Teacher development center digital management platform based on artificial intelligence

Abstract

The invention relates to the technical field of digital management, and particularly discloses a teacher development center digital management platform based on artificial intelligence, which comprises a teaching point teaching resource evaluation module, a teacher group description value determination module, a teacher rating module and an intelligent occupational planning module, determining a teaching resource evaluation level of each teaching point in the management area of the teacher development center, obtaining a teacher group description value of each teaching point in the management area of the teacher development center, and determining a teacher rating of any teacher based on the teaching resource evaluation level and the teacher group description value, based on the teacher rating of any teacher and the teaching resource evaluation grade of the teaching point where the teacher is located, intelligent professional planning for the teacher is carried out, and comprehensive analysis of personal ability, group requirements and teaching resources of the teacher is realized by introducing a multi-dimensional and comprehensive evaluation model and combining an artificial intelligence technology. Teacher and teaching point resources are dynamically matched, and efficient configuration of the resources and accurate development support of teachers are achieved.

Description

Technical Field

[0001] The present invention relates to the field of digital management technology, and in particular to a digital management platform for a teacher development center based on artificial intelligence. Background Art

[0002] With the development and progress of the digital age, digital management has become an important engine to promote management development and innovation. The implementation of digital management in teacher development in the era of informatization and intelligence can open up new business models for teacher development management by adopting advanced technologies such as big data analysis and the Internet of Things, achieve development and growth at a higher level of management services, and help organizations improve management efficiency and achieve sustainable development. Through digital tools, the cumbersome teacher assessment process can be automated, saving human resources while reducing errors caused by human subjective judgment, thereby making teacher development decisions faster and more accurate. By collecting and analyzing data through digital management to realize data-driven decision-making processes, teachers' training needs and performance can be understood more accurately to improve teachers' teaching quality and development potential.

[0003] Today, there are still some shortcomings in the digital management platform of the teacher development center based on artificial intelligence. Traditional teacher development assessments are mostly based on teachers' personal achievements and single-dimensional resource evaluations. They lack comprehensiveness and objectivity, and it is difficult to fully reflect the true development status of teachers. Traditional career planning methods often only focus on teachers' personal abilities, but ignore their match with the teaching environment and team resources. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a digital management platform for a teacher development center based on artificial intelligence, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an artificial intelligence-based digital management platform for a teacher development center, comprising a teaching resource evaluation module for a teaching point, a teacher portrait description value determination module, a teacher rating module and a career intelligence planning module, wherein: the teaching resource evaluation module for a teaching point is used to determine the teaching resource evaluation level of each teaching point within the management area of ​​the teacher development center; the teacher portrait description value determination module is used to obtain the teacher portrait description value of each teaching point within the management area of ​​the teacher development center; the teacher rating module is used to determine the teacher rating of any teacher based on the teaching resource evaluation level and the teacher portrait description value; the career intelligence planning module is used to carry out career intelligence planning for any teacher based on the teacher rating of the teacher and the teaching resource evaluation level of the teaching point where the teacher is located.

[0006] As a further solution, the method of obtaining the teaching resource evaluation level of each teaching point within the management area of ​​the teacher development center includes the following specific analysis processes: obtaining the basic teaching resource parameters of any teaching point within the management area of ​​the teacher development center, the basic teaching resource parameters including the average holding time of case course sharing accounts, the update frequency of educational research materials in the same subject, the average duration of teacher training course assessments, and the electronic public use rate of teaching materials; obtaining the teaching resource parameter weight factor of the corresponding teaching point; calculating the teaching resource evaluation value of any teaching point within the management area of ​​the teacher development center based on the basic teaching resource parameters of any teaching point within the management area of ​​the teacher development center and the corresponding teaching resource parameter weight factor; obtaining the endpoints of the teaching resource evaluation value interval stored in the database, the endpoints of the teaching resource evaluation value interval stored in the database serving as the basis for obtaining the teaching resource evaluation level of any teaching point within the management area of ​​the teacher development center according to the teaching resource evaluation value of the teaching point; obtaining the teaching resource evaluation level of each teaching point based on the endpoints of the teaching resource evaluation value interval stored in the database and the teaching resource evaluation value of each teaching point.

[0007] As a further solution, the teaching resource parameter weight factor of the corresponding teaching point is obtained, and the specific analysis process is as follows: obtaining the basic parameters of history teaching resources of any teaching point in the management area of ​​the teacher development center, the basic parameters of history teaching resources are obtained based on the training situation of the teaching point in the past teacher training cycle, including the average holding time of the history case course sharing account, the updating frequency of the history subject education research materials, the average duration of the history teacher training course assessment, and the electronic public use rate of history teaching materials; obtaining the teaching resource basic parameter correction factor set set in the database, the basic parameter correction factor set of teaching resources includes the correction factor of the average holding time of the case course sharing account, the updating frequency correction factor of the same subject education research materials, the average duration correction factor of the teacher training course assessment, and the electronic public use rate correction factor of the teaching materials;

[0008] Based on the basic parameters of historical teaching resources of any teaching point and the set of correction factors for basic parameters of teaching resources set in the database, the total value of the basic parameters of historical teaching resources of the teaching point is calculated; the basic parameters of overall teaching resources in the management area of ​​the teacher development center are obtained, and the basic parameters of overall teaching resources are obtained based on the training situation of the teacher training cycle in the management area of ​​the teacher development center in the past, including the average holding time of the overall case course sharing account, the overall updating frequency of the same subject education research materials, the average duration of the overall teacher training course assessment, and the overall electronic public use rate of teaching materials; the total value of the overall teaching resource basic parameters is calculated based on the basic parameters of overall teaching resources in the management area of ​​the teacher development center and the set of correction factors for basic parameters of overall teaching resources set in the database, and the set of correction factors for basic parameters of teaching resources includes the correction factor for the average holding time of the overall case course sharing account, the correction factor for the updating frequency of the same subject education research materials, the correction factor for the average duration of the overall teacher training course assessment and the correction factor for the overall electronic public use rate of teaching materials;

[0009] The teaching resource parameter weight factor of any teaching point is calculated based on the total value of the historical teaching resource basic parameters and the total value of the overall teaching resource basic parameters of the teaching point. The teaching resource parameter weight factor of each teaching point is equal to the ratio of the total value of the historical teaching resource basic parameters of each teaching point to the total value of the overall teaching resource basic parameters.

[0010] As a further solution, the method for obtaining the total value of the basic parameters of the historical teaching resources, the total value of the basic parameters of the overall teaching resources and the weight factor of the teaching resource parameters is as follows:

[0011]

[0012] Among them, i is the teaching point number, X i is the total value of the basic parameters of the history teaching resources of the i-th teaching point, A 1i is the average holding time of the history case course sharing account of the i-th teaching site, A 2i is the updating frequency of the history subject education research data of the i-th teaching point, A 3i is the average duration of the history teacher training course assessment at the i-th teaching site, A 4i is the electronic public use rate of history teaching materials in the i-th teaching point, a 1i is the average holding time correction factor of the case course sharing account of the i-th teaching point, a 2i is the update frequency correction factor of the same subject education research data of the i-th teaching point, a 3i is the correction factor for the average duration of teacher training course assessment at the i-th teaching point, a 4i is the correction factor for the electronic public use rate of teaching materials at the i-th teaching point;

[0013] Y is the total value of the basic parameters of the overall teaching resources, B1 is the average holding time per person in the overall case course sharing account, B2 is the update frequency of the overall educational research materials of the same subject, B3 is the average duration of the overall teacher training course assessment, B4 is the overall electronic public use rate of teaching materials, b1 is the correction factor for the average holding time per person in the overall case course sharing account, b2 is the correction factor for the update frequency of the overall educational research materials of the same subject, b3 is the correction factor for the average duration of the overall teacher training course assessment, and b4 is the correction factor for the overall electronic public use rate of teaching materials;

[0014] q i is the teaching resource parameter weight factor of the i-th teaching point.

[0015] As a further solution, the calculation formula of the teaching resource evaluation value is as follows:

[0016]

[0017] In the formula, zy i is the teaching resource evaluation value of the i-th teaching point, g i is the average duration of the case course sharing account of the i-th teaching site, x i is the updating frequency of the educational research data of the same subject in the i-th teaching point, k i is the average duration of teacher training course assessment at the i-th teaching point, d i is the electronic public utilization rate of teaching materials in the ith teaching point, and e is a natural constant.

[0018] As a further solution, the teacher portrait description value of each teaching point within the management area of ​​the teacher development center is obtained, and the specific analysis process is: obtain the teacher portrait description parameters of any teaching point within the management area of ​​the teacher development center, and the teacher portrait description parameters include the proportion of master and doctoral degree levels, the pass rate of teaching design plans, the average years of teaching experience, and the teacher turnover rate; obtain the teacher portrait compensation factor set in the database; calculate the teacher portrait description value of each teaching point based on the teacher portrait compensation factor set in the database and the teacher portrait description parameters of any teaching point within the management area of ​​the teacher development center; mark the teacher portrait description value of each teaching point in the visual map of the management area of ​​the teacher development center according to the geographical location of each teaching point within the management area of ​​the teacher development center.

[0019] As a further solution, the teacher group portrait description value is calculated as follows:

[0020]

[0021] Where ρ is the teacher portrait description value, μ is the teacher portrait compensation factor set in the database, δ is the teacher turnover rate, c is the proportion of master and doctoral degree levels, w is the passing rate of teaching design plans, z is the average years of teaching experience, and e is a natural constant.

[0022] As a further solution, the teacher rating of any teacher is determined based on the teaching resource evaluation level and the teacher portrait description value. The specific analysis process is: obtaining the personal development evaluation parameters of any teacher, the personal development evaluation parameters include the teaching activity participation rate, the number of professional honor certificates, the average number of lesson plans per semester, the highest score in teacher training, and the frequency of academic paper publication; extracting the teacher portrait description value and the teaching resource evaluation level corresponding to the teaching point in the digital portrait of the teacher development center management area based on the teaching point where the teacher is located; obtaining the teacher rating portrait compensation factor set in the database based on the teacher portrait description value; obtaining the teacher rating resource compensation factor set in the database based on the teaching resource evaluation level; obtaining the teacher rating based on the teacher rating portrait compensation factor, the teacher rating resource compensation factor and the teacher's personal development evaluation parameters set in the database.

[0023] As a further solution, the teacher rating is calculated as follows:

[0024] PJ=tanh(N*β)*α*(e S +e D+G*L );

[0025] Where PJ is the teacher rating, α is the teacher rating group portrait compensation factor set in the database, β is the teacher rating resource compensation factor, N is the teaching activity participation rate, D is the number of professional honor certificates, G is the average number of lesson plans per semester, S is the highest score in teacher training, L is the frequency of academic paper publication, and e is a natural constant.

[0026] As a further solution, the method is used to carry out career intelligence planning for any teacher based on the teacher rating and the teaching resource evaluation level of the teaching point where the teacher is located. The specific analysis process is: obtain the teacher rating of any teacher; obtain the average teacher rating of the teaching point where the teacher is located; obtain the teacher rating weighting factor set in the database, and the teacher rating weighting factor is greater than 1; obtain the ratio of the teacher rating of the teacher to the average teacher rating; if the ratio is greater than the teacher rating weighting factor, determine whether the teaching resource evaluation level of the teaching point where the teacher is located is the highest level: if it is not the highest level, allocate the teacher to a teaching point one level higher than the teaching point where the teacher is located; if it is the highest level, retain the teacher at the current teaching point; if the ratio is not greater than the teacher rating weighting factor, retain the teacher at the current teaching point.

[0027] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0028] (1) By setting a standardized teaching resource evaluation system and a calculation model for the teacher group portrait description value, the platform can more accurately classify and manage the resources of each teaching point and identify advantages and disadvantages. This evaluation can not only help the teacher development center to optimize resource allocation in a targeted manner, but also improve resource utilization efficiency through detailed data analysis, ensuring that teachers and students can obtain better experience and results in the use of teaching resources. The teacher rating and career intelligence planning modules make the allocation of resources and talents more scientific, provide teachers with a suitable development path, and thus improve the quality of teaching.

[0029] (2) The present invention is based on a comprehensive teacher rating and career intelligent planning mechanism, and the platform can provide teachers with scientific and fair career development advice and intelligent planning. By combining multiple data such as the resource level of the teacher's teaching point and the group portrait description value of the teacher, the influence of single or subjective factors is reduced, ensuring the comprehensiveness and objectivity of the evaluation. Teachers can obtain more appropriate career development directions based on their personal ratings on the platform, thereby achieving relative fairness in teaching resources and development opportunities. At the same time, managers can also use this data to support fairness and transparency in the decision-making process. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0031] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0032] Figure 2 Diagram of steps for obtaining teacher ratings based on individual development assessment parameters. DETAILED DESCRIPTION

[0033] 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. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0034] See also Figure 1 , an embodiment of the present invention provides a technical solution: a digital management platform for a teacher development center based on artificial intelligence, including a teaching resource evaluation module for a teaching point, a teacher group portrait description value determination module, a teacher rating module and a career intelligence planning module.

[0035] The teaching resource evaluation module of teaching points is used to determine the teaching resource evaluation level of each teaching point within the management area of ​​the teacher development center.

[0036] The specific analysis process includes: obtaining the basic parameters of teaching resources of any teaching point within the management area of ​​the Teacher Development Center, including the average holding time of case course sharing accounts, the update frequency of educational research materials in the same subject, the average duration of teacher training course assessments, and the electronic public use rate of teaching materials.

[0037] It should be noted that the above-mentioned average persistence time of case course sharing accounts refers to the average duration of each user on the case course sharing account, reflecting the continuity and activeness of users in using case course resources on the platform; the updating frequency of educational research materials in the same subject refers to the updating frequency of educational research materials in the same subject, which mainly depends on the speed of information updating and the timeliness of resource updating; the average duration of teacher training course assessment refers to the average duration of assessment after teachers participate in training courses, reflecting the learning time and learning depth spent by teachers in training courses; the sharing rate of electronic teaching materials refers to the sharing rate of teaching materials in electronic form.

[0038] Obtain the teaching resource parameter weight factor of the corresponding teaching point; calculate the teaching resource evaluation value of any teaching point in the management area of ​​the teacher development center based on the basic teaching resource parameters of any teaching point in the management area of ​​the teacher development center and the corresponding teaching resource parameter weight factor;

[0039] It should be noted that the calculation formula for the teaching resource evaluation value is as follows:

[0040]

[0041] In the formula, zy i is the teaching resource evaluation value of the i-th teaching point, g i is the average duration of the case course sharing account of the i-th teaching site, x i is the updating frequency of the educational research data of the same subject in the i-th teaching point, k i is the average duration of teacher training course assessment at the i-th teaching point, d i is the electronic public utilization rate of teaching materials in the ith teaching point, and e is a natural constant.

[0042] It should be noted that zy i Used to evaluate the teaching resources of the teaching point, i The larger the g, the better the teaching resources of the teaching point. i This means that users have a high degree of recognition and use frequency of case course resources, which helps to improve the popularity and influence of teaching resources. iThis means that the latest achievements in the field of educational research can be reflected in teaching resources in a timely manner, providing more cutting-edge and practical teaching materials, which helps to improve the quality and attractiveness of teaching resources. i This means that teachers invest more energy and time in training courses, which improves the effectiveness of training and teaching level, thereby improving teachers' teaching ability and the quality of teaching resources. i It helps promote the interconnection and interoperability of resources and the shared use of teaching resources, improves the accessibility and sustainability of resources, and the degree of digitization and sharing of teaching resources.

[0043] Obtain the endpoints of the teaching resource evaluation value interval set in the database, and use the endpoints of the teaching resource evaluation value interval set in the database as the basis for obtaining the teaching resource evaluation grade of any teaching point within the management area of ​​the teacher development center according to the teaching resource evaluation value of the teaching point; obtain the teaching resource evaluation grade of each teaching point based on the teaching resource evaluation value interval endpoints stored in the database and the teaching resource evaluation values ​​of each teaching point.

[0044] It should be noted that the endpoints of the teaching resource evaluation value interval will define the range of each evaluation level. For example: Teaching resource evaluation level 1: the lower endpoint of the interval is 0, and the upper endpoint of the interval is 10. If the teaching resource evaluation value is 5 at this time, it is within the upper and lower endpoints of the teaching resource evaluation level 1 interval. Therefore, the teaching resource evaluation level corresponding to the teaching resource evaluation value is 1.

[0045] In a specific embodiment, by setting the basic parameters and weight factors of teaching resources, a standardized evaluation system can be established to help the teacher development center more accurately evaluate and compare the quality of teaching resources at various teaching points. The endpoints of the teaching resource evaluation value interval set in the database are based on the regulations and standards of the annual average teaching resources in the education industry. Further grading of the teaching resource evaluation value can handle the interference of subtle evaluation value differences in providing management guidance to the teacher development center. By calculating the teaching resource evaluation value and grade, the quality and effect of the teaching resources can be objectively evaluated.

[0046] According to the evaluation results, the Teacher Development Center can optimize the use and management of teaching resources in teaching sites in a targeted manner and conduct an objective evaluation of teachers' personal development in the future. At the same time, the standard evaluation and grade matching system can promote continuous improvement and innovation in the management decision-making process, improve resource utilization efficiency and teaching effectiveness, be more inclusive of different teaching resource situations, optimize subsequent resource allocation, and formulate development strategies.

[0047] The process of obtaining the teaching resource parameter weight factor of the corresponding teaching point is: obtaining the basic parameters of the history teaching resources of any teaching point within the management area of ​​the teacher development center. The basic parameters of the history teaching resources are obtained based on the training situation of the teaching point in the past teacher training cycle, including the average holding time of the history case course sharing account, the update frequency of the history subject education research materials, the average duration of the history teacher training course assessment, and the electronic public use rate of the history teaching materials.

[0048] A set of correction factors for basic parameters of teaching resources set in the database is obtained, wherein the correction factors for basic parameters of teaching resources include a correction factor for the average holding time of case course sharing accounts, a correction factor for the updating frequency of educational research materials in the same subject, a correction factor for the average duration of teacher training course assessments, and a correction factor for the public utilization rate of electronic teaching materials.

[0049] The total value of the basic parameters of historical teaching resources of any teaching point is calculated based on the basic parameters of historical teaching resources of the teaching point and a set of correction factors of basic parameters of historical teaching resources set in a database.

[0050] The basic parameters of the overall teaching resources in the teacher development center management area are obtained based on the training situation of the teacher training cycle in the overall teacher development center management area, including the average holding time of the overall case course sharing account, the update frequency of the overall education research materials in the same subject, the average duration of the overall teacher training course assessment, and the overall electronic public use rate of teaching materials.

[0051] The total value of the overall teaching resource basic parameters is calculated based on the overall teaching resource basic parameters of the teacher development center management area and the overall teaching resource basic parameter correction factor set set in the database. The teaching resource basic parameter correction factor set includes the overall case course sharing account per capita holding time correction factor, the overall same subject education research material update frequency correction factor, the overall teacher training course assessment average duration correction factor and the overall teaching material electronic public use rate correction factor.

[0052] The teaching resource parameter weight factor of any teaching point is calculated based on the total value of the historical teaching resource basic parameters and the total value of the overall teaching resource basic parameters of the teaching point. The teaching resource parameter weight factor of each teaching point is equal to the ratio of the total value of the historical teaching resource basic parameters of each teaching point to the total value of the overall teaching resource basic parameters.

[0053] The method for obtaining the total value of the basic parameters of historical teaching resources, the total value of the basic parameters of overall teaching resources and the weight factor of teaching resource parameters is as follows:

[0054]

[0055] Among them, i is the teaching point number, X iis the total value of the basic parameters of the history teaching resources of the i-th teaching point, A 1i is the average holding time of the history case course sharing account of the i-th teaching site, A 2i is the updating frequency of the history subject education research data of the i-th teaching point, A 3i is the average duration of the history teacher training course assessment at the i-th teaching site, A 4i is the electronic public use rate of history teaching materials in the i-th teaching point, a 1i is the average holding time correction factor of the case course sharing account of the i-th teaching point, a 2i is the update frequency correction factor of the same subject education research data of the i-th teaching point, a 3i is the correction factor for the average duration of teacher training course assessment at the i-th teaching point, a 4i is the correction factor for the electronic public use rate of teaching materials at the i-th teaching point;

[0056] Y is the total value of the basic parameters of the overall teaching resources, B1 is the average holding time per person in the overall case course sharing account, B2 is the update frequency of the overall educational research materials of the same subject, B3 is the average duration of the overall teacher training course assessment, B4 is the overall electronic public use rate of teaching materials, b1 is the correction factor for the average holding time per person in the overall case course sharing account, b2 is the correction factor for the update frequency of the overall educational research materials of the same subject, b3 is the correction factor for the average duration of the overall teacher training course assessment, and b4 is the correction factor for the overall electronic public use rate of teaching materials;

[0057] q i is the teaching resource parameter weight factor of the i-th teaching point.

[0058] It should be noted that by calculating the total value of the basic parameters of the historical teaching resources of the teaching point through the basic parameters of the teaching resources in the recent teacher training cycle of the Teacher Development Center and the correction factors set in the database, more specific and personalized teaching resource evaluation data can be obtained. The teacher resource parameter weight factor is the ratio of the total value of the basic parameters of the historical teaching resources of the teaching point to the total value of the basic parameters of the overall teaching resources, which is conducive to a more accurate evaluation of the quality of teaching resources.

[0059] The set of correction factors of basic parameters of teaching resources is extracted from the database and can be determined according to the objective assignment method.

[0060] The teacher group portrait description value determination module is used to obtain the teacher group portrait description value of each teaching point in the management area of ​​the teacher development center.

[0061] The specific analysis process is as follows: obtaining the teacher group description parameters of any teaching point within the management area of ​​the teacher development center, wherein the teacher group description parameters include the proportion of master's and doctoral degree levels, the pass rate of teaching design plans, the average years of teaching experience, and the teacher turnover rate. The proportion of master's and doctoral degree levels refers to the proportion of teachers with master's and doctoral degrees in the entire teacher group. The pass rate of teaching design plans refers to the proportion of teaching design plans submitted by teachers in the past teacher training cycle that have been reviewed and approved. The average years of teaching experience refers to the average number of years each teacher has been engaged in teaching in the education industry. The teacher turnover rate refers to the ratio of the number of teachers who left the teacher development center in the past teacher training cycle to the total number of teachers at the end of the cycle.

[0062] Obtain the teacher group portrait compensation factor set in the database; calculate the teacher group portrait description value of each teaching point based on the teacher group portrait compensation factor set in the database and the teacher group portrait description parameter of any teaching point in the teacher development center management area; mark the teacher group portrait description value of each teaching point in the visual map of the teacher development center management area according to the geographical location of each teaching point in the teacher development center management area.

[0063] Specifically, the teacher group portrait description value is calculated as follows:

[0064]

[0065] Where ρ is the teacher portrait description value, μ is the teacher portrait compensation factor set in the database, δ is the teacher turnover rate, c is the proportion of master and doctoral degree levels, w is the passing rate of teaching design plans, and z is the average years of teaching experience.

[0066] It should be noted that the teacher group portrait description parameters are stored as teacher group portrait description designated tags, the teacher group portrait description designated tags are compared with the teacher group portrait description setting tags stored in the database, the teacher group portrait description setting tag that is the same as the teacher group portrait description designated tag is determined, and the teacher group portrait compensation factor corresponding to the teacher group portrait description setting tag is obtained.

[0067] ρ is an evaluation index for the teacher portrait of each teaching point in the management area of ​​the teacher development center, which is used to describe the teaching quality level of the teacher portrait of the teaching point and the overall teaching quality of the teacher portrait. The larger the δ, the negative impact of the working environment, salary or career development opportunities on the stable cultivation of the teacher portrait, and the worse the overall stability of the teacher portrait. c can reflect the academic level and degree of specialization of the teacher portrait. Generally, a higher c means that the teacher has a deeper theoretical foundation in academic research and teaching. z reflects the teacher's business familiarity by reflecting the time the teacher has been involved in teaching. A higher z means that the teacher has accumulated rich teaching experience as a whole, has a deeper understanding of the course content and student needs, and has a better teaching quality of the teacher portrait.

[0068] w is an indicator for evaluating the results of teachers' teaching design plans. Teachers with higher w have stronger teaching design capabilities and are more able to meet the teaching standards and requirements of educational institutions, thereby demonstrating better teaching quality. Teachers' academic qualifications are usually related to their professional knowledge and teaching ability. Higher c may have a stronger theoretical foundation and practical ability in teaching design, thereby improving w.

[0069] The teacher rating module is used to determine the teacher rating of any teacher based on the teaching resource evaluation level and the teacher group portrait description value.

[0070] Specifically, Figure 2 As shown in the figure, the specific analysis process is: obtain the personal development evaluation parameters of any teacher, and the personal development evaluation parameters include the participation rate in teaching activities, the number of professional honor certificates, the average number of lesson plans in a semester, the highest score in teacher training, and the frequency of academic paper publication. The participation rate in teaching activities refers to the proportion of teachers participating in various teaching activities, including lectures, seminars, and curriculum development. The number of professional honor certificates refers to the number of honor certificates related to their majors obtained by teachers. The average number of lesson plans in a semester refers to the number of lesson plans written by teachers in the past teacher training cycle. The highest score in teacher training refers to the highest score obtained by teachers in various training courses or professional development activities in the past teacher training cycle. The frequency of academic paper publication refers to the frequency of academic papers published by teachers in the past teacher training cycle.

[0071] Based on the teaching point where the teacher is located, extract the teacher group portrait description value and the teaching resource evaluation level corresponding to the teaching point in the digital portrait of the teacher development center management area; based on the teacher group portrait description value, obtain the teacher rating group portrait compensation factor set in the database; based on the teaching resource evaluation level, obtain the teacher rating resource compensation factor set in the database; based on the teacher rating group portrait compensation factor, teacher rating resource compensation factor and the teacher's personal development evaluation parameters set in the database, obtain the teacher rating. The above-mentioned teacher rating group portrait compensation factor and teacher rating resource compensation factor can be obtained in the form of a mapping set stored in the database. For example, the teacher group portrait description value corresponds to the teacher rating group portrait compensation factor one by one, and the corresponding teacher rating group portrait compensation factor can be directly obtained through the current teacher group portrait description value.

[0072] In a specific embodiment, the evaluation and grading of the current development status of teachers not only considers the teaching resource status of the teacher development center teaching point where the teacher is located, but also considers the status of the teacher group. By comprehensively considering the teaching resource status of the teacher development center teaching point and the status of the teacher group, the development status of teachers can be evaluated more comprehensively, which helps to improve the objectivity of the evaluation perspective and the fairness of the influencing factors, reduce the impact of subjective factors on the evaluation results, and help teachers to complete the deployment of teaching practice and improve the accuracy of teacher development intelligent planning decisions.

[0073] Specifically, the calculation process of teacher rating is as follows:

[0074] PJ=tanh(N*β)*α*(e S +e D+G*L );

[0075] Where PJ is the teacher rating, α is the teacher rating group portrait compensation factor set in the database, β is the teacher rating resource compensation factor, N is the teaching activity participation rate, D is the number of professional honor certificates, G is the average number of lesson plans per semester, S is the highest score in teacher training, L is the frequency of academic paper publication, and e is a natural constant.

[0076] In a specific embodiment, PJ is used to quantitatively represent the individual comprehensive level of teachers. A higher N indicates that teachers actively participate in teaching reform and professional development, and the teaching quality and personal professional qualities of teachers are more cultivated and improved. D represents the achievements and recognition of teachers in the field of teaching profession. Teachers with more D may have a higher professional level in teaching and research and better comprehensive quality. Similarly, more G indicates the degree of teachers' investment in course preparation and teaching design, reflecting the greater workload and higher teaching enthusiasm of teachers.

[0077] S can reflect the learning ability and achievements of teachers in professional training. Teachers with higher S are usually more forward-looking in teaching methods and educational concepts. Higher L usually indicates the teacher's activeness and contribution in academic research, which can reflect the teacher's higher research ability and academic influence.

[0078] It should be noted that Table 1 shows example values ​​of the teaching activity participation rate in teacher ratings, which shows intuitively how the teaching activity participation rate affects the teacher rating. The greater the teaching activity participation rate, the greater the teacher rating. As the teaching activity participation rate increases, the impact of the teaching activity participation rate on the teacher rating gradually decreases. The teacher rating group compensation factor set in the database is set to 0.5 unchanged, the teacher rating resource compensation factor set in the database is set to 0.2 unchanged, the number of professional honor certificates is set to 3 unchanged, the average number of lesson plans per semester is set to 2 unchanged, the highest score in teacher training is set to 6 unchanged, and the frequency of academic paper publication is set to 0.2 unchanged. Only the size of the teaching activity participation rate is changed.

[0079] Table 1: Example values ​​of teaching activity participation rate in teacher rating

[0080]

[0081] The career intelligence planning module is used to carry out career intelligence planning for any teacher based on the teacher rating and the teaching resource evaluation level of the teaching point where the teacher is located.

[0082] Get the teacher rating of any teacher; get the average teacher rating of the teaching point where the teacher is located; get the teacher rating weighting factor set in the database, wherein the teacher rating weighting factor is greater than 1; get the ratio of the teacher rating of the teacher to the average teacher rating; if the ratio is greater than the teacher rating weighting factor, determine whether the teaching resource evaluation level of the teaching point where the teacher is located is the highest level: if it is not the highest level, transfer the teacher to a teaching point one level higher than the teaching point where the teacher is located; if it is the highest level, retain the teacher at the current teaching point; if the ratio is not greater than the teacher rating weighting factor, retain the teacher at the current teaching point.

[0083] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. The digital management platform of the teacher development center based on artificial intelligence is characterized by: It includes the teaching resource evaluation module of teaching points, the teacher group description value determination module, the teacher rating module and the career intelligence planning module, among which: The teaching resource evaluation module of the teaching point is used to determine the teaching resource evaluation level of each teaching point in the management area of ​​the teacher development center; The teacher group portrait description value determination module is used to obtain the teacher group portrait description value of each teaching point in the management area of ​​the teacher development center; The teacher rating module is used to determine the teacher rating of any teacher based on the teaching resource evaluation level and the teacher group portrait description value; The professional intelligence planning module is used to carry out professional intelligence planning for any teacher based on the teacher rating of the teacher and the teaching resource evaluation level of the teaching point where the teacher is located.

2. The digital management platform for teacher development center based on artificial intelligence according to claim 1 is characterized by: The specific analysis process of obtaining the teaching resource evaluation level of each teaching point in the management area of ​​the teacher development center includes: Obtain the basic parameters of teaching resources of any teaching point in the management area of ​​the Teacher Development Center, including the average holding time of case course sharing accounts, the update frequency of educational research materials in the same subject, the average duration of teacher training course assessment, and the electronic public use rate of teaching materials; Obtain the teaching resource parameter weight factor of the corresponding teaching point; The teaching resource evaluation value of any teaching point in the management area of ​​the teacher development center is calculated based on the basic parameters of the teaching resources of any teaching point in the management area of ​​the teacher development center and the corresponding teaching resource parameter weight factor; Obtaining the endpoints of the teaching resource evaluation value interval stored in the database, the endpoints of the teaching resource evaluation value interval stored in the database being used as a basis for obtaining the teaching resource evaluation grade of any teaching point in the management area of ​​the teacher development center according to the teaching resource evaluation value of the teaching point; The teaching resource evaluation level of each teaching point is obtained based on the teaching resource evaluation value interval endpoints stored in the database and the teaching resource evaluation value of each teaching point.

3. The digital management platform for teacher development center based on artificial intelligence according to claim 2 is characterized by: The specific analysis process of obtaining the teaching resource parameter weight factor of the corresponding teaching point is as follows: Obtain the basic parameters of history teaching resources of any teaching point in the management area of ​​the teacher development center. The basic parameters of history teaching resources are obtained based on the training situation of the teacher training cycle of the teaching point in the past, including the average holding time of the history case course sharing account, the updating frequency of history and other subject education research materials, the average duration of history teacher training course assessment, and the electronic public use rate of history teaching materials; Obtaining a set of correction factors for basic parameters of teaching resources set in a database, wherein the set of correction factors for basic parameters of teaching resources includes a correction factor for the average holding time of a case course sharing account, a correction factor for the updating frequency of educational research materials in the same subject, a correction factor for the average duration of teacher training course assessment, and a correction factor for the public utilization rate of electronic teaching materials; Calculate the total value of the basic parameters of historical teaching resources of any teaching point based on the basic parameters of historical teaching resources of the teaching point and the basic parameter correction factor set of teaching resources set in the database; Obtaining the basic parameters of the overall teaching resources in the management area of ​​the teacher development center, which are obtained based on the training situation of the teacher training cycle in the management area of ​​the teacher development center in the past, including the average holding time of the overall case course sharing account, the overall updating frequency of the same subject education research materials, the overall average duration of the teacher training course assessment, and the overall electronic public use rate of teaching materials; The total value of the overall teaching resource basic parameters is calculated based on the overall teaching resource basic parameters of the teacher development center management area and the overall teaching resource basic parameter correction factor set set in the database, wherein the teaching resource basic parameter correction factor set includes the overall case course sharing account per capita holding time correction factor, the overall same subject education research data update frequency correction factor, the overall teacher training course assessment average duration correction factor and the overall teaching material electronic public use rate correction factor; The teaching resource parameter weight factor of any teaching point is calculated based on the total value of the historical teaching resource basic parameters and the total value of the overall teaching resource basic parameters of the teaching point. The teaching resource parameter weight factor of each teaching point is equal to the ratio of the total value of the historical teaching resource basic parameters of each teaching point to the total value of the overall teaching resource basic parameters.

4. The digital management platform for teacher development center based on artificial intelligence according to claim 3 is characterized by: The method for obtaining the total value of the basic parameters of the historical teaching resources, the total value of the basic parameters of the overall teaching resources and the weight factor of the teaching resource parameters is as follows: Among them, i is the teaching point number, X i is the total value of the basic parameters of the history teaching resources of the i-th teaching point, A 1i is the average holding time of the history case course sharing account of the i-th teaching site, A 2i is the updating frequency of the history subject education research data of the i-th teaching point, A 3i is the average duration of the history teacher training course assessment at the i-th teaching site, A 4i is the electronic public use rate of history teaching materials in the i-th teaching point, a 1i is the average holding time correction factor of the case course sharing account of the i-th teaching point, a 2i is the update frequency correction factor of the same subject education research data of the i-th teaching point, a 3i is the correction factor for the average duration of teacher training course assessment at the i-th teaching point, a 4i is the correction factor for the electronic public use rate of teaching materials at the i-th teaching point; Y is the total value of the basic parameters of the overall teaching resources, B1 is the average holding time per person in the overall case course sharing account, B2 is the update frequency of the overall educational research materials of the same subject, B3 is the average duration of the overall teacher training course assessment, B4 is the overall electronic public use rate of teaching materials, b1 is the correction factor for the average holding time per person in the overall case course sharing account, b2 is the correction factor for the update frequency of the overall educational research materials of the same subject, b3 is the correction factor for the average duration of the overall teacher training course assessment, and b4 is the correction factor for the overall electronic public use rate of teaching materials; q i is the teaching resource parameter weight factor of the i-th teaching point.

5. The digital management platform for teacher development center based on artificial intelligence according to claim 4 is characterized by: The calculation formula of the teaching resource evaluation value is as follows: In the formula, zy i is the teaching resource evaluation value of the i-th teaching point, g i is the average duration of the case course sharing account of the i-th teaching site, x i is the updating frequency of the educational research data of the same subject in the i-th teaching point, k i is the average duration of teacher training course assessment at the i-th teaching point, d i is the electronic public utilization rate of teaching materials in the ith teaching point, and e is a natural constant.

6. The digital management platform for teacher development center based on artificial intelligence according to claim 1 is characterized by: Get the teacher group description value of each teaching point in the management area of ​​the teacher development center. The specific analysis process is as follows: Obtaining teacher group description parameters of any teaching point in the management area of ​​the teacher development center, wherein the teacher group description parameters include the proportion of master's and doctoral degree levels, the passing rate of teaching design plans, the average years of teaching experience, and the teacher turnover rate; Obtain the teacher group image compensation factor set in the database; Calculate the teacher group image description value of each teaching point based on the teacher group image compensation factor set in the database and the teacher group image description parameter of any teaching point in the management area of ​​the teacher development center; According to the geographical location of each teaching point in the teacher development center management area, the teacher group portrait description value of each teaching point is marked in the teacher development center management area visual map.

7. The digital management platform for teacher development center based on artificial intelligence according to claim 6 is characterized by: The specific calculation formula of the teacher group portrait description value is: Where ρ is the teacher portrait description value, μ is the teacher portrait compensation factor set in the database, δ is the teacher turnover rate, c is the proportion of master and doctoral degree levels, w is the passing rate of teaching design plans, z is the average years of teaching experience, and e is a natural constant.

8. The digital management platform for teacher development center based on artificial intelligence according to claim 1 is characterized by: The teacher rating of any teacher is determined based on the teaching resource evaluation level and the teacher group description value. The specific analysis process is as follows: Obtaining the personal development evaluation parameters of any teacher, including the participation rate in teaching activities, the number of professional honor certificates, the average number of teaching plans per semester, the highest score in teacher training, and the frequency of academic paper publication; Based on the teaching point where the teacher is located, extract the teacher group portrait description value and teaching resource evaluation level corresponding to the teaching point in the digital portrait of the teacher development center management area; Acquire a teacher rating group image compensation factor set in a database based on the teacher group image description value; Acquire the teacher rating resource compensation factor set in the database based on the teaching resource evaluation level; The teacher rating is obtained based on the teacher rating group image compensation factor, the teacher rating resource compensation factor and the teacher's personal development assessment parameters set in the database.

9. The digital management platform for teacher development center based on artificial intelligence according to claim 8 is characterized by: The specific calculation process of the teacher rating is as follows: PJ=tanh(N*β)*α*(e S +e D+G*L ): Where PJ is the teacher rating, α is the teacher rating group portrait compensation factor set in the database, β is the teacher rating resource compensation factor, N is the teaching activity participation rate, D is the number of professional honor certificates, G is the average number of lesson plans per semester, S is the highest score in teacher training, L is the frequency of academic paper publication, and e is a natural constant.

10. The digital management platform for teacher development center based on artificial intelligence according to claim 1 is characterized by: The method for performing career intelligence planning for any teacher based on the teacher rating and the teaching resource evaluation level of the teaching point where the teacher is located is as follows: Get teacher ratings for any teacher; Get the average teacher rating of the teacher's teaching point; Obtaining a teacher rating weighting factor set in a database, wherein the teacher rating weighting factor is greater than 1; Get the ratio of the teacher's teacher rating to the average teacher rating; If the ratio is greater than the teacher rating weighting factor, it is determined whether the teaching resource evaluation level of the teacher's teaching point is the highest level: If it is not the highest level, the teacher will be assigned to a teaching point at a higher level than the teaching point where the teacher is currently working; If it is the highest level, the teacher will remain at the current teaching point; If the ratio is not greater than the teacher rating weighting factor, the teacher will remain at the current teaching point.

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