mapping teaching indicators; selecting analysis models of the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data according to the analysis logic; evaluating the teaching ability of each teacher according to the classroom basic data, the student academic data, the teaching behavior data and the interactive feedback data through the analysis models; the analysis of the teaching short board indicators and the short board state descriptions of each teacher according to the evaluation results, and the determination of the ability improvement demand parameters according to the teaching short board indicators and the short board state descriptions comprises: determining a short board teaching dimension of each teacher according to the evaluation results, and determining target quantitative evaluation indicators corresponding to the short board teaching dimension as the teaching short board indicators; determining a short board type of the teaching short board indicators, and obtaining interactive behavior parameters of each teacher with students under the teaching short board indicators according to the short board type; extracting relevant state descriptions of the teaching short board indicators according to the interactive behavior parameters, and determining an optimization target according to the relevant state descriptions and the teaching short board indicators; determining optimization behavior parameters of each teacher on the teaching short board indicators according to the optimization target, and determining the ability improvement demand parameters according to the optimization behavior parameters.

2. The teacher teaching ability improvement training method according to claim 1, wherein Before the obtaining of the historical teaching state parameters input by each teacher and the evaluation of the teaching ability of each teacher according to the historical teaching state parameters, the method further comprises: determining a teaching subject of each teacher, obtaining teaching scene parameters corresponding to the teaching subject, and determining a teaching emphasis label of the teaching subject according to the teaching scene parameters; determining a plurality of necessary teaching indicators of each teacher based on the teaching emphasis label through an evaluation analysis data model; obtaining a teaching form and a teaching system corresponding to the teaching subject of each teacher, and giving weights to each necessary teaching indicator according to the teaching form and the teaching system; screening out key necessary teaching indicators and non-key necessary teaching indicators according to the given weights of each necessary teaching indicator.

3. The teacher teaching ability improvement training method according to claim 1, wherein The method comprises the following steps: According to the education standard, determine the multiple evaluation dimensions of the teacher's teaching ability, and determine the education data source of each evaluation dimension; Collect teaching data of each evaluation dimension from the education data source, and extract dynamic behavior data from the teaching data; According to the extracted dynamic behavior data and its behavior conclusion, determine the quantitative evaluation index of each evaluation dimension, and determine the course three-dimensional label demand according to the quantitative evaluation index; Based on the course three-dimensional label demand, obtain multiple training course resources, based on the historical teaching situation of each training course resource, perform quality identification on the training course resource, and according to the identification result, filter out multiple high-quality training course resources of each quantitative evaluation index.

4. The teacher teaching ability improvement training method according to claim 1, wherein The method comprises the following steps: According to the analysis model, according to the classroom basic data, student academic data, teaching behavior data and interactive feedback data, the teaching ability of each teacher is evaluated, which comprises the following steps: According to the analysis model, according to the classroom basic data, student academic data, teaching behavior data and interactive feedback data, the mapping teaching index based on time series growth evaluation parameter is outputted; According to the mapping teaching index based on time series growth evaluation parameter, the growth trend of the mapping teaching index is determined; According to the growth trend, the first mapping teaching index of normal development and steady development and the second mapping teaching index of downward trend are filtered out; 5. The teacher teaching ability improvement training method according to claim 2, wherein Determine the evaluation dimension to which the first mapping teaching index and the second mapping teaching index belong respectively, and construct the teaching ability histogram of each teacher according to the evaluation dimension. After analyzing the teaching short board index and short board state description of each teacher according to the evaluation result, the method further comprises the following steps: Determine whether the teaching short board index of each teacher is a non-key essential teaching index of the teacher, if yes, obtain the qualified state parameter of the teaching short board index; According to the qualified state parameter, determine the theoretical improvement amplitude of each teacher on the teaching short board index, and determine the training intensity of each teacher on the teaching short board index based on the theoretical improvement amplitude; According to the training intensity, determine the training priority of each teaching short board index, and sort the teaching short board index of each teacher according to the training priority; 6. The teacher teaching ability improvement training method according to claim 1, wherein The sorting result is used as a reference condition for formulating a training plan. The method comprises the following steps: Determine the multiple intervention strategies corresponding to the ability improvement demand parameter, and obtain the time cost parameter and energy cost parameter of each intervention strategy; According to the time cost parameter and the energy cost parameter, the best intervention strategy is filtered out, and the matching high-quality training course resource of the best intervention strategy is determined; 7. The teacher teaching ability improvement training method according to claim 1, wherein Through a multi-dimensional matching algorithm, the matching degree score of each matching high-quality training course resource is calculated, and the matching high-quality training course resource with the highest matching degree score is selected as the target training course resource. The method comprises the following steps: According to the training plan, the teaching ability of each teacher is trained, which comprises the following steps: Collect multi-dimensional historical learning data of each teacher, and calculate learning ability index of each teacher based on learning ability quantitative indicators and the multi-dimensional historical learning data; Determine a course outline and content volume of the target training course resource, and determine a course load coefficient based on the course outline and the content volume; Formulate a plurality of learning stages and stage targets of each learning stage according to the course load coefficient and the learning ability index of each teacher; Formulate a training plan according to the plurality of learning stages, the stage targets of each learning stage, and a time arrangement parameter of each teacher, and perform teaching ability improvement training on each teacher according to the training plan.

8. A teacher teaching ability improvement training system characterized by, The system comprises: An acquisition module configured to determine a plurality of evaluation dimensions of the teaching ability of the teachers, acquire quantitative evaluation indicators of each evaluation dimension, and acquire a plurality of high-quality training course resources based on the quantitative evaluation indicators; An evaluation module configured to acquire historical teaching state parameters input by each teacher, and perform teaching ability evaluation on each teacher based on the historical teaching state parameters; A determination module configured to analyze teaching short board indicators and short board state descriptions of each teacher based on the evaluation results, and determine ability improvement demand parameters based on the teaching short board indicators and the short board state descriptions; A training module configured to select target training course resources from the plurality of high-quality training course resources based on the ability improvement demand parameters, formulate a training plan based on the target training course resources and learning ability information of each teacher, and perform teaching ability improvement training on each teacher according to the training plan; The acquisition of the historical teaching state parameters input by each teacher and the teaching ability evaluation on each teacher based on the historical teaching state parameters comprise: Collecting classroom basic data, student academic data, teaching behavior data, and interactive feedback data input by each teacher as historical teaching state parameters; Determining respective mapping teaching indicators of the classroom basic data, the student academic data, the teaching behavior data, and the interactive feedback data, and determining analysis logic of the mapping teaching indicators; Selecting analysis models of the classroom basic data, the student academic data, the teaching behavior data, and the interactive feedback data according to the analysis logic; Performing teaching ability evaluation on each teacher based on the classroom basic data, the student academic data, the teaching behavior data, and the interactive feedback data through the analysis models; The analysis of the teaching short board indicators and the short board state descriptions of each teacher based on the evaluation results, and the determination of the ability improvement demand parameters based on the teaching short board indicators and the short board state descriptions comprise: Determining a short board teaching dimension of each teacher based on the evaluation results, and determining target quantitative evaluation indicators corresponding to the short board teaching dimension as the teaching short board indicators; Determining a short board type of the teaching short board indicators, and acquiring interactive behavior parameters of each teacher with students under the teaching short board indicators based on the short board type; Extracting related state descriptions of the teaching short board indicators based on the interactive behavior parameters, and determining optimization targets based on the related state descriptions and the teaching short board indicators; Determining optimization behavior parameters of each teacher on the teaching short board indicators based on the optimization targets, and determining the ability improvement demand parameters based on the optimization behavior parameters.

Images