CN113744101A

CN113744101A - Intelligent examinee volunteer filling method and device in new high-level examination mode and computer equipment

Info

Publication number: CN113744101A
Application number: CN202111062181.7A
Authority: CN
Inventors: 胡永春; 柯维海; 赵汝源; 彭奕灵; 徐锦才; 熊志伟; 陆明珠
Original assignee: Guangdong Decheng Scientific Education Co ltd
Current assignee: Guangdong Decheng Scientific Education Co ltd
Priority date: 2021-09-10
Filing date: 2021-09-10
Publication date: 2021-12-03

Abstract

The invention relates to a method, a device and computer equipment for intelligently filling examinee volunteers in a new college entrance examination mode, wherein the method comprises the steps of obtaining college entrance examination information of the examinee and obtaining an intelligent filling mode selected by the examinee; if the examinee selects autonomous filling, receiving a screening condition, determining a first college and school professional set according to the screening condition, college entrance examination information and an autonomous filling volunteer recommendation strategy, and taking the first college and school professional set as a first recommended volunteer; if the examinee selects evaluation filling, acquiring career planning evaluation information, determining the intention specialty of the examinee according to the career planning evaluation information, determining a second college and school specialty set according to the intention specialty, college entrance examination information and evaluation information volunteer recommendation strategy, and taking the second college and school specialty set as a second recommended volunteer; and generating a volunteer fill-in report according to the first recommended volunteer or the second recommended volunteer. The method, the device and the computer equipment provided by the invention can realize intelligent application of volunteers according to the requirements of examinees, simplify the application process and save application time.

Description

Intelligent examinee volunteer filling method and device in new high-level examination mode and computer equipment

Technical Field

The invention relates to the field of college entrance examination volunteer recommendation, in particular to a method and a device for intelligently filling examinee volunteers in a new college entrance examination mode and computer equipment.

Background

After the new college entrance examination reform policy is implemented, except the change on the selection mode, the volunteer filling mode is also adjusted greatly, taking the ordinary class enrollment in Guangdong province as an example, the old college entrance examination mode is to fill 15 colleges and universities and major (classes), and 90 major can be filled; and in the new high-level entrance examination mode, 45 college and university professional groups need to be filled in 270 professionals. The filling quantity and complexity are greatly improved, and if 45 college professional groups are carefully filled, the filling time is about 1-2 hours, and if the filling time is long, few persons can finish the filling accurately and quickly if no professional person is present or the persons have very specific directions to the self-intention professional or college.

Although college entrance examination volunteer simulation filling systems are developed in many education institutions in the market at present, the filling method still needs to add a specialty to a volunteer form for the students with specific target colleges and universities, and the college entrance vocals and the college vocals can be selected by the students in person. However, for students who are not highly targeted or are not skilled in the system, the filling method is not only time-consuming, but also has the problem that how to fill the report is unknown.

Disclosure of Invention

In order to solve the technical problems, the invention provides a method, a device and computer equipment for intelligently filling the volunteers in a new college entrance examination mode, which greatly simplify the volunteer filling process and save the filling time.

The invention provides an examinee volunteer intelligent filling method in a new college entrance examination mode, which comprises the steps of obtaining college entrance examination information of an examinee, wherein the college entrance examination information comprises college entrance examination scores, intra-provincial ranks, provinces where the college entrance is located and department selection combinations; acquiring an intelligent filling mode selected by an examinee, wherein the intelligent filling mode comprises autonomous filling and evaluation filling; if the examinee selects self-help filling, the screening condition selected by the examinee is received, a first college and school professional set is determined according to screening of the screening condition, college entrance examination information and a preset self-help filling volunteer recommendation strategy, and the first college and school professional set is used as a first recommendation volunteer; if the examinee selects evaluation reporting, acquiring career planning evaluation information of the examinee, determining the intention major of the examinee according to the career planning evaluation information, recommending a strategy second college major set according to the intention major, college entrance examination information and preset evaluation information, and taking the second college major set as a second recommended volunteer; and generating a volunteer fill-in report according to the first recommended volunteer or the second recommended volunteer.

Further, the screening condition includes a reporting intent and/or a physical health condition, wherein the reporting intent includes one or more of an intent area, an intent institution and an intent specialty, or the reporting intent is unintentional.

Further, if the volunteer reporting mode of the province where the examinee is located is an institution professional group mode, the first institution professional set is composed of a plurality of institution professional groups, if the number of institution professional groups in the first institution professional set is smaller than a first preset threshold, the strategy is relaxed according to preset conditions, one or more screening conditions are cancelled, and the number of institution professional groups in the first institution professional set is filled to the first preset threshold; and if the volunteering mode of the province of the examinee is professional (class) + colleges, the first college and university professional set consists of a plurality of college and university professionals, if the number of the college and university professionals in the first college and university professional set is less than a second preset threshold, one or more screening conditions are cancelled according to a preset condition relaxation strategy, and the number of the college and university professionals in the first college and university professional set is filled to the second preset threshold.

Further, determining a first college and school professional set according to the screening conditions, the college entrance examination information and a preset voluntary reporting volunteer recommending strategy, wherein the step of taking the first college and school professional set as a first recommending volunteer comprises the following steps: determining a third college professional set which accords with the selection combination according to the selection combination, determining a fourth college professional set which accords with the screening condition from the third college professional set according to the screening condition, and calculating the probability of the examinee being recorded by each college professional or college professional group in the fourth college professional set according to the college score, the intra-provincial ranking and the province of the examinee; and according to a preset recording hierarchical division strategy and recording probability, performing recording hierarchical division on each college specialty or college specialty group in the fourth college specialty set to generate an impact volunteer group, a safe volunteer group and a guaranteed volunteer group, and selecting a preset number of college specialties from the impact volunteer group, the safe volunteer group and the guaranteed volunteer group as the first college specialty set.

Further, the career planning evaluation information comprises a subject interest evaluation result, a Holland career interest evaluation result, a multi-element intelligent evaluation result and an MBTI career evaluation result, wherein the subject interest evaluation result, the Holland career interest evaluation result, the multi-element intelligent evaluation result and the MBTI career evaluation result respectively comprise one or more recommendation majors.

Further, determining the intention speciality of the examinee according to the career planning evaluation information comprises: counting the recommended times of each recommended specialty in the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational character evaluation result, and determining the recommendation degree of each recommended specialty according to the recommended times of each recommended specialty; and selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees according to the recommendation degree.

The invention also provides an examinee voluntary reporting device in a new high-examination mode, which comprises an examinee information acquisition module, an autonomous reporting module, an evaluation reporting module and a voluntary reporting table generation module, wherein: the examinee information acquisition module is connected with the autonomous filling module and the evaluation filling module and is used for acquiring the high-level examination information of the examinee, wherein the high-level examination information comprises a high-level examination score, an intra-provincial ranking, a provincial share and a department selection combination, and acquiring an intelligent filling mode selected by the examinee, and the intelligent filling mode comprises autonomous filling and evaluation filling; the system comprises an autonomous filling module, a pre-set recommendation module and a first college and university professional set, wherein the autonomous filling module is connected with a voluntary filling table generation module and used for receiving a screening condition selected by an examinee when the examinee selects autonomous filling, determining the first college and university professional set according to the screening condition, college entrance examination information and a preset autonomous filling volunteer recommendation strategy, and taking the first college and university professional set as a first recommended volunteer; the assessment filling module is connected with the volunteer filling table generating module and used for acquiring career planning assessment information of the examinee when the examinee selects assessment filling, determining the intention specialty of the examinee according to the career planning assessment information, determining a second college and school specialty set according to the intention specialty, college entrance examination information and a preset assessment information volunteer recommending strategy, and taking the second college and school specialty set as a second recommending volunteer; and the volunteer form filling generation module is used for generating a volunteer form filling according to the first recommended volunteer or the second recommended volunteer.

Further, the autonomous filling module comprises a receiving unit, a screening unit and a first recommended volunteer generating unit, wherein: the receiving unit is connected with the screening unit and used for receiving the screening conditions selected by the examinees; the screening unit is connected with the first volunteer recommending unit and used for determining a third college professional set which accords with the selection combination according to the selection combination and determining a fourth college professional set which accords with the screening condition from the third college professional set according to the screening condition; the first recommended volunteer generating unit is used for calculating the admission probability of the examinee for each institution professional or institution professional group in the professional set of the fourth institution according to the college entrance score, the subject selection combination, the intra-provincial ranking and the provincial share of the examinee; and according to a preset recording level division strategy and a preset recording probability, performing recording level division on each institution specialty or institution specialty group in a fourth institution specialty set to generate an impact volunteer group, a conservative volunteer group and a conservative volunteer group, selecting a preset number of institution specials or institution specialty groups from the impact volunteer group, the conservative volunteer group and the conservative volunteer group as a first institution specialty set, and taking the first institution specialty set as a first recommended volunteer.

Further, the evaluation reporting module comprises a subject interest evaluation unit, a Holland occupational interest evaluation unit, a multi-element intelligent evaluation unit, an MBTI occupational performance evaluation unit, an intention professional determination unit and a second recommendation volunteer generation unit, wherein: the subject interest evaluation unit is connected with the intention specialty determining unit and used for performing subject interest evaluation on the examinees according to a preset subject interest evaluation strategy to generate a subject interest evaluation result, and the subject interest evaluation result comprises one or more recommendation specialties; the Harand occupational interest evaluation unit is connected with the intention professional determination unit and is used for carrying out Harand occupational interest evaluation on the students according to a preset Harand occupational interest evaluation strategy to generate a Harand occupational interest evaluation result, and the Harand occupational interest evaluation result comprises one or more recommendation professionals; the multivariate intelligent evaluation unit is connected with the intention professional determination unit and is used for performing multivariate intelligent evaluation on the examinee according to a preset multivariate intelligent evaluation strategy to generate a multivariate intelligent evaluation result, and the multivariate intelligent evaluation result comprises one or more recommendation professionals; the MBTI occupational character evaluation unit is connected with the intention professional determination unit and is used for carrying out MBTI occupational character evaluation on the examinee according to a preset MBTI occupational character evaluation strategy to generate an MBTI occupational character evaluation result, and the MBTI occupational character evaluation result comprises one or more recommendation professionals; the intention specialty determining unit is connected with the first recommending volunteer generating unit and is used for counting the recommended times of each recommending specialty in the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational character evaluation result and determining the recommendation degree of each recommending specialty according to the recommended times of each recommending specialty; according to the recommendation degree, selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees; and the second recommended volunteer generating unit is used for determining a second college and school professional set according to the intention specialty, the subject combination, the college entrance examination information and a preset evaluation information volunteer recommending strategy, and taking the second college and school professional set as a second recommended volunteer.

The invention also provides a computer device comprising a processor and a memory, wherein the memory stores computer readable instructions which, when executed by the processor, perform the steps of the method.

The examinee volunteer intelligent filling method, the examinee volunteer intelligent filling device and the computer equipment in the new college entrance examination mode have the following beneficial effects: the volunteer filling report can be generated by obtaining the college entrance examination information of the examinees, the screening conditions selected by the examinees or the career planning evaluation information of the examinees, the examinees do not need to add the volunteers into the volunteer report one by one, and for the examinees with weak target or unskilled filling systems, the volunteer filling process is greatly simplified, and the filling time is saved.

Drawings

FIG. 1 is a flowchart of an intelligent examinee volunteer filling method in a new high-level examination mode according to an embodiment of the present invention;

FIG. 2 is a flowchart of a first recommended volunteer generation step in one embodiment of the present invention;

FIG. 3 is a flow chart of intent specialty determination steps in one embodiment of the present invention;

FIG. 4 is a structural diagram of an intelligent examinee volunteer filling device in a new entrance examination mode according to an embodiment of the present invention;

FIG. 5 is a block diagram of an autonomous reporting module according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of an evaluation reporting module according to an embodiment of the present invention;

FIG. 7 is a diagram illustrating a computer device according to an embodiment of the present invention;

401-examinee information acquisition module, 402-autonomous filling module, 403-evaluation filling module, 404-wish filling generation module, 4021-receiving unit, 4033-screening unit, 4023-first recommendation wish generation unit, 4031-subject interest evaluation unit, 4032-Holland occupational interest evaluation unit, 4033-multi-intelligent evaluation unit, 4034-MBTI occupational character evaluation unit, 4035-intention specialty determination unit, 4036-second recommendation wish generation unit, 7-computer equipment, 701-processor, 702-memory and 703-communication bus.

Detailed Description

The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without any inventive step, are within the scope of the present invention.

In an embodiment of the present invention, an examinee volunteer intelligent filling method in a new college entrance examination mode is provided, as shown in fig. 1, the method includes the following steps:

step S101: and obtaining college entrance examination information of the examinees, wherein the college entrance examination information comprises college entrance examination scores, intra-provincial ranks, provinces where the college entrance examination scores are located and subject selection combinations.

Specifically, the examinee can log in the intelligent voluntary reporting system through the personal terminal device, and input college entrance score and/or intra-provincial rank, and the combination of the province and the department of choice in the system. If the examinee only inputs one of the information of the college entrance score or the intra-provincial ranking, after the system receives the college entrance score or the intra-provincial ranking, the corresponding one-by-one college entrance table in the current year can be obtained according to the combination of the province and the selection department where the examinee is located, and therefore the examinee is obtained without inputting the other information.

In a new college entrance examination mode adopted by college entrance examination in Guangdong province: the "3 +1+ 2" department selection mode is taken as an example, namely, the language number is a necessary subject, 1 department is independently selected from 2 physical and historical subjects as a preferred subject, and 2 departments are independently selected from 4 subjects of ideological and political administration, geography, chemistry and biology as a reselected subject; in this example, the selection combination refers to the preferred subject + the reselected subject. When the scores of college entrance examinations are published, the education examination department of each province also publishes a first-choice subject of the province, namely a physical college entrance one-by-one table, and a first-choice subject, namely a history one-by-one table, which is equivalent to a science college entrance examination one-by-one table and a literature college entrance examination one-by-one table in the college entrance examinations in the past. Therefore, when the examinee inputs one of the college entrance score and the intra-provincial ranking, the corresponding one-segment table can be obtained according to the combination of the province and the selection department of the examinee, and the other information of the college entrance score or the intra-provincial ranking can be obtained.

Step S102: and acquiring an intelligent filling mode selected by the examinee, wherein the intelligent filling mode comprises autonomous filling and evaluation filling.

Similarly, after the examinee inputs the college entrance score and/or the intra-provincial rank and the combination of the province and the subject, the examinee selects a required intelligent filling mode on the intelligent voluntary filling system, if the intelligent filling mode selected by the examinee is self-filling, the step S103 is executed, and if the intelligent filling mode selected by the examinee is evaluation filling, the step S104 is executed.

Step S103: and receiving the screening conditions selected by the examinee, determining a first college and school professional set according to the screening conditions, college entrance examination information and a preset voluntary reporting volunteer recommending strategy, and taking the first college and school professional set as a first recommending volunteer.

Specifically, in this step, the screening condition includes a reporting intention and/or a physical health condition, wherein the reporting intention includes one or more of an intention region, an intention institution and an intention specialty, or the reporting intention is not intention. The physical health condition may include conditions of color blindness, color weakness, disability, and the like.

More specifically, the new college entrance examination volunteer filling mode can be a college professional group or a professional (class) + college mode. If the model is a professional group model of the institutions, the professional groups are determined by all the institutions, one institution can set a plurality of professional groups, each professional group comprises different numbers of professionals, the requirement of each professional for selecting the subject in the same professional group is the same, the first professional group of the institutions can be a set formed by the professional groups of the institutions, and each professional group of the institutions comprises a plurality of professionals. How is the professional (class) + institution model, the first institution specialty set is a set of multiple institution specialties.

Similarly, the examinee can check in the intelligent voluntary reporting system or fill in the screening conditions.

In an implementation manner of this embodiment, as shown in fig. 2, determining a first college and school specialty set according to a screening condition, college entrance examination information, and a preset recommendation policy for voluntary reporting volunteers, and taking the first college and school specialty set as a first recommendation volunteer includes the following steps:

step S201: and determining a third college and university professional set which meets the selection combination according to the selection combination, and determining a fourth college and university professional set which meets the screening condition from the third college and university professional set according to the screening condition.

Specifically, the enrollment information of all institutions in the country is stored in the database of the voluntary intelligent enrollment system, and in the new high-level examination mode, each institution sets a subject selection requirement for each specialty enrolled by the institution, and only if the subject selection combination of the examinee can meet the subject selection requirement, the corresponding specialty can be enrolled, so in this step, the institution specialty capable of being enrolled by the examinee is determined as a third institution specialty set according to the subject selection combination, and then a fourth institution specialty set meeting the screening conditions set by the examinee is screened from the third institution specialty set capable of being enrolled by the examinee according to the screening conditions set by the examinee/examinee.

Further, in this step, if the college entrance wish reporting mode is a college professional group, the third college professional set and the fourth college professional set are composed of a plurality of college professional groups, each college professional group includes a plurality of professionals, and the subject selection requirements of the plurality of professionals in each college professional group are the same.

Step S202: and calculating the admission probability of the examinee for each institution professional or institution professional group in the fourth institution professional set according to the college entrance score, the selection combination, the intra-provincial ranking and the province of the examinee.

Specifically, the method for calculating the admission probability of each institution may be a conventional calculation method in the prior art, which is not limited in the present invention. Preferably, in order to improve the accuracy of the admission probability, when the admission probability of each department professional is calculated, the corresponding historical school gear-casting line of the school to be predicted and the corresponding historical professional gear-casting line of the department to be predicted of the school to be predicted can be obtained according to the selection combination and the province where the selection combination is located; and acquiring corresponding historical school gear shifting positions according to the historical school gear shifting lines, predicting the school gear shifting positions of the school to be predicted in the current year by using a regression prediction method, and taking the scores corresponding to the school gear shifting positions of the school in the current year as the school gear shifting lines of the school to be predicted in the current year. Subtracting historical school casting lines of corresponding years from historical professional casting lines to obtain historical score line differences of the specialties to be predicted (if the historical score line differences are multiple, taking an average value); and (4) predicting the professional casting line of the current year according to the historical score line difference of the professional to be predicted and the school casting line of the current year (adding the school casting line of the current year and the historical score line difference). Calculating a first score difference value between the college entrance examination score and the professional gear casting line of the current year, and a second score difference value between the college entrance examination score and the school gear casting line of the current year; acquiring a selection combination and a one-to-one section table of historical college entrance examination corresponding to the province where the selection combination is located, and determining a third score difference value between a score of the province interior ranking in the one-to-one section table of the historical college entrance examination and a historical professional gear casting line according to the province interior ranking; determining historical professional enrollment probability and current-year professional enrollment probability according to the professional primary enrollment probability-score difference corresponding relation, the first score difference and the third score difference; determining school admission probability according to the corresponding relation of the school admission probability and the score difference and the second score difference; according to the formula: the method comprises the steps of calculating the admission probability of a to-be-predicted student in a to-be-predicted school, wherein the admission probability of the to-be-predicted student is school admission probability a + historical professional admission probability average of the to-be-predicted student b + current-year professional admission probability c, and calculating the admission probability of the to-be-predicted student in the to-be-predicted school, wherein a, b and c are preset probability correction coefficients, a + b + c is 1, and in one implementation mode, a is 0.2, b is 0.6 and c is 0.2.

More specifically, in the preliminary professional admission probability-score difference value correspondence relationship, each score difference value corresponds to a professional admission probability, and similarly, in the school admission probability-score difference value correspondence relationship, each score difference value corresponds to a school admission probability, so that under the condition that the first difference value, the second difference value and the third difference value are known, the professional admission probability in the current year corresponding to the first difference value, the school admission probability corresponding to the second difference value and the historical professional admission probability corresponding to the third difference value can be obtained. And substituting the calculated historical professional admission probability, the professional admission probability in the current year and the school admission probability into a professional admission probability formula to calculate the professional admission probability.

In the method for calculating the admission probability provided in the step, the dynamic change of the gear-casting line is considered, the current-year school gear-casting line and the current-year professional gear-casting line of the school to be predicted are predicted according to the historical school gear-casting line and the historical professional gear-casting line, and then the probability that the examinee to be predicted is admitted by the professional to be predicted of the school to be predicted is calculated according to the college score, the intra-provincial ranking, the current-year professional gear-casting line, the historical professional gear-casting line, the current-year school gear-casting line and the preset college professional admission probability prediction strategy, so that the predicted professional admission probability result can be more accurate. Meanwhile, when calculating the professional enrollment probability of the examinee to be predicted, the school enrollment probability, the examinee historical professional enrollment probability to be predicted and the examinee current-year professional enrollment probability to be predicted are integrated, and corresponding probability correction coefficients are given to the school enrollment probability, the examinee historical professional enrollment probability to be predicted and the examinee current-year professional enrollment probability to be predicted, so that the professional enrollment probability of the examinee to be predicted is finally obtained, and the calculation accuracy is further improved.

Further, when calculating the professional admission probability, the schools can be further divided into provinces and provinces, the primary admission probability-score difference corresponding relation of the professional and the primary admission probability-score difference corresponding relation of the school and the admission probability-score difference corresponding relation of the school, each score difference corresponds to an intra-province professional admission probability, an extra-province professional admission probability, an intra-province school admission probability and an extra-province school admission probability, and the corresponding intra-province professional admission probability or the extra-province professional admission probability and the intra-province school admission probability or the extra-province school admission probability are selected according to whether the school to be predicted is the intra-province school or the extra-province school, so that the calculation accuracy is further improved.

Of course, the following influence factors may also be considered to influence the admission probability, so as to adjust the admission probability: the method comprises the following steps that (I) school levels are divided into two first-class schools, national key universities, provincial co-construction colleges, general provincial home schools, civil home schools and the like according to the level division basis of the colleges, wherein the higher the level of the school for reporting and checking is, the lower the admission probability is; (II) school types, wherein according to Chinese university classification (schools are generally divided into comprehensive classes, reason classes, finance classes, political classes, medicine classes, teaching classes, languages, agriculture and forestry classes, ethnic classes, military classes, artistic classes and sports classes), in schools with the same level, the project line recorded and classified in the reason class schools is higher than the project line recorded and classified in other types of schools, and the recording probability is lower; (III) in school distribution, colleges and universities of the same level and type, the admission scores of professional colleges and universities in developed areas are generally higher than those in underdeveloped areas, and those in coastal areas are generally higher than those in inland and remote areas, and correspondingly, the admission probability of the colleges and universities is lower; (IV) the number of professional enrollment plans is changed, if the number of the professional enrollment plans is changed compared with the number of the professional enrollment plans in the past year, the corresponding professional gear shifting line is also changed (note: the gear shifting line has larger fluctuation range, and the gear shifting line correspondingly has larger fluctuation); (V) major events (including school renaming, national policy, newly-established school district, international relationship, epidemic situation and the like) such as the epidemic situation in 2020 can cause the number of persons in the medical special industry of the examination reporting medicine to increase, and the admission probability of examinees can be reduced; and (VI) deeply analyzing the mentioned industries according to the future development planning of the country and refining the specialties corresponding to the travel industry, wherein the specialties are basically promising in future. Thus, the probability of enrollment for reporting such specialties is relatively small.

More specifically, if the college entrance wish reporting mode of the province of the examinee is the college professional group mode, after the admission probability of each college professional is calculated, the admission probability of each college professional group in the fourth college professional group is calculated by taking the college professional group as a unit, wherein the admission probability of each college professional group is the average value of the admission probabilities of the college professionals in the college professional group.

Step S203: and performing admission hierarchical division on each college specialty or college specialty group in the fourth college specialty set according to a preset admission hierarchical division strategy and admission probability to generate an impact volunteer group, a stable volunteer group and a preserved volunteer group.

Specifically, in this step, corresponding admission probability ranges may be preset for the impact volunteer group, the conservative volunteer group, and the guarantor volunteer group, and then each institution specialty or institution specialty group in the fourth institution specialty set may be hierarchically divided according to the admission probability of each institution specialty or institution specialty group in the fourth institution specialty set to generate the impact volunteer group, the conservative volunteer group, and the guarantor volunteer group. For example, the enrollment probability range for the impact volunteer group is [ 30%, 49.99% ], the enrollment probability range for the conservative volunteer group is [ 50%, 79.99% ], and the enrollment probability range for the undermining volunteer group is [ 80%, 100% ], although if the enrollment probability is less than 30%, the examinee is not advised to fill out.

Step S204: and selecting a preset number of college majors or college majors from the impact volunteer group, the conservative volunteer group and the bottom-protected volunteer group as a first college major.

Specifically, when college entrance examination is filled with volunteers, the number of college entrance examination is limited, for example, taking the guangdong as an example, the college entrance examination is in a college professional group mode, 45 college professional groups are filled at most, and 6 professions are filled in each college professional group at most, that is, 270 professions in total, so that when filling is performed, a preset number of college professional groups are respectively selected from the impact volunteer group, the safe volunteer group and the insurance volunteer group to serve as a second college professional set. For example, 15 college professional groups (6 college professionals at most in each college professional group) are selected from the impulse volunteer group, 15 college professional groups (6 college professionals at most in each college professional group) are selected from the conservative volunteer group, and 15 college professional groups (6 college professionals at most in each college professional group) are selected from the conservative volunteer group.

More specifically, the preset number may be set by the examinee according to the requirement of the number of filled college entrance examination volunteers in the province, or may be set by the technician according to the requirement of the number of filled college entrance examination volunteers in the province, which is not limited in the present invention.

In another implementation manner, during autonomous filling, the examinee may select a filling scheme (an impact type, a conservative type, a bottom-preserving type or a self-defined type), specifically, the number of impact volunteers, bottom-preserving volunteers and conservative volunteers in the impact type filling scheme, the conservative type filling scheme and the bottom-preserving type filling scheme is preset by a technician, and the number of impact volunteers, bottom-preserving volunteers and conservative volunteers in the self-defined type filling scheme is set by the user, which is not limited by the present invention.

Preferably, taking a college entrance examination filing volunteer as a professional group mode of colleges and universities as an example, 15 groups of impact volunteers, 15 groups of stable volunteers and 15 groups of bottom-preserving volunteers are adopted in the impact type filing scheme; in the safe type filling scheme, the number of impact volunteers is 5, the number of safe volunteers is 20, and the number of bottom-preserving volunteers is 20; in the conservative filling scheme, the impact volunteers are 1 group, the conservative volunteers are 20 groups, and the bottom-preserving volunteers are 24 groups.

For the convenience of the skilled person to understand, the following description is given by way of example, and the Guangdong example can report at most 45 college major groups, and assume that the selection combination of the same school A is physics + chemistry + biology and the input score is 550 points. Firstly, the system screens out college and university professional groups which can be filled under the selection combination according to the selection combination of examinees, and 1000 groups are assumed; the intention areas selected by the college A are places such as Guangdong, Beijing, Shanghai and the like, the system is limited to all the admission institutions of the three areas from 1000 college and university professional groups, and 500 college and university professional groups meeting the conditions are assumed; the types of colleges selected by the students A are comprehensive colleges, reason-of-work colleges and medical colleges, the system can screen out the schools which accord with the three types selected on the basis of the professional groups of the 500 colleges, and 300 groups which accord with the conditions are assumed; then according to intention specialties (classes) (computer class, clinical medicine, law class and economics class) set by the class A, the system screens professional groups with the intention specialties (classes) of the class A from the basis of 300 college professional groups, supposes that 100 college professional groups meeting all conditions are finally screened, and finally, the system selects 45 college professional groups according to the admission probability of each group and fills the 45 college professional groups into a volunteer form by using a 'punching, stabilizing and guaranteeing' rule.

Further, when the autonomous filling is performed, and the screening condition is limited too much, the first recommending volunteer recommended by the system may be less than the highest value capable of being filled required by the province, and at this time, the examinee can automatically check whether the system is used for automatic replenishment or not, and when the examinee selects the system for automatic replenishment. The system automatically fills up to the highest value of the provincial requirement that can be filled in.

If the volunteering mode of the province of the examinee is a college professional group mode, the first college professional set is composed of a plurality of college professional groups, if the number of the college professional groups in the first college professional set is smaller than a first preset threshold (the first preset threshold is determined by the requirement of the province of the examinee, for example, 45 college professional groups are filled in the Guangdong province at most, the first preset threshold is 45), releasing a strategy according to preset conditions, canceling one or more screening conditions, and filling up the number of the college professional groups in the first college professional set to the first preset threshold;

if the volunteering mode of the province of the examinee is professional (class) + colleges, the first college professional set is composed of a plurality of college professionals, if the number of the college professionals in the first college professional set is smaller than a second preset threshold (the second preset threshold is determined by the requirement of the college professional in the province, for example, the maximum 96 college professionals are filled in the Hebei province, the second preset threshold is 96), the strategy is released according to preset conditions, one or more screening conditions are cancelled, and the number of the college professionals in the first college professional set is supplemented to the second preset threshold.

For the skilled person to understand, the following are exemplified: assuming that the score input by the college department B is 600 minutes, and other selected conditions are the same as those of the college department A, only 30 college professional groups meeting the conditions are finally screened by the system, when the system automatically supplements volunteers, the system can firstly put the regional screening conditions, namely searching the college professional groups meeting other conditions in the whole country, and if the number of the regional screening conditions is less than 45, the second regional type limiting condition is put aside until the inquired college professional groups meet 45. Of course, in the practical application process, it is also possible to set a professional screening condition and the like, which is only an example and is not a limitation to the present invention.

Step S104: acquiring career planning evaluation information of the examinee, determining the intention specialty of the examinee according to the career planning evaluation information, determining a second college and school specialty set according to the intention specialty, college entrance examination information and a preset evaluation information volunteer recommending strategy, and taking the second college and school specialty set as a second recommending volunteer.

In this step, the career planning evaluation information includes a subject interest evaluation result, a hollander career interest evaluation result, a multi-element intelligent evaluation result, and an MBTI career evaluation result, where the subject interest evaluation result, the hollander career interest evaluation result, the multi-element intelligent evaluation result, and the MBTI career evaluation result respectively include one or more recommendation specialties.

Further, the career planning evaluation information also includes an occupational value observation and evaluation result, and specifically, the occupational value observation and evaluation result is obtained by using a WorkValueInventory (Super, 1970) occupational value observation and evaluation scale (WVI). The table can be used for knowing the priority of the importance of various characteristics of the work, helping people to establish and form own professional value views and providing reference for users when selecting in future professions.

Furthermore, after the career planning evaluation information (the subject interest evaluation result, the hollander professional interest evaluation result, the multi-element intelligent evaluation result, the MBTI professional evaluation result, and the professional value evaluation result) is obtained, the subject interest evaluation result, the hollander professional interest evaluation result, the multi-element intelligent evaluation result, and the MBTI professional evaluation result are used for determining the professional of the examinee, and the subject interest evaluation result, the hollander professional interest evaluation result, the multi-element intelligent evaluation result, the MBTI professional evaluation result, and the professional value evaluation result are integrated to generate a career planning evaluation report for the examinee to refer to when selecting the professional.

As shown in fig. 3, determining the intention specialty of the examinee according to the career planning evaluation information includes the steps of:

step S301: counting the recommended times of each recommended specialty in the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational character evaluation result, and determining the recommendation degree of each recommended specialty according to the recommended times of each recommended specialty;

specifically, the higher the recommendation frequency is, the higher the professional recommendation degree is, a comparison relationship table of the recommendation frequency and the recommendation degree may be preset, and the recommendation degree of each recommendation specialty may be determined according to the comparison relationship table and the recommendation frequency.

Step S302: and selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees according to the recommendation degree.

Specifically, the recommendation professionals can be ranked from large to small according to the recommendation degree, and 5-10 recommendation professionals with high recommendation degrees are selected from the recommendation professionals as the intention professionals of the examinees.

After the intention specialties of the examinees are obtained, a fifth college and university professional set which accords with the intention specialties can be screened out according to the intention specialties, the recording probability of each college and university professional in the fifth college and university professional set is calculated according to the college entrance information, and the second college and university professional set is determined as a second recommended aspiration according to the recording probability (the calculation method of the specific recording probability can be the same as the calculation method mentioned above, and the method for determining the second college and university professional set according to the recording probability can be the same as the method for determining the first college and university professional set according to the recording probability mentioned above).

Step S105: and generating a volunteer fill-in report according to the first recommended volunteer or the second recommended volunteer.

In the step, the first recommended volunteers or the second recommended volunteers are automatically added into the volunteer filling report to generate a volunteer filling report, the format of the volunteer filling report is consistent with that of a volunteer filling system of an education examination hall, and subsequent examinees can directly fill volunteers in the volunteer filling system of each education examination hall according to the generated volunteer filling report, so that the method is convenient and fast, and the filling process is simplified.

According to the intelligent volunteer recommendation method in the new college entrance examination mode, the volunteer filling report can be generated by obtaining college entrance examination information of the examinees, the screening conditions selected by the examinees or career planning evaluation information of the examinees, the examinees do not need to add volunteers into the volunteer report one by one, and for the examinees with weak target or unskilled filling and reporting systems, the volunteer filling and reporting process is greatly simplified, and the filling and reporting time is saved. And the recommended volunteers can realize accurate recommendation of the volunteers of the examinees due to the comprehensive examination reporting intention, physical health conditions or occupational interests of the examinees, so that the requirements of the examinees are met.

In another embodiment of the present invention, as shown in fig. 4, there is further provided an intelligent examinee volunteer filling device in a new high-level examination mode, which includes an examinee information acquisition module 401, an autonomous filling module 402, an assessment filling module 403, and a volunteer filling table generation module 404, where:

the examinee information acquisition module 401 is connected with the autonomous filling module 402 and the evaluation filling module 403 and is used for acquiring college entrance examination information of the examinee, wherein the college entrance examination information comprises college entrance examination scores, intra-provincial ranks, provinces where the college entrance is located and department selection combinations, and acquiring an intelligent filling mode selected by the examinee, and the intelligent filling mode comprises autonomous filling and evaluation filling;

the autonomous filling module 402 is connected 404 with the voluntary filling form generation module and is used for receiving the screening conditions selected by the examinee, determining a first college professional set according to the screening conditions, the college entrance examination information and a preset autonomous filling volunteer generation strategy, and taking the first college professional set as a first recommended volunteer;

the assessment reporting module 403 is connected to the volunteer reporting table generating module 404, and is configured to acquire career planning assessment information of an examinee when the examinee selects assessment reporting, determine an intention specialty of the examinee according to the career planning assessment information, determine a second college and school specialty set according to the intention specialty, the college and school information, and a preset assessment information volunteer recommending strategy, and use the second college and school specialty set as a second recommending volunteer.

And a volunteer fill-up report generating module 404, configured to generate a volunteer fill-up report according to the first recommended volunteer or the second recommended volunteer.

In another embodiment of the present invention, as shown in fig. 5, the autonomous filling module 402 includes a receiving unit 4021, a screening unit 4022, and a first recommended volunteer generating unit 4023, wherein:

a receiving unit 4021 connected to the screening unit 4022, and configured to receive the screening conditions selected by the examinee;

the screening unit 4022 is connected with the first volunteer recommending unit 4023 and is used for determining a third college professional set meeting the selection combination according to the selection combination and determining a fourth college professional set meeting the screening condition from the third college professional set according to the screening condition;

the first recommended volunteer generating unit 4023 is used for calculating the admission probability of the examinee for each institution specialty or institution specialty group in the fourth institution specialty set according to the college score, the subject combination, the intra-provincial ranking and the corresponding province of the examinee; and according to a preset recording level division strategy and recording probability, performing recording level division on each institution specialty or institution specialty group in a fourth institution specialty set to generate an impact volunteer group, a safe volunteer group and a preserved volunteer group, selecting a preset number of institution specialers or institution specialty groups from the impact volunteer group, the safe volunteer group and the preserved volunteer group as a first institution specialty set, and taking the first institution specialty set as a first recommended volunteer.

In still another embodiment of the present invention, as shown in fig. 6, the evaluation reporting module 403 includes a discipline interest evaluation unit 4031, a hollander occupational interest evaluation unit 4032, a multivariate intelligent evaluation unit 4033, an MBTI occupational performance evaluation unit 4034, an intention specialty determination unit 4035, and a second recommended aspiration generation unit 4036, wherein:

the subject interest evaluation unit 4031 is connected with the intention specialty determination unit 4035 and is used for performing subject interest evaluation on the examinees according to a preset subject interest evaluation strategy to generate a subject interest evaluation result, wherein the subject interest evaluation result comprises one or more recommended specialties; specifically, the subject interest assessment is to perform scientific scale investigation on learning or behavior items related to 13 subjects such as Chinese, mathematics, English, physics, chemistry, biology, history, geography, politics, art, music, sports, technology and the like to obtain which subject is more interested by the examinee, and then recommend the corresponding specialty according to the subject interested by the examinee and the preset subject-specialty corresponding relation.

The hollander occupational interest evaluation unit 4032 is connected with the intention specialty determination unit 4035 and is used for performing hollander occupational interest evaluation on the examinees according to a preset hollander occupational interest evaluation strategy to generate a hollander occupational interest evaluation result, and the hollander occupational interest evaluation result comprises one or more recommendation specialties; the american college of vocational guidance, John hollanded (John Holland), professionally directed by John hopkins university psychology professor, usa, proposed a theory of professional interest with broad social impact in 1959. The types and interests of the people considered by the people are closely related to occupation, the interests are huge motivations for the people to move, and the professional interests and the people have high correlation. According to different interests, the personality can be divided into six dimensions of research type (I), art type (A), social type (S), enterprise type (E), traditional type (C) and reality type (R), and the personality of each person is the combination of the six dimensions in different degrees. Based on the theory, each question corresponds to one kind of professional interest by setting related questions, the examinee selects options conforming to the examinee according to personal actual conditions, and after all the questions are completed, the Holland professional interest evaluation unit integrates the answer conditions of the students to determine the professional interest types of the examinee, for example: and the social + art + enterprise type recommends the professions corresponding to the professional interest type according to the professional interest type and the preset professional interest type-professional corresponding relation.

The multivariate intelligent evaluation unit 4033 is connected with the intention specialty determination unit 4035 and is used for performing multivariate intelligent evaluation on the examinees according to a preset multivariate intelligent evaluation strategy to generate multivariate intelligent evaluation results, wherein the multivariate intelligent evaluation results comprise one or more recommendation specialties; specifically, based on the multivariate intelligent theory of the teaching of gardner of the united states harvard university, 8 kinds of intelligence are used for replacing the traditional ability concept mainly based on language intelligence and logic intelligence, and the intelligent advantages of the user are more comprehensively known. The 8 kinds of intelligence are as follows: 1. language Intelligence (Linguistic Intelligence)2 Logical-Mathematical Intelligence (Logical-Mathematical Intelligence)3 Spatial Intelligence (Spatial Intelligence)4 physical-Kinesthetic Intelligence (body-Kinesthetic Intelligence)5 Musical Intelligence (music Intelligence) 6 human Intelligence (internal Intelligence)7 provincial Intelligence (internal Intelligence)8 natural cognitive Intelligence (natural Intelligence). And determining the multivariate intelligent type of the examinee by setting related questions, and recommending the profession corresponding to the multivariate intelligent type according to the preset multivariate intelligent type-profession corresponding relation.

The MBTI occupational character evaluation unit 4034 is connected with the intention specialty determination unit 4035 and is used for carrying out MBTI occupational character evaluation on the examinees according to a preset MBTI occupational character evaluation strategy to generate an MBTI occupational character evaluation result, and the MBTI occupational character evaluation result comprises one or more recommendation majors; specifically, the MBTI is a theoretical model as a judgment and analysis of personality, and induces and extracts 4 key elements, namely, a power source, an information collection, a decision-making mode and a behavior mode, from complicated personality characteristics to perform analysis and judgment, so as to distinguish people with different 16 personality types. The evaluation adopts an MBTI theoretical model and college professional data to determine the character of an examinee, and recommends a professional corresponding to the character according to a preset character-professional corresponding relation.

An intention specialty determining unit 4035 connected to the second recommended volunteer generating unit 4036, and configured to count recommended times of each recommended specialty in the science interest evaluation result, the hollander professional interest evaluation result, the multivariate intelligent evaluation result, and the MBTI professional character evaluation result, and determine a recommendation degree of each recommended specialty according to the recommended times of each recommended specialty; selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees according to the recommendation degree;

and a second recommended volunteer generating unit 4036, configured to determine a second college and school professional set according to the intention specialty, the college entrance examination information, and the preset evaluation information volunteer recommendation policy, and use the second college and school professional set as a second recommended volunteer.

In still another embodiment of the present invention, as shown in fig. 7, there is also provided a computer apparatus 7 including: the processor 701 and the memory 702, the processor 701 and the memory 702 being interconnected and communicating with each other via a communication bus 703 and/or other form of connection mechanism (not shown), the memory 702 storing a computer program executable by the processor 701, the processor 701 executing the computer program when the computing device is running to perform the method in any of the alternative implementations of the embodiments described above.

The examinee volunteer intelligent filling method, the examinee volunteer intelligent filling device and the computer equipment in the new college entrance examination mode can help the examinee to fill in volunteers quickly, the examinee can complete filling in of the volunteers in one key (5-10 minutes in the whole process) only by filling in necessary information (the examinee college entrance examination information, screening conditions selected by the examinee or career planning evaluation information of the examinee) according to the instructions, and the individual exclusive volunteer filling form is obtained without the need of adding the volunteers into the volunteer form one by one. And the method can be read by matching with professional personnel (the operation can be omitted, and the volunteer filling process is simple and easy to understand), and creative labor and exploration and research are not required to be carried out again. For students with weak target or unskilled filling system, the voluntary filling process is greatly simplified, and the filling time is saved. And when the evaluation report is adopted, according to the results of subject interest evaluation, Holland occupational interest evaluation, multivariate intelligent evaluation and MBTI occupational character evaluation, the intention specialty is comprehensively determined, and the predicted examinee intention specialty is more reasonable.

The terms and expressions used in the specification of the present invention have been set forth for illustrative purposes only and are not meant to be limiting. The terms "first," "second," "third," "fourth," and "fifth" used herein in the claims and the description of the present invention are for convenience of distinction, have no particular meaning, and are not intended to limit the invention to the embodiments shown and described, but rather, those skilled in the art will understand that various changes may be made in the details of the embodiments without departing from the principles of the disclosed embodiments. The scope of the invention is, therefore, indicated by the appended claims, in which all terms are to be understood in their broadest reasonable sense unless otherwise indicated.

Claims

1. An examinee volunteer intelligent filling method in a new high-level examination mode is characterized by comprising the following steps:

obtaining college entrance examination information of an examinee, wherein the college entrance examination information comprises college entrance examination scores, intra-provincial ranks, provinces where the college entrance examination scores are located and a subject selection combination;

acquiring an intelligent filling mode selected by an examinee, wherein the intelligent filling mode comprises autonomous filling and evaluation filling;

if the examinee selects autonomous filling, receiving a screening condition selected by the examinee, determining a first college and school professional set according to the screening condition, the college entrance examination information and a preset autonomous filling volunteer recommendation strategy, and taking the first college and school professional set as a first recommendation volunteer;

if the examinee selects evaluation reporting, acquiring career planning evaluation information of the examinee, determining an intention specialty of the examinee according to the career planning evaluation information, determining a second college and school specialty set according to the intention specialty, the college entrance examination information and a preset evaluation information volunteer recommendation strategy, and taking the second college and school specialty set as a second recommendation volunteer;

and generating a volunteering form according to the first recommended volunteer or the second recommended volunteer.

2. The method for intelligently filling examinee's volunteers in the new college entrance examination mode according to claim 1, wherein the screening condition comprises filling intention and/or physical health condition, wherein the filling intention comprises one or more of intention region, intention college and intention specialty, or the filling intention is unintentional.

3. The intelligent examination room volunteer filling method under the new college entrance examination mode according to claim 1, wherein if the volunteer filling mode of the province where the examination room is located is a college professional group mode, the first college professional set consists of a plurality of college professional groups, if the number of the college professional groups in the first college professional set is less than a first preset threshold, the strategy is relaxed according to preset conditions, one or more screening conditions are cancelled, and the number of the college professional groups in the first college professional set is supplemented to the first preset threshold;

and if the volunteering mode of the province of the examinee is professional (class) + colleges, the first college and university professional set is composed of a plurality of college and university professionals, if the number of the college and university professionals in the first college and university professional set is less than a second preset threshold, one or more screening conditions are cancelled according to a preset condition relaxation strategy, and the number of the college and university professionals in the first college and university professional set is filled to the second preset threshold.

4. The method for intelligently filling examinee's volunteers in a new college entrance examination mode according to claim 1, wherein the determining a first college and school specialty set according to the screening conditions, the college entrance examination information and a preset recommendation strategy for voluntary filling volunteers comprises:

determining a third college and university professional set meeting the selection combination according to the selection combination, and determining a fourth college and university professional set meeting the screening condition from the third college and university professional set according to the screening condition;

calculating the admission probability of the examinee for each institution professional or each institution professional group in the fourth institution professional set according to the college entrance score, the intra-provincial ranking, the selection combination and the province of the examinee;

performing admission hierarchical division on each college specialty or college specialty group in the fourth college specialty set according to a preset admission hierarchical division strategy and admission probability to generate an impact volunteer group, a safe volunteer group and a bottom-conserving volunteer group;

and selecting a preset number of college majors or college majors from the impact volunteer group, the conservative volunteer group and the bottom-protected volunteer group as the first college major set.

5. The method of claim 1, wherein the evaluation information of career planning comprises a subject interest evaluation result, a Holland occupational interest evaluation result, a multivariate intelligent evaluation result and an MBTI occupational performance evaluation result, wherein the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational performance evaluation result respectively comprise one or more recommended specialties.

6. The method for intelligently filling examinee's volunteers in the new college entrance examination mode according to claim 5, wherein the determining the examinee's intention speciality according to the career planning evaluation information comprises:

counting the recommended times of each recommended specialty in the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational character evaluation result, and determining the recommendation degree of each recommended specialty according to the recommended times of each recommended specialty;

and selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees according to the recommendation degree.

7. The utility model provides an examinee's volunteer intelligence is filled in and is reported device under new high examination mode, a serial communication port, the device is including examinee's information acquisition module, independently fill in and report module, test and appraise and fill in and report module and volunteer and fill in and report the form and generate the module, wherein:

the examinee information acquisition module is connected with the autonomous filling module and the evaluation filling module and is used for acquiring college entrance examination information of the examinee, wherein the college entrance examination information comprises college entrance examination scores, intra-provincial ranks, provinces where the college entrance examination belongs and department selection combinations, and acquiring an intelligent filling mode selected by the examinee, and the intelligent filling mode comprises autonomous filling and evaluation filling;

the autonomous filling module is connected with the volunteer filling table generating module and used for receiving a screening condition selected by an examinee when the examinee selects autonomous filling, determining a first college and school professional set according to the screening condition, the college entrance examination information and a preset autonomous filling volunteer recommending strategy, and taking the first college and school professional set as a first recommending volunteer;

the assessment filling module is connected with the volunteer filling table generating module and used for acquiring career planning assessment information of an examinee when the examinee selects assessment filling, determining the intention specialty of the examinee according to the career planning assessment information, determining a second college and school specialty set according to the intention specialty, the college and school information and a preset assessment information volunteer recommending strategy, and taking the second college and school specialty set as a second recommending volunteer;

and the volunteer filling report generating module is used for generating a volunteer filling report according to the first recommended volunteer or the second recommended volunteer.

8. The intelligent examinee volunteer filling device in the new high-examination mode according to claim 7, wherein the autonomous filling module comprises a receiving unit, a screening unit and a first recommended volunteer generating unit, wherein:

the receiving unit is connected with the screening unit and used for receiving the screening conditions selected by the examinees;

the screening unit is connected with the first volunteer recommending unit and used for determining a third college professional set meeting the selection combination according to the selection combination and determining a fourth college professional set meeting the screening condition from the third college professional set according to the screening condition;

the first recommended volunteer generating unit is used for calculating the admission probability of the examinee for each institution specialty or institution specialty group in the fourth institution specialty set according to the college entrance score, the subject combination, the intra-provincial ranking and the province of the examinee; and according to a preset recording level division strategy and recording probability, performing recording level division on each institution specialty or institution specialty group in the fourth institution specialty set to generate an impact volunteer group, a conservative volunteer group and a bottom-preserving volunteer group, selecting a preset number of institution specials or institution specialty groups from the impact volunteer group, the conservative volunteer group and the bottom-preserving volunteer group as the first institution specialty set, and taking the first institution specialty set as a first recommended volunteer.

9. The intelligent examinee volunteer filling device in the new high-examination mode according to claim 7, wherein the evaluation and filling module comprises a subject interest evaluation unit, a Holland occupational interest evaluation unit, a multivariate intelligent evaluation unit, an MBTI occupational performance evaluation unit, an intention specialty determination unit and a second recommended volunteer generation unit, wherein:

the subject interest evaluation unit is connected with the intention specialty determining unit and is used for performing subject interest evaluation on the examinees according to a preset subject interest evaluation strategy to generate a subject interest evaluation result, and the subject interest evaluation result comprises one or more recommendation specialties;

the Hirand occupational interest evaluation unit is connected with the intention professional determination unit and is used for carrying out the Hirand occupational interest evaluation on the examinee according to a preset Hirand occupational interest evaluation strategy and generating a Hirand occupational interest evaluation result, and the Hirand occupational interest evaluation result comprises one or more recommendation professionals;

the multivariate intelligent evaluation unit is connected with the intention specialty determining unit and is used for performing multivariate intelligent evaluation on the examinee according to a preset multivariate intelligent evaluation strategy to generate a multivariate intelligent evaluation result, and the multivariate intelligent evaluation result comprises one or more recommendation specialties;

the MBTI occupational character evaluation unit is connected with the intention professional determination unit and is used for carrying out MBTI occupational character evaluation on the examinees according to a preset MBTI occupational character evaluation strategy and generating an MBTI occupational character evaluation result, and the MBTI occupational character evaluation result comprises one or more recommendation professionals;

the intention specialty determining unit is connected with the first recommending volunteer generating unit and is used for counting the recommended times of each recommending specialty in the subject interest evaluation result, the Holland occupational interest evaluation result, the multivariate intelligent evaluation result and the MBTI occupational character evaluation result and determining the recommendation degree of each recommending specialty according to the recommended times of each recommending specialty; selecting a preset number of recommendation majors from the recommendation majors as intention majors of the examinees according to the recommendation degree;

and the second recommending volunteer generating unit is used for determining a second college and school professional set according to the intention specialty, the college entrance examination information and a preset evaluation information volunteer recommending strategy, and taking the second college and school professional set as a second recommending volunteer.

10. A computer device comprising a processor and a memory, said memory storing computer readable instructions which, when executed by said processor, perform the steps of the method of any one of claims 1 to 6.