College and university teacher inbreeding dynamic monitoring model based on resume analysis method
Through the dynamic monitoring model of inbreeding for college teachers based on resume analysis, teachers' inbreeding behaviors are monitored and early warning of teachers' inbreeding behaviors, the negative impact of inbreeding on academic output is solved and teachers' academic output is improved.
Patent Information
- Application Number
- CN202411152054.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-21
- Publication Date
- 2025-01-10
AI Technical Summary
Inbreeding has affected the academic output of college teachers, and it is difficult for existing technologies to effectively monitor and solve this problem.
Dynamic monitoring model of inbreeding teachers inbreeding by colleges and universities based on resume analysis method. Through the combination of storage system, analysis system, dynamic monitoring module, flow monitoring module and early warning module, a dynamic monitoring model of teachers is constructed to monitor the academic flow and inbreeding behavior of teachers. , provide an automatic warning mechanism.
By analyzing teachers' learning history and time intervals, establishing relevant models, monitoring and early warning of inbreeding behavior, avoiding the emergence of a large number of inbreeding teachers and improving teachers' academic output.
Smart Images
Figure CN119293304A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of dynamic information monitoring, and in particular to a dynamic monitoring model for inbreeding of university teachers based on a resume analysis method. Background Art
[0002] Webster's Third New International Dictionary explains the borrowed meaning of the concept of "inbreeding" as: obtaining narrow sources of knowledge and culture from limited professional fields; the phenomenon of hiring in an organization, a large proportion of newly recruited personnel are those who have received education in the organization.
[0003] The intervals between undergraduate and master's degrees and between master's degrees and doctoral degrees for "inbred" university teachers were 1.43 years and 2.58 years, respectively, much higher than the 1.18 years and 1.83 years for "non-inbred" teachers. Compared with non-inbred teachers, the average interval between doctoral graduation and academic work for "inbred" teachers was shorter. The average time between doctoral graduation and university work for inbred teachers was 1.2 years, while that for non-inbred teachers was 2.4 years, almost double the difference between the two.
[0004] Therefore, inbreeding will cause a certain impact on teachers' academic output. In order to solve this problem, it is necessary to provide a dynamic monitoring model of inbreeding among university teachers based on resume analysis to monitor teachers' inbreeding. Summary of the invention
[0005] In view of the deficiencies of the prior art, the present invention provides a dynamic monitoring model for inbreeding of university teachers based on resume analysis, which solves the current problems.
[0006] A dynamic monitoring model for inbreeding of university teachers based on resume analysis method includes a storage system, the storage system is communicatively connected to an analysis system for analyzing resumes, the storage system outputs information to a cloud transmission system, wherein the analysis system includes: an input module, for scanning resumes in different file formats and extracting the scanned information, the input module is connected to a classification module, the classification module performs classification according to the information inside the resume; a dynamic monitoring module, for monitoring teachers according to their resumes and their work information, the dynamic monitoring module is connected to a model building module, the model building module builds a model according to the real-time data in the teacher's resume, and then dynamically monitors the teacher's inbreeding behavior.
[0007] Based on the above technical solution, the dynamic monitoring module further monitors the teacher's final degree, current title, age and job mobility, and updates the module once every quarter.
[0008] Based on the above technical solution, further, the analysis system also includes: a flow monitoring module that is communicatively connected to the dynamic monitoring module, the flow monitoring module is used to monitor the work flow range and time of teachers, the flow monitoring module is communicatively connected to the early warning module, and the early warning module is used to warn of the flow of talents in academic exchanges.
[0009] Based on the above technical solution, further, the early warning module is communicated with the model building module. After the model building module completes the establishment of the corresponding models of talents and teachers, the early warning module monitors and warns whether the teachers are inbred and the scope of the teachers' academic mobility according to the changes in the constructed models.
[0010] Based on the above technical solution, further, when monitoring the academic mobility of teachers in universities, the variables involved in the monitoring include at least: undergraduate school as the employed school, master's school as the employed school, doctoral school as the employed school, final degree and gender.
[0011] Based on the above technical solution, further, the classification module is connected to a judgment module, which judges the talent and teacher information, and the judgment module is communicated with the early warning module, and when it is judged to be inbreeding, an automatic early warning is issued.
[0012] Based on the above technical solution, further, the judgment process of the judgment module is: obtain whether the teacher's current teaching school is the same as the schools where he / she received his / her undergraduate, master's, doctoral, and postdoctoral degrees; and how many of them are the same; when any of the educational units is the same as the current teaching unit, it is judged that there is a risk of inbreeding, and an automatic warning is issued.
[0013] Based on the above technical solution, further, the information required for building the model includes at least the school and major in the educational background and the unit information in the work experience.
[0014] Based on the above technical solution, further, after the teacher's resume is entered into the model, the model is dynamically changed, and whether the teacher is inbred is determined based on the changed model.
[0015] Based on the above technical solution, further, the cloud transmission system transmits and stores the teacher's data information and updates the teacher information database, wherein the cloud transmission system also compares the information of different teachers.
[0016] The present invention provides a dynamic monitoring model for inbreeding of university teachers based on resume analysis. Compared with the prior art, it has the following beneficial effects:
[0017] The present invention analyzes the learning history of teachers and their time intervals, and establishes relevant models and analyzes them according to the connection between their colleges and universities, as well as the number of years of service, and establishes corresponding models based on the teachers to monitor the inbreeding problem of teachers during their tenure, thereby ensuring that it is within a reasonable range, avoiding the generation of a large number of inbred teachers, and thus improving the academic output of teachers. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1 It is a schematic diagram of module connection of the present invention.
[0019] Reference numerals:
[0020] 1. Storage system; 2. Cloud transmission system; 3. Analysis system; 31. Input module; 32. Classification module; 33. Dynamic monitoring module; 34. Model building module; 35. Flow monitoring module; 36. Early warning module; 37. Judgment module. DETAILED DESCRIPTION
[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0022] See also Figure 1 The present invention provides a dynamic monitoring model for inbreeding of university teachers based on resume analysis. After analyzing the resume, a dynamic monitoring model for teachers can be established, so as to monitor the inbreeding of teachers accordingly. The dynamic monitoring model includes a storage system 1, wherein the storage system stores some required information, and the storage system is connected to an analysis system 3 for analyzing the resume. The storage system 1 output is connected to a cloud transmission system 2, wherein the analysis system 3 includes:
[0023] The input module 31 is communicated with the analysis system 3, and is used to scan resumes in different file formats and extract the scanned information. The input module 31 is communicated with the classification module 32, and the classification module 32 can classify or divide according to the information inside the resume. For example, it can be determined whether the teacher is an inbred teacher based on the teacher's undergraduate, master's and doctoral study units and the school where he works in the resume.
[0024] The dynamic monitoring module 33 is connected to the classification module 32 for monitoring the teacher according to his / her resume and related work information. In this embodiment, the resume information at least includes the teacher's name, current department, title, gender and other personal information, the start and end dates of each education stage and work stage, the undergraduate, postgraduate and doctoral education units, and the postdoctoral and work unit information. The work information mainly includes whether the teacher is teaching directly in a university or working as a postdoctoral fellow or in an enterprise, the specific unit name of the previous work, the time period, the name of the department under the current work unit, the title and other information.
[0025] The dynamic monitoring module 33 is in communication connection with the model building module 34, and the model building module 34 builds the model according to the relevant data in the teacher's resume. For example, according to the teacher's name, gender, major category, education experience, work experience and other relevant data in the teacher's resume, the teacher can be divided into a liberal arts teacher or a science and engineering teacher according to the professional category, that is, the model building is completed.
[0026] In this embodiment, separate models are established for different teachers, wherein building the model requires information such as the school and major in the educational background and the unit in the work experience; the collected information (such as resumes) can be standardized to ensure the consistency and accuracy of the data, wherein the standardization process includes data cleaning, data binning, data encoding, and data normalization. If necessary, the standardization process is an existing means and is not recorded in detail here; then based on the processed data, machine learning, graphical models and other technologies are used to construct a model reflecting the inbreeding relationship, wherein the graphical model of machine learning can adopt existing methods such as Bayesian networks and Markov networks to construct a dynamic model graph that can reflect the relationship.
[0027] After the teacher's resume is entered, the model can be changed, so that the model changes. Whether the teacher is inbred is determined within the range of the model change, and the range of inbreeding changes is a custom setting range. For example, new information such as educational background and work unit changes in the teacher's resume will cause changes in the model; the range of model changes refers to the adjustment range of model parameters, such as the strength of the relationship between teachers and colleges, changes in nodes and edges in the network, etc.; if the teacher has close ties with multiple teachers in the same school or unit, the teacher's correlation parameters in the model will change significantly.
[0028] In one embodiment, the dynamic monitoring module 33 monitors teachers' ultimate degree, current job title, age, and job mobility, and updates the information every quarter.
[0029] In this embodiment, by monitoring the teacher's final degree, current title, age, and job mobility, the teacher's academic output and academic mobility can be monitored accordingly, thereby ensuring that inbreeding problems can be avoided during the teacher's tenure.
[0030] In one embodiment, the analysis system 3 further comprises:
[0031] The flow monitoring module 35 is connected to the dynamic monitoring module 33 by communication to realize information transmission, and is used to monitor the scope and time of teachers' work flow. The flow monitoring module 35 is connected to the early warning module 36 by communication connection to realize information transmission. The early warning module 36 is used to warn the flow of talents in academic exchanges.
[0032] In this embodiment, since talents will have one-way flow during academic mobility, resulting in talent loss, we should be vigilant against this phenomenon and actively guide students to return. Therefore, talents are monitored during their academic mobility and early warnings are issued at the stage when talents are prone to one-way flow, so as to actively guide students and increase the return rate of talents.
[0033] In one embodiment, the early warning module 36 is connected to the model building module 34. After the model building module 34 completes the establishment of the corresponding models of talents and teachers, the early warning module 36 monitors whether they are inbred and their academic mobility range according to the changes in the models.
[0034] In this embodiment, the talent and teacher models will have a certain range after being established, and a reasonable setting range will be selected from the generated range. When the talent or teacher is within or close to the range, an early warning can be issued, thereby reminding the academic mobility of the talent and teacher, thereby reducing the occurrence of inbreeding.
[0035] In one embodiment, when monitoring the academic mobility of teachers, the variables involved in the monitoring are: undergraduate school as the employed school, master's school as the employed school, doctoral school as the employed school, final degree, and gender.
[0036] In this embodiment, the process situation is monitored and analyzed in combination with the correlation coefficient. Specifically, as shown in Table 1, the correlation coefficients are arranged from high to low as follows: "undergraduate school is the employment school", "master's school is the employment school", "doctoral school is the employment school", "final degree" and "gender", where P is the correlation coefficient; n is the number of valid cases; sig. indicates significance; each correlation coefficient is the Kendall rank correlation coefficient (tau_b); "**" indicates that the correlation is significant when the significance level is 0.01 (bilateral), and "*" indicates that the correlation is significant when the significance level is 0.05 (bilateral); for example, "academic mobility" is related to "undergraduate school is the employment school", "master's school is the employment school" and "doctoral school is the employment school". The correlation coefficients of "the doctoral school is the employed school" are 0.640, 0.421 and 0.757 respectively, which shows that academic talents whose undergraduate and doctoral schools are employed schools (a certain degree of inbreeding) are often not easy to move. Further regression analysis was used to study the impact of demographic variables, location variables and degree variables on the academic mobility of teachers in the two universities. The logistic regression model automatically eliminated the three variables of "gender", "age" and "current title", showing that only the four variables of "final degree", "undergraduate school", "master's school" and "doctoral school" have substantial impact on the model of factors affecting academic mobility.
[0037] For example, the logistic regression analysis method was used to analyze the academic mobility of Chinese and foreign teachers, the academic relationship variable (undergraduate school is the employed school, master's school is the employed school, doctoral school is the employed school) and degree variable (final degree), and the regression model of the impact of academic mobility of Chinese and foreign teachers was designed:
[0038] y=B0+B1x1+B2x2+...+Bkxk+ε;
[0039] In the formula, B0, B1, B2,…, Bk are the parameters of the model; ε is the error term.
[0040] Table 1 Kendall coefficients of university teachers' academic mobility and various factors
[0041]
[0042] As shown in Table 2, substituting the coefficients in the table into the equation:
[0043] y=4.219x1+1.047x2+2.319x3+0.846x4-13.683+ε;
[0044] y means “there is academic mobility”, x1 means “undergraduate school is the working school”, x2 means “master’s school is the working school”, x3 means “doctoral school is the working school”, and x4 means “final degree”.
[0045] Table 2
[0046] Explanation coefficient B Standard error SE Wald Degrees of freedom df Significance Exp(B) undergraduate school 4.219 0.228 341.185 1 0.00 67.993 Master School 1.047 0.19 30.331 1 0.00 2.85 Doctoral School 2.319 0.23 101.872 1 0.00 10.163 Final Degree 0.846 0.094 80.548 1 0.00 2.33 constant -13.683 0.78 307.578 1 0.00 0.00
[0047] Among them, Wald is a test method that tests the importance of the explanatory variable to the explained variable; Exp(B) represents the OR value of the corresponding variable. For the four categorical variables of undergraduate school as the employed school, master's school as the employed school, doctoral school as the employed school and final degree, the OR value means: relative to the research objects with lower assigned values (undergraduate school assigned with "1" is the employed school, master's school assigned with "1" is the employed school, doctoral school assigned with "1" is the employed school, and final degree assigned with "1" is the bachelor's degree), what is the probability of mobility of the research objects with higher assigned values (undergraduate, master's and doctoral schools are not employed schools, and the final degree is a doctoral degree) (67.993 times, 2.85 times, 10.163 times, 2.33 times).
[0048] In one embodiment, the classification module 32 is connected to the judgment module 37 for information transmission. The judgment module 37 judges the information related to talents and teachers by the classification module 32, and the judgment module 37 is connected to the warning module 36, and can automatically warn after judging inbreeding. The judgment process is: whether the current school where the teacher teaches is the same as the schools where he / she received his / her undergraduate, master's, doctoral, and postdoctoral degrees. How many of them are the same; when any of the educational units is the same as the current teaching unit, it is judged that there is a risk of inbreeding, and then an automatic warning is issued.
[0049] In this embodiment, the information classified by the classification module 32 is: whether the graduation school is the current school, the interval time from undergraduate to master's degree and from master's degree to doctorate, whether the teacher has work experience, whether the teacher's relevant work experience is related to his or her subject major and the number of years of work, so as to judge the teacher's relevant data information.
[0050] In one embodiment, the cloud transmission system 2 can transmit and update the teacher information database based on the teacher's relevant data information, wherein the cloud transmission system 2 can perform relevant comparisons based on the teacher's information.
[0051] In this embodiment, information comparison can be used to obtain information comparison of teachers, and the probability of inbreeding can be determined from multiple aspects such as talent titles and academic achievements, so as to provide corresponding references for colleges and universities to recruit teachers and reduce the occurrence of inbreeding problems. For example, if different teachers have the same talent title, their academic achievements or other information can be compared.
[0052] The systems, circuits and electronic components involved in the present invention are all prior art and can be fully implemented by those skilled in the art without further elaboration. It should be noted that the contents not described in detail in this specification are all prior art known to those skilled in the art.
[0053] It should be noted that, in this article, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus.
[0054] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. A dynamic monitoring model for inbreeding of university teachers based on resume analysis, including a storage system, characterized by: The storage system is connected to the analysis system for analyzing the resume, and the storage system outputs the information to the cloud transmission system, wherein the analysis system includes: The input module is used to scan resumes in different file formats and extract the scanned information. The input module is connected to the classification module, and the classification module classifies the resumes according to the information inside the resumes; The dynamic monitoring module monitors teachers according to their resumes and work information. The dynamic monitoring module is connected to a model building module. The model building module builds a model according to the real-time data in the teacher's resume, and then dynamically monitors the teacher's inbreeding behavior.
2. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 1 is characterized by: The dynamic monitoring module monitors teachers' final degree, current title, age, and job mobility, and updates the information every quarter.
3. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 1 is characterized by: The analysis system further comprises: The flow monitoring module is communicatively connected to the dynamic monitoring module, and the flow monitoring module is used to monitor the scope and time of teachers' work flow. The flow monitoring module is communicatively connected to the early warning module, and the early warning module is used to warn of the flow of talents in academic exchanges.
4. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 3 is characterized by: The early warning module is communicatively connected with the model building module. After the model building module completes the establishment of the corresponding models of talents and teachers, the early warning module monitors and warns whether the teachers are inbred and the scope of the teachers' academic mobility according to the changes in the constructed models.
5. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 4 is characterized by: When monitoring the academic mobility of teachers, the variables involved in the monitoring include at least: undergraduate school as the employed school, master's school as the employed school, doctoral school as the employed school, final degree, and gender.
6. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 3 is characterized by: The classification module is connected to a judgment module, which judges the talent and teacher information, and the judgment module is connected to the early warning module for communication, and when inbreeding is judged, an automatic early warning is issued.
7. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 6 is characterized by: The judgment process of the judgment module is as follows: Obtain information about whether the current school where a teacher teaches is the same as the schools where he / she received his / her undergraduate, master's, doctoral, or postdoctoral degrees; and how many of them are the same; if any of the educational institutions is the same as the current teaching institution, it is judged as a risk of inbreeding, and an automatic warning is issued.
8. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 1 is characterized by: The information required to build the model includes at least the school and major in the educational background and the unit information in the work experience.
9. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 8 is characterized by: After the teacher's resume is entered into the constructed model, the model will undergo dynamic changes, and the changed model will be used to determine whether the teacher is inbred.
10. The dynamic monitoring model for inbreeding of university teachers based on resume analysis method according to claim 1 is characterized by: The cloud transmission system transmits and stores teachers' data information and updates the teacher information database. The cloud transmission system also compares the information of different teachers.