A Digital Twin-Based Information Management System and Method for Labor Education

Abstract

This invention relates to the field of information management technology, specifically disclosing a labor education information management system and method based on digital twins. This system, through the establishment of modules for online student job assignment, student labor education supervision and management, assessment and evaluation feedback value acquisition, and student labor education total score comparison, solves the problems of uneven distribution of teaching resources, difficulty in guaranteeing teaching quality, and insufficient comprehensive management of the labor education process in traditional practical teaching management. It enables the quantification and evaluation of educational effects, helps teachers comprehensively grasp students' labor education status, accurately assess students' overall development level, facilitates school management and record-keeping of student grades, allows for more convenient and quick viewing of student performance, supports students' academic development and graduation applications, and can also motivate students to study hard and perform well, thereby promoting student enthusiasm and participation to a certain extent.

Description

Technical Field

[0001] This invention relates to the field of information management technology, specifically to a labor education information management system and method based on digital twins. Background Technology

[0002] With the rapid development of information technology, digital education is gradually becoming more widespread and in-depth. Digital twin technology provides more possibilities for education management, enabling the teaching process to be more intelligent, personalized, and efficient. Labor education is an important way to cultivate students' practical abilities, innovative thinking, and cooperative spirit, and can improve the effectiveness and quality of labor education. Digital twin technology can provide more detailed data analysis and feedback, helping administrators to better monitor and improve the practical teaching process. By leveraging advanced digital technologies, labor education management can be optimized and improved, thereby enhancing teaching quality and students' learning experience.

[0003] Currently, there are still some shortcomings in the research on information management systems and methods for labor education based on digital twins. Specifically, traditional practical teaching management suffers from uneven distribution of teaching resources, difficulty in guaranteeing teaching quality, and incomplete management of the labor education process. This makes it difficult to quantify and evaluate educational effectiveness. Incomplete management makes it difficult for teachers to fully grasp students' labor education situation and accurately assess their comprehensive development level. Students lack sufficient supervision and guidance in practical teaching, which may lead to non-standard behaviors or learning attitudes. This increases the difficulty for education administrators to supervise students and may also lead to improper allocation of educational resources. Some students may not receive sufficient support and guidance, affecting their learning outcomes and development. The lack of comprehensive management of the labor education process may prevent effective guidance and support for students' individual learning needs, limiting students' space for individual development and improvement in practical teaching. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a labor education information management system and method based on digital twins, which can effectively solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a digital twin-based information management system for labor education, including a student online job assignment module, a student labor education supervision and management module, an assessment and evaluation feedback value acquisition module, and a student labor education total score comparison module. Specifically: the student online job assignment module acquires a dataset of basic information filled in by students online, and matches the most suitable labor education job for each student based on this dataset; the student labor education supervision and management module acquires a dataset of the student labor education process, and supervises and manages the student labor education process and records the supervision and management results based on this dataset; the assessment and evaluation feedback value acquisition module acquires a dataset of teacher assessment and evaluation feedback after the completion of student labor education, and comprehensively analyzes this dataset to obtain the teacher assessment and evaluation feedback value after the completion of student labor education; the student labor education total score comparison module compares the teacher assessment and evaluation feedback value after the completion of student labor education to obtain the student labor education total score and records the student labor education total score.

[0006] As a further solution, a dataset of basic information for students' online job postings will be provided, specifically including the weekly free time, the historical labor education work hours, and the body mass index.

[0007] As a further solution, based on the acquired dataset of students' online job application information, the most suitable labor education positions are matched for each student. The specific analysis process is as follows: Based on the acquired dataset of students' online job application information, a comprehensive analysis is performed to obtain the feature values ​​of the students' online job application information. These feature values ​​serve as the basis for matching students with the most suitable labor education positions. The feature values ​​of the students' online job application information are then matched with the labor education positions corresponding to each student's online job application information feature value stored in the database. This results in the labor education position corresponding to the student's online job application information feature value, which is considered the most suitable labor education position for that student.

[0008] As a further solution, the student labor education process dataset specifically includes the total actual duration of student labor education, the energy consumption generated by student labor education, and the number of steps in the student labor education process.

[0009] As a further solution, based on the acquired student labor education process dataset, the student labor education process is supervised and managed, and the results of the supervision and management are recorded. The specific analysis process is as follows: Based on the acquired student labor education process dataset, a comprehensive analysis is performed to obtain the student labor education process supervision and management feature value, which serves as the basis for supervising and managing the student labor education process; the student labor education process supervision and management feature value is compared with the student labor education process supervision and management definition feature value stored in the database; if the student labor education process supervision and management feature value is higher than the student labor education process supervision and management definition feature value, the student labor education process is marked as excellent and recorded on the student's historical labor education page; if the student labor education process supervision and management feature value is equal to the student labor education process supervision and management definition feature value, the student labor education process is marked as qualified and recorded on the student's historical labor education page; if the student labor education process supervision and management feature value is lower than the student labor education process supervision and management definition feature value, the student labor education process is marked as unqualified and recorded on the student's historical labor education page.

[0010] As a further solution, the specific analysis process for the characteristic values ​​of student labor education process supervision and management is as follows: ; In the formula, For the characteristic values ​​of supervision and management of students' labor education process, The total actual time for students' labor education. Energy consumption generated for students' labor education For the number of steps in the process of students' labor education, The total reference duration of student labor education stored in the database. Define the energy consumption generated by students' labor education, as stored in the database. This refers to the defined steps in the student labor education process stored in the database. This is a compensation factor set for the actual total duration of students' labor education. This is a compensation factor for the energy consumption generated during student labor education. e is a compensation factor for the number of steps in the student labor education process, where e is a natural constant.

[0011] As a further step, a dataset of teacher evaluation feedback after the completion of student labor education is obtained. Based on this dataset, a comprehensive analysis is conducted to obtain the evaluation value for teacher evaluation feedback after the completion of student labor education. The specific analysis process is as follows: The dataset includes the percentage of positive reviews from the student affairs office, the percentage of positive reviews from assigned teachers, and the percentage of positive reviews from homeroom teachers. Based on this dataset, a comprehensive analysis is conducted to obtain the evaluation value for teacher evaluation feedback after the completion of student labor education. This evaluation value serves as the basis for comparing and obtaining the total score for student labor education.

[0012] As a further measure, the evaluation feedback value for teachers after the completion of students' labor education will be analyzed in the following manner: ; In the formula, This refers to the evaluation score provided by teachers after students complete their labor education program. The percentage of positive reviews from the student affairs office after the completion of student labor education in the total number of evaluation bytes. The percentage of positive teacher reviews after students complete their labor education out of the total number of reviews. The percentage of positive feedback from homeroom teachers after students complete their labor education activities out of the total number of evaluation words. For setting Weighting factors For setting Weighting factors For setting Weighting factors.

[0013] As a further solution, based on the teacher evaluation feedback value after the completion of students' labor education, the total score of students' labor education is obtained by comparison, and the total score of students' labor education is recorded. The specific analysis process is as follows: the teacher evaluation feedback value after the completion of students' labor education is compared with the total score of students' labor education corresponding to the teacher evaluation feedback value after the completion of students' labor education stored in the database, and the total score of students' labor education corresponding to the teacher evaluation feedback value after the completion of students' labor education is obtained. The total score of students' labor education is then recorded on the historical labor education page of the student corresponding to the teacher evaluation feedback value after the completion of students' labor education.

[0014] The second aspect of this invention provides a digital twin-based method for information management of labor education, comprising the following steps: acquiring a dataset of basic information filled in by students online for their assigned positions; matching students with the most suitable labor education positions based on the acquired dataset; acquiring a dataset of students' labor education process; supervising and managing the students' labor education process based on the acquired dataset and recording the supervision and management results; acquiring a dataset of teacher evaluation feedback after students' labor education ends; comprehensively analyzing the acquired dataset to obtain the teacher evaluation feedback assessment value after students' labor education ends; comparing the teacher evaluation feedback assessment value after students' labor education ends to obtain the students' total labor education score, and recording the students' total labor education score.

[0015] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a labor education information management system and method based on digital twins. By obtaining the data set of students' online job information, the most suitable labor education job is matched for students. The personal information, abilities and interests of students can be accurately matched with the requirements of labor education jobs, thereby improving the accuracy of matching. After students are assigned to the most suitable labor education job, they can better exert their abilities and potential, improve their enthusiasm and participation, and promote their all-round development. Through the information management system, students' labor education jobs can be effectively matched and managed, the optimal allocation of resources can be realized, the utilization rate and efficiency of educational resources can be improved, and the quality and effect of labor education can be improved.

[0016] (2) By acquiring a dataset of students’ labor education process, this invention can supervise and manage the process of students’ labor education and record the results of supervision and management. It can promptly identify problems and difficulties that students encounter in the process of labor education, intervene and guide them in a timely manner, help students solve problems, improve learning effectiveness and management quality, promote students’ all-round development, understand students’ needs and situations, adjust and optimize the allocation and utilization of educational resources in a targeted manner, improve the rationality and efficiency of educational resources, and help schools continuously improve and optimize labor education management strategies and measures to enhance the level of education and management effectiveness.

[0017] (3) This invention obtains the teacher assessment and evaluation feedback dataset after the completion of students' labor education, compares it to obtain the total score of students' labor education, and records the total score of students' labor education. This can objectively evaluate the students' performance and achievements in the process of labor education, thereby obtaining a comprehensive and accurate total score of students' labor education, providing a reference for the comprehensive quality evaluation of students, which is conducive to the school's management and record of students' grades, and can make it easier and faster to view students' grades, providing support for students' academic development and graduation application, and can also encourage students to study hard and perform well, thereby promoting students' enthusiasm and participation to a certain extent. Attached Figure Description

[0018] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0020] Figure 2 This is a schematic diagram of the method steps of the present invention. Detailed Implementation

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] Reference Figure 1 As shown, the first aspect of the present invention provides a labor education information management system based on digital twins, including a student online job assignment module, a student labor education supervision and management module, an assessment and evaluation feedback value acquisition module, and a student labor education total score comparison module.

[0023] The online job assignment module for students is used to obtain a dataset of basic information filled in by students for online job assignments. Based on the obtained dataset of basic information filled in by students for online job assignments, the module matches the most suitable labor education positions for students.

[0024] Specifically, the student online job application data set includes the following: weekly free time, historical labor education work hours, and body mass index (BMI). Weekly free time refers to the total amount of free time a student can dedicate to online job applications within a week, helping to understand how much time a student can allocate to complete tasks. Historical labor education work hours indicate the cumulative time a student has spent on labor education work in the past, reflecting their work experience and skill level. The BMI is calculated based on the student's height and weight, reflecting their health and physical fitness to some extent, and may have a certain impact on certain job positions.

[0025] In one specific implementation, a student with more free time during the week will typically have more opportunities to engage in labor education work, accumulating more work experience and skills. It is possible that the length of a student's historical labor education work is positively correlated with the length of free time per week. The experience and skills accumulated by students in historical labor education work may require a certain level of physical fitness, and longer periods of labor education work may place a certain burden on the body. There may be a certain correlation between the length of historical labor education work and the body mass index. Students with more free time per week may have more time to exercise and maintain their health, which may be positively correlated.

[0026] Specifically, based on the dataset of students' online job application information, the most suitable labor education positions are matched for each student. The specific analysis process is as follows: Based on the dataset of students' online job application information, a comprehensive analysis is performed to obtain the feature values ​​of the students' online job application information. These feature values ​​serve as the basis for matching students with the most suitable labor education positions. The feature values ​​of the students' online job application information are then matched with the labor education positions corresponding to each student's online job application information feature value stored in the database. This results in the labor education position corresponding to the student's online job application information feature value, which is considered the most suitable labor education position for that student.

[0027] In one specific embodiment, matching students with the most suitable labor education positions allows them to perform their jobs more effectively, improving work efficiency and output. Matching them with the most suitable positions also makes it easier for students to apply their existing knowledge and skills, increasing job satisfaction and thus stimulating their learning motivation and enthusiasm. Furthermore, selecting the most suitable labor education position allows students to better leverage their strengths, complete work tasks, and enhance job satisfaction and a sense of accomplishment. Accurately matching students with labor education positions effectively utilizes students' strengths and talents, optimizing the allocation of labor resources and improving work efficiency.

[0028] It should be explained that the above-mentioned method of obtaining a dataset of students' online job application information and matching them with the most suitable labor education positions can accurately match students' personal information, abilities, and interests with the requirements of labor education positions, thereby improving the accuracy of the matching. After being assigned to the most suitable labor education positions, students can better utilize their abilities and potential, increase their enthusiasm and participation, and promote their all-round development. Through the information management system, students' labor education positions can be effectively matched and managed, achieving optimal allocation of resources, improving the utilization rate and efficiency of educational resources, and contributing to the improvement of the quality and effectiveness of labor education.

[0029] In one specific embodiment, the analysis process for the basic information feature values ​​filled in by students for online job postings is as follows: ; In the formula, Fill in the basic information and characteristic values ​​for students' online job positions. Students fill in their weekly free time for online job postings. Students fill in the historical labor education work hours for their online job postings. Students fill out their Body Mass Index (BMI) for online job postings. Fill in the weekly free time for the online job postings of students stored in the database. Fill in the online job postings of students stored in the database with reference to the working hours of labor education. Fill in the reference body mass index for the online job postings of students stored in the database. For the online positions designated for students, fill in the compensation factor for weekly free time. For the designated online positions for students, fill in the compensation factor for the historical labor education work hours. Fill in the compensation factor of body mass index for the set online positions for students.

[0030] It should be explained that the aforementioned characteristic values ​​of the basic information filled in by students in online job postings are calculated based on the weekly free time filled in by students in online job postings, the historical labor education work hours filled in by students in online job postings, and the body mass index filled in by students in online job postings. The weekly free time filled in by students in online job postings helps schools and teachers understand students' free time during the week, thereby arranging students' labor education tasks and activities in a targeted manner to maximize the use of students' time resources. The historical labor education work hours filled in by students in online job postings can record the cumulative time students have spent in labor education work, which helps to track students' accumulation of work experience and development process in labor education, and provides a basis for evaluation and guidance. Providing data support, students' online BMI (Body Mass Index) reporting helps schools monitor students' physical condition, promptly identify potential health problems, and take corresponding management and health care measures to ensure students' health and safety. Through the calculated basic information characteristic values, schools and teachers can conduct data analysis on students' learning, work, and physical condition, providing personalized guidance and services to help students develop and improve. Recording these basic information characteristic values ​​in student files helps to comprehensively evaluate students' overall quality and ability performance, providing more comprehensive data support for school management and development. Students can report their weekly free time by filling out forms or online questionnaires, or by entering data through the student personal information system or dedicated student management software. Students record their work hours in the online job reporting, and the system automatically accumulates students' historical labor education work hours. Students can measure their BMI themselves using tools such as scales and height charts, and then input the data into the system for recording. The system automatically calculates students' BMI values ​​based on height and weight data. The reference values ​​can be standard values ​​stipulated by the school's education bureau or health management department, or reference ranges and thresholds set by the school. These reference values ​​are usually pre-set by professionals or administrators and are included in the system. The data is configured and stored for subsequent data comparison and analysis. The compensation factors for students' weekly free time in online job postings, historical labor education work hours, and body mass index are obtained from the database. A mapping set is established between historical students' weekly free time in online job postings, historical labor education work hours, and body mass index and the compensation factors for students' weekly free time in online job postings, historical labor education work hours, and body mass index. The compensation factors for students' weekly free time in online job postings, historical labor education work hours, and body mass index corresponding to the current students' weekly free time in online job postings, historical labor education work hours, and body mass index are obtained.

[0031] The student labor education supervision and management module is used to acquire a dataset of student labor education processes, supervise and manage the student labor education process based on the acquired dataset, and record the supervision and management results.

[0032] Specifically, the student labor education process dataset includes the actual total duration of student labor education, the energy consumption generated during student labor education, and the number of steps taken during student labor education. The actual total duration of student labor education refers to the total time that students actually spend on labor during the labor education process. It can be used to measure the time and energy students spend on labor education, and can also reflect the intensity and duration of labor education. The energy consumption generated during student labor education refers to the energy consumed by students during the labor education process. Labor education may require students to perform physical labor, and it can be used to assess the intensity and energy consumption of students during labor education. The number of steps taken during student labor education refers to the number of steps that students actually take during the labor education process. The number of steps can reflect the amount of activity and exercise of students during labor education. More steps may indicate that students are active and engaged in labor education, while fewer steps may indicate that students are relatively static or quiet during labor education.

[0033] It should be explained that students with a longer actual total duration of labor education may consume more energy and take more steps. This is because over a longer period, students have more opportunities to participate in labor and are more active, naturally consuming more energy. At the same time, the number of steps may also increase with the time spent. This is because students are more active and take more actions during a longer period of labor education, resulting in more steps and potentially consuming more energy. The more steps a student takes, the greater the activity level, and the more energy they consume. This means that the higher a student's activity level and the more actions they take during labor education, the more energy they may consume.

[0034] Furthermore, based on the acquired student labor education process dataset, the student labor education process is supervised and managed, and the results are recorded. The specific analysis process is as follows: Based on the acquired student labor education process dataset, a comprehensive analysis is performed to obtain the student labor education process supervision and management feature value, which serves as the basis for supervising and managing the student labor education process. The student labor education process supervision and management feature value is compared with the student labor education process supervision and management definition feature value stored in the database. If the student labor education process supervision and management feature value is higher than the student labor education process supervision and management definition feature value, the student labor education process is marked as excellent and recorded on the student's historical labor education page. If the student labor education process supervision and management feature value is equal to the student labor education process supervision and management definition feature value, the student labor education process is marked as qualified and recorded on the student's historical labor education page. If the student labor education process supervision and management feature value is lower than the student labor education process supervision and management definition feature value, the student labor education process is marked as unqualified and recorded on the student's historical labor education page.

[0035] In a specific embodiment, establishing and defining supervisory and management characteristic values ​​allows for standardized evaluation and comparison of students' labor education processes, ensuring objectivity and fairness. Dividing students' labor education processes into three levels—excellent, satisfactory, and unsatisfactory—helps motivate students to improve their performance, promotes active participation and performance in labor education, thereby enhancing overall educational quality. Recording students' historical labor education records helps better understand their performance and development, providing personalized development guidance and support to help them grow and improve themselves. Evaluating and marking students' labor education processes establishes incentive and reward mechanisms, encouraging active participation in labor education activities and stimulating their learning enthusiasm and motivation. The supervisory and management process helps administrators quickly and accurately assess students' labor education performance, enabling timely guidance and assistance, and improving the efficiency and effectiveness of supervision and management.

[0036] It should be explained that by acquiring a dataset of students' labor education process, supervising and managing the process, and recording the results, the aforementioned methods can promptly identify problems and difficulties encountered by students during labor education, enabling timely intervention and guidance to help students solve problems, improve learning outcomes and management quality, and promote students' all-round development. This also allows for understanding students' needs and situations, targeted adjustments and optimizations to the allocation and utilization of educational resources, improving the rationality and effectiveness of educational resources. Furthermore, it helps schools continuously improve and optimize their labor education management strategies and measures, thereby enhancing educational standards and management effectiveness.

[0037] Specifically, the characteristic values ​​of supervision and management in the process of student labor education are analyzed as follows: ; In the formula, For the characteristic values ​​of supervision and management of students' labor education process, The total actual time for students' labor education. Energy consumption generated for students' labor education For the number of steps in the process of students' labor education, The total reference duration of student labor education stored in the database. Define the energy consumption generated by students' labor education, as stored in the database. This refers to the defined steps in the student labor education process stored in the database. This is a compensation factor set for the actual total duration of students' labor education. This is a compensation factor for the energy consumption generated during student labor education. e is a compensation factor for the number of steps in the student labor education process, where e is a natural constant.

[0038] It should be explained that the aforementioned student labor education process supervision and management characteristic values ​​are calculated based on the actual total duration of student labor education, the energy consumption generated during student labor education, and the number of steps taken during the process. Monitoring and recording the actual total duration of student labor education allows for timely understanding of students' participation and attitude, helping teachers and administrators to determine whether students are actively participating in labor education activities and whether they are seriously engaged. Data such as energy consumption and steps can assess the intensity and amount of labor and activity during the process, helping to understand students' workload and physical exertion, providing a reference for optimizing labor education activities. The supervision and management characteristic values ​​can encourage students to actively participate in labor education activities, allowing students to know their participation status and... Labor intensity is recorded and assessed, potentially motivating students to participate more actively and utilize their abilities. Monitoring students' labor education process allows for real-time monitoring of their activity levels and physical condition. Based on data such as energy expenditure and steps, tailored labor education plans can be developed to address individual student differences, contributing to improved physical fitness. Analyzing and monitoring supervisory characteristics allows schools and teachers to understand student participation and the effectiveness of labor education, providing data support for educational management. This data enables adjustments to educational plans and policies, enhancing the quality and effectiveness of labor education. The total duration of labor education activities can be calculated using start and end times, which can be achieved through the use of timers, clocks, and educational class management systems. Tools can be used to obtain data. Energy consumption can be calculated by the difference in students' weight before and after participating in labor education activities, combined with the time span of weight change and activity time for estimation. Alternatively, sports and health monitoring devices or applications, such as smart bracelets and fitness trackers, can be used to monitor students' energy consumption in real time. Step count can be obtained by students wearing smartwatches, smart bracelets, or mobile apps. These devices can record students' steps, distance, and activity intensity in real time for subsequent data analysis and storage. The total duration can be preset by education departments, school administrators, or education professionals and configured and stored in the education management system. Standardizing the duration of students' participation in labor education activities is an educational goal. As part of the requirements, the values ​​for energy consumption and steps can also be pre-set by relevant professionals or managers and stored in a database. This serves as the basis for assessing student participation and activity intensity. The compensation factors for the actual total duration of student labor education, energy consumption, and steps during the process are obtained from the database. A mapping set is established between historically measured actual total duration of student labor education, energy consumption, and steps during the process, and the compensation factors for these parameters. This yields the compensation factors corresponding to the current actual total duration of student labor education, energy consumption, and steps during the process.

[0039] The assessment and evaluation feedback value acquisition module is used to obtain the teacher assessment and evaluation feedback dataset after the completion of student labor education. Based on the obtained teacher assessment and evaluation feedback dataset after the completion of student labor education, a comprehensive analysis is performed to obtain the teacher assessment and evaluation feedback value after the completion of student labor education.

[0040] Specifically, the dataset of teacher evaluation feedback after the completion of student labor education is obtained. Based on this dataset, a comprehensive analysis is conducted to obtain the evaluation values ​​for teacher evaluation feedback after the completion of student labor education. The specific analysis process is as follows: The dataset includes the percentage of positive reviews from the student affairs office in the total number of evaluation bytes, the percentage of positive reviews from assigned teachers in the total number of evaluation bytes, the percentage of positive reviews from homeroom teachers in the total number of evaluation bytes, the percentage of positive reviews from the student affairs office in the total number of evaluation words, the percentage of positive reviews from assigned teachers in the total number of evaluation words, and the percentage of positive reviews from homeroom teachers in the total number of evaluation words. The percentage of positive feedback in the total evaluation count refers to the proportion of positive evaluations from the Student Affairs Office, assigned teachers, and homeroom teachers in the feedback received after the completion of student labor education. A high percentage of positive feedback from the Student Affairs Office indicates that the school administration highly affirms and praises the students' performance in labor education. A high percentage of positive feedback from assigned teachers indicates that professional teachers highly evaluate and recognize the students' performance in their specific work positions. A high percentage of positive feedback from homeroom teachers indicates that homeroom teachers highly evaluate the students' overall qualities and comprehensive performance. Based on the obtained dataset of teacher evaluation feedback after the completion of student labor education, a comprehensive analysis is conducted to obtain the teacher evaluation feedback assessment value. This assessment value serves as the basis for comparing and obtaining the total score for student labor education.

[0041] It should be explained that if the positive comments from the student affairs office account for a high percentage of the total evaluation, it may mean that the school administration is more focused on the overall quality and performance of students in labor education. If the positive comments from the teaching staff account for a high percentage of the total evaluation, it may mean that the teaching staff is more focused on the performance and ability development of students in their specific work positions. If the positive comments from the homeroom teacher account for a high percentage of the total evaluation, it may mean that the homeroom teacher is more focused on the students' performance and growth in all aspects of learning and life. The evaluation results of different evaluators may influence each other, and the students' performance in labor education will be affected by the comprehensive influence of multiple evaluations.

[0042] It should be explained that the aforementioned dataset of teacher evaluation feedback after the completion of student labor education includes the percentage of positive comments from the student affairs office, assigned teachers, and homeroom teachers. This dataset can comprehensively assess students' performance and attitude during the labor education process, providing a more holistic understanding of their overall qualities and abilities from multiple dimensions. The comprehensive analysis of the evaluation values ​​allows for a more objective and accurate assessment of students' performance after labor education, avoiding the influence of subjective opinions and personal biases, and improving the objectivity and accuracy of the evaluation. Based on the teacher evaluation feedback values ​​after the completion of student labor education, more targeted and personalized learning guidance and development suggestions can be provided to students, helping them better identify and solve problems, achieve self-improvement and growth. Using the teacher evaluation feedback values ​​after the completion of student labor education as a basis for comparing students' total scores, a reward and punishment mechanism can be established to incentivize excellent students and improve those who are lacking, playing an incentive and guiding role in student education management. Comprehensive analysis of student and teacher evaluation feedback data provides a more intuitive understanding of students' performance and development during labor education, contributing to the comprehensive development and improvement of students' overall qualities.

[0043] It should be explained that the above-mentioned method of obtaining the teacher assessment feedback dataset after the completion of students' labor education, comparing it to obtain the total score of students' labor education, and recording the total score of students' labor education can objectively evaluate students' performance and achievements in the process of labor education. This results in a comprehensive and accurate total score of students' labor education, providing a reference for the comprehensive quality evaluation of students. It is beneficial for schools to manage and record students' grades, making it easier and faster to view students' grades, supporting students' academic development and graduation applications, and also motivating students to study hard and perform well, thereby promoting students' enthusiasm and participation to a certain extent.

[0044] Furthermore, the evaluation feedback values ​​for teachers after the completion of students' labor education are analyzed in the following specific process: ; In the formula, This refers to the evaluation score provided by teachers after students complete their labor education program. The percentage of positive reviews from the student affairs office after the completion of student labor education in the total number of evaluation bytes. The percentage of positive teacher reviews after students complete their labor education out of the total number of reviews. The percentage of positive feedback from homeroom teachers after students complete their labor education activities out of the total number of evaluation words. For setting Weighting factors For setting Weighting factors For setting Weighting factors.

[0045] It should be explained that the aforementioned teacher evaluation feedback values ​​after the completion of student labor education are calculated based on the percentage of positive reviews from the student affairs office, the percentage of positive reviews from assigned teachers, and the percentage of positive reviews from homeroom teachers. Statistical analysis of the percentage of positive reviews from different teachers in the total evaluation results after the completion of student labor education allows for an objective evaluation of students' performance and achievements in labor education. This helps identify students' strengths and areas for improvement. Positive teacher feedback can motivate students to participate more actively in labor education activities, strive to improve their performance and achievements, and thus promote student development. Teacher feedback carries significant weight in student evaluations, reflecting participation and learning enthusiasm. Statistical analysis of the percentage of positive teacher feedback reveals teachers' approval of students' performance in labor education, enhancing the accuracy and authority of teacher assessments. School administrators can analyze this feedback data to promptly understand and adjust labor education plans, policies, and measures, optimizing educational management and improving the quality and effectiveness of labor education. The student affairs office can set evaluation criteria, requiring a certain number of positive comments in post-labor education evaluations. This can be collected through evaluation forms, questionnaires, etc., followed by statistical analysis to calculate the percentage of positive comments in the total evaluation. (The last sentence appears to be incomplete and possibly refers to a separate point about teachers.) Teachers who guide students during labor education can be asked to evaluate students' performance and indicate the number of words in positive feedback. This can be collected through oral feedback, written evaluations, etc., and then statistically analyzed to calculate the percentage of positive feedback in the total evaluation count. Class teachers, who typically provide comprehensive management and attention to student performance, can evaluate students after labor education and indicate the number of words in positive feedback. These evaluations can be collected through individual conversations, etc., and then statistically analyzed to calculate the percentage of positive feedback in the total evaluation count. Weighting factors are obtained from a database, establishing the percentage of positive feedback from the student management office and the percentage of positive feedback from assigned teachers in the total evaluation count after historical student labor education. The mapping set of compensation factors for the proportion of positive reviews in the total evaluation bytes, the proportion of positive reviews in the total evaluation bytes, the proportion of positive reviews in the student management office, the proportion of positive reviews in the post teachers, and the proportion of positive reviews in the total evaluation bytes after the completion of student labor education is obtained.

[0046] The module for comparing students' total labor education scores is used to compare the scores with the teacher's evaluation feedback after the completion of students' labor education, and then record the total scores of students' labor education.

[0047] Specifically, based on the teacher evaluation feedback value after the completion of students' labor education, the total score of students' labor education is obtained by comparison, and the total score of students' labor education is recorded. The specific analysis process is as follows: the teacher evaluation feedback value after the completion of students' labor education is compared with the total score of students' labor education corresponding to the teacher evaluation feedback value after the completion of students' labor education stored in the database, and the total score of students' labor education corresponding to the teacher evaluation feedback value after the completion of students' labor education is obtained. The total score of students' labor education is then recorded on the historical labor education page of the student corresponding to the teacher evaluation feedback value after the completion of students' labor education.

[0048] In one specific embodiment, recording the teacher evaluation feedback value and total score after the completion of students' labor education can effectively integrate students' performance data in labor education, enabling a comprehensive evaluation of students' overall quality. Recording the total score of students' labor education allows for the creation of a complete data archive on the student's historical labor education page, facilitating schools and teachers to track and record students' development in labor education, providing a reference for subsequent evaluation, guidance, and decision-making. By recording the total score of students' labor education, the evaluation results can be visualized and statistically analyzed, making it easier for teachers, students, and parents to intuitively compare and analyze students' development in labor education, promoting transparency and fairness in the evaluation results. Recording the total score of students' labor education and matching it with the teacher feedback evaluation value can provide personalized development guidance and suggestions for each student, helping them to fully realize their potential, make up for their shortcomings, and achieve personalized educational services.

[0049] Reference Figure 2 As shown, the second aspect of this invention provides a digital twin-based information management method for labor education, comprising the following steps: acquiring a dataset of basic information filled in by students online for their job assignments; matching the most suitable labor education job for each student based on the acquired dataset; acquiring a dataset of students' labor education process; supervising and managing the students' labor education process based on the acquired dataset and recording the supervision and management results; acquiring a dataset of teacher evaluation feedback after students' labor education ends; comprehensively analyzing the acquired dataset to obtain the teacher evaluation feedback assessment value after students' labor education ends; comparing the teacher evaluation feedback assessment value after students' labor education ends to obtain the total score of students' labor education, and recording the total score of students' labor education.

[0050] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A labor education information management system based on digital twins, characterized in that, This includes modules for online job placement for students, supervision and management of student labor education, acquisition of assessment and evaluation feedback scores, and comparison of total scores for student labor education. The online job assignment module for students is used to obtain a dataset of basic information filled in by students in online job assignments, and to match the most suitable labor education positions for students based on the obtained dataset of basic information filled in by students in online job assignments. The student labor education supervision and management module is used to acquire a dataset of student labor education processes, supervise and manage the student labor education process based on the acquired dataset, and record the supervision and management results. The assessment and evaluation feedback value acquisition module is used to acquire the teacher assessment and evaluation feedback dataset after the completion of student labor education. Based on the acquired teacher assessment and evaluation feedback dataset after the completion of student labor education, the assessment and evaluation feedback value of the teacher after the completion of student labor education is obtained through comprehensive analysis. The module for comparing students' total labor education scores is used to compare the scores with the teacher's evaluation feedback after the completion of students' labor education, and then record the total scores of students' labor education.

2. The labor education information management system based on digital twins according to claim 1, characterized in that: The dataset of basic information filled in by students for online job postings specifically includes the weekly free time filled in by students for online job postings, the historical labor education work hours filled in by students for online job postings, and the body mass index filled in by students for online job postings.

3. The labor education information management system based on digital twins according to claim 2, characterized in that: The process of matching students with the most suitable labor education positions based on the dataset of basic information filled in by students online is as follows: Based on the dataset of students' online job application information, a comprehensive analysis was conducted to obtain the feature values ​​of students' online job application information. These feature values ​​were used as the basis for matching students with the most suitable labor education positions. The basic information feature value filled in by the student in the online job is matched with the labor education position corresponding to the basic information feature value filled in by each student in the online job stored in the database. The labor education position corresponding to the basic information feature value filled in by the student in the online job is obtained. This labor education position is the most suitable labor education position for the student corresponding to the basic information feature value filled in by the student in the online job.

4. The labor education information management system based on digital twins according to claim 1, characterized in that: The dataset of student labor education process specifically includes the total actual duration of student labor education, the energy consumption generated by student labor education, and the number of steps in the student labor education process.

5. The labor education information management system based on digital twins according to claim 4, characterized in that: The process of supervising and managing the student labor education process based on the acquired student labor education process dataset and recording the results of the supervision and management is as follows: Based on the acquired dataset of student labor education process, a comprehensive analysis was conducted to obtain the characteristic values ​​of supervision and management of student labor education process. These characteristic values ​​serve as the basis for analysis in supervising and managing the student labor education process. Compare the characteristic values ​​of student labor education process supervision and management with the characteristic values ​​of student labor education process supervision and management stored in the database; If the characteristic value of the supervision and management of the student's labor education process is higher than the defined characteristic value of the supervision and management of the student's labor education process, then the student's labor education process will be marked as excellent and recorded on the student's historical labor education page. If the characteristic value of the supervision and management of the student's labor education process is equal to the defined characteristic value of the supervision and management of the student's labor education process, then the student's labor education process is marked as qualified and recorded on the student's historical labor education page. If the characteristic value of the supervision and management of the student's labor education process is lower than the defined characteristic value of the supervision and management of the student's labor education process, the student's labor education process will be marked as unqualified and recorded on the student's historical labor education page.

6. The labor education information management system based on digital twins according to claim 5, characterized in that: The specific analysis process for the characteristic values ​​of the supervision and management of the student labor education process is as follows: ; In the formula, For the characteristic values ​​of supervision and management of students' labor education process, The total actual duration of labor education for students. Energy consumption generated for students' labor education For the number of steps in the process of students' labor education, The total reference duration of student labor education stored in the database. Define the energy consumption generated by students' labor education, as stored in the database. This refers to the defined steps in the student labor education process stored in the database. This is a compensation factor set for the actual total duration of students' labor education. This is a compensation factor for the energy consumption generated during student labor education. e is a compensation factor for the number of steps in the student labor education process, where e is a natural constant.

7. The labor education information management system based on digital twins according to claim 1, characterized in that: The process of obtaining the teacher evaluation feedback dataset after the completion of student labor education, and then comprehensively analyzing it to obtain the evaluation value of the teacher evaluation feedback after the completion of student labor education, is as follows: Obtain the teacher evaluation feedback dataset after the completion of student labor education. Specifically, the teacher evaluation feedback dataset after the completion of student labor education includes the percentage of positive comments from the student management office in the total number of evaluation bytes, the percentage of positive comments from teachers in their respective positions in the total number of evaluation bytes, and the percentage of positive comments from homeroom teachers in the total number of evaluation bytes. Based on the obtained dataset of teacher evaluation feedback after the completion of student labor education, a comprehensive analysis was conducted to obtain the evaluation value of teacher evaluation feedback after the completion of student labor education. This evaluation value was used as the basis for comparison to obtain the total score of student labor education.

8. The labor education information management system based on digital twins according to claim 7, characterized in that: The specific analysis process for the teacher assessment feedback evaluation value after the completion of student labor education is as follows: ; In the formula, This refers to the evaluation score provided by teachers after students complete their labor education program. The percentage of positive reviews from the student affairs office after the completion of student labor education in the total number of evaluation bytes. The percentage of positive teacher reviews after students complete their labor education out of the total number of reviews. The percentage of positive feedback from homeroom teachers after students complete their labor education activities out of the total number of evaluation words. For setting Weighting factors For setting Weighting factors For setting Weighting factors.

9. The labor education information management system based on digital twins according to claim 8, characterized in that: The process involves comparing the student's total labor education score with the teacher's evaluation feedback after the completion of the student's labor education, recording the total score, and then analyzing the results. The evaluation value of the teacher's assessment after the completion of the student's labor education is compared with the total score of the student's labor education stored in the database. The total score of the student's labor education corresponding to the teacher's assessment after the completion of the student's labor education is obtained, and the total score of the student's labor education is recorded on the student's historical labor education page corresponding to the teacher's assessment after the completion of the student's labor education.

10. A method for information-based management of labor education based on digital twins, characterized in that: The labor education information management system based on digital twins as described in any one of claims 1-9 includes the following steps: Obtain a dataset of basic information filled in by students for online job postings, and match the most suitable labor education positions for students based on the obtained dataset of basic information filled in by students for online job postings. Obtain a dataset of students' labor education process, and based on the obtained dataset, supervise and manage the students' labor education process and record the results of the supervision and management. Obtain the teacher evaluation feedback dataset after the completion of student labor education, and based on the obtained teacher evaluation feedback dataset after the completion of student labor education, conduct a comprehensive analysis to obtain the evaluation value of teacher evaluation feedback after the completion of student labor education. Based on the evaluation feedback from teachers after the completion of students' labor education, the total score of students' labor education is obtained by comparison and recorded.

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