Intelligent college entrance examination application adaptation method and system

Abstract

The invention discloses an intelligent college entrance examination voluntary adaptation method and system, relates to the technical field of education examination assistance, and aims to solve the problems of information asymmetry, individual difference of examinees and voluntary filling efficiency and accuracy during voluntary filling of the examinees. According to the method, advanced technologies such as big data analysis and an artificial intelligence algorithm are integrated, a personalized and accurate volunteer filling scheme is provided for examinees, and the scientificity and rationality of volunteer selection are remarkably improved. The system automatically processes mass data, relieves the burden of examinees, updates information in real time, and ensures the accuracy of decision basis. And meanwhile, the system ensures fairness and transparency, the educational resource distribution is optimized, and the admission satisfaction is improved. Generally speaking, the patent not only renovates a traditional volunteer filling mode and improves efficiency and satisfaction, but also promotes educational fairness through a scientific method and realizes effective adaptation between examinees and colleges.

Description

Technical Field

[0001] The present invention relates to the field of educational examination auxiliary technology, and specifically to a method and system for intelligent adaptation of college entrance examination volunteers. Background Art

[0002] When candidates and parents are selecting alternative choices that suit their own preferences from the list, the traditional college entrance examination application system has problems. Due to improper filling out of the college entrance examination application form, candidates may be rejected, receive a low-level job with high scores, or be admitted to an unsatisfactory major. At the same time, there is information asymmetry, individual differences among candidates, and the efficiency and accuracy of application filling out.

[0003] Therefore, a method and system for intelligent adaptation of college entrance examination volunteers are needed to solve the above problems. Summary of the invention

[0004] In order to solve the problems of the prior art, the present invention provides an intelligent adaptation method and system for college entrance examination volunteers, aiming to solve the problems of information asymmetry, individual differences among candidates, and efficiency and accuracy of volunteer filling when candidates fill in their volunteers.

[0005] In order to solve the above technical problems, the present invention is implemented by the following technical solutions: a method for intelligent adaptation of college entrance examination volunteers, comprising the following steps:

[0006] Step 1: Collect historical college entrance examination admission data and enrollment policy information of various colleges and universities to build a database;

[0007] Collect historical admission data from provinces, cities and universities across the country, including admission scores, the number of admissions for each major, etc.

[0008] Obtain policy information on each university's professional settings, admission regulations, elective subject requirements, and more.

[0009] After cleaning and organizing, these data are stored in the database to ensure the integrity and accuracy of the data.

[0010] Step 2: Based on the database, use data analysis technology to analyze the change trend of admission data and the popularity of majors;

[0011] Use statistical analysis and data mining techniques to identify trends and changes in admission score lines.

[0012] Analyze the application popularity of different majors in different years, and understand the dynamics of popular and unpopular majors.

[0013] Assess the impact of geographical factors on major selection and admission outcomes.

[0014] Step 3: Design and implement an intelligent adaptation algorithm that comprehensively considers the candidates’ elective subjects, grades, major interests, regional preferences, school types, and application types;

[0015] A predictive model is built using machine learning algorithms, which allows for intelligent adaptation based on the examinee’s grades, elective subjects, and professional interests.

[0016] Taking regional preferences into consideration, we match candidates with appropriate colleges and universities in their area.

[0017] Consider the type of institution and match the appropriate type of institution for the candidates.

[0018] Step 4: Generate personalized volunteer application suggestions for each candidate based on the intelligent adaptation algorithm;

[0019] The algorithm generates a personalized ranking list of preferences based on candidate demand information and historical data.

[0020] Ability to fine-tune and optimize suggestions based on the specific needs of candidates.

[0021] Step 5: Dynamically update system data and intelligent adaptation algorithms to respond to changes in college entrance examination policies and college admission information;

[0022] Establish a real-time data update mechanism to ensure that changes in enrollment policies and admission rules can be quickly captured by the system and updated to the database.

[0023] Regularly evaluate and adjust intelligent adaptation algorithms to ensure the accuracy of predictions and the timeliness of recommendations.

[0024] Step 6: Provide a user interface that allows candidates to make voluntary selections and adjustments based on the suggestions and provide real-time feedback.

[0025] A user-friendly interface is designed to enable candidates and parents to easily input information, view and adjust volunteer recommendations.

[0026] Establish a feedback mechanism to allow candidates to question and modify the suggestions generated by the system to provide better personalized services.

[0027] Provide real-time interactive guidance and expert consultation to help candidates make more informed decisions.

[0028] The intelligent adaptation algorithm further takes into account the admission scores of previous years and the provincial rankings of candidates, forming a tiered volunteer combination of "strive, be stable, and ensure."

[0029] During the steps of dynamically updating system data and intelligent adaptation algorithms, the system informs candidates of the latest changes via push notifications.

[0030] A college entrance examination volunteer intelligent adaptation system, comprising:

[0031] Data collection and analysis module, used to collect and organize historical college entrance examination admission data and enrollment policy information of various colleges and universities, and to establish and update the database;

[0032] Collect data: Integrate historical admission data from provinces, cities and universities across the country, including admission scores over the years, the number of admissions for each major, requirements for elective subjects, school information, major settings, etc.

[0033] Policy information: Real-time tracking of changes in college entrance examination policies of the Ministry of Education and various provinces and cities, and timely feedback of changes to the system.

[0034] Database establishment: Use an efficient database management system to store and manage the collected data to ensure the integrity and accuracy of the data.

[0035] Data analysis: Use statistical analysis and data mining techniques to identify trends and patterns in data and provide reliable data support for algorithms.

[0036] The intelligent adaptation algorithm module, based on big data analysis technology and artificial intelligence technology, generates personalized volunteer application plans according to the candidates' personal information and preferences;

[0037] The result feedback module is used to collect the candidates' application results and admission status to evaluate the accuracy and effectiveness of the system, conduct self-learning and improvement based on actual results, and improve its accuracy and effectiveness.

[0038] Specialized training: Aiming at the specific task of filling out college entrance examination applications, the selected large model is further trained to enable it to understand and analyze the needs of candidates, accurately adapt to colleges and majors, predict admission probabilities, and conduct risk assessments.

[0039] Personalized suggestion generation: Based on the candidate’s personal information and preferences, an algorithm is used to generate an application plan that meets the candidate’s needs.

[0040] Dynamic update and real-time feedback module, used to monitor and respond to changes in college entrance examination policies and college admission information, and update the adaptation algorithm in real time;

[0041] Monitoring and response: Continuously monitor changes in college entrance examination policies and college admission information, and dynamically adjust the adaptation algorithm accordingly to ensure the accuracy and timeliness of system recommendations.

[0042] Real-time feedback: Provide candidates with real-time feedback and revision suggestions to help them make more reasonable decisions during the application process.

[0043] User interaction interface module, used to display the filling suggestions generated by the system and allow candidates to make selections and adjustments;

[0044] Interface design: Design a user-friendly interface so that candidates and parents can easily input information, view and adjust volunteer recommendations.

[0045] Interactive experience: Provide clear navigation and operation guides to ensure that users can use the system without obstacles.

[0046] Security and privacy protection module to ensure the security and privacy of candidates’ personal information;

[0047] Data security: Encryption technology and security measures are used to protect stored and transmitted data.

[0048] Privacy protection: Strictly abide by relevant laws and regulations to protect the security and privacy of candidates' personal information.

[0049] The intelligent adaptation algorithm module includes:

[0050] Data collection and preprocessing: Based on student information and school information, the preset algorithm is used to adapt and find the school and major that best suits the student.

[0051] It further includes a result feedback module for collecting the results filled in by the examinees and serving as reference data for subsequent algorithm optimization;

[0052] Collection of application results: Collect the actual admission results after the candidates fill in the application.

[0053] Algorithm optimization: Use the collected data as a reference for subsequent algorithm optimization to improve the accuracy and efficiency of system adaptation.

[0054] A storage medium having a computer program product stored thereon, the computer program product implementing the above-mentioned intelligent adaptation method for college entrance examination volunteers;

[0055] The storage medium is a non-temporary medium selected from one or more of a hard disk, a solid state drive, an optical disk, a USB flash drive, and a memory.

[0056] A computer program product, comprising a set of instructions, which, when executed on a computing device, implements the above-mentioned intelligent adaptation method for college entrance examination volunteers;

[0057] The program product is distributed via the Internet and supports online updates and maintenance.

[0058] The program product is integrated into a cloud platform, allowing multiple users to access it simultaneously.

[0059] The beneficial effects of the present invention are:

[0060] 1. The present invention integrates advanced technologies such as big data analysis and artificial intelligence algorithms to provide candidates with personalized and accurate volunteer reporting solutions, significantly improving the scientificity and rationality of volunteer selection. The system automatically processes massive amounts of data, reduces the burden on candidates, updates information in real time, and ensures the accuracy of decision-making basis. At the same time, the system ensures fairness and transparency, optimizes the allocation of educational resources, and improves admission satisfaction. Overall, this patent not only innovates the traditional volunteer reporting method, improves efficiency and satisfaction, but also achieves effective adaptation between candidates and colleges;

[0061] 2. The system of the present invention can provide personalized volunteer application plans based on the candidates' personal circumstances, interests, hobbies, personality characteristics and other factors, ensuring that each candidate can find the most suitable college and major for themselves. Through advanced technologies such as big data analysis and artificial intelligence algorithms, the system can accurately predict the probability of admission and professional prospects, providing candidates with scientific and reliable decision-making basis;

[0062] 3. The system of the present invention provides a unified intelligent adaptation service for all candidates, which is not affected by factors such as region and background, ensuring the fairness of volunteer application. The system can show candidates the detailed adaptation process and reasons, improve the transparency of volunteer application, and enable candidates to trust and accept the suggestions of the system more;

[0063] 4. The system is based on scientific means such as big data analysis and artificial intelligence algorithms, which avoids interference from human factors and improves the scientific nature of volunteer reporting. The system can objectively evaluate the situation and needs of candidates, avoid subjective assumptions and blindly follow the trend, and make volunteer reporting more objective and rational.

[0064] 5. Through intelligent adaptation, the system can reasonably allocate candidates to various colleges and majors, avoid waste of resources and congestion, and improve the utilization efficiency of educational resources; the system can improve the candidates' satisfaction with their application and the probability of admission, and reduce the risk of failure and adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the system structure of the present invention.

[0066] Figure 2 It is a schematic diagram of the internal structure of the system of the present invention.

[0067] Figure 3 It is a schematic diagram of the user implementation flow of the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] like Figure 1-3 The college entrance examination volunteer intelligent adaptation system shown in the figure is designed to provide personalized, scientific and accurate volunteer application suggestions for college entrance examination candidates. The system includes data collection and analysis module, intelligent adaptation algorithm module, dynamic update and real-time feedback module, user interaction interface module, security and privacy protection module and result feedback module.

[0070] Module specific implementation

[0071] Data collection and analysis module:

[0072] Data collection: This module integrates historical admission data from provinces, cities and universities across the country through API interfaces, crawler technology and partner sharing, including admission scores over the years, the number of admissions for each major, school information, major settings, etc. It also tracks changes in the college entrance examination policies of the Ministry of Education and various provinces and cities in real time, and promptly feeds back changes to the system.

[0073] Database establishment: Use an efficient database management system to store and manage the collected data to ensure the integrity and accuracy of the data.

[0074] Data analysis: Use statistical analysis and data mining techniques to identify trends and patterns in data and provide reliable data support for algorithms.

[0075] Intelligent adaptation algorithm module:

[0076] For the specific task of filling out college entrance examination applications, the selected large model is further trained to enable it to understand and analyze the needs of candidates, accurately adapt to colleges and majors, predict admission probabilities, and conduct risk assessments.

[0077] Personalized suggestion generation: Based on the candidate’s personal information and preferences, an algorithm is used to generate an application plan that meets the candidate’s needs.

[0078] Dynamic update and real-time feedback module:

[0079] Monitoring and response: Continuously monitor changes in college entrance examination policies and college admission information, and dynamically adjust the adaptation algorithm accordingly to ensure the accuracy and timeliness of system recommendations.

[0080] Real-time feedback: Provide candidates with real-time feedback and revision suggestions to help them make more reasonable decisions during the application process.

[0081] User interface module:

[0082] Interface design: Design a user-friendly interface so that candidates and parents can easily input information, view and adjust volunteer recommendations.

[0083] Interactive experience: Provide clear navigation and operation guides to ensure that users can use the system without obstacles.

[0084] Security and privacy protection module:

[0085] Data security: Encryption technology and security measures are used to protect stored and transmitted data.

[0086] Privacy protection: Strictly abide by relevant laws and regulations to protect the security and privacy of candidates' personal information.

[0087] Result feedback module:

[0088] Collection of application results: Collect the actual admission results after the candidates fill in the application.

[0089] Algorithm optimization: Use the collected data as a reference for subsequent algorithm optimization to improve the accuracy and efficiency of system adaptation.

[0090] System deployment and maintenance

[0091] The college entrance examination volunteer intelligent adaptation system of the present invention can be deployed on a cloud server and provide users with access in the form of Web services. The system should be regularly maintained and updated to ensure the accuracy of data and the advancement of algorithms.

[0092] like Figure 3 Shown: Application Examples

[0093] Step 1: Register and log in

[0094] Li found the official website of the college entrance examination volunteer intelligent adaptation system through a search engine, and registered and logged in.

[0095] Step 2: Enter basic information and college entrance examination scores

[0096] After logging in, Li entered basic personal information under the guidance of the system, including name, admission ticket number, contact information, high school, etc., and the scores of Chinese, mathematics, English and elective subjects. The system automatically generated Li's total score and provincial ranking.

[0097] Step 3: Check your differentiated personality preferences

[0098] Under the guidance of the system, Li checked the regional requirements, professional classification, school requirements, application type, etc. The system used natural language processing technology to accurately grasp Li's basic information and understand Li's needs.

[0099] Step 4: Intelligent adaptation algorithm generates personalized solutions

[0100] Based on Li's input information, the system combined historical admission data, the enrollment policy of the year and the information of the colleges and universities, and generated a personalized volunteer application plan for Li through an intelligent adaptation algorithm. The plan includes three different levels of college and major recommendations: "sprint", "safe" and "safe".

[0101] Step 5: Fine-tune the plan and finalize it

[0102] Li carefully reviewed the volunteer application plan generated by the system and made minor adjustments to some of the suggestions. He fed back to the system based on his actual situation and future plans, and the system adjusted the order of some colleges or majors based on the secondary feedback. After the adjustment was completed, the final volunteer application plan was formed.

[0103] Dynamic updates and real-time feedback

[0104] After completing the application, the system provided Li with dynamic updates and real-time feedback services based on the latest admission results and policy changes. He can check his application status and possible admission results at any time.

[0105] Result feedback and optimization

[0106] When the admission results were announced, Li was successfully admitted to his favorite college. He filled in his actual admission results through the system's result feedback module, providing valuable data for the system's algorithm optimization. At the same time, he also expressed his gratitude to the system, believing that the system provided him with scientific, accurate, and personalized volunteer application suggestions, helping him successfully enter his ideal university.

[0107] In summary, Li successfully filled out the application that suited him by using the college entrance examination application intelligent adaptation system, and was eventually admitted to the college of his choice. This process not only reduced his decision-making burden, but also increased his satisfaction with the application and his probability of admission. Through this case, we can see the important role and value of the college entrance examination application intelligent adaptation system in assisting college entrance examination candidates to fill out their applications.

[0108] In summary, the patent of the college entrance examination volunteer intelligent adaptation system of the present invention is mainly intended to solve the following problems:

[0109] Information asymmetry problem: When filling out their applications, candidates and parents often find it difficult to fully and accurately understand the key information such as the admission policies, majors, and admission data of various colleges and universities, which leads to blindness and uncertainty when filling out their applications. The system integrates massive data to provide candidates with comprehensive and accurate information support, effectively solving the information asymmetry problem.

[0110] Individual differences: Each candidate has different subjects, interests, strengths, and personalities. The traditional volunteer application method is difficult to fully consider these individual differences, resulting in some candidates being unable to find the most suitable colleges and majors for themselves. The system uses a personalized adaptation algorithm to fully tap the individual characteristics of candidates and tailor a volunteer application plan for each candidate to meet the candidates' different preferences for cities, colleges, and majors (categories), effectively solving the problem of individual differences.

[0111] Efficiency and accuracy of volunteer applications: The traditional volunteer application method relies on manual collection, organization, and analysis of data, which is not only time-consuming and labor-intensive, but also prone to errors. The system greatly improves the efficiency and accuracy of volunteer applications through automated processing and intelligent algorithms, allowing candidates to complete volunteer applications easily and quickly.

[0112] Reasonable allocation of educational resources: Due to information asymmetry and individual differences, some colleges and majors may have insufficient or overcrowded students, affecting the reasonable allocation of educational resources. The system uses intelligent adaptation technology to reasonably allocate candidates to various colleges and majors, promoting the balanced use and optimal allocation of educational resources.

[0113] Educational equity issues: Candidates from different regions and backgrounds face different challenges and opportunities when filling out their applications, which may lead to educational equity issues. The system provides unified and fair intelligent adaptation services for all candidates, which are not affected by external factors and help improve educational equity.

[0114] 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. An intelligent adaptation method for college entrance examination volunteers, characterized in that: The following steps are involved: Step 1: Collect historical college entrance examination admission data and enrollment policy information of various colleges and universities to build a database; Step 2: Based on the database, use data analysis technology to analyze the change trend of admission data and the popularity of majors; Step 3: Design and implement an intelligent adaptation algorithm that comprehensively considers the candidates’ elective subjects, grades, major interests, regional preferences, school types, and application types; Step 4: Generate personalized volunteer application suggestions for each candidate based on the intelligent adaptation algorithm; Step 5: Provide a user interface to allow candidates to select and adjust their choices based on the suggestions and provide real-time feedback; Step 6: Dynamically update system data and intelligent adaptation algorithms to respond to changes in college entrance examination policies and college admission information.

2. The intelligent adaptation method for college entrance examination volunteers according to claim 1 is characterized in that: The intelligent adaptation algorithm further considers the admission scores of previous years and the provincial ranking of candidates to form a tiered volunteer combination of "strive, stabilize, and protect".

3. The intelligent adaptation method for college entrance examination volunteers according to claim 1 is characterized in that: In the step of dynamically updating system data and intelligent adaptation algorithms, the system informs candidates of the latest changes by means of push notifications.

4. The intelligent adaptation system for college entrance examination volunteers is characterized by: include: Data collection and analysis module, used to collect and organize historical college entrance examination admission data and enrollment policy information of various colleges and universities, and to establish and update the database; The intelligent adaptation algorithm module, based on big data analysis technology and artificial intelligence technology, generates personalized volunteer application plans according to the candidates' personal information and preferences; Dynamic update and real-time feedback module, used to monitor and respond to changes in college entrance examination policies and college admission information, and update the adaptation algorithm in real time; User interaction interface module, used to display the filling suggestions generated by the system and allow candidates to make selections and adjustments; Security and privacy protection module to ensure the security and privacy of candidates’ personal information; The result feedback module is used to collect the candidates' application results and admission status to evaluate the accuracy and effectiveness of the system, conduct self-learning and improvement based on actual results, and improve its accuracy and effectiveness.

5. The intelligent adaptation system for college entrance examination volunteers according to claim 4 is characterized in that: The intelligent adaptation algorithm module adapts the student information and school information through a preset algorithm to find the school and major that best suits the student.

6. The intelligent adaptation system for college entrance examination volunteers according to claim 4 is characterized in that: It further includes a result feedback module, which is used to collect the admission results after the candidates fill in the application form and serve as reference data for subsequent algorithm optimization.

7. A storage medium having a computer program product stored thereon, characterized in that: The computer program product implements the intelligent adaptation method for college entrance examination volunteers as claimed in claim 1; The storage medium is a non-temporary medium selected from one or more of a hard disk, a solid state drive, an optical disk, a USB flash drive, and a memory.

8. A computer program product, characterized in that It includes a set of instructions, which, when executed on a computing device, implements the intelligent adaptation method for college entrance examination volunteers as claimed in claim 1; The program product is distributed via the Internet and supports online updates and maintenance.

9. The computer program product according to claim 1, characterized in that: The program product is integrated into a cloud platform, allowing multiple users to access it simultaneously.

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