Employee training method and employee training device based on teacher-apprentice mechanism

Abstract

The invention provides an employee training method and an employee training device based on a teacher-apprentice mechanism. The method comprises the following steps: acquiring a first skill matrix of a tutor and a second skill matrix of each student; calculating a matching degree based on the first skill matrix and the second skill matrix; distributing the students to the tutor with the maximum matching degree to obtain a first teaching scheme; a teaching task is sent according to the first teaching scheme, and a real-time third skill matrix of the student is acquired; decomposing an actual business task into a plurality of sub-tasks, and respectively constructing corresponding demand skill matrixes; calculating the matching degree according to the demand skill matrix and the third skill matrix, sending the subtask corresponding to the maximum matching degree to the student terminal, and determining the task completion degree according to feedback; and adjusting the first teaching scheme based on the task completion degree and sending the first teaching scheme to the student terminal and the tutor terminal. The method solves the problem that the method in the prior art cannot be flexibly matched with the trainee ability, so that the cultivation direction is deviated, the cultivation efficiency is reduced, and the cultivation cost is high.

Description

Technical Field

[0001] The present invention relates to the technical field of human resource management, and more particularly, to an employee training method, an employee training device, a computer-readable storage medium, and a human resource management system based on a master-apprentice mechanism. Background Art

[0002] In the context of the current digital transformation and the rapid development of cloud computing, communication enterprises are facing an increasingly complex business environment, including the diversified development of cloud computing services, the deployment of 5G networks, the integration of technologies such as the Internet of Things, big data, and artificial intelligence. The development of the business environment's requirements for the rapid iteration and improvement of employees' skills is an important factor in supporting the enterprise's business innovation and competitiveness improvement.

[0003] Traditional talent cultivation methods mainly rely on unified training courses or on-the-job practices. However, due to the complexity of technologies and the diversity of scenarios, it is difficult for the above methods to meet the requirements. For example, cloud platforms involve multiple fields from architecture to design and then to operation and maintenance, requiring relevant employees to have an interdisciplinary and multi-level skill system.

[0004] To address the above challenges, many enterprises have adopted the master-apprentice mechanism to drive the growth of new employees through experienced mentors. However, the traditional master-apprentice mechanism mainly has the following problems:

[0005] 1) Based on department or position division, it is difficult to achieve a high degree of matching of skills between mentors and trainees, as well as the accurate analysis of interests and learning needs, resulting in a low ability matching degree between mentors and trainees and affecting the training effect;

[0006] 2) Training is carried out in the form of daily guidance and question answering, and it is difficult to provide real-time and accurate guidance during the actual operation process. Especially in the complex scenarios of cloud services, in-depth understanding and improvement of practical skills are required;

[0007] 3) The supervision and effect evaluation of the master-apprentice training process usually rely on manual experience, lacking systematic and data-based management means, unable to form a quantitative analysis of training effects, and it is also difficult to provide effective references for subsequent optimization.

[0008] In summary, the existing technologies rely on manual matching and manual supervision, which are greatly affected by subjective factors and are difficult to ensure accuracy and standardization. Summary of the Invention

[0009] The main objective of this application is to provide an employee training method, an employee training device, a computer-readable storage medium, and a human resource management system based on a master-apprentice mechanism, so as to at least solve the problem that the methods in the existing technologies cannot be flexibly matched with the abilities of trainees, resulting in deviation of the training direction and decline in training efficiency, and thus higher training costs.

[0010] To achieve the above object, according to one aspect of the present application, there is provided an employee training method based on a master-apprentice mechanism, including: obtaining the skill matrices of each mentor from the employee skill assessment system to obtain M first skill matrices, obtaining the skill matrices required by each trainee from the trainee induction training system to obtain N second skill matrices, and the elements in the skill matrices at least include the level scores of business skills; calculating the matching degrees of each first skill matrix and each second skill matrix to obtain M*N first matching degrees, one trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees; allocating each trainee to the mentor corresponding to the maximum value of the corresponding M first matching degrees to obtain N first teaching plans; sending teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically obtaining the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix; obtaining the actual business tasks and decomposing the actual business tasks into multiple subtasks, respectively constructing skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask; calculating the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, sending the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determining the task completion degree according to the completion situation of the subtask; adjusting the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree, and sending them to the trainee terminal and the mentor terminal.

[0011] Optionally, calculating the matching degrees of each first skill matrix and each second skill matrix to obtain M*N first matching degrees includes: determining the importance weights of each business skill according to the enterprise development plan to obtain the first target weights; calculating the first matching degrees according to the first skill matrix, the second skill matrix and the first target weights: Where M is the first matching degree, n is the number of business skills in the first skill matrix and the second skill matrix, W i is the first target weight, S i =|S Di -S Li | represents the difference value between the element S Di in the first skill matrix and the element S Li in the second skill matrix.

[0012] Optionally, calculating the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, sending the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determining the task completion degree according to the completion situation of the subtask includes: determining the importance levels of each business skill in the required skill matrix in the subtask to obtain multiple second target weights; calculating the second matching degrees according to the second target weights, the third skill matrix of the target trainee and the required skill matrix: Where M(T i, C) is the second matching degree between subtask Ti and trainee C, and W j is the second target weight, is the j-th element in the required skill matrix of subtask Ti, and C j is the business skill j of the third skill matrix of target trainee C. m is the number of elements in the required skill matrix. Send the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, and receive the processed subtask uploaded by the trainee terminal. Determine the performance score based on the completion degree of the subtask. Determine the third target weight according to the importance of the subtask in the actual business task. Calculate the task completion degree according to the third target weight and the performance score; where P is the task completion degree, z is the number of actual business tasks, and Q k is the third target weight of the subtask assigned to the trainee terminal in the k-th actual business task, and D k is the performance score of the subtask assigned to the trainee terminal in the k-th actual business task.

[0013] Optionally, after sending the subtask corresponding to the maximum value of the second matching degree of each trainee to each trainee terminal, the method further includes: receiving the processed subtask, generating a target instruction according to the processed subtask and sending it to the tutor terminal. The target instruction is used to instruct the tutor to score the business skills used by the trainee in the subtask according to the completion status of the subtask; receiving the score uploaded by the tutor terminal to obtain the mastery progress score of each business skill of the trainee.

[0014] Optionally, adjusting the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree includes: obtaining all the task completion degrees corresponding to the trainee terminal before the current moment, and obtaining the fourth target weight according to the importance of the actual business tasks corresponding to each task completion degree in the project to which they belong; calculating the learning progress score of the trainee terminal according to the task completion degree and the fourth target weight: where P t is the learning progress score, w o is the fourth target weight corresponding to the 0-th actual business task, and P o is the task completion degree corresponding to the o-th actual business task; obtaining all the mastery progress scores corresponding to the trainee terminal before the current moment, and obtaining the fifth target weight according to the importance of the subtasks corresponding to each mastery progress score among all the subtasks involving the corresponding business skills; calculating the skill proficiency score of the trainee terminal according to the mastery progress score and the fifth target weight: where R f is the skill proficiency score corresponding to skill f, g is the number of subtasks, and T h,f is the fifth target weight of subtask h relative to business skill f, and F h,fScore the progress of mastering business skill f in subtask h; obtain the number of subtasks completed by the trainee before the current moment and the total number of subtasks, to get the first target number and the second target number; calculate the task completion rate according to the first target number and the second target number; adjust the overall period of the first teaching plan based on the learning progress score, adjust the teaching task proportion of each business skill in the first teaching plan based on the skill proficiency score, and adjust the period of the remaining first teaching plan based on the task completion degree.

[0015] Optionally, after adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, the method further includes: calculating the matching degree based on the third skill matrix and the corresponding second skill matrix to obtain the third matching degree, and determining the completion degree of the first teaching plan based on the interval where the third matching degree is located; every time the completion degree increases by a preset value, determine the task completion quality of the trainee according to the completion status of the actual business tasks, determine the problem-solving efficiency according to the tutor's response speed to the trainee's questions, and determine the business contribution degree according to the proportion of the actual business tasks completed by the trainee under the tutor's guidance in the project; perform weighted calculation according to the task completion quality, problem-solving efficiency and business contribution degree to obtain the comprehensive teaching score; in the case where the comprehensive teaching score is greater than the second threshold, keep the first teaching plan unchanged; in the case where the comprehensive teaching score is less than or equal to the second threshold, recalculate the matching degree based on the third skill matrix at the current moment and each first skill matrix to obtain the fourth matching degree; assign the trainees with the comprehensive teaching score less than the second threshold to the tutor corresponding to the second skill matrix corresponding to the maximum value of the fourth matching degree to obtain the second teaching plan.

[0016] Optionally, after adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, in the case where the first teaching plan is completed, calculate the ability assessment score according to the grade scores of all elements in the third skill matrix at the current moment; determine the trainee's skill interest tendency according to the third skill matrix at the current moment; decompose the enterprise development plan into multiple development sub-plans according to the development direction, and calculate the matching degree according to each development sub-plan and the skill interest tendency to obtain the demand matching degree; calculate the matching degree according to the third skill matrix and each development sub-plan to obtain the ability matching degree; perform weighted calculation on the ability assessment score respectively with each demand matching degree and the corresponding ability matching degree to obtain multiple career matching degrees, determine the development direction corresponding to the development sub-plan corresponding to the maximum value of the career matching degree as the target career development direction, and send the target career development direction to the trainee terminal.

[0017] According to another aspect of the present application, there is provided an employee training device based on a master-apprentice mechanism. The device includes: a first acquisition unit for acquiring the skill matrices of each mentor from an employee skill assessment system to obtain M first skill matrices, and acquiring the skill matrices required by each trainee from a trainee induction training system to obtain N second skill matrices. The elements in the skill matrix at least include the level scores of business skills; a first calculation unit for calculating the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees; a first matching unit for assigning each trainee to the mentor corresponding to the maximum value of the corresponding M first matching degrees to obtain N first teaching plans; a second acquisition unit for sending teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically acquiring the real-time skill matrix of the trainee during the teaching process to obtain a third skill matrix; a third acquisition unit for acquiring actual business tasks and decomposing the actual business tasks into multiple subtasks, and constructing skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask; a second calculation unit for calculating the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, sending the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determining the task completion degree according to the completion situation of the subtask; a first sending unit for adjusting the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the mentor terminal.

[0018] According to yet another aspect of the present application, there is provided a computer-readable storage medium. The computer-readable storage medium includes a stored program. When the program runs, it controls the device where the computer-readable storage medium is located to execute any one of the methods.

[0019] According to still another aspect of the present application, there is provided a human resource management system, including: one or more processors, a memory, and one or more programs. Among them, one or more programs are stored in the memory and are configured to be executed by one or more processors. The one or more programs include methods for executing any one of them.

[0020] Applying the technical solution of the present application in the above-mentioned employee training method based on the master-apprentice mechanism, first, obtain the skill matrices of each mentor from the employee skill evaluation system to obtain M first skill matrices, and obtain N second skill matrices of the skills required by each trainee from the trainee induction training system. The elements in the skill matrix at least include the level scores of business skills. Then, calculate the matching degrees between each first skill matrix and each second skill matrix to obtain M×N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees. After that, assign each trainee to the mentor corresponding to the maximum value of the M first matching degrees to obtain N first teaching plans. After that, send teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix. After that, obtain the actual business tasks and decompose the actual business tasks into multiple subtasks, and construct skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask. After that, calculate the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, send the subtask corresponding to the maximum value of the second matching degree of each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask. Finally, adjust the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree, and send them to the trainee terminal and the mentor terminal. The present application represents the abilities of the mentors and the abilities that the trainees need to learn through matrices respectively, and conducts master-apprentice matching guided by the matching degrees between the matrices. Compared with the prior art that conducts matching based on departments or positions, it is refined to matching based on professional skills, and can achieve more accurate talent cultivation. Further, during the teaching process, the present application uses the actual business tasks in the actual business scenario as the practical operation objects of the trainees, decomposes the tasks based on the actual business tasks, and distributes the tasks based on the matching degrees to avoid the practical operation objects of the trainees exceeding the capabilities of the trainees. Compared with the prior art that only conducts theoretical guidance or directly engages in practice, it improves the practice effect of practical operations and improves the accuracy and efficiency of talent cultivation. In summary, the present application solves the problem that the talent cultivation method in the prior art cannot be flexibly matched with the abilities of the trainees, resulting in deviation of the cultivation direction and decline of the cultivation efficiency, and high cultivation costs. Description of the Drawings

[0021] Figure 1 Shows the hardware structure block diagram of a mobile terminal for an employee training method based on the master-apprentice mechanism provided in an embodiment of the present application;

[0022] Figure 2 Shows the flowchart of an employee training method based on the master-apprentice mechanism provided in an embodiment of the present application;

[0023] Figure 3The block diagram of an employee training device based on a master-apprentice mechanism provided according to an embodiment of the present application is shown.

[0024] Among them, the above-mentioned drawings include the following reference numerals:

[0025] 102, processor; 104, memory; 106, transmission device; 108, input / output device. Detailed implementation manners

[0026] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0027] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so as to implement the embodiments of the present application described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] As introduced in the background art, in the prior art, it relies on manual matching and manual supervision, which is greatly affected by subjective factors and is difficult to ensure accuracy and standardization. To solve the problem that the methods in the prior art cannot be flexibly matched with the abilities of trainees, resulting in deviation of the training direction and decline in training efficiency, and thus higher training costs, the embodiments of the present application provide an employee training method, an employee training device, a computer-readable storage medium, and a human resource management system based on a master-apprentice mechanism.

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

[0031] The method embodiments provided in the embodiments of the present application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of a method for employee training based on a master-apprentice mechanism according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in Figure 1 processors 102 (the processors 102 may include, but are not limited to, processing devices such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown in Figure 1 is only schematic and does not limit the structure of the above mobile terminal. For example, the mobile terminal may further include more or fewer components than

[0032] shown in

[0033] Figure 1 shown, or have a different configuration from

[0032] shown.

[0033] The memory 104 can be used to store computer programs. For example, software programs and modules of application software, such as the computer program corresponding to the method for employee training based on the master-apprentice mechanism in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above method. The memory 104 may include a high-speed random access memory, and may further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories may be connected to the mobile terminal through a network. Examples of the above network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0033] In this embodiment, a method for employee training based on a master-apprentice mechanism running on a mobile terminal, a computer terminal, or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0034] Figure 2 It is a flowchart of a method for employee training based on a master-apprentice mechanism according to an embodiment of the present application. As Figure 2 shown, the method includes the following steps:

[0035] Step S201, obtain the skill matrices of each mentor from the employee skill assessment system to obtain M first skill matrices, and obtain N second skill matrices from the trainee onboarding training system for the skill matrices required by each trainee. The elements in the skill matrix at least include the level scores of business skills;

[0036] Specifically, this application obtains skill matrix data from two sources - the skill matrix of the mentor and the demand matrix of the trainee. Among them, the skill matrix of the mentor is obtained through the employee skill assessment system, including but not limited to multiple dimensions such as business skills, project experience, and soft power, and is presented in the form of level scores. The demand matrix of the trainee is automatically generated in the onboarding training system according to the job requirements and personal growth plan, and also covers multi-dimensional skill requirements.

[0037] In one example, the above first skill matrix can be S D ={S D1 ,S D2 ,…,S Dn}, where the elements respectively represent the level scores of the mentor in different skills. The above second skill matrix can be S L ={S L1 ,S L2 ,…,S Ln}, where the elements represent the improvement requirements of the trainee in the corresponding skills.

[0038] Step S202, calculate the matching degree between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees;

[0039] Specifically, this application calculates the first matching degree between the mentor and the trainee by using the method of weighted summation to reflect the difference between the mentor and the trainee.

[0040] In specific implementation, weights for different skills can also be set according to the importance of the skills in the core business requirements of the enterprise to further adjust the fitness.

[0041] Step S203: Allocate each trainee to the tutor corresponding to the maximum value of the M first matching degrees to obtain N first teaching plans.

[0042] Specifically, for the matching between trainees and tutors, this application proposes to follow the principle of minimizing skill differences, the principle of workload balance, and business priority. Among them, business priority is reflected by the above weights to ensure that tutors with specific skill specialties are preferentially matched. According to the principle of minimizing skill differences, tutors with skills closest to the growth direction of trainees are preferentially matched for allocation. According to the principle of workload balance, the situation where a single tutor has too many teaching tasks and it is difficult to take care of each trainee, resulting in a decline in tutor efficiency is avoided. For example, during the allocation process, if the number of trainees matched by a tutor reaches the first threshold, the tutor will no longer participate in the matching.

[0043] Step S204: Send teaching tasks to the trainee terminal and the tutor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainees during the teaching process to obtain the third skill matrix.

[0044] Specifically, after the matching relationship between the tutor and the trainee is established, the system will generate a personalized teaching plan, that is, the first teaching plan, and push it to the tutor terminal and the trainee terminal. Further, the system will also periodically obtain the real-time skill matrix of the trainees (the third skill matrix C = {C1, C2,..., C m}, where the elements can include level scores and problem-solving abilities, etc.). It can be understood that the above third skill matrix can be updated through the evaluation records of the trainees during the actual operation process to provide data support for the reasonable allocation of subsequent actual operation training tasks.

[0045] Step S205: Obtain the actual business tasks and decompose the actual business tasks into multiple subtasks. Respectively construct skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask.

[0046] Specifically, to ensure the close combination of learning and practice, this application decomposes the actual business tasks into multiple subtasks T = {T1, T2,..., T n}, where the elements can include skill requirements and difficulty levels, etc. Each subtask has a corresponding required skill matrix, and a skill compliance target is set for each subtask.

[0047] For example, for a cloud resource optimization project, it can be decomposed into subtask A (cloud architecture evaluation), subtask B (performance bottleneck analysis), and subtask C (security vulnerability detection), which respectively correspond to different business skill requirements.

[0048] Step S206: Calculate the matching degrees between each requirement skill matrix and each third skill matrix to obtain multiple second matching degrees. Send the subtasks corresponding to the maximum value of the second matching degree of each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtasks.

[0049] Specifically, the system calculates the second matching degree based on the requirement skill matrix of each subtask and the real-time skill matrix of the trainee. Similarly, based on the deviation between the requirement skills of the subtask and the current skills of the trainee, the subtask that best matches the current skills of the trainee is assigned to the trainee to ensure the effect of practical training. Further, the task completion degree is evaluated based on the task completion status after the trainee's practical operation.

[0050] Step S207: Adjust the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree, and send them to the trainee terminal and the tutor terminal.

[0051] Specifically, determine the current learning progress of the trainee based on the task completion degree. Further, based on the learning progress of the trainee, further optimize the above teaching tasks, and update the teaching tasks of the trainee terminal and the tutor terminal. For example, strengthen the training of the trainee in a certain skill, or provide more subtasks with a high matching degree to the trainee's skills. This adjustment mechanism ensures the dynamic consistency between the teaching plan and the actual needs and ability levels of the trainees, and improves the pertinence of teaching.

[0052] In a specific embodiment, the above actual business tasks can be obtained from a pre-constructed instance task library. The instance task library covers operation tasks in enterprise core business scenarios such as cloud resource management, service optimization, and performance tuning. It is divided into multi-level tasks according to the difficulty level, stored in the task library, and the operation objectives, skill requirements, and completion indicators of the tasks are marked, so as to be assigned to the corresponding trainees, guide the trainees to operate, and facilitate the subsequent evaluation of the completion degree of the trainees.

[0053] Through this embodiment, first, obtain the skill matrices of each tutor from the employee skill assessment system to obtain M first skill matrices, and obtain N second skill matrices of the skills required by each trainee from the trainee induction training system. The elements in the skill matrix at least include the level scores of business skills. Then, calculate the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one tutor corresponds to N first matching degrees. After that, assign each trainee to the tutor corresponding to the maximum value of the M first matching degrees to obtain N first teaching plans. After that, send teaching tasks to the trainee terminal and the tutor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix. After that, obtain the actual business tasks and decompose the actual business tasks into multiple subtasks, and construct skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask. After that, calculate the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, send the subtask corresponding to the maximum value of the second matching degrees of each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask. Finally, adjust the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree and send them to the trainee terminal and the tutor terminal. In this application, the abilities of the tutors and the abilities that the trainees need to learn are respectively represented by matrices, and the master-apprentice matching is guided by the matching degree between the matrices. Compared with the prior art that matches based on departments or positions, it is refined to match based on professional skills, and can achieve more accurate talent cultivation. Further, in the teaching process, this application uses the actual business tasks in the actual business scenario as the practical operation objects of the trainees, and decomposes the tasks based on the actual business tasks. The task assignment based on the matching degree avoids the practical operation objects of the trainees exceeding the capabilities of the trainees. Compared with the prior art that only provides theoretical guidance or directly engages in practice, it improves the practice effect, improves the accuracy and efficiency of talent cultivation. In summary, this application solves the problem that the talent cultivation method in the prior art cannot be flexibly matched with the abilities of the trainees, resulting in deviation of the cultivation direction and decline of the cultivation efficiency, leading to higher cultivation costs.

[0054] In an optional implementation manner, in order to calculate the above first matching degree, step S202 includes:

[0055] Step S2021, determine the importance weights of each business skill according to the enterprise development plan to obtain the first target weights;

[0056] Specifically, according to the above enterprise development plan, determine the importance weights of each business skill. For example, if the current development direction of the enterprise is to strengthen the CDN network optimization, then increase the weight of the skills related to CDN.

[0057] Step S2022, calculate the first matching degree according to the first skill matrix, the second skill matrix and the first target weight:

[0058]

[0059] where M is the first matching degree, n is the number of business skills in the first skill matrix and the second skill matrix, W i is the first target weight, and S i = |S Di - S Li | represents the difference value between the element S Di in the first skill matrix and the element S Li in the second skill matrix.

[0060] Specifically, S i = |S Di - S Li | represents the difference between the tutor and the trainee in the i-th skill.

[0061] Through the above embodiments, the matching degree between the tutor and the trainee at the skill level is presented in a quantitative form, realizing the precise docking of skill requirements and supply, and improving the training efficiency. By setting the upper limit of the number of trainees that a tutor can receive, the overconsumption of individual tutor resources is avoided, ensuring the fairness and sustainability of the master-apprentice mechanism.

[0062] In order to evaluate the learning progress of the trainee, in an alternative embodiment, the above step S206 includes:

[0063] Step S2061, determine the importance degree of each business skill in the demand skill matrix in the subtask, and obtain multiple second target weights;

[0064] Specifically, the weighted analysis of the importance degree of business skills in the subtask, that is, the "second target weight" (W j ), is used to balance the proportion of different skills in the task.

[0065] Step S2062, calculate the second matching degree according to the second target weight, the third skill matrix of the target trainee and the demand skill matrix:

[0066]

[0067] where M(T i , C) is the second matching degree between the subtask Ti and the trainee C, W j is the second target weight, is the j-th element in the demand skill matrix of the subtask Ti, and C j is the business skill j of the third skill matrix of the target trainee C, and m is the number of elements in the demand skill matrix;

[0068] Specifically, the deviation is calculated based on the business skills required by the subtasks and the current business skills of the trainee to determine the above-mentioned second matching degree.

[0069] Step S2063: Send the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, and receive the processed subtask uploaded by the trainee terminal. Determine the performance score based on the completion degree of the subtask.

[0070] Specifically, the subtask with the highest real-time skill matching degree with the trainee is assigned to the trainee. After the trainee completes the subtask, the result needs to be uploaded, and the system gives a "performance score" based on the completion of the subtask. This score reflects the trainee's comprehensive operation ability in the subtask.

[0071] Step S2064: Determine the third target weight according to the importance of the subtask in the actual business task.

[0072] Specifically, a weighted analysis is performed on the importance of the subtask in the actual business task, that is, the above-mentioned third target weight.

[0073] Step S2065: Calculate the task completion degree according to the third target weight and the performance score.

[0074]

[0075] Where P is the task completion degree, z is the number of actual business tasks, Q k The third target weight of the subtask assigned to the trainee terminal in the kth actual business task, D k Is the performance score of the subtask assigned to the trainee terminal in the kth actual business task.

[0076] Specifically, a weighted calculation and aggregation are performed on the performance score based on the weight to reflect a scientific evaluation of the overall training effect of the trainee. The task completion degree not only reflects the trainee's specific performance in the subtask but also considers the importance of the task to the business, thus obtaining a more comprehensive and objective evaluation result.

[0077] Through the above embodiments, through the precise allocation of subtasks, trainees can concentrate on improving the skills most relevant to the actual business, significantly accelerating the growth of their cloud operation and maintenance capabilities. The calculation of the task completion degree makes the training effect quantifiable and comparable, helping the company's management better understand the learning progress of trainees and providing data support for the optimization of the training plan. The subtask allocation mechanism ensures the effective use of each tutor's guidance time, avoids the situation of over-guidance or under-guidance, and realizes the optimal allocation of human resources.

[0078] In order to evaluate the specific business skill mastery of the trainees, in an alternative implementation, after sending the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, the above method further includes:

[0079] Step S301: Receive the processed subtask, generate a target instruction based on the processed subtask, and send it to the tutor terminal. The target instruction is used to instruct the tutor to score the business skills used by the trainee in the subtask according to the completion status of the subtask.

[0080] Specifically, after the trainee completes the subtask and uploads the result, the system immediately generates a target instruction and sends it to the tutor terminal. The above target instruction contains the business skill information specifically used by the trainee in the subtask, and requires the tutor to score according to the performance of the trainee.

[0081] Step S302: Receive the score uploaded by the tutor terminal to obtain the mastery progress score of each business skill of the trainee.

[0082] Specifically, after receiving the target instruction, the tutor scores the business skills demonstrated by the trainee based on the trainee's actual operations, problem-solving abilities, innovative thinking, etc. in the subtask. The scoring criteria need to be refined to ensure that different skill points can be comprehensively evaluated. The tutor terminal uploads the scoring data to the system to obtain the above mastery progress score.

[0083] Through the above embodiments, the real-time upload and analysis of the scoring data provide a clear employee skill growth path for the management, facilitating timely adjustment of human resource allocation to ensure that key businesses have sufficient skill support. The tutor scoring mechanism enables the system to accurately understand the mastery of each business skill by the trainees, thereby formulating a more personalized subsequent training plan for each trainee, such as strengthening theoretical learning and practical training in a certain aspect.

[0084] In order to achieve the dynamic optimization of teaching tasks, in an alternative implementation, the above step S207 includes:

[0085] Step S2071: Obtain all the task completion degrees corresponding to the trainee terminal before the current moment, and obtain the fourth target weight according to the importance of the actual business tasks corresponding to each task completion degree in the project to which they belong.

[0086] Step S2072: Calculate the learning progress score of the trainee terminal according to the task completion degree and the fourth target weight:

[0087]

[0088] where P t is the learning progress score, w o is the fourth target weight corresponding to the 0th actual business task, Po is the task completion rate corresponding to the o-th actual business task;

[0089] Specifically, each time after the trainee finishes a learning activity, the system automatically obtains the trainee's previous task completion rate, calculates the trainee's comprehensive performance according to the above formula, and obtains the learning progress score.

[0090] Step S2073: Obtain all the mastery progress scores corresponding to the trainee terminal before the current moment, and obtain the fifth target weight according to the importance of the subtasks corresponding to each mastery progress score among all the subtasks related to the corresponding business skills;

[0091] Step S2074: Calculate the skill proficiency score of the trainee terminal according to the mastery progress score and the fifth target weight:

[0092]

[0093] where, R f is the skill proficiency score corresponding to skill f, g is the number of subtasks, T h,f is the fifth target weight of subtask h relative to business skill f, F h,f is the mastery progress score of business skill f in subtask h;

[0094] Similarly, each time after the trainee finishes a learning activity, the system automatically obtains the trainee's previous mastery progress score, and calculates the trainee's skill proficiency according to the above formula to obtain the above skill proficiency score.

[0095] Step S2075: Obtain the number of subtasks completed by the trainee and the total number of subtasks before the current moment, and obtain the first target number and the second target number;

[0096] Step S2076: Calculate the task completion rate according to the first target number and the second target number;

[0097] Specifically, present the ratio of the tasks completed by the trainee to the total tasks in percentage:

[0098]

[0099] where, C is the task completion rate; N c is the number of completed tasks (the first target number); N t is the total number of tasks (the second target number).

[0100] Step S2077: Adjust the overall period of the first teaching plan based on the learning progress score, adjust the teaching task proportion of each business skill in the first teaching plan based on the skill proficiency score, and adjust the remaining period of the first teaching plan based on the task completion rate.

[0101] Specifically, by comparing the current learning progress score of the trainee with the expected learning progress score, when the former is higher, the overall cycle of the first teaching plan can be shortened so that the trainee can engage in practice as soon as possible. Conversely, when the former is lower, the overall cycle of the first teaching plan can be extended to ensure that the trainee can meet the requirements of practical application after completing the learning.

[0102] Similarly, if the skill proficiency score of a certain skill of the trainee is compared with the expected learning progress score, when the former is higher, the practice of this business skill in subsequent learning can be reduced, and other business skills below the expectation can be arranged. Conversely, relevant tasks or courses can be arranged for the skills below the expectation to enhance the skills.

[0103] Similarly, if the task completion degree of the trainee is lower than expected, a course needs to be added to teach the trainee a plan to improve efficiency.

[0104] In order to achieve the dynamic adjustment of the master-apprentice relationship, in an optional implementation manner, after adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, the above method further includes:

[0105] Step S401: Calculate the matching degree based on the third skill matrix and the corresponding second skill matrix to obtain the third matching degree, and determine the completion degree of the first teaching plan based on the interval where the third matching degree is located;

[0106] Specifically, by comparing the real-time skill matrix (the third skill matrix) after the trainee completes the subtasks with the initially set teaching goal (the second skill matrix), the third matching degree is calculated. This matching degree reflects the difference between the trainee's skill growth and the expected goal. By setting different matching degree intervals, the system can quantitatively evaluate the completion degree of the first teaching plan.

[0107] Step S402: Every time the completion degree increases by a preset value, determine the task completion quality of the trainee according to the completion status of the actual business task, determine the problem-solving efficiency according to the response speed of the tutor to the trainee's questions, and determine the business contribution degree according to the proportion of the actual business tasks completed by the trainee under the guidance of the tutor in the project;

[0108] Step S403: Perform weighted calculation according to the task completion quality, problem-solving efficiency and business contribution degree to obtain the comprehensive teaching score;

[0109] Specifically, the comprehensive teaching score is obtained by weighted calculation of the task completion quality of the trainee, the problem-solving efficiency of the tutor and the business contribution degree. Specifically, the task completion quality reflects the performance of the trainee in the actual business task, the problem-solving efficiency examines the tutor's ability to quickly respond to the trainee's questions, and the business contribution degree measures the actual output value of the master-apprentice in the project.

[0110] Step S404, when the comprehensive teaching score is greater than the second threshold, keep the first teaching plan unchanged;

[0111] Step S405, when the comprehensive teaching score is less than or equal to the second threshold, recalculate the matching degree according to the third skill matrix at the current moment and each first skill matrix to obtain the fourth matching degree;

[0112] Specifically, based on the above evaluation, if the comprehensive teaching score exceeds the second threshold, the system determines that the teaching plan is effective and does not need to be adjusted; otherwise, if the score is lower than the second threshold, it triggers a re-evaluation and adjustment of the teaching plan. Recalculate the matching degree based on the third skill matrix at the current moment and the first skill matrices of all tutors to obtain the fourth matching degree.

[0113] Step S406, allocate the students with a comprehensive teaching score less than the second threshold to the tutor corresponding to the second skill matrix with the maximum fourth matching degree to obtain the second teaching plan.

[0114] Specifically, the above process aims to find a tutor who is more compatible with the current skill level of the student in order to optimize the teaching plan. The system assigns a new tutor to the student according to the calculation result of the fourth matching degree to form the second teaching plan, expecting that under the new mentoring relationship, the student can more efficiently improve the required skills while enhancing the tutor's ability to meet the individual needs of the students.

[0115] Through the above embodiments, by introducing a dynamic evaluation and adjustment mechanism, the efficiency and effectiveness of the mentoring mechanism are significantly improved. This teaching plan adjustment mechanism based on real-time data and dynamic evaluation can not only accelerate the skill growth of employees, but also more accurately match the business needs of the enterprise, which is an important tool for modern enterprise human resource management.

[0116] In order to plan the development direction of the students, in an alternative embodiment, after adjusting the teaching tasks of the sub-tasks required for the business skills in the first teaching plan based on the task completion degree and sending them to the student terminal and the tutor terminal, the above method further includes:

[0117] Step S501, when the first teaching plan is completed, calculate the ability evaluation score according to the grade scores of all elements in the third skill matrix at the current moment;

[0118] Specifically, after the student completes a series of sub-tasks, the system calculates an ability evaluation score according to the grade scores of all elements in its third skill matrix. This score reflects the comprehensive ability level of the student in key skills such as cloud computing, network optimization, and data storage.

[0119] Step S502, determine the student's skill interest tendency according to the third skill matrix at the current moment;

[0120] Specifically, the system further analyzes the third skill matrix to identify the skill areas in which the trainee shows a high level of interest.

[0121] In a specific implementation, the skill interest tendency of the trainee is determined according to the level scores corresponding to all elements in the second skill matrix at the current moment, including:

[0122] Calculate the matching degree between the third skill matrix and each preset skill matrix to obtain the fifth matching degree. The preset skill matrix corresponds to a technical field one by one;

[0123] Determine the technical field corresponding to the maximum value of the fifth matching degree as the interest tendency.

[0124] Specifically, the system calculates the matching degree with multiple preset skill matrices according to the third skill matrix at the current moment to obtain the fifth matching degree. These preset skill matrices cover various technical fields required by the enterprise, such as cloud computing, network optimization, data storage, etc. The fifth matching degree reflects the degree of fit between the employee's skills and the requirements of a specific technical field. The system determines the technical field corresponding to the maximum value of the fifth matching degree as the skill interest tendency of the trainee.

[0125] Step S503: Decompose the enterprise development plan into multiple development sub-plans according to the development direction, and calculate the matching degree according to each development sub-plan and the skill interest tendency to obtain the demand matching degree;

[0126] Specifically, decompose the enterprise development plan, such as the business expansion goal, technological innovation direction, etc., into multiple development sub-plans. Each sub-plan has its specific skill requirements and goals. The system calculates a series of demand matching degrees according to the skills required by each development sub-plan and the trainee's skill interest tendency. This matching degree reflects the degree of fit between the trainee's interest preference and the enterprise's needs.

[0127] In a specific implementation, decompose the enterprise development plan into multiple development sub-plans according to the development direction, and calculate the matching degree according to each development sub-plan and the skill interest tendency to obtain the demand matching degree, including:

[0128] Determine the required vocational skills based on the development sub-plan, and construct a fourth skill matrix according to the vocational skills;

[0129] Calculate the matching degree between the fourth skill matrix and the preset skill matrix to obtain the demand matching degree.

[0130] Specifically, the enterprise first divides the overall development blueprint into multiple specific development sub-plans according to its strategic plan. For example, the development plan for cloud services is decomposed into sub-plans such as cloud architecture upgrade, CDN optimization, and cloud security enhancement. The system determines the required business skills based on each development sub-plan and constructs a fourth skill matrix related to the sub-plan. The fourth skill matrix includes the key skills required to complete each sub-plan and their importance, and then calculates the matching degree, which can reflect the degree of fit between employees' interests and the enterprise's development direction.

[0131] Step S504: Calculate the matching degree based on the third skill matrix and each development sub-plan to obtain the ability matching degree.

[0132] Specifically, at the same time, the system also calculates the ability matching degree based on the third skill matrix of the trainees and the skills required for each development sub-plan. This matching degree quantifies the gap between the trainees' current skills and the enterprise's planned skill requirements.

[0133] In specific implementation, calculating the matching degree based on the third skill matrix and each development sub-plan to obtain the ability matching degree includes:

[0134] Calculate the matching degree between the third skill matrix and the fourth skill matrix to obtain the ability matching degree.

[0135] Step S505: Perform weighted calculations on the ability assessment scores respectively with each demand matching degree and the corresponding ability matching degree to obtain multiple career matching degrees. Determine the development direction corresponding to the development sub-plan with the maximum career matching degree as the target career development direction, and send the target career development direction to the trainee terminal.

[0136] Specifically, the system performs weighted calculations on the ability assessment scores, the demand matching degrees, and the ability matching degrees to obtain multiple career matching degrees. The weight setting is adjusted according to the enterprise's strategic needs, ensuring the flexibility and adaptability of the plan. Finally, the system selects the development sub-plan corresponding to the maximum career matching degree and determines it as the trainee's target career development direction. This direction will be informed to the trainee through the trainee terminal, providing clear guidance for subsequent career development.

[0137] Through the above embodiments, by identifying the skill interest tendency, it is ensured that employees find the best balance between personal interests and enterprise needs, improving the training effect and employee satisfaction. Specific career development suggestions are generated for each employee to help employees clarify their future career goals, and at the same time provide a basis for the enterprise's human resource planning. Based on the matching degree calculation of the enterprise's strategic plan and development sub-plans, the close coupling of personal growth and the enterprise's strategic goals is achieved, ensuring the effectiveness and forward-looking of human resource planning. The career path planning is based on data and algorithms rather than subjective judgments, making the decision-making process more objective and scientific, and improving the efficiency and effect of human resource management.

[0138] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0139] The embodiment of the present application also provides an employee training device based on the master-apprentice mechanism. It should be noted that the employee training device based on the master-apprentice mechanism in the embodiment of the present application can be used to execute the employee training method based on the master-apprentice mechanism provided by the embodiment of the present application. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0140] The following introduces the employee training device based on the master-apprentice mechanism provided by the embodiment of the present application.

[0141] Figure 3 is a structural block diagram of the employee training device based on the master-apprentice mechanism according to the embodiment of the present application. As Figure 3 shown, the device includes:

[0142] A first acquisition unit 10, configured to obtain the skill matrices of each mentor from the employee skill assessment system to obtain M first skill matrices, and obtain N second skill matrices of the skill requirements of each trainee from the trainee induction training system. The elements in the skill matrix at least include the grade scores of business skills;

[0143] A first calculation unit 20, configured to calculate the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees;

[0144] A first matching unit 30, configured to assign each trainee to the mentor corresponding to the maximum value of the corresponding M first matching degrees to obtain N first teaching plans;

[0145] A second acquisition unit 40, configured to send teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainee during the teaching process to obtain a third skill matrix;

[0146] A third acquisition unit 50, configured to obtain actual business tasks and decompose the actual business tasks into multiple subtasks, and respectively construct skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask;

[0147] A second computing unit 60, configured to calculate the matching degrees between each demand skill matrix and each third skill matrix, obtain a plurality of second matching degrees, send the subtasks corresponding to the maximum value of the second matching degree of each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtasks;

[0148] A first sending unit 70, configured to adjust the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree, and send them to the trainee terminal and the tutor terminal.

[0149] Specifically, the current learning progress of the trainee is determined based on the task completion degree. Further, based on the learning progress of the trainee, the above teaching tasks are further optimized, and the teaching tasks of the trainee terminal and the tutor terminal are updated. For example, the training of a certain skill of the trainee is strengthened, or more subtasks with a high matching degree with the skills of the trainee are provided. This adjustment mechanism ensures the dynamic consistency between the teaching plan and the actual needs and ability levels of the trainees, and improves the pertinence of teaching.

[0150] In a specific embodiment, the above actual business tasks can be obtained from a pre-constructed instance task library, which covers operation tasks in enterprise core business scenarios such as cloud resource management, service optimization, and performance tuning, and are divided into multi-level tasks according to the difficulty level, stored in the task library, and the operation objectives, skill requirements, and completion indicators of the tasks are marked, so as to be assigned to the corresponding trainees to guide the trainees to operate and facilitate the subsequent evaluation of the completion degree of the trainees.

[0151] Through this embodiment, the first acquisition unit obtains the skill matrices of each tutor from the employee skill assessment system, obtaining M first skill matrices, and obtains the skill matrices required by each trainee from the trainee induction training system, obtaining N second skill matrices. The elements in the skill matrix at least include the level scores of business skills; the first calculation unit calculates the matching degrees between each first skill matrix and each second skill matrix, obtaining M*N first matching degrees. One trainee corresponds to M first matching degrees, and one tutor corresponds to N first matching degrees; the first matching unit assigns each trainee to the tutor corresponding to the maximum value of the corresponding M first matching degrees, obtaining N first teaching plans; the second acquisition unit sends teaching tasks to the trainee terminal and the tutor terminal according to the first teaching plan, and periodically obtains the real-time skill matrix of the trainee during the teaching process, obtaining the third skill matrix; the third acquisition unit obtains the actual business tasks and decomposes the actual business tasks into multiple subtasks, constructs skill matrices according to the business skills required by each subtask respectively, obtaining the required skill matrices corresponding to each subtask; the second calculation unit calculates the matching degrees between each required skill matrix and each third skill matrix, obtaining multiple second matching degrees, sends the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determines the task completion degree according to the completion situation of the subtask; the first sending unit adjusts the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree, and sends them to the trainee terminal and the tutor terminal. In this application, the abilities of the tutors and the abilities that the trainees need to learn are respectively represented by matrices, and the master-apprentice matching is guided by the matching degree between the matrices. Compared with the prior art that matches based on departments or positions, it is refined to match based on professional skills, and can achieve more accurate talent cultivation. Further, during the teaching process, this application uses the actual business tasks in the actual business scenario as the practical operation objects of the trainees, and decomposes the tasks based on the actual business tasks. The task assignment based on the matching degree avoids the practical operation objects of the trainees exceeding the abilities of the trainees. Compared with the prior art that only conducts theoretical guidance or directly invests in practice, it improves the practice effect of the practical operation and improves the accuracy and efficiency of talent cultivation. In summary, this application solves the problem that the talent cultivation method in the prior art cannot be flexibly matched with the abilities of the trainees, resulting in deviation of the cultivation direction and decline of the cultivation efficiency, and leading to higher cultivation costs.

[0152] In an alternative embodiment, in order to calculate the above first matching degree, the above first calculation unit includes:

[0153] The first determination module is used to determine the importance weights of each business skill according to the enterprise development plan, obtaining the first target weights;

[0154] The first calculation module is used to calculate the first matching degree according to the first skill matrix, the second skill matrix and the first target weights:

[0155]

[0156] Among them, M is the first matching degree, n is the number of business skills in the first skill matrix and the second skill matrix, and W i is the first target weight, and S i = |S Di - S Li | represents the difference value between the element S Di in the first skill matrix and the element S Li in the second skill matrix.

[0157] In order to evaluate the learning progress of the trainees, in an optional implementation manner, the above-mentioned second calculation unit includes:

[0158] A second determination module, configured to determine the importance degree of each business skill in the required skill matrix in the subtask, and obtain a plurality of second target weights;

[0159] A second calculation module, configured to calculate a second matching degree according to the second target weight, the third skill matrix of the target trainee, and the required skill matrix:

[0160]

[0161] Among them, M(T i , C) is the second matching degree between the subtask Ti and the trainee C, W j is the second target weight, is the j-th element in the required skill matrix of the subtask Ti, and C j is the business skill j of the third skill matrix of the target trainee C, and m is the number of elements in the required skill matrix;

[0162] A first sending module, configured to send the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, and receive the processed subtask uploaded by the trainee terminal, and determine a performance score based on the completion degree of the subtask;

[0163] A third determination module, configured to determine a third target weight according to the importance degree of the subtask in the actual business task;

[0164] A third calculation module, configured to calculate a task completion degree according to the third target weight and the performance score;

[0165]

[0166] Among them, P is the task completion degree, z is the number of actual business tasks, Q k is the third target weight of the subtask assigned to the trainee terminal in the k-th actual business task, and D k is the performance score of the subtask assigned to the trainee terminal in the k-th actual business task.

[0167] In an alternative implementation, to evaluate the specific business skill mastery of trainees, the above device further includes:

[0168] A second sending unit, configured to, after sending the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, receive the processed subtask, generate a target instruction according to the processed subtask, and send the target instruction to the tutor terminal, where the target instruction is used to instruct the tutor to score the business skills used by the trainee in the subtask according to the completion status of the subtask;

[0169] A fourth obtaining unit, configured to receive the scores uploaded by the tutor terminal to obtain the mastery progress scores of each business skill of the trainee.

[0170] In an alternative implementation, to achieve dynamic optimization of teaching tasks, the above first sending unit includes:

[0171] A first obtaining module, configured to obtain all task completion degrees corresponding to the trainee terminal before the current moment, and obtain a fourth target weight according to the importance of the actual business tasks corresponding to each task completion degree in the project to which they belong;

[0172] A fourth calculation module, configured to calculate the learning progress score of the trainee terminal according to the task completion degree and the fourth target weight:

[0173]

[0174] where P t is the learning progress score, w o is the fourth target weight corresponding to the 0th actual business task, and P o is the task completion degree corresponding to the oth actual business task;

[0175] A second obtaining module, configured to obtain all mastery progress scores corresponding to the trainee terminal before the current moment, and obtain a fifth target weight according to the importance of the subtasks corresponding to each mastery progress score among all subtasks related to the corresponding business skill;

[0176] A fifth calculation module, configured to calculate the skill proficiency score of the trainee terminal according to the mastery progress score and the fifth target weight:

[0177]

[0178] where R f is the skill proficiency score corresponding to skill f, g is the number of subtasks, T h,f is the fifth target weight of subtask h relative to business skill f, and F h,f is the mastery progress score of business skill f in subtask h;

[0179] A third acquisition module, configured to acquire the number of subtasks completed by a trainee before the current moment and the total number of subtasks, to obtain a first target number and a second target number;

[0180] A sixth calculation module, configured to calculate a task completion rate according to the first target number and the second target number;

[0181] A processing module, configured to adjust the overall period of the first teaching plan based on the learning progress score, adjust the teaching task proportion of each business skill in the first teaching plan based on the skill proficiency score, and adjust the remaining period of the first teaching plan based on the task completion degree.

[0182] To achieve dynamic adjustment of the master-apprentice relationship, in an alternative implementation, the above device further includes:

[0183] A third calculation unit, configured to, after adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, calculate a matching degree based on the third skill matrix and the corresponding second skill matrix, to obtain a third matching degree, and determine the completion degree of the first teaching plan based on the interval where the third matching degree is located;

[0184] A first determination unit, configured to, for each increase of a preset value in the completion degree, determine the task completion quality of the trainee according to the completion status of the actual business task, determine the problem-solving efficiency according to the response speed of the tutor to the trainee's questions, and determine the business contribution degree according to the proportion of the actual business tasks completed by the trainee under the guidance of the tutor in the project;

[0185] A fourth calculation unit, configured to perform weighted calculation according to the task completion quality, the problem-solving efficiency, and the business contribution degree, to obtain a comprehensive teaching score;

[0186] A first processing unit, configured to, when the comprehensive teaching score is greater than a second threshold, keep the first teaching plan unchanged;

[0187] A second processing unit, configured to, when the comprehensive teaching score is less than or equal to the second threshold, recalculate the matching degree according to the third skill matrix at the current moment and each first skill matrix, to obtain a fourth matching degree;

[0188] A third sending unit, configured to allocate the trainees with a comprehensive teaching score less than the second threshold to the tutor corresponding to the second skill matrix with the maximum fourth matching degree, to obtain a second teaching plan.

[0189] To plan the development direction of the trainee, in an alternative implementation, the above device further includes:

[0190] A fifth computing unit, configured to, after adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, calculate an ability evaluation score according to the grade scores of all elements in the third skill matrix at the current moment when the first teaching plan is completed;

[0191] A second determination unit, configured to determine the skill interest tendency of the trainee according to the third skill matrix at the current moment;

[0192] A sixth computing unit, configured to decompose the enterprise development plan into multiple development sub-plans according to the development direction, calculate the matching degree according to each development sub-plan and the skill interest tendency, and obtain the demand matching degree;

[0193] A seventh computing unit, configured to calculate the matching degree according to the third skill matrix and each development sub-plan, and obtain the ability matching degree;

[0194] A third determination unit, configured to perform weighted calculation on the ability evaluation score respectively with each demand matching degree and the corresponding ability matching degree to obtain multiple career matching degrees, determine the development direction corresponding to the development sub-plan with the maximum career matching degree as the target career development direction, and send the target career development direction to the trainee terminal.

[0195] The above-mentioned employee training device based on the master-apprentice mechanism includes a processor and a memory. The above-mentioned first acquisition unit, first calculation unit, first matching unit, second acquisition unit, third acquisition unit, fourth calculation unit, and first sending unit, etc. are all stored in the memory as program units, and the corresponding functions are implemented by the processor executing the above program units stored in the memory. The above modules are all located in the same processor; alternatively, the above-mentioned each module is located in different processors in any combination form.

[0196] The processor contains a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the efficiency of talent cultivation can be improved by adjusting the kernel parameters.

[0197] The memory may include non-permanent memory in the computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one storage chip.

[0198] An embodiment of the present invention provides a computer-readable storage medium, and the above-mentioned computer-readable storage medium includes a stored program, wherein when the above-mentioned program runs, it controls the device where the above-mentioned computer-readable storage medium is located to execute the above-mentioned employee training method based on the master-apprentice mechanism.

[0199] An embodiment of the present invention provides a processor, which is used to run a program. When the program runs, it executes the employee training method based on the master-apprentice mechanism.

[0200] An embodiment of the present invention provides a human resource management system. The human resource management system includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps of at least the employee training method based on the master-apprentice mechanism.

[0201] The present application also provides a computer program product, which is suitable for executing a program initialized with the steps of at least the employee training method based on the master-apprentice mechanism when executed on a data processing device.

[0202] Obviously, those skilled in the art should understand that the various modules or steps of the above-mentioned present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. They can be implemented by program code executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately made into individual integrated circuit modules, or multiple modules or steps among them can be made into a single integrated circuit module to implement. In this way, the present invention is not limited to any specific combination of hardware and software.

[0203] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present 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 memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0204] The present 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 the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, 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 functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0205] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes and / or boxes Figure 1 of one or more of the processes and / or boxes Figure 1 specified in the flowchart.

[0206] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes and / or boxes Figure 1 of one or more of the processes and / or boxes Figure 1 specified in the flowchart.

[0207] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0208] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory. Memory is an example of computer-readable media.

[0209] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0210] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0211] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0212] 1) The employee training method based on the master-apprentice mechanism of the present application first obtains the skill matrices of each mentor from the employee skill assessment system to obtain M first skill matrices, and obtains the skill matrices required by each trainee from the trainee induction training system to obtain N second skill matrices. The elements in the skill matrix at least include the level scores of business skills. Then, calculate the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees. After that, allocate each trainee to the mentor corresponding to the maximum value of the M first matching degrees to obtain N first teaching plans. After that, send teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix. After that, obtain the actual business tasks and decompose the actual business tasks into multiple subtasks, and construct skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask. After that, calculate the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, send the subtask corresponding to the maximum value of the second matching degrees of each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask. Finally, adjust the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree, and send them to the trainee terminal and the mentor terminal. In the present application, the abilities of the mentors and the abilities that the trainees need to learn are respectively represented by matrices, and the master-apprentice matching is guided by the matching degree between the matrices. Compared with the prior art that matches based on departments or positions, it is refined to match based on professional skills, and can achieve more accurate talent cultivation. Further, in the teaching process, the present application uses the actual business tasks in the actual business scenario as the practical operation objects of the trainees, and decomposes the tasks based on the actual business tasks. The task allocation based on the matching degree avoids the practical operation objects of the trainees exceeding the abilities of the trainees. Compared with the prior art that only provides theoretical guidance or directly engages in practical work, it improves the practice effect of practical operations and improves the accuracy and efficiency of talent cultivation. In summary, the present application solves the problem that the talent cultivation method in the prior art cannot be flexibly matched with the abilities of the trainees, resulting in deviation of the cultivation direction and decline of the cultivation efficiency, and high cultivation costs.

[0213] 2) The employee training device based on the master-apprentice mechanism of the present application. The first acquisition unit obtains the skill matrices of each mentor from the employee skill evaluation system to obtain M first skill matrices, and obtains the skill matrices required by each trainee from the trainee induction training system to obtain N second skill matrices. The elements in the skill matrix at least include the level scores of business skills. The first calculation unit calculates the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one mentor corresponds to N first matching degrees. The first matching unit assigns each trainee to the mentor corresponding to the maximum value of the corresponding M first matching degrees to obtain N first teaching plans. The second acquisition unit sends teaching tasks to the trainee terminal and the mentor terminal according to the first teaching plan, and periodically obtains the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix. The third acquisition unit obtains the actual business tasks and decomposes the actual business tasks into multiple subtasks, and constructs skill matrices according to the business skills required by each subtask to obtain the required skill matrices corresponding to each subtask. The second calculation unit calculates the matching degrees between each required skill matrix and each third skill matrix to obtain multiple second matching degrees, sends the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determines the task completion degree according to the completion situation of the subtask. The first sending unit adjusts the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree and sends them to the trainee terminal and the mentor terminal. In the present application, the abilities of the mentors and the abilities that the trainees need to learn are respectively represented by matrices, and the master-apprentice matching is guided by the matching degree between the matrices. Compared with the prior art that matches based on departments or positions, it is refined to match based on professional skills, and can achieve more accurate talent cultivation. Further, during the teaching process, the present application uses the actual business tasks in the actual business scenario as the practical operation objects of the trainees, and decomposes the tasks based on the actual business tasks. The task assignment based on the matching degree avoids the practical operation objects of the trainees exceeding the capabilities of the trainees. Compared with the prior art that only conducts theoretical guidance or directly invests in practice, it improves the practice effect of practical operation and improves the accuracy and efficiency of talent cultivation. In summary, the present application solves the problem that the talent cultivation method in the prior art cannot be flexibly matched with the capabilities of the trainees, resulting in deviation of the cultivation direction and decline of the cultivation efficiency, and high cultivation costs.

[0214] The above are only the preferred embodiments of the present application and are not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An employee training method based on a master-apprentice mechanism, characterized in that, including: Obtain the skill matrices of each tutor from the employee skill assessment system to get M first skill matrices, and obtain the skill matrices required by each trainee from the trainee induction training system to get N second skill matrices. The elements in the skill matrix at least include the level scores of business skills. Calculate the matching degrees between each of the first skill matrices and each of the second skill matrices to obtain M*N first matching degrees. One trainee corresponds to M of the first matching degrees, and one tutor corresponds to N of the first matching degrees. Assign each of the trainees to the tutor corresponding to the maximum value of the M first matching degrees to obtain N first teaching plans. Send teaching tasks to the trainee terminal and the tutor terminal according to the first teaching plan, and periodically obtain the real-time skill matrix of the trainee during the teaching process to get the third skill matrix. Obtain the actual business tasks and decompose the actual business tasks into multiple subtasks. Construct the skill matrix according to the business skills required by each of the subtasks to obtain the required skill matrices corresponding to each of the subtasks. Calculate the matching degrees between each of the required skill matrices and each of the third skill matrices to obtain multiple second matching degrees. Send the subtask corresponding to the maximum value of the second matching degrees for each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask. Adjust the teaching tasks of the business skills required by the subtasks in the first teaching plan based on the task completion degree and send them to the trainee terminal and the tutor terminal.

2. The method according to claim 1, wherein Calculate the matching degrees between each of the first skill matrices and each of the second skill matrices to obtain M*N first matching degrees, including: Determine the importance weights of each of the business skills according to the enterprise development plan to obtain the first target weights. Calculate the first matching degree according to the first skill matrix, the second skill matrix, and the first target weights. Wherein, M is the first matching degree, n is the number of the business skills in the first skill matrix and the second skill matrix, W i is the first target weight, S i = |S Di - S Li | represents the difference value between the element S Di in the first skill matrix and the element S Li in the second skill matrix.

3. The method according to claim 1, wherein Calculate the matching degrees between each of the required skill matrices and each of the third skill matrices to obtain multiple second matching degrees. Send the subtask corresponding to the maximum value of the second matching degrees for each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask, including: Determine the importance levels of each of the business skills in the required skill matrix in the subtask to obtain multiple second target weights. Calculate the second matching degree according to the second target weights, the third skill matrix of the target trainee, and the required skill matrix. where M(T i , C) is the second matching degree between the subtask Ti and the trainee C, W j is the second target weight, R Tij is the j-th element in the required skill matrix of the subtask Ti, C j is the business skill j of the third skill matrix of the target trainee C, and m is the number of elements in the required skill matrix; Send the subtask corresponding to the maximum value of the second matching degree to the trainee terminal, and receive the processed subtask uploaded by the trainee terminal. Determine the performance score based on the completion degree of the subtask. Determine the third target weights according to the importance level of the subtask in the actual business task. Calculate the task completion degree according to the third target weights and the performance score. Among them, P is the task completion degree, z is the number of the actual business tasks, and Q k is the third target weight of the subtask assigned to the trainee terminal in the k-th actual business task, D k is the performance score of the subtask assigned to the trainee terminal in the k-th actual business task.

4. The method according to claim 2, wherein After sending the subtask corresponding to the maximum value of the second matching degrees for each trainee to each trainee terminal, the method further includes: Receive the processed subtasks, generate a target instruction based on the processed subtasks and send it to the tutor terminal, where the target instruction is used to instruct the tutor to score the business skills used by the trainee in the subtask according to the completion status of the subtask; Receive the scores uploaded by the tutor terminal to obtain the proficiency scores of the trainee's various business skills.

5. The method according to claim 4, characterized in that, Adjust the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree, including: Obtain all the task completion degrees corresponding to the trainee terminal before the current moment, and obtain the fourth target weight according to the importance of the actual business tasks corresponding to each task completion degree in the project; calculate the learning progress score of the trainee terminal according to the task completion degree and the fourth target weight: Among them, P t is the learning progress score, w o is the fourth target weight corresponding to the 0th actual business task, P o is the task completion degree corresponding to the oth actual business task; Obtain all the proficiency scores corresponding to the trainee terminal before the current moment, and obtain the fifth target weight according to the importance of the subtasks corresponding to each proficiency score among all the subtasks involving the corresponding business skills; Calculate the skill proficiency score of the trainee terminal according to the proficiency score and the fifth target weight; Among them, R f is the skill proficiency score corresponding to skill f, g is the number of the subtasks, T h,f is the fifth target weight of subtask h relative to the business skill f, F h,f is the mastery progress score of the business skill f in subtask h; Obtain the number of completed subtasks and the total number of subtasks of the trainee before the current moment to obtain the first target number and the second target number; Calculate the task completion rate according to the first target number and the second target number; Adjust the overall cycle of the first teaching plan based on the learning progress score, adjust the teaching task proportion of each business skill in the first teaching plan based on the skill proficiency score, and adjust the remaining cycle of the first teaching plan based on the task completion degree.

6. The method according to claim 1, wherein After adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, the method further includes: Calculate the matching degree based on the third skill matrix and the corresponding second skill matrix to obtain the third matching degree, and determine the completion degree of the first teaching plan based on the interval where the third matching degree is located; Every time the completion degree increases by a preset value, determine the task completion quality of the trainee according to the completion status of the actual business task, determine the problem-solving efficiency according to the tutor's response speed to the trainee's questions, and determine the business contribution degree according to the proportion of the actual business tasks completed by the trainee under the tutor's guidance in the project; Perform weighted calculation according to the task completion quality, the problem-solving efficiency and the business contribution degree to obtain the comprehensive teaching score; When the comprehensive teaching score is greater than the second threshold, keep the first teaching plan unchanged; When the comprehensive teaching score is less than or equal to the second threshold, recalculate the matching degree according to the third skill matrix at the current moment and each first skill matrix to obtain the fourth matching degree; Assign the trainees with the comprehensive teaching score less than the second threshold to the tutor corresponding to the second skill matrix with the maximum fourth matching degree to obtain the second teaching plan.

7. The method according to claim 5, characterized in that, After adjusting the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and sending them to the trainee terminal and the tutor terminal, the method further includes: When the first teaching plan is completed, calculating an ability evaluation score based on the grade scores of all elements in the third skill matrix at the current moment; Determining the skill interest tendency of the trainee according to the third skill matrix at the current moment; Decomposing the enterprise development plan into multiple development sub-plans according to the development directions, calculating the matching degree according to each development sub-plan and the skill interest tendency, and obtaining the demand matching degree; Calculating the matching degree according to the third skill matrix and each development sub-plan to obtain the ability matching degree; Performing weighted calculation on the ability evaluation score with each demand matching degree and the corresponding ability matching degree respectively to obtain multiple career matching degrees, determining the development direction corresponding to the development sub-plan corresponding to the maximum value of the career matching degree as the target career development direction, and sending the target career development direction to the trainee terminal.

8. An employee training device based on a master-apprentice mechanism, characterized in that, The device includes: A first acquisition unit, configured to acquire the skill matrices of each tutor from the employee skill evaluation system to obtain M first skill matrices, and acquire the skill matrices required by each trainee from the trainee induction training system to obtain N second skill matrices. The elements in the skill matrix at least include the grade scores of business skills; A first calculation unit, configured to calculate the matching degrees between each first skill matrix and each second skill matrix to obtain M*N first matching degrees. One trainee corresponds to M first matching degrees, and one tutor corresponds to N first matching degrees; A first matching unit, configured to assign each trainee to the tutor corresponding to the maximum value of the M first matching degrees corresponding to the trainee to obtain N first teaching plans; A second acquisition unit, configured to send teaching tasks to the trainee terminal and the tutor terminal according to the first teaching plan, and periodically acquire the real-time skill matrix of the trainee during the teaching process to obtain the third skill matrix; A third acquisition unit, configured to acquire actual business tasks and decompose the actual business tasks into multiple subtasks, and respectively construct the skill matrix according to the business skills required by each subtask to obtain the demand skill matrix corresponding to each subtask; A second calculation unit, configured to calculate the matching degrees between each demand skill matrix and each third skill matrix to obtain multiple second matching degrees, send the subtask corresponding to the maximum value of the second matching degrees corresponding to each trainee to each trainee terminal, and determine the task completion degree according to the completion situation of the subtask; A first sending unit, configured to adjust the teaching tasks of the business skills required for the subtasks in the first teaching plan based on the task completion degree and send them to the trainee terminal and the tutor terminal.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program runs, it controls the device where the computer-readable storage medium is located to execute the method according to any one of claims 1 to 7.

10. A human resource management system, characterized in that, Including: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include those for performing the method according to any one of claims 1 to 7.

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