Student comprehensive quality evaluation system based on big data
Through a comprehensive student quality evaluation system combining big data analysis and multi-party evaluation, the problem of insufficient objectivity of practical skills evaluation is solved, and accurate evaluation of students' practical skills and effective supervision by parents is achieved.
Patent Information
- Application Number
- CN202510908520.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-02
- Publication Date
- 2025-08-01
AI Technical Summary
In the prior art, there is insufficient objectivity in the evaluation of practical skills, which is difficult to accurately reflect students' practical operation ability, and supervision and evaluation during the training stage lack objectivity and fairness.
A comprehensive student quality evaluation system based on big data is adopted, through multi-party data collection and analysis on the student side, teacher side, administrator side and parent side, combined with preset evaluation standards and feature analysis, standardized scoring and correction of students' practical performance is achieved, ensuring the accuracy and fairness of the evaluation results.
The objective comprehensive evaluation of students' practical skills has been achieved, the supervision and management effect of parents has been enhanced, and the accuracy and fairness of the evaluation results have been ensured.
Smart Images
Figure CN120409970A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of data analysis, and particularly relates to a student comprehensive quality evaluation system based on big data. Background Art
[0002] In educational practice, the evaluation criteria for the theoretical knowledge learning status of student users are often objective. Based on written answering methods such as periodic class tests and cyclic examinations, the mastery and application abilities of student users' theoretical knowledge can be verified relatively objectively. Practical skills learning has stronger practicality compared to theoretical knowledge learning. Therefore, simply using the written answering method to test the mastery and application abilities of student users' practical skills often results in the situation of "high scores but low abilities", which is not conducive to accurately knowing the proficiency of student users' practical operation abilities.
[0003] College students' practical training is an important part of higher education, which enables students to combine the theoretical knowledge learned in class with actual operations, thereby improving their comprehensive qualities and employment competitiveness. Practical training provides students with an opportunity to apply theoretical knowledge to practice. The theoretical knowledge learned in class is often abstract and theoretical, while through practical training, students can test and consolidate the knowledge they have learned in actual operations. This practical experience not only helps students deepen their understanding of professional content, but also helps students better master the methods and skills of solving practical problems. However, during the practical training stage, students are separated from the campus environment and enter enterprises and factories that match their majors for study and life. At the same time, they need to adapt to the work rhythm, and it may be difficult to adapt. In this case, it is very difficult for teachers to supervise students. At the same time, the practical training scores are only obtained through the objective evaluation of enterprise responsible persons, which has the problems of one-sidedness and inadequate evaluation.
[0004] In view of the above technical defects, a solution is proposed now. Summary of the Invention
[0005] The purpose of the present invention is to: obtain an objective comprehensive evaluation result by standardizing the scores of students' actual performances during the practice process, and further correct the result by combining the subjective evaluations of the teacher side and the person in charge of the practical project, ensuring the accuracy and fairness of the evaluation result. At the same time, a parent side is also provided to ensure that parents can obtain the daily activities of students during the time when students are away from school, enhancing the effect of parental supervision and management.
[0006] To achieve the above purpose, the present invention adopts the following technical solution: a student comprehensive quality evaluation system based on big data, including a student side, a teacher side, an administrator side, and a quality evaluation platform; The student side is used to establish a student account based on the student's personal information and obtain the course schedule and work schedule through the student side; The teacher's terminal is used to create a teacher account based on the classes the teacher is responsible for, obtain students' daily behavior data and practical assessment data during the practice process, give teacher evaluation results according to the daily behavior data and practical assessment data, and send them to the quality evaluation platform; The administrator's terminal is used to create an administrator account based on the functional department where the administrator is located and the personal information of the students under their management, obtain students' daily behavior data and practical assessment data during the practice process, give administrator evaluation results according to the daily behavior data and practical assessment data, and send them to the quality evaluation platform; The quality evaluation platform includes a comprehensive analysis unit, a standard evaluation unit, a feedback correction unit, and a result output unit; The comprehensive analysis unit includes a data acquisition module and a data analysis module. The data acquisition module is used to obtain students' daily behavior data during the practice process through the enterprise's attendance system, obtain students' practical assessment data during the practice process through the enterprise's project supervision department, and send them to the data analysis module, the teacher's terminal, and the administrator's terminal; The data analysis module is used to obtain the daily behavior data and practical assessment data, quantify the daily behavior data and practical assessment data into assessment scores according to the preset assessment criteria, calculate the students' quality evaluation coefficients based on the assessment scores, and send them to the standard evaluation unit; The standard evaluation unit is used to obtain the standard judgment data during the practical learning process, compare the data in combination with the students' quality evaluation coefficients, obtain the learning difference evaluation value, judge the students' comprehensive performance according to the preset difference judgment interval, obtain the objective comprehensive evaluation result, and output it to the feedback correction unit and the administrator's terminal; The feedback correction unit is used to obtain the objective comprehensive evaluation result and the administrator evaluation result from the administrator's terminal, extract keywords based on the administrator evaluation result and teacher evaluation result from the administrator's terminal, obtain the correction factor after feature analysis, optimize the students' comprehensive quality evaluation result based on the correction factor, and output the students' comprehensive quality evaluation result to the result output unit.
[0007] Furthermore, it also includes a parent's terminal. The parent's terminal is used to derive a parent account based on the student account, obtain the students' daily behavior data during the practice process and the living area information data of the enterprise where the students are located, and at the same time obtain the students' comprehensive quality evaluation result of the quality evaluation platform.
[0008] Further, the result output unit obtains the comprehensive quality evaluation results of students, and sends the comprehensive quality evaluation results of students to the teacher terminal, the administrator terminal and the parent terminal respectively, and visualizes them through mobile terminals and PC terminals. At the same time, the teacher terminal obtains the comprehensive quality evaluation results corresponding to all student terminals in the classes responsible by the teacher, the administrator terminal obtains the comprehensive quality evaluation results corresponding to all student terminals in the personal information of the students it manages, and the parent terminal obtains the comprehensive quality evaluation results corresponding to the student terminals associated with it.
[0009] Further, the specific process of calculating the quality evaluation coefficient of students according to the evaluation scores is as follows: S101. Obtain daily behavior data, where the daily behavior data includes attendance rate, task progress efficiency, and task completion rate. Among them: the attendance rate is the ratio of the actual working hours Ti to the total working hours Ts, that is ; The task progress efficiency is the ratio of the real-time task completion volume Sd to the total task cycle Ds: that is , where Sy is the total task volume, and Di is the real-time task progress cycle; The task completion rate is the ratio of the completion volume Ci after the task ends to the predetermined task volume Cs, that is ; S102. According to the preset evaluation criteria, quantify the attendance rate A, task progress efficiency B, and task completion rate C into evaluation scores one by one to obtain the attendance score a, task progress score b, and task completion score c; S103. Obtain practical evaluation data, where the practical evaluation data includes communication ability score e, learning ability score f, and innovation ability score g; S104. Calculate the quality evaluation coefficient Mk of students according to the following formula: , where e1, e2, e3, e4, e5, e6, α, and β are all preset weight coefficients. The quality evaluation coefficient of students is used to reflect the comprehensive performance status of students in practical projects. The higher the quality evaluation coefficient of students, the better the comprehensive performance of students in practical projects. On the contrary, the higher the quality evaluation coefficient of students, the worse the comprehensive performance of students in practical projects.
[0010] Further, the specific process of obtaining the objective comprehensive evaluation result is as follows: S201. Obtain the standard judgment data in the practical learning process. The standard judgment data is specifically the qualified attendance score, qualified task progress score, qualified task completion score, qualified communication ability score, qualified learning ability score, and qualified innovation ability score of students in the practical process; S202. Calculate the standard quality evaluation coefficient Mi according to the formula in the above S104, and then calculate the learning difference evaluation value: ; S203. Obtain the preset difference judgment interval (Mmin, Mmax). If the learning difference evaluation value is less than or equal to Mmin, the objective comprehensive evaluation result is that the performance in the practice process is excellent; If the learning difference evaluation value is less than Mmax or greater than Mmin, the objective comprehensive evaluation result is that the performance in the practice process is good; If the learning difference evaluation value is greater than or equal to Mmax, the objective comprehensive evaluation result is that the performance in the practice process is poor.
[0011] Furthermore, the specific process of obtaining the comprehensive quality evaluation result of students is as follows: S301. Obtain the evaluation keywords stored in the network database, and use TfidfVectorizer in sklearn to extract features from the evaluation keywords to obtain the standard vector Fn; S302. Obtain the administrator evaluation result and the teacher evaluation result at the administrator end, and use TfidfVectorizer in sklearn again to extract features from the administrator evaluation result and the teacher evaluation result in turn to obtain the feature vector F1 and the feature vector F2. The , ; S303. Calculate the vector similarity S1(F1, Fn) according to the following formula in turn: ; The vector similarity S2(F2, Fn): ; S303. Obtain the preset similarity threshold. If the vector similarity S1 is greater than or equal to the similarity threshold, use the administrator evaluation result as a correction factor to optimize the comprehensive quality evaluation result of students to obtain the comprehensive quality evaluation result of students; If the vector similarity S2 is greater than or equal to the similarity threshold, use the teacher evaluation result as a correction factor to optimize the comprehensive quality evaluation result of students to obtain the comprehensive quality evaluation result of students.
[0012] Furthermore, the specific process of deriving the parent account is as follows: S401. Obtain the student account, where the student account includes the account name, account password, and student personal information. The student personal information includes the student's name, the class where the student is located, the functional department where the student serves during the practice process, and the name and contact information of the student's parents; S402. Generate an account name suffix based on the kinship between parents and students, obtain the contact information of the students' parents, and verify the authenticity through text messages. After obtaining a qualified verification result, integrate the student account name with the account name suffix to generate the parent account name, and obtain the account password provided by the parent to integrate it into the parent account.
[0013] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows: For the student comprehensive quality evaluation system based on big data, the present invention obtains daily behavior data and practical evaluation data, quantifies the daily behavior data and practical evaluation data into evaluation scores according to the preset evaluation criteria, calculates the quality evaluation coefficient of the students based on the evaluation scores, and compares the data by combining the standard judgment data and the quality evaluation coefficient of the students to obtain an objective comprehensive evaluation result. Based on the administrator evaluation result and teacher evaluation result on the administrator side, keyword extraction is performed, and a correction factor is obtained after feature analysis. Based on the correction factor, the student comprehensive quality evaluation result is optimized to obtain the student comprehensive quality evaluation result. By standardizing the scoring of the actual performance of the students during the practice process, an objective comprehensive evaluation result is obtained. At the same time, the result is further corrected by combining the subjective evaluations of the teacher side and the person in charge of the practice project, ensuring the accuracy and fairness of the evaluation result. At the same time, a parent side is also provided to ensure that parents can obtain the daily activities of the students during the time when the students leave school, enhancing the effect of parental supervision and management. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] Figure 1 Shows the overall structural schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0015] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a 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 those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0016] Embodiment: As Figure 1 shown, a student comprehensive quality evaluation system based on big data includes a student side, a teacher side, an administrator side, and a quality evaluation platform; The student side is used to establish a student account based on the student's personal information and obtain the course schedule and work schedule through the student side; The teacher side is used to establish a teacher account based on the class responsible by the teacher, obtain the daily behavior data and practical evaluation data of the students during the practice process, give the teacher evaluation result according to the daily behavior data and practical evaluation data, and send it to the quality evaluation platform; The administrator terminal is used to establish an administrator account based on the functional department where the administrator is located and the personal information of the corresponding managed students, and is used to obtain the daily behavior data and practical evaluation data of the students during the practice process, give the administrator evaluation results according to the daily behavior data and practical evaluation data, and send them to the quality evaluation platform; The quality evaluation platform includes a comprehensive analysis unit, a standard evaluation unit, a feedback correction unit, and a result output unit; The comprehensive analysis unit includes a data acquisition module and a data analysis module. The data acquisition module is used to obtain the daily behavior data of students during the practice process through the enterprise's attendance system, obtain the practical evaluation data of students during the practice process through the enterprise's project supervision department, and send them to the data analysis module, the teacher terminal, and the administrator terminal; The data analysis module is used to obtain the daily behavior data and practical evaluation data, quantify the daily behavior data and practical evaluation data into evaluation scores according to the preset evaluation criteria, and calculate the quality evaluation coefficient of the students according to the evaluation scores and send it to the standard evaluation unit; The specific process of calculating the quality evaluation coefficient of students according to the evaluation scores is as follows: S101. Obtain the daily behavior data. The daily behavior data includes the attendance rate, task progress efficiency, and task completion degree. Among them: the attendance rate is the ratio of the actual working hours Ti to the total working hours Ts, that is ; The task progress efficiency is the ratio of the real-time task completion amount Sd to the total task cycle Ds: that is , where Sy is the total task amount, and Di is the real-time progress cycle of the task; The task completion degree is the ratio of the completion amount Ci after the task ends to the predetermined amount Cs of the task, that is ; S102. According to the preset evaluation criteria, quantify the attendance rate A, task progress efficiency B, and task completion degree C into evaluation scores one by one to obtain the attendance score a, task progress score b, and task completion score c; S103. Obtain the practical evaluation data. The practical evaluation data includes the communication ability score e, learning ability score f, and innovation ability score g; S104. Calculate the quality evaluation coefficient Mk of the students according to the following formula: , where e1, e2, e3, e4, e5, e6, and α, β are all preset weight coefficients. The quality evaluation coefficient of the students is used to reflect the comprehensive performance status of the students in the practical project. The higher the quality evaluation coefficient of the students, the better the comprehensive performance of the students in the practical project. On the contrary, the higher the quality evaluation coefficient of the students, the worse the comprehensive performance of the students in the practical project.
[0017] The standard evaluation unit is used to obtain the standard judgment data in the practical learning process, compare the data in combination with the quality evaluation coefficient of the students, obtain the learning difference evaluation value, judge the comprehensive performance of the students according to the preset difference judgment interval, obtain the objective comprehensive evaluation result, and output it to the feedback correction unit and the administrator terminal; The specific process of obtaining the objective comprehensive evaluation result is as follows: S201. Obtain the standard judgment data in the practical learning process. The standard judgment data specifically includes the qualified attendance score, qualified task progress score, qualified task completion score, qualified communication ability score, qualified learning ability score, and qualified innovation ability score of the students during the practice process; S202. Calculate the standard quality evaluation coefficient Mi according to the formula in the above S104, and then calculate the learning difference evaluation value: ; S203. Obtain the preset difference judgment interval (Mmin, Mmax). If the learning difference evaluation value is less than or equal to Mmin, the objective comprehensive evaluation result is that the performance in the practice process is excellent; If the learning difference evaluation value is less than Mmax or greater than Mmin, the objective comprehensive evaluation result is that the performance in the practice process is good; If the learning difference evaluation value is greater than or equal to Mmax, the objective comprehensive evaluation result is that the performance in the practice process is poor.
[0018] The feedback correction unit is used to obtain the objective comprehensive evaluation result and the administrator evaluation result from the administrator terminal, extract keywords based on the administrator evaluation result and the teacher evaluation result on the administrator terminal, obtain the correction factor after feature analysis, and optimize the comprehensive quality evaluation result of the students based on the correction factor to obtain the comprehensive quality evaluation result of the students and output it to the result output unit.
[0019] The specific process of obtaining the comprehensive quality evaluation result of the students is as follows: S301. Obtain the evaluation keywords stored in the network database, use TfidfVectorizer in sklearn to extract features from the evaluation keywords, and obtain the standard vector Fn; S302. Obtain the administrator evaluation result and the teacher evaluation result from the administrator terminal, and use TfidfVectorizer in sklearn again to extract features from the administrator evaluation result and the teacher evaluation result in turn, and obtain the feature vector F1 and the feature vector F2, , ; S303. Calculate the vector similarity S1(F1, Fn) according to the following formula in turn: ; The vector similarity S2(F2, Fn): ; S303. Obtain a preset similarity threshold. If the vector similarity S1 is greater than or equal to the similarity threshold, use the administrator's evaluation result as a correction factor, that is, the administrator's evaluation result is more inclined to the preset evaluation keywords, and its evaluation is more in line with the evaluation criteria, and optimize the student's comprehensive quality evaluation result to obtain the student's comprehensive quality evaluation result. If the vector similarity S2 is greater than or equal to the similarity threshold, that is, the teacher's evaluation result is more inclined to the preset evaluation keywords, and its evaluation is more in line with the evaluation criteria, then use the teacher's evaluation result as a correction factor to optimize the student's comprehensive quality evaluation result to obtain the student's comprehensive quality evaluation result.
[0020] It also includes a parent terminal, which is used to derive a parent account based on the student account, obtain the daily behavior data of the student during the practice process and the living area information data of the enterprise where the student is located, and at the same time obtain the student's comprehensive quality evaluation result of the quality evaluation platform, so as to ensure that during the period when the student leaves school, the parents can also master the student's life and learning trends, and can directly understand the student's comprehensive quality evaluation result, and the parents can also play a role in supervision and management.
[0021] The specific process of deriving the parent account is as follows: S401. Obtain the student account, which includes the account name, account password, and student's personal information. The student's personal information includes the student's name, the class where the student is located, the functional department where the student holds a position during the practice process, and the names and contact information of the student's parents. S402. Generate an account name suffix according to the kinship between the parent and the student, obtain the contact information of the student's parents, and verify the authenticity through text messages. After obtaining the verification qualified result, integrate the student account name and the account name suffix to generate the parent account name, and obtain the account password provided by the parent to integrate into the parent account.
[0022] The result output unit obtains the student's comprehensive quality evaluation result and sends the student's comprehensive quality evaluation result to the teacher terminal, the administrator terminal, and the parent terminal respectively for visual display through the mobile terminal and the PC terminal. At the same time, the teacher terminal obtains the student's comprehensive quality evaluation results corresponding to all student terminals in the class responsible by the teacher, the administrator terminal obtains the student's comprehensive quality evaluation results corresponding to all student terminals in the student personal information managed by the administrator, and the parent terminal obtains the student's comprehensive quality evaluation results corresponding to the student terminals associated with it.
[0023] The present invention obtains daily behavior data and practical evaluation data, quantifies the daily behavior data and practical evaluation data into evaluation scores according to a preset evaluation standard, calculates the quality evaluation coefficient of a student based on the evaluation scores, compares the data by combining the standard judgment data and the quality evaluation coefficient of the student to obtain an objective comprehensive evaluation result, extracts keywords based on the administrator evaluation result and teacher evaluation result on the administrator side, obtains a correction factor after feature analysis, optimizes the comprehensive evaluation result of the student's quality based on the correction factor to obtain the comprehensive evaluation result of the student's quality, obtains an objective comprehensive evaluation result by performing a standardized score on the actual performance of the student during the practice process, and further corrects the result by combining the subjective evaluations of the teacher side and the person in charge of the practice project, ensuring the accuracy and fairness of the evaluation result. At the same time, a parent side is also provided to ensure that parents can obtain the daily activities of the student during the time when the student is away from school, enhancing the effect of parental supervision and management.
[0024] The setting of the size of the interval and threshold is for the convenience of comparison. Regarding the size of the threshold, it depends on the amount of sample data and the number of base numbers set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.
[0025] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes should be covered within the protection scope of the present invention.
Claims
1. A student comprehensive quality evaluation system based on big data, characterized in that, It includes a student terminal, a teacher terminal, an administrator terminal, and a quality evaluation platform; The student terminal is used to establish a student account based on the student's personal information, and obtain the course schedule and work schedule through the student terminal; The teacher terminal is used to establish a teacher account based on the classes responsible by the teacher, obtain the daily behavior data and practical evaluation data of students during the practice process, give the teacher evaluation results according to the daily behavior data and practical evaluation data, and send them to the quality evaluation platform; The administrator terminal is used to establish an administrator account based on the functional department where the administrator is located and the corresponding student personal information managed, obtain the daily behavior data and practical evaluation data of students during the practice process, give the administrator evaluation results according to the daily behavior data and practical evaluation data, and send them to the quality evaluation platform; The quality evaluation platform includes a comprehensive analysis unit, a standard evaluation unit, a feedback correction unit, and a result output unit; The comprehensive analysis unit includes a data acquisition module and a data analysis module. The data acquisition module is used to obtain the daily behavior data of students during the practice process through the enterprise's attendance system, obtain the practical evaluation data of students during the practice process through the enterprise's project supervision department, and send them to the data analysis module, the teacher terminal, and the administrator terminal; The data analysis module is used to obtain the daily behavior data and practical evaluation data, quantify the daily behavior data and practical evaluation data into evaluation scores according to the preset evaluation criteria, calculate the quality evaluation coefficient of the student according to the evaluation scores, and send it to the standard evaluation unit; The standard evaluation unit is used to obtain the standard judgment data during the practical learning process, compare the data in combination with the quality evaluation coefficient of the student, obtain the learning difference evaluation value, judge the comprehensive performance of the student according to the preset difference judgment interval, obtain the objective comprehensive evaluation result, and output it to the feedback correction unit and the administrator terminal; The feedback correction unit is used to obtain the objective comprehensive evaluation result and the administrator evaluation result from the administrator terminal, extract keywords based on the administrator evaluation result and teacher evaluation result from the administrator terminal, obtain the correction factor after feature analysis, and optimize the student comprehensive quality evaluation result based on the correction factor to obtain the student comprehensive quality evaluation result and output it to the result output unit.
2. The student comprehensive quality evaluation system based on big data according to claim 1, characterized in that, It also includes a parent terminal. The parent terminal is used to derive a parent account based on the student account, obtain the daily behavior data of the student during the practice process and the living area information data of the enterprise where the student is located, and at the same time obtain the student comprehensive quality evaluation result of the quality evaluation platform.
3. The student comprehensive quality evaluation system based on big data according to claim 1, characterized in that The result output unit obtains the student comprehensive quality evaluation result, and sends the student comprehensive quality evaluation result to the teacher terminal, the administrator terminal, and the parent terminal respectively, and conducts visual display through the mobile terminal and the PC terminal. At the same time, the teacher terminal obtains the student comprehensive quality evaluation results corresponding to all student terminals in the class responsible by the teacher, the administrator terminal obtains the student comprehensive quality evaluation results corresponding to all student terminals in the student personal information managed, and the parent terminal obtains the student comprehensive quality evaluation results corresponding to the student terminal associated with it.
4. A student comprehensive quality evaluation system based on big data according to claim 1, characterized in that, The specific process of calculating the quality evaluation coefficient of the student according to the evaluation score is as follows: S101. Obtain daily behavior data, where the daily behavior data includes attendance rate, task progress efficiency, and task completion rate, and: the attendance rate is the ratio of the actual working hours Ti to the total working hours Ts, that is ; The task progress efficiency is the ratio of the real-time task completion quantity Sd to the total task cycle Ds: that is , where Sy is the total task quantity and Di is the real-time task progress cycle; The task completion rate is the ratio of the completed quantity Ci after the task ends to the predetermined quantity Cs of the task, that is ; S102. Quantify the attendance rate A, task progress efficiency B, and task completion rate C into evaluation scores one by one according to the preset evaluation criteria to obtain the attendance evaluation score a, task progress evaluation score b, and task completion evaluation score c; S103. Obtain the practical evaluation data, where the practical evaluation data includes the communication ability score e, learning ability score f, and innovation ability score g; S104. Calculate the quality evaluation coefficient Mk of the student according to the following formula: , where e1, e2, e3, e4, e5, e6, and α, β are all preset weight coefficients, and the quality evaluation coefficient of the student is used to reflect the comprehensive performance status of the student in the practical project.
5. The student comprehensive quality evaluation system based on big data according to claim 4, wherein The specific process of obtaining the objective comprehensive evaluation result is as follows: S201. Obtain the standard judgment data in the practical learning process. The standard judgment data is specifically the qualified attendance evaluation score, qualified task progress evaluation score, and qualified task completion evaluation score of the student during the practical process, as well as the qualified communication ability score, qualified learning ability score, and qualified innovation ability score; S202. Calculate the standard quality evaluation coefficient Mi according to the formula in the above S104, and then calculate the learning difference evaluation value: ; S203. Obtain the preset difference judgment interval (Mmin, Mmax). If the learning difference evaluation value is less than or equal to Mmin, the objective comprehensive evaluation result is that the practical process score is excellent; If the learning difference evaluation value is less than Mmax or greater than Mmin, the objective comprehensive evaluation result is that the performance in the practical process is good; If the learning difference evaluation value is greater than or equal to Mmax, the objective comprehensive evaluation result is that the performance in the practical process is poor.
6. The student comprehensive quality evaluation system based on big data according to claim 1, characterized in that, The specific process of obtaining the comprehensive quality evaluation result of the student is as follows: S301. Obtain the evaluation keywords stored in the network database, and use TfidfVectorizer in sklearn to extract features from the evaluation keywords to obtain the standard vector Fn; S302. Obtain the administrator evaluation results and teacher evaluation results on the administrator side. Use the TfidfVectorizer in sklearn again to perform feature extraction on the administrator evaluation results and teacher evaluation results in sequence, and obtain the feature vector F1 and the feature vector F2. The , ; S303. Calculate the vector similarity S1(F1, Fn) successively according to the following formula: ; Vector similarity S2(F2, Fn): ; S303. Obtain the preset similarity threshold. If the vector similarity S1 is greater than or equal to the similarity threshold, use the administrator evaluation result as a correction factor to optimize the comprehensive quality evaluation result of the student to obtain the comprehensive quality evaluation result of the student; If the vector similarity S2 is greater than or equal to the similarity threshold, use the teacher evaluation result as a correction factor to optimize the comprehensive quality evaluation result of the student to obtain the comprehensive quality evaluation result of the student.
7. The student comprehensive quality evaluation system based on big data according to claim 2, wherein, The specific process of deriving the parent account is as follows: S401. Obtain the student account, where the student account includes the account name, account password, and student personal information. The student personal information includes the student's name, the class where the student is located, the functional department where the student holds a position during the practical process, and the name and contact information of the student's parents; S402. Generate an account name suffix according to the kinship between the parent and the student, obtain the contact information of the student's parents, and verify the authenticity through text messages. After obtaining the verification qualified result, integrate the student account name and the account name suffix to generate the parent account name, and obtain the account password provided by the parent to integrate into the parent account.
Citation Information
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