A Visualized and Intelligent Course Scheduling Method and System Based on Big Data

Abstract

This invention relates to the technical field of teaching scheduling management, and discloses a method and system for visualized intelligent scheduling of student learning courses based on big data. The system includes a student preset timetable management module, a student customized timetable management module, and a student timetable comprehensive creation module. It dynamically creates personalized blank timetables for student groups based on table text processing, enabling students to rationally and scientifically arrange their course order according to their personal learning plans. Based on the blank timetable text information and contact information of target students, and combined with a course management platform and social software, it autonomously and efficiently performs the task of creating and collecting timetable text information for the target student group at specific times. Simultaneously, it combines data analysis to comprehensively analyze the existence of timetable customization results for the student group, achieving reliable timetable creation based on both preset and customized timetables, thus improving the scientific nature and personalization of scheduling management.

Description

Technical Field

[0001] This invention relates to the technical field of teaching scheduling management, specifically to a method and system for visual intelligent scheduling of student learning courses based on big data. Background Technology

[0002] A teaching scheduling system is an intelligent academic management tool based on advanced algorithms and big data technology, designed to automatically complete complex tasks such as course arrangement, teacher allocation, and classroom scheduling. These systems are typically built using technologies such as Spring Boot and Vue.js, and include three core modules: scheduling algorithms, user interface, and data management. Key technologies such as genetic algorithms, greedy algorithms, and backtracking algorithms can handle multi-dimensional constraints such as teacher time conflicts and classroom capacity limitations. Modern teaching scheduling systems utilize AI-driven intelligent scheduling engines and possess high concurrency processing capabilities, capable of handling peak traffic of tens of thousands of people simultaneously selecting courses online. The system also integrates mobile collaboration functions, allowing teachers and parents to view real-time class rescheduling updates. However, existing teaching scheduling systems cannot intelligently customize schedules based on preset timetables and students' individual learning plans, nor can they comprehensively optimize teaching scheduling based on customized timetable results, thus failing to improve the scientific nature and quality of teaching scheduling.

[0003] Chinese invention patent application CN116563066A, published on August 8, 2023, discloses an intelligent scheduling system based on an artificial intelligence self-learning algorithm. By establishing a self-learning model, it automatically calculates the scheduling difficulty of teachers, classes, and classrooms to determine the initial queuing training model for teaching tasks. After self-learning queuing training, a reasonable order is finally obtained, and the scheduling is completed. The technical solution provided by this invention achieves artificial intelligence self-learning training, obtaining charts and data of "unscheduled class hours" and "undesired class hours" in each round of the self-learning process. It allows users to select rounds with 0 "unscheduled class hours" and the fewest "undesired class hours" to obtain the optimal timetable, thus achieving more efficient intelligent scheduling. However, the above technical solution cannot simultaneously and scientifically reconcile the contradiction between the stability of traditional fixed timetables and the flexibility of personalized timetables, easily leading to a waste of teaching resources and an increased teaching burden. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] To address the shortcomings of existing teaching scheduling systems, such as their inability to intelligently customize timetables based on preset schedules and individual student learning plans, and their inability to comprehensively optimize teaching scheduling based on customized timetable results, thus improving the scientific nature and quality of teaching scheduling, this system aims to achieve the following: efficiently collect characteristic information of target student groups and specific time points for student scheduling; accurately search for contact information of target students; autonomously search and obtain preset timetables for target student groups at specific time points; scientifically construct blank timetables for target student groups; efficiently search for teaching course information for target student groups at specific time points; efficiently customize and collect customized timetables for target students; dynamically analyze the feedback results of timetable development for target student groups; intelligently analyze the types of customized timetables for target students; accurately evaluate the optimal customized timetable for target student groups; and comprehensively develop teaching timetables for target student groups at specific time points.

[0006] (II) Technical Solution

[0007] This invention is achieved through the following technical solution: a student learning course visualization and intelligent scheduling method based on big data, the method comprising the following steps:

[0008] S1. Collect characteristic information of the target student group and information on specific time points of student class scheduling; search and process the contact information of individual students in the target student group to obtain the contact information of the target students; identify and process the text information of the preset timetable of the target student group at specific time points to obtain the text information of the preset timetable of the target student group at specific time points.

[0009] S2. Construct and process the teaching course information and blank timetables required for scheduling classes for the target student group at a specific time point, and obtain the teaching course information and blank timetable text information of the target student group at a specific time point respectively.

[0010] S3. Perform the task of creating and collecting timetable text information for the target student group at a specific time point, obtain the customized timetable text information for the target students, and analyze and process the feedback results of the timetable customization for the target student group at a specific time to obtain the timetable customization feedback result information for the target student group; if there is no customized timetable, directly execute step S5;

[0011] S4. When customized timetables exist, classify the customized timetables of the target students to obtain the text information of the customized timetables of the target students; evaluate the optimal customized timetable required by the target student group at a specific time point to obtain the text information of the optimal customized timetable of the target student group.

[0012] S5. Comprehensively formulate and process the teaching schedules for the target student group at specific time points, obtain the text information of the teaching schedules for the target student group at specific time points, and output it.

[0013] Preferably, the steps for collecting characteristic information of the target student group and information on specific time points in student class scheduling are as follows: Searching and processing the contact information of individual students in the target student group to obtain their contact information; and recognizing and processing the text information of the preset timetable for the target student group at specific time points to obtain the text information of the preset timetable for the target student group at those specific time points.

[0014] S11. Collect the class name and class number characteristics of the target student group waiting for customized course scheduling online through the course management platform, and obtain the target student group characteristic information; the course management platform includes any one of Blue Crane Course Schedule Management Platform, School Butler Intelligent Course Scheduling Management Platform, and Cloud Classroom Course Scheduling Management Platform;

[0015] The course management platform collects information on the specific future dates and times of the target student group waiting for customized course scheduling, and obtains the specific time information of the student's course scheduling; the unit of the specific time information of the student's course scheduling is mainly composed of year, month and day;

[0016] S12. Based on the target student group feature information and the student group standard student individual contact information database matrix, perform search processing on the contact information of the students in the target student group to obtain the target student contact information set; based on the target student group feature information, the student scheduling specific time point information and the student group's preset timetable text information set at different times, perform preset timetable text information recognition processing on the target student group at a specific time point to obtain the target student group's preset timetable text information at a specific time point.

[0017] Preferably, the following steps are taken to perform a search for individual student contact information within the target student group based on the target student group's characteristic information and the standard student individual contact information database matrix, to obtain a target student contact information set; and to perform a recognition process for the target student group's preset timetable text information at a specific time point based on the target student group's characteristic information, the student's specific time point scheduling information, and the student group's preset timetable text information set at different times, to obtain the target student group's preset timetable text information at a specific time point, as follows:

[0018] S121. Establish a database matrix of student group standard student individual contact information. ,in Indicates the first A standard student individual contact information database for each student group, wherein the standard student individual contact information database represents a database of standard student individual contact information set for different student groups, wherein the student individual contact information includes each student's QQ number and WeChat ID;

[0019] Establish a text information set of pre-set class schedules for different time periods for student groups. ,in Indicates the first The text information refers to the preset timetables for different student groups at different times, which represent the teaching course schedules preset for different student groups at different times of the day. The teaching course schedules include student group information, teaching day time, teaching course name information, and teaching course time period. The teaching course time period is mainly composed of year, month, day, hour, and minute.

[0020] S122. Using a breadth-first search algorithm, the target student group feature information is compared with the student group's standard student individual contact information matrix. The student group standard student individual contact information database described in the article Perform student group feature information matching to search the standard student individual contact information database corresponding to the target student group feature information. And through data identification, a set of contact information for target scheduling students is generated. ,in Indicates the first among the target student group The target scheduling student contact information corresponds to each individual student, and the target scheduling student contact information represents the contact information of each individual student waiting for scheduling in the target student group;

[0021] S123. Using the breadth-first search algorithm as in step S122, the target student group feature information, the student class scheduling specific time point information, and the student group's pre-set timetable text information set at different times are compared. The text information of the preset class schedules for different time periods for the student groups described in the article Matching student group characteristics with class scheduling time information, the system retrieves the target student group's characteristic information and the specific class scheduling time information corresponding to different preset time schedules for that student group. The system generates a pre-set timetable text information for a specific time point for the target student group through data identification.

[0022] Preferably, the steps for constructing and processing the teaching course information and blank timetables required for scheduling classes for the target student group at a specific time point, and obtaining the teaching course information and blank timetable text information for the target student group at a specific time point, are as follows:

[0023] S21. Input the text information of the preset timetable for the target student group at a specific time point into the course management platform. The course management platform uses table editing software to cut and extract the teaching course name information in each table of the preset timetable to obtain the teaching course information for the target student group at a specific time point. The table editing software includes either EXCEL or WPS.

[0024] S22. Set the teaching course information for specific time points of the target student group as dynamic teaching course drop-down list options in each table of the preset timetable after information cutting and extraction processing, and construct blank timetable text information for the target students; wherein the dynamic teaching course drop-down list option means that once a course option in the teaching course drop-down list is selected, it will be actively excluded to avoid duplicate course selection; the blank timetable text information for the target students represents the teaching course table text information that provides students with personalized selection of teaching order based on the preset timetable; the blank timetable text information for the target students includes student group information, teaching day time points, teaching course name information in drop-down list format and teaching course teaching time period, wherein the unit of teaching course teaching time period is mainly composed of year, month, day, hour and minute.

[0025] Preferably, the task of creating and collecting timetable text information for the target student group at a specific time point is performed to obtain the customized timetable text information for the target students, and the feedback results of the timetable customization for the target student group at a specific time are analyzed and processed to obtain the timetable customization feedback result information for the target student group; when there is no customized timetable, the operation steps of step S5 are directly executed as follows:

[0026] S31. Using the course management platform, the blank timetable text information of the target scheduled students is used to generate the contact information set of the target scheduled students. Contact information of students in the target scheduling program. Based on individual student IDs and in conjunction with social media, the text message of the timetable is systematically pushed to the target student group to assign homework at specific times within the designated time slots. The system collects completed timetable text information through the course management platform to obtain a set of customized timetable text information for students with target course scheduling. ,in Indicates the first among the target student group The text information of the target student's customized timetable for each individual student, wherein the text information of the target student's customized timetable for each individual student in the target student group represents the text information of the personal teaching course table created by each individual student in the target student group; the social software includes QQ and WeChat;

[0027] S32. Use the KD-tree nearest neighbor search algorithm to customize the timetable text information set for the target students. The target scheduling student-customized timetable text information described in the text Perform timetable text data search and processing, and generate timetable customization feedback information for the target student group based on the timetable text data search and processing;

[0028] when If no timetable text data is found, it means that the target student group does not need to customize a timetable. In this case, the timetable customization feedback information for the target student group is output as "no timetable customization exists". At this time, step S5 is executed directly.

[0029] when When timetable text data is found in the search, it indicates that the target student group needs to customize timetables. The output of the timetable customization feedback information for the target student group is "Customized timetables exist".

[0030] Preferably, when customized timetables exist, the customized timetables for the target students are categorized by type to obtain text information on the customized timetables categorized by target students; the steps for evaluating the optimal customized timetable required by the target student group at a specific time point to obtain the optimal customized timetable text information for the target student group are as follows:

[0031] S41. When the feedback information of the timetable customization of the target student group indicates that a customized timetable exists, the customized timetable of the target students is classified based on the text information set of the customized timetable of the target students to obtain the text information set of the customized timetable of the target students.

[0032] S42. Based on the target student customized timetable text information set and the target student categorized customized timetable text information set, perform evaluation processing on the optimal customized timetable required by the target student group at a specific time point to obtain the optimal customized timetable text information for the target student group.

[0033] Preferably, when the feedback information for the timetable customization of the target student group indicates that customized timetables exist, the operation steps for classifying the customized timetable types of the target students based on the text information set of customized timetables of the target students are as follows:

[0034] S411. When the feedback information for the timetable customization of the target student group indicates that a customized timetable exists, the XGBoost search algorithm is used to sequentially search the text information set of the customized timetable for the target students according to their individual student object numbers. The target scheduling student-customized timetable text information described in the text Data mining was performed on the corresponding teaching course information to retrieve customized timetable text information with different course ordering, thus constructing a set of customized timetable text information for target student categories. ,in The first one is customized for the target student group. The text information of the target student categories customized timetables corresponding to the customized timetable types, wherein the customized timetable type refers to the teaching timetable table with different order of teaching courses customized by the target student; the text information of the target student categories customized timetables refers to the text information of different types of customized timetables customized by the target student group.

[0035] Preferably, the steps for evaluating the optimal customized timetable required by the target student group at a specific time point based on the target student customized timetable text information set and the target student categorized customized timetable text information set, to obtain the optimal customized timetable text information for the target student group, are as follows:

[0036] S421. Obtain the text information set of the target student's customized timetable. And the target student-categorized customized timetable text information set ;

[0037] S422. Using the BERT language model algorithm, customize the timetable text information set based on the target student classification for time scheduling. The text information described in the target scheduling document describes student classification and customized timetables. The target student customized timetable text information set The search retrieved text information related to the target student's customized timetable classification. The corresponding teaching courses are ordered in the same order, and all the target courses are scheduled according to the student-customized timetable text information. The total number of students, and generate a set of customized timetables for each student category in the target scheduling. ,in The first one is customized for the target student group. The number of customized timetables for each type of customized timetable corresponds to the target student group, where the number of customized timetables for each type of customized timetable represents the total number of different types of customized timetables customized for the target student group.

[0038] S423, regarding the set of student-categorized customized timetables for the target scheduling... The search query returned the largest number of customized timetables for the target student category. The corresponding customized timetable type information, and the customized timetable text information set for the target student class. The search query retrieves the number of customized timetables for the target student category based on the customized timetable type information, with the largest number of such timetables. The corresponding target student-categorized customized timetable text information The optimal customized timetable text information for the target student group is generated through data identification. The optimal customized timetable text information for the target student group represents the optimal teaching course schedule text information collectively customized by the target student group at a specific point in time.

[0039] Preferably, the steps for comprehensively processing and processing the teaching schedules of the target student group at specific time points to obtain and output the text information of the teaching schedules of the target student group at specific time points are as follows:

[0040] S51. When the feedback information of the timetable customization of the target student group is that there is no customized timetable, the text information of the preset timetable of the target student group at a specific time point is constructed into the text information of the teaching timetable of the target student group at a specific time point through data identification.

[0041] When the feedback information of the timetable customization for the target student group indicates that a customized timetable exists, the optimal customized timetable text information for the target student group is constructed into a teaching timetable text information for a specific time point for the target student group through data identification.

[0042] S52. Transmit the text information of the teaching schedule for the target student group at a specific time point to the course management platform through a mobile communication network, and display it online with a display screen.

[0043] A big data-based student learning course visualization and intelligent scheduling system is used to implement the big data-based student learning course visualization and intelligent scheduling method. The system includes a student preset timetable management module, a student customized timetable management module, and a student timetable comprehensive creation module.

[0044] The student preset timetable management module includes a target student group characteristic information collection unit, a student scheduling specific time point collection unit, a student group standard student individual contact information database storage unit, a target scheduling student contact information search unit, a student group different time preset timetable text information storage unit, and a target student group specific time point preset timetable identification unit.

[0045] The target student group feature information collection unit collects target student group feature information through the course management platform; the student scheduling specific time point collection unit collects student scheduling specific time point information through the course management platform; the student group standard student individual contact information database storage unit stores the student group standard student individual contact information database; the target scheduling student contact information search unit searches for the target student group's scheduling student individual contact information based on the target student group feature information and the student group standard student individual contact information database to obtain the target scheduling student contact information; the student group different time preset timetable text information storage unit stores the student group's different time preset timetable text information; the target student group specific time point preset timetable identification unit identifies the target student group's preset timetable text information at a specific time point based on the target student group feature information, the student scheduling specific time point information, and the student group's different time preset timetable text information to obtain the target student group's specific time point preset timetable text information.

[0046] The student-customized timetable management module includes a target student group's specific time point teaching course information search unit, a target student group's blank timetable construction unit, a target student group's timetable formulation and collection unit, a target student group's timetable customization feedback result analysis unit, a target student group's timetable type analysis unit, and a target student group's optimal customized timetable evaluation unit.

[0047] The target student group's specific time-point teaching course information search unit, based on the target student group's specific time-point preset timetable text information and combined with the course management platform and spreadsheet editing software, constructs the teaching course information required for the target student group's specific time-point scheduling, obtaining the target student group's specific time-point teaching course information; the target student blank timetable construction unit, based on the target student group's specific time-point preset timetable text information and the target student group's specific time-point teaching course information, constructs the target student's specific time-point blank timetable text information, obtaining the target student's specific timetable blank timetable text information; the target student timetable creation and collection unit, based on the target student's specific timetable blank timetable text information and the target student's contact information, and combined with the course management platform and social software, executes the target student group's specific time-point scheduling... The process involves: 1) Creating and collecting timetable text information to obtain customized timetable text information for target students; 2) Analyzing the feedback results of timetable customization for the target student group based on the customized timetable text information to obtain timetable customization feedback results for the target student group at a specific time; 3) Analyzing the types of customized timetables for the target students based on the customized timetable text information to obtain categorized customized timetable text information for the target students; and 4) Evaluating the optimal customized timetable for the target student group based on the customized timetable text information and the categorized customized timetable text information to evaluate the optimal customized timetable required by the target student group at a specific time point to obtain the optimal customized timetable text information for the target student group.

[0048] The student timetable comprehensive planning module includes a target student group specific time point teaching timetable planning unit and a target student group specific time point teaching timetable planning output unit.

[0049] The target student group's timetable creation unit performs comprehensive timetable creation processing based on the timetable customization feedback information or the optimal customized timetable text information of the target student group, resulting in the target student group's timetable text information at a specific time. The target student group's timetable creation output unit, based on the target student group's timetable text information and in conjunction with the course management platform and display screen, executes the student learning course scheduling result output task.

[0050] (III) Beneficial Effects

[0051] This invention provides a method and system for visualized intelligent scheduling of student learning courses based on big data. It has the following beneficial effects:

[0052] I. By acquiring real-time characteristic information of target student groups and specific time points of student scheduling through the course management platform, precise management of course scheduling for different student groups at different time points can be achieved. Based on student group information and scheduling time points, and combined with big data technology, the contact information of individual students in the student group and the preset timetable of the student group can be efficiently and accurately obtained, providing reliable data support for ensuring personalized course scheduling for student groups, realizing scientific and personalized management of student learning courses based on big data, and improving the effectiveness of course scheduling management.

[0053] Second, by dynamically creating personalized blank timetables for student groups based on table text processing, students can rationally and scientifically arrange their course order according to their personal learning plans, improving the rationality of teaching and learning safety; based on the blank timetable text information and contact information of target students, combined with the course management platform and social software, the system can autonomously and efficiently execute the task of creating and collecting timetable text information for target student groups at specific time points, achieving efficient creation and collection of personalized timetables for student groups; at the same time, by combining data analysis, the system can conduct a comprehensive analysis of the existence of timetable customization results for student groups, achieving reliable timetable creation based on a combination of preset and customized timetables, improving the scientific and personalized nature of timetable management; based on timetable classification and big data analysis, the system can scientifically create the optimal timetable that best suits the learning plans of student groups, improving the quality of timetable management.

[0054] Third, by using feedback information from the timetable customization of the target student group or the optimal customized timetable text information of the target student group, the teaching timetable for the target student group at specific time points is comprehensively formulated. This enables global intelligent formulation of student timetables based on the timetable customization results of the student group, and realizes that timetable management takes into account both teaching tasks and student learning differences, thereby improving the applicability of timetable management. Based on the teaching timetable text information of the target student group at specific time points, and combined with the course management platform and display screen, the learning course scheduling results are visualized and output, realizing visual and intuitive feedback on the scheduling results, and improving the convenience of timetable management. Attached Figure Description

[0055] Figure 1 A schematic diagram of the modules of the big data-based student learning course visualization and intelligent scheduling system provided by the present invention;

[0056] Figure 2 The flowchart illustrates the big data-based student learning course visualization and intelligent scheduling method provided by this invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] An example of the big data-based student learning course visualization and intelligent scheduling method and system is as follows:

[0059] Example 1:

[0060] Please see Figures 1-2 A big data-based method for visualizing and intelligently scheduling student learning courses includes the following steps:

[0061] S1. Collect characteristic information of the target student group and information on specific time points of student class scheduling; search and process the contact information of individual students in the target student group to obtain the contact information of the target students; identify and process the text information of the preset timetable of the target student group at specific time points to obtain the text information of the preset timetable of the target student group at specific time points.

[0062] S2. Construct and process the teaching course information and blank timetables required for scheduling classes for the target student group at a specific time point, and obtain the teaching course information and blank timetable text information of the target student group at a specific time point respectively.

[0063] S3. Perform the task of creating and collecting timetable text information for the target student group at a specific time point, obtain the customized timetable text information for the target students, and analyze and process the feedback results of the timetable customization for the target student group at a specific time to obtain the timetable customization feedback result information for the target student group; if there is no customized timetable, directly execute step S5;

[0064] S4. When customized timetables exist, classify the customized timetables of the target students to obtain the text information of the customized timetables of the target students; evaluate the optimal customized timetable required by the target student group at a specific time point to obtain the text information of the optimal customized timetable of the target student group.

[0065] S5. Comprehensively formulate and process the teaching schedules for the target student group at specific time points, obtain the text information of the teaching schedules for the target student group at specific time points, and output it.

[0066] For further details, please refer to Figures 1-2The steps involved are as follows: collecting characteristic information of the target student group and information on specific time points in student class scheduling; searching and processing individual contact information of students within the target student group to obtain their contact information; and recognizing and processing the text information of the target student group's pre-set class schedule at specific time points to obtain the text information of the target student group's pre-set class schedule at those specific time points.

[0067] S11. Collect the class name and class number characteristics of the target student group waiting for customized course scheduling online through the course management platform, and obtain the characteristic information of the target student group; the course management platform includes any one of Blue Crane Course Schedule Management Platform, School Butler Intelligent Course Scheduling Management Platform, and Cloud Classroom Course Scheduling Management Platform;

[0068] The course management platform collects information on the specific future dates and times of the target student group waiting for customized course scheduling, and obtains the specific time information of the student's course scheduling. The unit of the specific time information of the student's course scheduling is mainly composed of year, month and day.

[0069] S12. Based on the target student group feature information and the student group standard student individual contact information database matrix, perform search and processing of the contact information of the students in the target student group to obtain the target student contact information set; based on the target student group feature information, the student scheduling specific time point information and the student group's preset timetable text information set at different times, perform preset timetable text information recognition and processing of the target student group at a specific time point to obtain the target student group's preset timetable text information at a specific time point.

[0070] Based on the target student group's characteristic information and the standard student individual contact information matrix, the contact information of individual students in the target student group is searched and processed to obtain the target student contact information set. Then, based on the target student group's characteristic information, student scheduling information at specific time points, and the set of preset timetable text information for different times, the preset timetable text information of the target student group at specific time points is identified and processed to obtain the preset timetable text information of the target student group at specific time points. The operation steps are as follows:

[0071] S121. Establish a database matrix of student group standard student individual contact information. ,in Indicates the first The standard student individual contact information database for each student group represents a database of standard student individual contact information set for different student groups. The student individual contact information includes each student's QQ number and WeChat ID.

[0072] Establish a text information set of pre-set class schedules for different time periods for student groups. ,in Indicates the first This refers to the text information of the preset timetable for different student groups at specific time points. The text information of the preset timetable for different student groups at different time points represents the text information of the teaching course table preset for different student groups at different time points on different days. The teaching course table includes student group information, teaching day time point, teaching course name information, and teaching course teaching time period. The teaching course teaching time period is mainly composed of year, month, day, hour, and minute.

[0073] S122. Use a breadth-first search algorithm to compare the target student group feature information with the student group's standard student individual contact information matrix. Standard Student Individual Contact Information Database for Middle School Students Perform student group characteristic information matching to search the standard student individual contact information database corresponding to the target student group characteristic information. And through data identification, a set of contact information for target scheduling students is generated. ,in Indicates the first among the target student group The target scheduling student contact information corresponds to each individual student. The target scheduling student contact information represents the contact information of each individual student waiting for scheduling in the target student group.

[0074] S123. Using the breadth-first search algorithm as in step S122, the target student group feature information, student class scheduling specific time point information, and student group time preset time schedule text information set are compared with the target student group's time preset time schedule text information set. Preset timetable text information for middle school students at different times Matching student group characteristics with class scheduling time information, the system retrieves pre-set timetable text information for different time slots corresponding to the target student group's characteristics and specific class scheduling time points. The system generates a pre-set timetable text information for a specific time point for the target student group through data identification.

[0075] By combining the target student group characteristic information collection unit and the student scheduling specific time point collection unit, the course management platform acquires target student group characteristic information and student scheduling specific time point information in real time, enabling precise management of course scheduling for different student groups at different times. The target scheduling student contact information search unit and the target student group specific time point preset timetable identification unit work together to efficiently and accurately acquire individual student contact information and preset timetables for the student group based on student group information and scheduling time points, combined with big data technology. This provides reliable data support for ensuring personalized course scheduling for student groups, achieving big data-driven scientific personalized management of student learning courses and improving the effectiveness of course scheduling management.

[0076] For further details, please refer to Figures 1-2 The steps for constructing and processing the teaching course information and blank timetables required for scheduling classes for the target student group at a specific time point, and obtaining the teaching course information and blank timetable text information for the target student group at a specific time point, are as follows:

[0077] S21. Input the text information of the preset timetable for the target student group at a specific time point into the course management platform. The course management platform uses a table editing software to cut and extract the teaching course name information in each table of the preset timetable to obtain the teaching course information for the target student group at a specific time point. The table editing software includes either EXCEL or WPS.

[0078] S22. Set the teaching course information for specific time points of the target student group as dynamic teaching course drop-down list options in each table of the preset timetable after information cutting and extraction processing, and construct the blank timetable text information for the target students. The dynamic teaching course drop-down list option means that once a course option in the teaching course drop-down list is selected, it will be actively excluded to avoid duplicate course selection. The blank timetable text information for the target students represents the teaching course table text information that provides students with personalized selection of teaching order based on the preset timetable. The blank timetable text information for the target students includes student group information, teaching day time points, teaching course name information in drop-down list format and teaching course teaching time period information, where the teaching course teaching time period unit is mainly composed of year, month, day, hour and minute.

[0079] The task involves creating and collecting timetable text information for the target student group at specific time points. This yields the customized timetable text information for the target students, and the feedback results of the timetable customization for the target student group at specific time points are analyzed and processed to obtain the timetable customization feedback results for the target student group. If no customized timetable exists, the operation steps in step S5 are directly executed as follows:

[0080] S31. Using the course management platform, the blank timetable text information of the target students is combined with the contact information set of the target students. Contact information for students in the target course scheduling Based on individual student IDs and in conjunction with social media, the text message of the timetable is systematically pushed to the target student group to assign homework at specific times within the designated time slots. The system collects completed timetable text information through the course management platform to obtain a set of customized timetable text information for students with target course scheduling. ,in Indicates the first among the target student group The text information of the target student's customized timetable for each individual student represents the personal teaching course schedule text information created by each individual student in the target student group; social software includes QQ and WeChat;

[0081] S32. Use the KD-tree nearest neighbor search algorithm to customize the text information set of the timetable for the target students. Student-customized timetable text information for target-oriented course scheduling Perform timetable text data search and processing, and generate timetable customization feedback information for the target student group based on the timetable text data search and processing;

[0082] when If no timetable text data is found, it means that the target student group does not need to customize timetables. In this case, the timetable customization feedback information for the target student group is "no timetable customization exists". At this time, proceed directly to step S5.

[0083] when When the search engine finds timetable text data, it indicates that the target student group needs to customize timetables. The output of the timetable customization feedback information for the target student group is "Customized timetables exist".

[0084] When customized timetables exist, the customized timetables for the target students are categorized by type to obtain text information about the customized timetables for each student category. The steps for evaluating the optimal customized timetable required by the target student group at a specific time point to obtain the optimal customized timetable text information for the target student group are as follows:

[0085] S41. When the feedback information of the timetable customization of the target student group is that a customized timetable exists, the customized timetable of the target students is classified based on the text information set of the customized timetable of the target students to obtain the text information set of the customized timetable of the target students.

[0086] S42. Based on the text information set of customized timetables for target students and the text information set of customized timetables for different categories of target students, evaluate the optimal customized timetables required by the target student group at a specific time point to obtain the optimal customized timetable text information for the target student group.

[0087] When the feedback information for the target student group's customized timetables indicates that customized timetables exist, the following steps are taken to classify the types of customized timetables for the target students based on the text information set of customized timetables for the target students:

[0088] S411. When the feedback information for the customized timetables of the target student group indicates that customized timetables exist, the XGBoost search algorithm is used to search the text information set of customized timetables for the target students in an orderly manner according to the individual student object number. Student-customized timetable text information for target-oriented course scheduling Data mining was performed on the corresponding teaching course information to retrieve customized timetable text information with different course ordering, thus constructing a set of customized timetable text information for target student categories. ,in The first one is customized for the target student group. The text information for customized timetables corresponding to different types of customized timetables for target students is as follows: the customized timetable type refers to the teaching timetable table with different course orderings customized by individual target students; the text information for customized timetables by target students refers to the text information for customized timetables of different types customized by the target student group.

[0089] The steps for evaluating and processing the optimal customized timetables needed by the target student group at a specific time point, based on the target student group's customized timetable text information set and the target student group's categorized customized timetable text information set, are as follows:

[0090] S421. Obtain the text information set of customized class schedules for target students. And target scheduling, student classification, customized timetable text information set ;

[0091] S422. Using the BERT language model algorithm to customize timetable text information sets based on target scheduling student classification. Targeted scheduling, student-categorized customized timetable text information Text information set of customized timetables for students in the target scheduling Searching for text information related to customized timetables for target students reveals relevant information. All target courses with the same order are scheduled in the student-customized timetable text information. The total number of students, and generate a set of customized timetables for each student category in the target scheduling. ,in The first one is customized for the target student group. The number of customized timetables for each type of customized timetable corresponds to the target student group's customized timetables. The number of customized timetables for each type of customized timetable represents the total number of different types of customized timetables customized for the target student group.

[0092] S423, Customize the number of timetables for students categorized by target scheduling criteria. The search returned the largest number of students categorized and customized timetables for the target course. Corresponding customized timetable type information, and customized timetable text information sets for target students. The search query retrieves the target course schedule with the largest number of customized timetables for each student category, based on the customized timetable type information. Corresponding target student classification and customized timetable text information The optimal customized timetable text information for the target student group is generated through data identification. The optimal customized timetable text information for the target student group represents the optimal teaching course schedule text information collectively customized by the target student group at a specific point in time.

[0093] The system utilizes a collaborative approach: a unit for searching course information at specific times for the target student group and a unit for constructing blank timetables for target students. Based on table text processing, it dynamically creates personalized blank timetables for each student group, enabling students to rationally and scientifically arrange their course order according to their individual learning plans, thus improving the rationality of course safety. A unit for creating and collecting timetables for target students and a unit for analyzing the feedback results of timetable customization for the target student group work together. Based on the blank timetable text information and contact information of target students, and combined with the course management platform and social software, they autonomously and efficiently execute the creation and collection of timetable text information for the target student group at specific times, achieving efficient creation and collection of personalized timetables for each student group. Simultaneously, data analysis is used to comprehensively analyze the existence of timetable customization results for the student group, achieving reliable timetable creation based on a combination of preset and customized timetables, improving the scientific and personalized nature of course scheduling management. Finally, a unit for analyzing the types of customized timetables for target students and a unit for evaluating the optimal customized timetable for the target student group work together. Based on timetable classification and big data analysis, they scientifically create the optimal timetable that best suits the learning plans of the student group, improving the quality of course scheduling management.

[0094] For further details, please refer to Figures 1-2 The steps for comprehensively developing and processing the teaching schedules for the target student group at specific time points, obtaining the text information of the teaching schedules for the target student group at specific time points, and outputting it are as follows:

[0095] S51. When the feedback information for the timetable customization of the target student group is that there is no customized timetable, the text information of the preset timetable for the target student group at a specific time point is constructed into the text information of the teaching timetable for the target student group at a specific time point after data identification.

[0096] When the feedback information for the timetable customization of the target student group indicates that a customized timetable exists, the optimal customized timetable text information of the target student group will be constructed into the teaching timetable text information of the target student group at a specific time point after data identification;

[0097] S52. Transmit the text information of the teaching schedule for specific time points of the target student group to the course management platform through the mobile communication network, and display it online with the help of the display screen.

[0098] The system utilizes a time-specific timetable creation unit for the target student group. Based on feedback from the timetable customization process or the optimal timetable text information, it comprehensively creates timetables for the target student group at specific times. This enables globally intelligent timetable creation based on the timetable customization results, balancing teaching tasks with student learning differences and improving the applicability of scheduling management. The system also includes a time-specific timetable creation output unit. Based on the timetable text information for the target student group at specific times, and combined with the course management platform and display screen, it visually outputs the course scheduling results, providing intuitive feedback and enhancing the convenience of scheduling management.

[0099] Example 2:

[0100] Please see Figures 1-2 The student learning course visualization and intelligent scheduling system based on big data is used to realize the student learning course visualization and intelligent scheduling method based on big data. The system includes a student preset timetable management module, a student customized timetable management module, and a student timetable comprehensive creation module.

[0101] The student preset timetable management module includes a target student group characteristic information collection unit, a student scheduling specific time point collection unit, a student group standard student individual contact information database storage unit, a target scheduling student contact information search unit, a student group different time preset timetable text information storage unit, and a target student group specific time point preset timetable identification unit.

[0102] The system comprises the following components: a target student group characteristic information collection unit, which collects target student group characteristic information through the course management platform; a student scheduling specific time point collection unit, which collects student scheduling specific time point information through the course management platform; a standard student individual contact information database storage unit, which stores the standard student individual contact information database; a target scheduling student contact information search unit, which searches for and processes the target student group's scheduling individual contact information based on the target student group characteristic information and the standard student individual contact information database to obtain the target scheduling student contact information; a student group preset timetable text information storage unit, which stores the student group's preset timetable text information at different times; and a target student group specific time point preset timetable identification unit, which identifies and processes the target student group's preset timetable text information at a specific time point based on the target student group characteristic information, student scheduling specific time point information, and the student group's preset timetable text information at different times to obtain the target student group's specific time point preset timetable text information.

[0103] The student-customized timetable management module includes a unit for searching teaching course information for a specific time point for a target student group, a unit for constructing blank timetables for target students, a unit for creating and collecting timetables for target students, a unit for analyzing feedback results of timetable customization for target students, a unit for analyzing the types of customized timetables for target students, and a unit for evaluating the optimal customized timetable for the target student group.

[0104] The system comprises three parts: a target student group's course information search unit, a target student group's course information search unit, and a target student group's time-specific course information search unit. The target student group's time-specific course information search unit uses a pre-set timetable text information and a course management platform and spreadsheet software to construct the required course information for scheduling at that specific time. A target student blank timetable construction unit uses the pre-set timetable text information and the target student group's time-specific course information to construct the required blank timetables for scheduling at that specific time. A target student timetable creation and collection unit uses the target student blank timetable text information and the target student's contact information, combined with the course management platform and social media software, to execute the target student group's time-specific course schedule creation and collection. The system comprises the following modules: Timetable text information creation and collection, resulting in customized timetable text information for target students; a feedback analysis unit for the customized timetables of the target student group, which analyzes and processes the feedback results of timetable customization for the target student group at specific times based on the customized timetable text information, resulting in timetable customization feedback information for the target student group; a timetable type analysis unit for the customized timetables of the target students, which categorizes the customized timetables of the target students based on the customized timetable text information, resulting in categorized customized timetable text information for the target students; and an optimal customized timetable evaluation unit for the target student group, which evaluates the optimal customized timetable required by the target student group at a specific time point based on the customized timetable text information of the target students and the categorized customized timetable text information for the target students, resulting in the optimal customized timetable text information for the target student group.

[0105] The module for comprehensive student timetable development includes a unit for developing timetables for specific student groups at specific times, and an output unit for developing timetables for specific student groups at specific times.

[0106] The target student group's timetable creation unit processes the timetable for specific time points based on feedback information from the timetable customization of the target student group or the optimal customized timetable text information of the target student group, and obtains the timetable text information for the target student group at specific time points. The target student group's timetable creation output unit outputs the timetable creation results based on the timetable text information for the target student group at specific time points and in conjunction with the course management platform and display screen.

[0107] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A student learning course visualization and intelligent scheduling method based on big data, characterized in that: The method includes the following steps: S1. Collect characteristic information of the target student group and information on specific time points of student scheduling; search and process the contact information of individual students in the target student group to obtain the contact information of the target students; identify and process the text information of the preset timetable of the target student group at specific time points to obtain the text information of the preset timetable of the target student group at specific time points. S2. Construct and process the teaching course information and blank timetables required for scheduling classes for the target student group at a specific time point, and obtain the teaching course information and blank timetable text information of the target student group at a specific time point respectively. S3. Perform the task of creating and collecting timetable text information for the target student group at a specific time point, obtain the customized timetable text information for the target students, and analyze and process the feedback results of the timetable customization for the target student group at a specific time to obtain the timetable customization feedback result information for the target student group; if there is no customized timetable, directly proceed to step S5; S4. When customized timetables exist, classify the customized timetables of the target students to obtain text information of customized timetables categorized by type; evaluate the optimal customized timetable required by the target student group at a specific time point to obtain text information of the optimal customized timetable for the target student group. The operation steps of S4 are as follows: S41. When the feedback information of the timetable customization of the target student group indicates that a customized timetable exists, the customized timetable of the target students is classified based on the text information set of the customized timetable of the target students to obtain the text information set of the customized timetable of the target students. The operation steps of S41 are as follows: S411. When the feedback information for the timetable customization of the target student group indicates that a customized timetable exists, the XGBoost search algorithm is used to search in order according to the individual student object number. middle Data mining was performed on the corresponding teaching course information to retrieve customized timetable text information with different course ordering, thus constructing a set of customized timetable text information for target student categories. The include ;in The first one is customized for the target student group. The text information of the customized timetable text corresponding to the target student classification for each type of customized timetable; in This represents a set of text information about the target student's customized timetable. include ;in Indicates the first among the target student group Customized timetable text information for each individual student's target course schedule; S42. Based on the target student customized timetable text information set and the target student categorized customized timetable text information set, perform evaluation processing on the optimal customized timetable required by the target student group at a specific time point to obtain the optimal customized timetable text information of the target student group. The operation steps of S42 are as follows: S421, Obtain the and stated ; S422, Using the BERT language model algorithm based on the above The above In the Searching for results related to the above All the corresponding teaching courses with the same order The total number of students, and generate a set of customized timetables for each student category in the target scheduling. The include ;in The first one is customized for the target student group. The number of customized timetables corresponding to the target student categories for each type of customized timetable; S423, in the above The search returned the largest number of values. The corresponding customized timetable type information, and in the above The search query retrieves the results with the largest number of results based on the customized timetable type information. The corresponding target student-categorized customized timetable text information And through data identification, the optimal customized timetable text information for the target student group is generated; S5. Comprehensively formulate and process the teaching schedules for the target student group at specific time points, obtain the text information of the teaching schedules for the target student group at specific time points, and output it.

2. The student learning course visualization and intelligent scheduling method based on big data according to claim 1, characterized in that: The operation steps of S1 are as follows: S11. Collect the class name and class number characteristics of the target student group waiting for customized course scheduling online through the course management platform, and obtain the characteristic information of the target student group; The course management platform collects information on the specific future dates and times of the target student group waiting for customized course scheduling, and obtains the specific time information of the student's course scheduling. S12. Based on the target student group feature information and the student group standard student individual contact information database matrix, perform search processing on the contact information of the students in the target student group to obtain the target student contact information set; based on the target student group feature information, the student scheduling specific time point information and the student group's preset timetable text information set at different times, perform preset timetable text information recognition processing on the target student group at a specific time point to obtain the target student group's preset timetable text information at a specific time point.

3. The student learning course visualization and intelligent scheduling method based on big data according to claim 2, characterized in that: The operation steps of S12 are as follows: S121. Establish a database matrix of student group standard student individual contact information. The include ;in Indicates the first A database of individual student contact information corresponding to each student group; Establish a text information set of pre-set class schedules for different time periods for student groups. The include ;in Indicates the first Text information on the pre-set class schedules for different time periods for a specific student group at a specific time point; S122. Use a breadth-first search algorithm to compare the target student group feature information with the... The above Perform student group feature information matching to search for the target student group feature information corresponding to the [specific information]. And through data identification, a set of contact information for target scheduling students is generated. The include ;in Indicates the first among the target student group Contact information for each student in the target scheduling program; S123. Using the breadth-first search algorithm as in step S122, the target student group feature information, the student scheduling specific time point information, and the... The above Matching student group characteristics with class scheduling time points, and searching for the target student group characteristics and the specific class scheduling time points corresponding to them. The system generates a pre-set timetable text information for a specific time point for the target student group through data identification.

4. The student learning course visualization and intelligent scheduling method based on big data according to claim 3, characterized in that: The operation steps of S2 are as follows: S21. Input the text information of the preset timetable for the target student group at a specific time point into the course management platform. The course management platform uses table editing software to cut and extract the teaching course name information in each table of the preset timetable to obtain the teaching course information for the target student group at a specific time point. S22. Set the teaching course information of the target student group at a specific time point as a dynamic teaching course drop-down list option in each table of the preset timetable after information cutting and extraction processing, and construct the blank timetable text information of the target student group; the blank timetable text information of the target student group includes student group information, teaching day time point, teaching course name information in drop-down list format and teaching course teaching time period.

5. The student learning course visualization and intelligent scheduling method based on big data according to claim 4, characterized in that: The operation steps of S3 are as follows: S31. The blank timetable text information of the target scheduled students is transferred to the course management platform based on the... The above Based on individual student IDs and in conjunction with social media, the text message of the timetable is systematically pushed to the target student group to assign homework at specific times within the designated time slots. The system collects completed timetable text information through the course management platform to obtain a set of customized timetable text information for students with target course scheduling. The include ;in Indicates the first among the target student group Customized timetable text information for each individual student's target course schedule; S32. The KD-tree nearest neighbor search algorithm is used to perform the above... The above Perform timetable text data search and processing, and generate timetable customization feedback information for the target student group based on the timetable text data search and processing; when If no timetable text data is found, the timetable customization feedback information for the target student group is output as "no customized timetable exists"; at this time, step S5 is executed directly. when When the timetable text data is found in the search, the timetable customization feedback information for the target student group is output as "Customized timetables exist".

6. The student learning course visualization and intelligent scheduling method based on big data according to claim 1, characterized in that: The operation steps of S5 are as follows: S51. When the feedback information of the timetable customization of the target student group is that there is no customized timetable, the text information of the preset timetable of the target student group at a specific time point is constructed into the text information of the teaching timetable of the target student group at a specific time point through data identification. When the feedback information of the timetable customization for the target student group indicates that a customized timetable exists, the optimal customized timetable text information for the target student group is constructed into a teaching timetable text information for a specific time point for the target student group through data identification. S52. Transmit the text information of the teaching schedule for the target student group at a specific time point to the course management platform through a mobile communication network, and display it online with a display screen.

7. A big data-based student learning course visualization and intelligent scheduling system, used to implement the big data-based student learning course visualization and intelligent scheduling method as described in any one of claims 1-6, characterized in that: The system includes a student preset timetable management module, a student customized timetable management module, and a student timetable comprehensive creation module.

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