Intelligent preschool education management method based on regional management

Abstract

The invention relates to the technical field of preschool education management, and discloses an intelligent preschool education management method based on regional management, which comprises the following steps that: basic information and teaching activity data of teachers and students are collected, the teachers input personal information through a login module of a system, and the personal information comprises names, genders, birth dates, educational background, title names and work experiences; the data acquisition process adopts a form form, so that the integrity and accuracy of information input are ensured; student information is input by a class owner or a school administrator in a unified mode and comprises names, genders, birth dates and parent contact information, the system provides a batch import function, data import in an Exce l file format is supported, and data input efficiency is improved. Through integration of teacher personnel archive management, teaching activity management, education supervision management, student comprehensive quality evaluation and an intelligent pick-up attendance system, intelligence and informatization of preschool education management are realized, and management efficiency and education quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of early childhood education management, and in particular to a smart early childhood education management method based on regional management. Background Art

[0002] With the development of society and changes in family structure, parents have higher and higher requirements for the quality of kindergarten education and service level. The emergence of smart early childhood education management methods is precisely to better meet these needs and improve the efficiency and quality of education management. By dividing kindergartens into different areas according to geographical location, it is helpful to more accurately understand and serve the needs of local families. Each area can adjust the teaching content, curriculum setting, teacher allocation, etc. according to specific circumstances, so that educational resources can be more balanced and effectively utilized.

[0003] At present, the following problems are common in early childhood education management: the information management of teachers and students is decentralized, and the efficiency of data collection and processing is low; there is a lack of systematic management of teaching activities and educational supervision, which makes it difficult to fully grasp the teaching quality and activity effects. The existing technology is difficult to provide an integrated management platform, and it is impossible to achieve comprehensive coverage and optimization of early childhood education management. For this reason, the present invention proposes a smart early childhood education management method based on regional management. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a smart preschool education management method based on regional management, which solves the problems of decentralized information management of teachers and students, low efficiency in data collection and processing, lack of systematic management of teaching activities and educational supervision, and difficulty in fully grasping the teaching quality and activity effects.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a smart early childhood education management method based on regional management, comprising the following steps:

[0006] Collect basic information and teaching activity data of teachers and students. Teachers enter personal information, including name, gender, date of birth, education, title, and work experience, through the system login module. The data collection process adopts a form to ensure the completeness and accuracy of the information input;

[0007] The student information is uniformly entered by the class teacher or school administrator, including name, gender, date of birth, and parent contact information. The system provides a batch import function and supports data import in Excel file format to improve data entry efficiency;

[0008] Teachers record detailed information of each teaching activity in the system, including teaching content, teaching methods, activity time, and participating students. The system provides an automated data entry interface, and teachers can enter data directly through a mobile app or computer, which is convenient and efficient.

[0009] Use data analysis algorithms to process and analyze the collected basic information and teaching activity data;

[0010] First, the collected data is cleaned, missing values ​​and outliers are processed to ensure the integrity and consistency of the data. For missing data, the system will mark it and notify relevant personnel to supplement it.

[0011] Then, a clustering algorithm was used to classify the teachers’ ages and titles, identifying the distribution of different age groups and titles;

[0012] The specific system will initialize K cluster centers, calculate the distance from each data point to the cluster center, assign the data point to the nearest cluster center, and then update the cluster center, repeating the above steps until the cluster center converges or reaches the maximum number of iterations:

[0013]

[0014] Among them, d(x i , c j ) is the distance from data point xi to cluster center c j The Euclidean distance, c j is the jth cluster center, x i is the ith data point, x ik is the data point x i The value in the kth dimension, c jk is the cluster center c j The value at the kth dimension, where n is the dimensionality of the data.

[0015] Cluster center update:

[0016]

[0017] Among them, |C j |The number of all data points belonging to the jth cluster.

[0018] Convergence conditions:

[0019]

[0020] The algorithm converges when the above values ​​change little between two iterations or when the maximum number of iterations is reached.

[0021] K is the number of clusters, ||x i -c j || is the data point x i To cluster center c j distance.

[0022] Through the management of teachers' personnel files, teaching activities, education supervision, comprehensive quality evaluation of students and intelligent pick-up and drop-off attendance, the management of preschool education in the region is intelligent and informationized;

[0023] In the management of teaching activities, organize and manage the teaching resource evaluation and teaching research activities in the region;

[0024] In the education supervision and management, supervise and evaluate the educational activities in the region;

[0025] In the evaluation of students’ comprehensive qualities, the comprehensive qualities of students are measured and managed;

[0026] In smart pick-up and attendance, facial recognition technology is used to achieve smart pick-up and attendance management for children and their parents.

[0027] Preferably, in the teacher personnel file management, the following steps are included:

[0028] Provide login portals for teachers, school administrators, and education bureau administrators;

[0029] Enter and manage teachers' basic information;

[0030] Display and manage information of all schools in the jurisdiction;

[0031] Analyze teacher data, including age distribution and job title distribution.

[0032] Preferably, in the teacher data analysis, a data analysis algorithm is used to classify and count the age distribution and professional title distribution of the teachers.

[0033] Preferably, in the teaching activity management, the following steps are included:

[0034] Release notices on teaching resource evaluation and teaching and research activities;

[0035] Teachers check the event details and sign up to participate;

[0036] Create and manage teaching activities, including setting activity content, time and location;

[0037] Record data during the activity, including the number of teachers participating and feedback.

[0038] Preferably, in the education supervision management, the following steps are included:

[0039] Develop a district-wide supervision plan and assign responsible supervisors;

[0040] Inspectors record and submit reports on each supervision activity;

[0041] Public supervision information is available for authorized users to view;

[0042] Manage and evaluate the activities of supervisors.

[0043] Preferably, the comprehensive quality evaluation of students includes the following steps:

[0044] Create comprehensive quality assessment tasks for each student, including academic performance, physical fitness tests, and artistic performance;

[0045] Enter the results of students completing the assessment task;

[0046] Generate a comprehensive quality evaluation report for students based on the evaluation results, and provide class and school evaluation statistical reports.

[0047] Preferably, the intelligent pick-up and drop-off attendance includes the following steps:

[0048] Collect attendance data of children and parents through facial recognition technology;

[0049] Generate and manage daily attendance data;

[0050] Push attendance data to parents, teachers and principals in real time.

[0051] Preferably, the steps of using face recognition technology include:

[0052] Use access control equipment to collect facial images;

[0053] Upload the collected facial images to the system for recognition;

[0054] Upload and receive identification information via wireless communication.

[0055] Preferably, the step of face recognition includes:

[0056] Grayscale value conversion, face area extraction and format standardization of face images;

[0057] Use the improved convolutional neural network (CNN) model for face recognition and attendance data generation;

[0058] The system collects facial images of children and parents through access control devices, performs facial recognition, and records pick-up and drop-off attendance data. The system pushes attendance information to parents, teachers, and principals in real time to ensure the safety of children.

[0059] The specific recognition process includes grayscale value conversion, face area extraction and format standardization. The improved convolutional neural network (CNN) model is used for face recognition and attendance data generation. The formula is as follows:

[0060] Convolution operation:

[0061] H ij =f(W·X ij +b)

[0062] H ij is the feature map output by the convolutional layer, f is the activation function ReLU, W is the convolution kernel (weight matrix), X ij is the local area of ​​the input image at position (i, j), and b is the bias term.

[0063] Max Pooling Layer:

[0064]

[0065] P ij is the output of the pooling layer, H (i+m)(j+n) is the value of the convolution layer output within the pooling window, and m and n are the sizes of the pooling window.

[0066] Fully connected layer:

[0067] y=f(W fc ·x+b fc )

[0068] y is the output of the fully connected layer, f is the activation function ReLU, W fc is the weight matrix of the fully connected layer, x is the input vector (the flattened feature map), b fc is the bias term of the fully connected layer.

[0069] Improved convolution kernel output:

[0070]

[0071] Among them, F i is the output of the i-th convolution kernel, W i is the weight matrix of the i-th convolution kernel, S is the input feature map, a i is the bias term of the i-th convolution kernel, λ is the regularization coefficient, X j is the set of weights associated with each class, where the ReLU loss function is:

[0072]

[0073] Among them, L is the loss function, y i is the actual label, is the predicted label and N is the number of samples.

[0074] Preferably, the collected data is processed and analyzed through deep learning technology to achieve intelligent management of teachers, students and teaching activities, thereby improving the efficiency and quality of preschool education management.

[0075] The present invention provides a smart early childhood education management method based on regional management. It has the following beneficial effects:

[0076] 1. The present invention realizes the intelligence and informatization of preschool education management and improves management efficiency and education quality by integrating teacher personnel file management, teaching activity management, education supervision management, student comprehensive quality evaluation and intelligent pick-up and attendance system.

[0077] 2. Through systematic data collection and analysis, the present invention improves the efficiency and accuracy of teacher personnel file management and student comprehensive quality evaluation, providing a scientific basis for educational management decision-making.

[0078] 3. The present invention improves the standardization and transparency of activity organization and supervision through systematic teaching activities and education supervision management, and enhances the effectiveness of activity participation and education quality supervision.

[0079] 4. The present invention ensures the safe pick-up and drop-off of children through intelligent pick-up and drop-off attendance management based on face recognition technology, and improves the efficiency and accuracy of attendance work. DETAILED DESCRIPTION

[0080] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0081] Embodiment 1: The embodiment of the present invention provides a smart early childhood education management method based on regional management, including teacher personnel file management:

[0082] 1. Test experiment:

[0083] Data Entry Test:

[0084] Purpose: To test the speed and accuracy of data entry into the system by teachers and school administrators.

[0085] Methods: In the test environment, 10 teachers and 5 school administrators were simulated to enter basic information, and the time and error rate were recorded.

[0086] Data collection: entry time, entry error rate.

[0087] Data analysis test:

[0088] Purpose: To test the system's ability to analyze teacher data.

[0089] Methods: Data of 1,000 teachers were imported, and the age distribution and job title distribution were analyzed using the system, and the analysis time and accuracy were recorded.

[0090] Data collection: analysis time, analysis accuracy.

[0091] 2. Comparative experiment:

[0092] Comparison with traditional paper file management:

[0093] Purpose: To compare the differences in efficiency and accuracy between traditional paper-based archive management and system management.

[0094] Methods: Data of the same batch of teachers were entered and analyzed using paper archives and the system, and the time and error rate were recorded.

[0095] Data collection: entry time, entry error rate, analysis time, analysis accuracy.

[0096] Embodiment 2: The embodiment of the present invention provides a smart early childhood education management method based on regional management, including teaching activity management:

[0097] 1. Test experiment:

[0098] Activity organization test:

[0099] Purpose: To test the efficiency of the system in publishing notifications on teaching resource evaluation and teaching and research activities.

[0100] Method: Publish 10 different types of activity notifications in the system and record the publishing time and participation rate.

[0101] Data collection: release time, participation rate.

[0102] Activity Management Test:

[0103] Purpose: To test the system's ability to manage activities.

[0104] Method: Create 5 activities in the system and record data during the activities, including the number of participants and feedback rate.

[0105] Data collection: activity creation time, number of participants, and feedback rate.

[0106] 2. Comparative experiment:

[0107] Traditional event management comparison:

[0108] Purpose: To compare the efficiency differences between traditional activity management methods and system management.

[0109] Methods: Five identical activities were managed using traditional methods and the system, and the organization and management time, number of participants, and feedback rate were recorded.

[0110] Data collection: organization time, management time, number of participants, and feedback rate.

[0111] Embodiment 3: The embodiment of the present invention provides a smart early childhood education management method based on regional management, including education supervision management:

[0112] 1. Test experiment:

[0113] Supervision activity test:

[0114] Purpose: To test the system's ability to manage and record educational supervision activities.

[0115] Methods: Ten supervisory activities were simulated and supervisors’ activity records and report submission time were recorded.

[0116] Data collection: activity recording time, report submission time.

[0117] Supervision of information disclosure test:

[0118] Purpose: To test the system's transparency in providing supervisory information.

[0119] Methods: Five supervision reports were made public and the number of views and feedback were recorded.

[0120] Data collection: number of views, feedback.

[0121] 2. Comparative experiment:

[0122] Comparison with traditional supervision management:

[0123] Purpose: To compare the differences in efficiency and transparency between traditional supervisory management methods and system management.

[0124] Methods: Ten supervision activities were managed using traditional methods and the system, and the activity recording time, report submission time, number of times the public information was viewed, and feedback were recorded.

[0125] Data collection: activity recording time, report submission time, number of views, and feedback.

[0126] Embodiment 4: The embodiment of the present invention provides a smart early childhood education management method based on regional management, including comprehensive quality evaluation of students

[0127] 1. Test experiment:

[0128] Assessment Management Test:

[0129] Purpose: To test the system's ability to create and manage comprehensive quality assessments of students.

[0130] Methods: Create assessment tasks for 100 students and record the creation time and the time of entering the assessment results.

[0131] Data collection: creation time, evaluation result entry time.

[0132] Data statistical test:

[0133] Purpose: To test the system's statistical and analytical capabilities for evaluation data.

[0134] Method: Import assessment data, generate class and school assessment reports, and record statistical time and accuracy.

[0135] Data collection: statistical time, statistical accuracy.

[0136] 2. Comparative experiment:

[0137] Comparison with traditional assessment management:

[0138] Purpose: To compare the differences in efficiency and accuracy between traditional assessment management methods and system management.

[0139] Methods: The traditional method and the system were used to conduct student assessments, and the creation time, assessment result entry time, statistical time and statistical accuracy were recorded.

[0140] Data collection: creation time, evaluation result entry time, statistical time, and statistical accuracy.

[0141] Embodiment 5: The embodiment of the present invention provides a smart early childhood education management method based on regional management, including intelligent pick-up and attendance management

[0142] 1. Test experiment:

[0143] Face recognition test:

[0144] Purpose: To test the accuracy and speed of the system's face recognition on young children and their parents.

[0145] Methods: 100 pick-up and drop-off attendances were simulated in the system, and the recognition accuracy and recognition time were recorded.

[0146] Data collection: recognition accuracy, recognition time.

[0147] Attendance data statistics test:

[0148] Purpose: To test the system's ability to collect and push attendance data.

[0149] Method: Simulate one month's attendance data statistics, record the statistical time and push success rate.

[0150] Data collection: statistics time, push success rate.

[0151] 2. Comparative experiment:

[0152] Comparison with traditional attendance management:

[0153] Purpose: To compare the differences in efficiency and accuracy between traditional attendance management methods and system management.

[0154] Methods: The traditional method and the system were used for pick-up and drop-off attendance, and the recognition accuracy, recognition time, statistical time and push success rate were recorded.

[0155] Data collection: recognition accuracy, recognition time, statistical time, and push success rate.

[0156] The comparative experimental data is shown in Table 1 below:

[0157]

[0158]

[0159] Table 1

[0160] Experimental results:

[0161] Management efficiency: The experimental group spent significantly less time on activity organization, data entry, and data analysis than the control group;

[0162] Data accuracy: The data entry error rate and face recognition error rate of the experimental group were significantly lower than those of the control group;

[0163] Conclusion: Through the above experiments and comparative data, it can be clearly seen that the smart early childhood education management method based on regional management is significantly superior to the traditional management method in terms of management efficiency, data accuracy, activity participation and feedback rate, thereby improving the overall quality and effectiveness of early childhood education management.

[0164] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart early childhood education management method based on regional management, characterized in that: The following steps are involved: Collect basic information of teachers and students and teaching activity data; Use data analysis algorithms to process and analyze the collected basic information and teaching activity data; Through the management of teachers' personnel files, teaching activities, education supervision, comprehensive quality evaluation of students and intelligent pick-up and drop-off attendance, the management of preschool education in the region is intelligent and informationized; In the management of teaching activities, organize and manage the teaching resource evaluation and teaching research activities in the region; In the education supervision and management, supervise and evaluate the educational activities in the region; In the evaluation of students’ comprehensive qualities, the comprehensive qualities of students are measured and managed; In smart pick-up and attendance, facial recognition technology is used to achieve smart pick-up and attendance management for children and their parents.

2. According to the method of smart early childhood education management based on regional management according to claim 1, it is characterized in that: In the management of teacher personnel files, the following steps are included: Provide login portals for teachers, school administrators, and education bureau administrators; Enter and manage teachers' basic information; Display and manage information of all schools in the jurisdiction; Analyze teacher data, including age distribution and job title distribution.

3. The method for smart early childhood education management based on regional management according to claim 2, characterized in that: In the teacher data analysis, data analysis algorithms are used to classify and count the age distribution and job title distribution of teachers.

4. The method for smart early childhood education management based on regional management according to claim 1, characterized in that: In the teaching activity management, the following steps are included: Release notices on teaching resource evaluation and teaching and research activities; Teachers check the event details and sign up to participate; Create and manage teaching activities, including setting activity content, time and location; Record data during the activity, including the number of teachers participating and feedback.

5. The method for smart early childhood education management based on regional management according to claim 1, characterized in that: In education supervision and management, the following steps are included: Develop a district-wide supervision plan and assign responsible supervisors; Inspectors record and submit reports on each supervision activity; Public supervision information is available for authorized users to view; Manage and evaluate the activities of supervisors.

6. The method for smart early childhood education management based on regional management according to claim 1, characterized in that: The comprehensive quality evaluation of students includes the following steps: Create comprehensive quality assessment tasks for each student, including academic performance, physical fitness tests, and artistic performance; Enter the results of students completing the assessment task; Generate a comprehensive quality evaluation report for students based on the evaluation results, and provide class and school evaluation statistical reports.

7. The method for smart early childhood education management based on regional management according to claim 1, characterized in that: In the smart pick-up and drop-off attendance, the following steps are included: Collect attendance data of children and parents through facial recognition technology; Generate and manage daily attendance data; Push attendance data to parents, teachers and principals in real time.

8. The method for managing smart early childhood education based on regional management according to claim 7, characterized in that: The steps to adopt facial recognition technology include: Use access control equipment to collect facial images; Upload the collected facial images to the system for recognition; Upload and receive identification information via wireless communication.

9. The method for managing smart early childhood education based on regional management according to claim 8, characterized in that: The steps of face recognition include: Grayscale value conversion, face area extraction and format standardization of face images; The improved convolutional neural network (CNN) model is used for face recognition and attendance data generation.

10. The smart early childhood education management method based on regional management according to claim 1, characterized in that: By processing and analyzing the collected data through deep learning technology, intelligent management of teachers, students and teaching activities can be achieved, thereby improving the efficiency and quality of preschool education management.

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