CN104572989A - Information recommendation method and system for assisting senior high school students to choose college majors - Google Patents

Information recommendation method and system for assisting senior high school students to choose college majors Download PDF

Info

Publication number
CN104572989A
CN104572989A CN201510003645.5A CN201510003645A CN104572989A CN 104572989 A CN104572989 A CN 104572989A CN 201510003645 A CN201510003645 A CN 201510003645A CN 104572989 A CN104572989 A CN 104572989A
Authority
CN
China
Prior art keywords
student
test
information
type
score
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510003645.5A
Other languages
Chinese (zh)
Other versions
CN104572989B (en
Inventor
赵丙来
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jiangsu Jin Huifu mountain Software Technology Co., Ltd.
Original Assignee
Suzhou Zhizhen Assessment Technology Software Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Suzhou Zhizhen Assessment Technology Software Technology Co Ltd filed Critical Suzhou Zhizhen Assessment Technology Software Technology Co Ltd
Priority to CN201510003645.5A priority Critical patent/CN104572989B/en
Publication of CN104572989A publication Critical patent/CN104572989A/en
Application granted granted Critical
Publication of CN104572989B publication Critical patent/CN104572989B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses an information recommendation method and system for assisting senior high school students to choose college majors. The information recommendation method comprises collecting personal data of every student in a preset test sample group through a preset test library; performing comparison on the personal data and scoring criteria of the preset test library to obtain the original test score of every student; performing mathematical statistics on the original test scores of the students in the test sample group and converting the original test score of every student into an export score which is used for reflecting the level of the student in the test sample group; searching a career test norm which is established in advance according to the export scores and finding out the personal characteristic information and the professional recommendation information which are corresponding to every student. According to the information recommendation method and system for assisting the senior high school students to choose the college majors, the major suitable for every student can be accurately and scientifically matched according to interests and hobbies, personality characteristics, professional potential and professional tendency of the student so as to provide the reasonable major recommendation for the student and avoid the influence of artificial factors.

Description

A kind of auxiliary high school student selects information recommendation method and the system of university's specialty
Technical field
The present invention relates to evaluation technology field, particularly relate to information recommendation method and system that a kind of auxiliary high school student selects university's specialty.
Background technology
Abroad student enter a higher school with careers guidance in have the developing history of decades, when student face enter a higher school and obtain employment time, many schools all can provide multiple psychological test to help student to understand oneself interest, hobby, ability and personality characteristics etc., for they select university's aspiration and occupation in future to provide advisory opinion.Such as American College Test center (ACT), to enter a higher school especially and instruct pendulum in critical positions, and register to combine closely with college entrance examination, when examinee registers, synchronously will carry out psychological test, student, except obtaining Entrance Examination, also can obtain a major choice test and appraisal suggestion.
Due to the singularity of domestic national conditions, the growth environment of student and social employment environment are all with distinct abroad, therefore external entering a higher school is instructed and is not suitable for Chinese student, domestic entering a higher school instructs main still depending on to seek advice from teacher or kith and kin etc. at present, impact by environment limitation and artificial subjective factor is larger, in addition on the one hand high school student due to the age less of autognosis imperfection, the specialty that causing enters a higher school makes a report on also is not suitable for oneself, is unfavorable for the abundant excavation of student's potential and following employment.
Summary of the invention
The object of the invention is to propose information recommendation method and the system that a kind of auxiliary high school student selects university's specialty, the idiosyncrasy drawing student that can be more accurate, more scientific and the specialty adapted to its idiosyncrasy, recommend for student makes more reasonably specialty, avoid the impact of human factor.
For reaching this object, the present invention by the following technical solutions:
Auxiliary high school student selects an information recommendation method for university's specialty, comprising:
The personal data of each student in the test sample book group preset by the collection of preset test exam pool, described test sample book group comprises multiple student;
The score standard of described personal data with the described test exam pool preset is compared, draws the original test result of each student;
Mathematical statistics being carried out to the original test result of student whole in test sample book group, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group;
Search the occupation test norm set up in advance according to described derived score, find out personal characteristic information corresponding to each student and professional recommendation information.
Wherein, described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
By the personal information of the multiple different occupation on-the-job personnel of preset test exam pool collecting test as normal data, build the score standard of described test exam pool according to described normal data;
Analyze the record information of described on-the-job personnel, extract the hobby of described on-the-job personnel, character trait, learn specialty and occupation type information architecture occupation test norm; Described occupation test norm comprises the professional recommendation information of personal characteristic information and correspondence.
Wherein, described occupation test norm comprises subclass: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type; Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence;
Described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
Derived score is divided into multiple numerical intervals, sets up associating of each subclass and described numerical intervals;
Described according to described derived score search set up in advance occupation test norm, find out personal characteristic information corresponding to each student and professional recommendation information, be specially:
Determine the numerical intervals belonging to described derived score;
Search the occupation test norm set up in advance, find out the subclass associated with described numerical intervals;
Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
Wherein, described derived score is percentile rank;
The described original test result to student whole in test sample book group carries out mathematical statistics, the original test of each student is divided the derived score being converted to and can reflecting this student residing level in described test sample book group, comprising:
The original test result of student whole in test sample book group is sorted from high to low, draws the ranking value of original test result in test sample book group of each student;
Calculating derived score PR according to the quantity of student whole in described ranking value, test sample book group is:
PR=100-(100R-50)/N,
Wherein, R is the ranking value of original test result in test sample book group of each student, and N is the quantity of whole student in test sample book group.
Wherein, described derived score is standardized score;
The described original test result to student whole in test sample book group carries out mathematical statistics, the original test of each student is divided the derived score being converted to and can reflecting this student residing level in described test sample book group, comprising:
Calculate the average of the original test result of all students in test sample book group, be designated as X1;
Calculate the standard deviation of the original test result of all students in test sample book group, be designated as S;
Calculate derived score Z according to described average, standard deviation be:
Z=X-X1/S,
Wherein, X is raw score.
Wherein, described personal data comprise: the information of hobby, character trait, professional potential and Career orientation aspect; Wherein, described Career orientation comprises extroversion, introversion, thinking, emotion and consciousness five dimensions;
The described score standard by described personal data and default described test exam pool is compared, and draws the original test result of each student, comprising:
The information of described hobby, character trait, professional potential and Career orientation aspect is compared with the score standard of described test exam pool preset respectively, draws the original measurement mark of the extroversion of each student, introversion, thinking, emotion and consciousness five dimensions respectively.
Wherein, the described original test result to student whole in test sample book group carries out mathematical statistics, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group, comprising:
Respectively mathematical statistics is carried out to the original measurement mark of five dimensions described in each student;
The original measurement mark of described five dimensions of each student is converted to respectively the extroversion of the extroversion for reflecting this student, introversion, thinking, emotion and consciousness five aspects residing level in described test sample book group, the interior derived score to, thinking, emotion and consciousness five dimensions.
Wherein, described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
The derived score of described five dimensions is divided into multiple numerical intervals respectively, and that sets up that each subclass combines with the numerical intervals of five dimensions associates;
Described according to described derived score search set up in advance occupation test norm, find out personal characteristic information corresponding to each student and professional recommendation information, comprising:
Determine the numerical intervals that the derived score of described five dimensions of each student is affiliated separately respectively;
Determine the numerical intervals combination that described numerical intervals is corresponding;
Search the occupation test norm set up in advance, find out and combine with described numerical intervals the subclass associated;
Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
Present invention also offers the information recommendation system that a kind of auxiliary high school student selects university's specialty, comprising:
Data acquisition module, for the personal data of each student in the test sample book group preset by the collection of preset test exam pool, described test sample book group comprises multiple student;
Scoring module, for the score standard of described personal data with the described test exam pool preset being compared, draws the original test result of each student;
Statistical analysis module, for carrying out mathematical statistics to the original test result of student whole in test sample book group, is converted to the derived score for reflecting this student residing level in described test sample book group by the original test result of each student;
Recommending module, for searching the occupation test norm set up in advance according to described derived score, finds out personal characteristic information corresponding to each student and professional recommendation information.
Wherein, also comprise:
Study module, for the personal information by the multiple different occupation on-the-job personnel of preset test exam pool collecting test as normal data, builds the score standard of described test exam pool according to described normal data; And for analyzing the record information of described on-the-job personnel, extract the hobby of described on-the-job personnel, character trait, learn specialty and occupation type information architecture occupation test norm; Described occupation test norm comprises the professional recommendation information of personal characteristic information and correspondence;
Module is set, for described occupation test norm is divided into multiple subclass: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type; Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence, and derived score is divided into multiple numerical intervals, sets up associating of each subclass and described numerical intervals.
Implement the embodiment of the present invention, there is following beneficial effect:
The embodiment of the present invention is by the personal data of each student in preset test exam pool collecting test sample group; The score standard of described personal data with the described test exam pool preset is compared, draws the original test result of each student; Mathematical statistics being carried out to the original test result of student whole in test sample book group, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group; Search the occupation test norm set up in advance according to described derived score, find out personal characteristic information corresponding to each student and professional recommendation information.Pass through the present invention program, can according to more accurate, the more scientific idiosyncrasy drawing student of the hobby of student, character trait, professional potential and Career orientation and the specialty adapted to its idiosyncrasy, student is made to make more reasonably major choice, avoid the impact of human factor, be conducive to that student is more scientific selects specialty effectively.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing described below is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet that the auxiliary high school student of first embodiment of the invention selects the information recommendation method of university's specialty.
Fig. 2 is the professional recommendation tables that the auxiliary high school student of first embodiment of the invention selects the information recommendation method of university's specialty.
Fig. 3 is the information recommendation system structural representation that the auxiliary high school student of second embodiment of the invention selects university's specialty.
Embodiment
Carry out clear, complete description below in conjunction with accompanying drawing of the present invention to the technical scheme in the embodiment of the present invention, obviously, described embodiment is only a part of embodiment of the present invention, instead of whole embodiments.Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under the prerequisite of not making creative work, all belongs to the scope of protection of the invention.
Composition graphs 1 pair of first embodiment of the present invention is described.
Fig. 1 is the information recommendation method process flow diagram that the auxiliary high school student of first embodiment of the invention selects university's specialty, and details are as follows:
Step S101, selectes the personal data of each student in test sample book group by the collection of preset test exam pool.
In a first embodiment, need pre-determine test sample book group, comprise multiple student in test sample book group, such as, can extract southern area of Jiangsu Province high school student and university student as test sample book group, usual test sample book group capacity required is enough large and representative.
Test exam pool can adopt the mode of multiple-choice question to arrange, by receiving the answer that student selects, collect the personal data of the information of the aspects such as the hobby of each student in test sample book group, character trait, professional potential and Career orientation, corresponding, the problem including the aspects such as hobby, character trait, professional potential and Career orientation in described test exam pool is arranged, more fully to collect the personal data of student, so that the idiosyncrasy determining student accurately and the specialty be applicable to.
Step S102, compares the score standard of described personal data with the described test exam pool preset, draws the original test result of each student.
In the present embodiment, can in advance by the personal information of the multiple different occupation on-the-job personnel of described test exam pool collecting test as normal data, build the score standard of described test exam pool according to described normal data.Representative industry elite can be chosen and carry out this test, to build standard of scoring more accurately.It should be noted that, also can the score standard built by which be adjusted, to make score standard more scientific more reasonable.
Contrasted with score standard by the personal data of the student collected, can obtain a test result, this test result is original test result.Such as, 1 point, 2 points, 3 points, 4 points that answer A, B, C, D in test exam pool are corresponding respectively, be added according to the selection situation score of student and can draw an original test result.But for student, this original test result is directly perceived not, is not easy to student and fully understands the idiosyncrasy of oneself and professional potential, therefore needing this original test result to be converted to student can the information of intuitivism apprehension.
Preferably, in the present embodiment, the information personal data of the hobby of student, character trait, professional potential and Career orientation aspect are compared with the score standard of the described test exam pool preset respectively, show that each student is at export-oriented, the interior original measurement mark to, thinking, emotion and consciousness five dimensions respectively, by the test result of refinement student, be conducive to clearer reflection student idiosyncrasy information in every respect.
Step S103, carries out mathematical statistics to the original test result of student whole in test sample book group, the original test result of each student is converted to the derived score for reflecting this student residing level in described test sample book group.
In the present embodiment, the object that this original test result is changed is: obtain and there is certain reference point and unit and the information that can mutually compare, the individual position residing in test sample book group of such as instruction (the such as export-oriented level of index in contemporary, the level etc. of emotional ability in contemporary), comparablely to measure to provide some, make relatively to become possibility to the individual test result of test.
Preferably, mathematical statistics can be carried out to the original measurement mark of five dimensions of each student respectively in the present embodiment; The original measurement mark of five dimensions is converted to respectively the extroversion of the extroversion for reflecting this student, introversion, thinking, emotion and consciousness five aspects residing level in described test sample book group, the interior derived score to, thinking, emotion and consciousness five dimensions.Derived score mentioned here can be percentile rank form, or standardized score form etc., described standardized score can for the mark being converted to 0 ~ 10.
As a preferred implementation, the method original test result being converted to the derived score of percentile rank can be as follows:
The original test result of student whole in test sample book group is sorted from high to low, draws the ranking value of original test result in test sample book group of each student; Can sort respectively to the original measurement mark of student's five dimension;
Quantity according to student whole in described ranking value, test sample book group calculates derived score, is designated as PR:
PR=100-(100R-50)/N, wherein, R is the ranking value of original test result in test sample book group of each student, and N is the quantity of whole student in test sample book group.
In the present embodiment, the derived score of each student 5 dimensions can be drawn, be designated as PR1, PR2, PR3, PR4, PR5.
As another preferred implementation, the method original test result being converted to the derived score of standardized score can be as follows:
Calculate the average of the original test result of all students in test sample book group, be designated as X1; In the present embodiment, the average of the original test result of 5 dimensions can be calculated respectively, be designated as X1_1, X1_2, X1_3, X1_4, X1_5. respectively
Calculate the standard deviation of the original test result of all students in test sample book group, be designated as S; In the present embodiment, the standard deviation of the original test result of 5 dimensions can be calculated respectively, be designated as S_1, S_2, S_3, S_4, S_5. respectively
Calculating derived score Z according to described average X1, standard S is:
Z=(X-X1)/S, wherein, X is raw score.Such as, the original test result of tested student is 34 points, and in test sample book group, the average mark of the original test result of whole student is 25 points, and standard deviation is 2.3, then show that criterion score is Z=(34-25)/2.3=3.91.
In the present embodiment, derived score Z_1, Z_2, Z_3, Z_4, Z_5 of 5 dimensions can be calculated respectively according to described average X1_1, X1_2, X1_3, X1_4, X1_5, standard S_1, S_2, S_3, S_4, S_5.To reflect the level condition that the situation of above-mentioned 5 dimensions of student is residing in test sample book group.
Step S104, searches the occupation test norm set up in advance, finds out personal characteristic information corresponding to each student and professional recommendation information according to described derived score.
In the present embodiment, obtain in advance and analyze the record information of on-the-job personnel participating in step score standard testing, extracting the hobby of described on-the-job personnel, character trait, institute learn specialty and occupation type information, building and professionally tests norm; Described occupation test norm includes the professional recommendation information of personal characteristic information and correspondence.
Preferably, described occupation test norm is refined as 15 subclasses by the present embodiment, is specially: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type.Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence.Corresponding, before step S104, also need in advance derived score to be divided into multiple numerical intervals, and set up associating of each subclass and described numerical intervals.Such as, for the derived score of percentile rank, derived score (0 ~ 100) is divided into 15 numerical intervals, concrete division can be determined according to actual conditions, sets up the corresponding relation of each numerical intervals and each subclass.Described according to described derived score search set up in advance occupation test norm, find out personal characteristic information corresponding to each student and professional recommendation information, be specially: first determine the numerical intervals belonging to derived score; Search the occupation test norm set up in advance again, find out the subclass associated with described numerical intervals; Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
Such as, test sample book group comprises 4563 students, the derived score of percentile rank is changed and is divided into 15 numerical intervals to be respectively: (0,6.5), (6.5,13), (13,19.5), (19.5,26), (26,32.5), (32.5,39), (39,45.5), (45.5,52), (52,58.5), (58.5,65), (65,71.5), (71.5,78), (78,84.5), (84.5,91), (91,100).Set up these 15 numerical intervals respectively to associate with achievement type subclass with actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, sexual type of taking a risk, children 's interests type.
Wherein the original measurement mark (the original measurement mark of such as perception dimension) of certain student sorts in described 4563 students is 200, derived score PR=100-(100*200-50)/4563=95.63 that the original measurement mark of this student is corresponding can be drawn, affiliated numerical intervals is (91,100), the subclass of corresponding achievement type.The idiosyncrasy that this subclass is corresponding and specialty are recommended as: people's enthusiasm of this type, friendliness, careful, responsive, like exchanging with people, be good at the discovery of individual and know from experience clear and pass to the people of surrounding exactly, wish to maintain a harmonious interpersonal atmosphere, social responsibility is stronger, hanker after utility, other people service of providing advice of hope purpose, wish the experience of oneself and show loving care for and give those people wanted help.They are conscientiously more careful in study and work, stress accurately, usually notice the problem that everybody easily ignores, have a preference for Methodistic environment, do not like not having well-regulated activity, live more regular; They also have certain interest to artistic work, have higher esthetic sentiment, and emotion is fine and smooth, get used to, by the abundant inner experience of color, figure and literal expression oneself, not liking task routinely, wishing that oneself is unusual.They at ordinary times to social community work, various training and consulting activity, management class books and newspapers, magazine, mail, to do class meeting record etc. movable interested, this to concert, visit art exhibition, to appreciate the activities such as work of fine arts also more earnest.It can also be seen that from your test, you are very confident to oneself in the vocational activity of Arts, social class, and this is that you are engaged in the advantage of Arts, social class occupation in the future.Form (Fig. 2) below gives 506 specialties that current China university is arranged, and according to the test result before you, and we are to the research and analysis of each specialty characteristics of colleges and universities, and we are applicable to the specialty learnt for you have selected.Wherein: 1, ★ ★ ★ represents the requirement that your everyway meets this specialty very much, be we strongly to you recommend specialty, advise you selection specialty in pay the utmost attention to.2, ★ ★ represents you and compares the requirement meeting this specialty in many-side, is the specialty that our emphasis is recommended to you, advises that your consider by the emphasis when selection specialty.3, some feature that ★ represents you meets the requirement of this specialty substantially, for generally recommending specialty, is also your admissible scope when selecting specialty.4, blank expression cannot make accurate judgement to your study whether applicable of this specialty according to test result, advises that you consider carefully in conjunction with other factors.5, × feature of representing you does not meet the requirement of this specialty very much, and you are not too applicable to selecting this specialty, advise your this specialty of careful selection.
By first embodiment of the invention, by the personal data of each student in preset test exam pool collecting test sample group; The score standard of described personal data with the described test exam pool preset is compared, draws the original test result of each student; Mathematical statistics being carried out to the original test result of student whole in test sample book group, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group; Search the occupation test norm set up in advance according to described derived score, find out personal characteristic information corresponding to each student and professional recommendation information.The present invention is tester turning to, study, take an advanced study, choose a job in seek to close commenting of positioning oneself and recommend report, thus find career development location accurately, a way to success of marching toward.Especially concerning the high school graduate of the university gate that is about to enter, carry out talent assessment, carry out study plan and be very important concerning individual man-based development.More scientific, the idiosyncrasy that draws student more accurately and the specialty adapted to its idiosyncrasy can be come by the test of student interests hobby, character trait, professional potential and Career orientation all sidedly by method of the present invention, auxiliary student selects specialty, avoids the cognitive limitation of individual and thinks the interference of factor.
The auxiliary high school student provided for the embodiment of the present invention below selects the embodiment of the information recommendation system of university's specialty.Embodiment and the above-mentioned embodiment of the method for described system belong to same design, and the detail content of not detailed description in the embodiment of system can with reference to said method embodiment.
The auxiliary high school student that Fig. 3 shows second embodiment of the invention selects the structural representation of the information recommendation system of university's specialty, is described in detail below.
Refer to Fig. 3, described system comprises: data acquisition module 310, scoring module 320, statistical analysis module 330, recommending module 340, be specifically described each module below.
Described data acquisition module 310, for the personal data of each student in the test sample book group preset by the collection of preset test exam pool, described test sample book group comprises multiple student.
In second embodiment, the test sample book group determined can be southern area of Jiangsu Province high school student and university student as test sample book group, and usual test sample book group capacity required is enough large and representative.And testing exam pool can adopt the mode of multiple-choice question to arrange, by receiving the answer that student selects, collect the personal data of the information of the aspects such as the hobby of each student in test sample book group, character trait, professional potential and Career orientation, corresponding, the problem including the aspects such as hobby, character trait, professional potential and Career orientation in described test exam pool is arranged, more fully to collect the personal data of student, so that the idiosyncrasy determining student accurately and the specialty be applicable to.
Described scoring module 320, for the score standard of described personal data with the described test exam pool preset being compared, draws the original test result of each student.
In the present embodiment, can in advance by the personal information of the multiple different occupation on-the-job personnel of described test exam pool collecting test as normal data, build the score standard of described test exam pool according to described normal data.Representative industry elite can be chosen and carry out this test, to build standard of scoring more accurately.It should be noted that, also can the score standard built by which be adjusted, to make score standard more scientific more reasonable.
Preferably, in the present embodiment, the information personal data of the hobby of student, character trait, professional potential and Career orientation aspect are compared with the score standard of the described test exam pool preset respectively, show that each student is at export-oriented, the interior original measurement mark to, thinking, emotion and consciousness five dimensions respectively, by the test result of refinement student, be conducive to clearer reflection student idiosyncrasy information in every respect.
Described statistical analysis module 330, for carrying out mathematical statistics to the original test result of student whole in test sample book group, is converted to the derived score for reflecting this student residing level in described test sample book group by the original test result of each student.
Contrasted with score standard by the personal data of the student collected, can obtain a test result, this test result is original test result.But for student, this original test result is directly perceived not, is not easy to student and fully understands the idiosyncrasy of oneself and professional potential, therefore needing this original test result to be converted to student can the information of intuitivism apprehension.In the present embodiment, the object that this original test result is changed is: obtain and there is certain reference point and unit and the information that can mutually compare, the individual position residing in test sample book group of such as instruction (the such as export-oriented level of index in contemporary, the level etc. of emotional ability in contemporary), comparablely to measure to provide some, make relatively to become possibility to the individual test result of test.
Preferably, mathematical statistics can be carried out to the original measurement mark of five dimensions of each student respectively in the present embodiment; The original measurement mark of five dimensions is converted to respectively the extroversion of the extroversion for reflecting this student, introversion, thinking, emotion and consciousness five aspects residing level in described test sample book group, the interior derived score to, thinking, emotion and consciousness five dimensions.Derived score mentioned here can be percentile rank form, or standardized score form etc., described standardized score can for the mark being converted to 0 ~ 10.Wherein, the method for the derived score of percentile rank can be as follows: sort from high to low to the original test result of student whole in test sample book group, draw the ranking value of original test result in test sample book group of each student; Quantity according to student whole in described ranking value, test sample book group calculates derived score, be designated as PR:PR=100-(100R-50)/N, wherein, R is the ranking value of original test result in test sample book group of each student, and N is the quantity of whole student in test sample book group.The method of the derived score of standardized score can be as follows: the average calculating the original test result of all students in test sample book group, is designated as X1; Calculate the standard deviation of the original test result of all students in test sample book group, be designated as S; Calculating derived score Z according to described average X1, standard S is: Z=(X-X1)/S, wherein, X is raw score.
Described recommending module 340, for searching the occupation test norm set up in advance according to described derived score, finds out personal characteristic information corresponding to each student and professional recommendation information.
Further, described auxiliary high school student selects the information recommendation system of university's specialty also to comprise study module 350, for the personal information by the multiple different occupation on-the-job personnel of preset test exam pool collecting test as normal data, build the score standard of described test exam pool according to described normal data; And for analyzing the record information of described on-the-job personnel, extract the hobby of described on-the-job personnel, character trait, learn specialty and occupation type information architecture occupation test norm; Described occupation test norm comprises the professional recommendation information of personal characteristic information and correspondence
Preferably, the system of the present embodiment also comprises and arranges module 360, for described occupation test norm is divided into 15 subclasses: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type; Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence, and derived score is divided into multiple numerical intervals, set up associating of each subclass and described numerical intervals, and in advance derived score is divided into multiple numerical intervals, and set up associating of each subclass and described numerical intervals.Such as, for the derived score of percentile rank, derived score (0 ~ 100) is divided into 15 numerical intervals, concrete division can be determined according to actual conditions, sets up the corresponding relation of each numerical intervals and each subclass.Corresponding described recommending module 340, can specifically for first determining the numerical intervals belonging to derived score; Search the occupation test norm set up in advance again, find out the subclass associated with described numerical intervals; Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
By the system described in second embodiment of the invention, for the puzzlement that existing high school student selects university's specialty to exist, the interest of student, hobby, ability and personality characteristics etc. are carried out to the analytic statistics of science, auxiliary student understanding clearly oneself, feature according to oneself selects major and career scientifically and rationally, increase the accuracy of choosing to specialty, avoid selecting wrong specialty.Following effect can be reached by this system:
1, auxiliary student understands the relative merits of oneself personality, knows self strengths and weaknesses ability;
2, auxiliary student fully understands the strengths and weaknesses of oneself attending school certain specialty;
3, auxiliary student is clearly familiar with oneself certain specialty whether applicable;
4, auxiliary student is according to the strengths and weaknesses of oneself ability quality, determines the career development direction of oneself;
5, auxiliary student improves the weak point of oneself ability quality targetedly, and make strength stronger, weak place is not weak
Above disclosedly be only present pre-ferred embodiments, certainly the right of the present invention can not be limited with this, therefore, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., still belong to the scope that the present invention is contained.

Claims (10)

1. auxiliary high school student selects an information recommendation method for university's specialty, it is characterized in that, comprising:
The personal data of each student in the test sample book group preset by the collection of preset test exam pool, described test sample book group comprises multiple student;
The score standard of described personal data with the described test exam pool preset is compared, draws the original test result of each student;
Mathematical statistics being carried out to the original test result of student whole in test sample book group, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group;
Search the occupation test norm set up in advance according to described derived score, find out personal characteristic information corresponding to each student and professional recommendation information.
2. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 1, it is characterized in that, described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
By the personal information of the multiple different occupation on-the-job personnel of preset test exam pool collecting test as normal data, build the score standard of described test exam pool according to described normal data;
Analyze the record information of described on-the-job personnel, extract the hobby of described on-the-job personnel, character trait, learn specialty and occupation type information architecture occupation test norm; Described occupation test norm comprises the professional recommendation information of personal characteristic information and correspondence.
3. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 1, it is characterized in that, described occupation test norm comprises subclass: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type; Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence;
Described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
Derived score is divided into multiple numerical intervals, sets up associating of each subclass and described numerical intervals;
Described according to described derived score search set up in advance occupation test norm, find out personal characteristic information corresponding to each student and professional recommendation information, be specially:
Determine the numerical intervals belonging to described derived score;
Search the occupation test norm set up in advance, find out the subclass associated with described numerical intervals;
Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
4. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 1, and it is characterized in that, described derived score is percentile rank;
The described original test result to student whole in test sample book group carries out mathematical statistics, the original test of each student is divided the derived score being converted to and can reflecting this student residing level in described test sample book group, comprising:
The original test result of student whole in test sample book group is sorted from high to low, draws the ranking value of original test result in test sample book group of each student;
Calculating derived score PR according to the quantity of student whole in described ranking value, test sample book group is:
PR=100-(100R-50)/N,
Wherein, R is the ranking value of original test result in test sample book group of each student, and N is the quantity of whole student in test sample book group.
5. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 1, and it is characterized in that, described derived score is standardized score;
The described original test result to student whole in test sample book group carries out mathematical statistics, the original test of each student is divided the derived score being converted to and can reflecting this student residing level in described test sample book group, comprising:
Calculate the average of the original test result of all students in test sample book group, be designated as X1;
Calculate the standard deviation of the original test result of all students in test sample book group, be designated as S;
Calculate derived score Z according to described average, standard deviation be:
Z=X-X1/S,
Wherein, X is raw score.
6. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 1, and it is characterized in that, described personal data comprise: the information of hobby, character trait, professional potential and Career orientation aspect; Wherein, described Career orientation comprises extroversion, introversion, thinking, emotion and consciousness five dimensions;
The described score standard by described personal data and default described test exam pool is compared, and draws the original test result of each student, comprising:
The information of described hobby, character trait, professional potential and Career orientation aspect is compared with the score standard of described test exam pool preset respectively, draws the original measurement mark of the extroversion of each student, introversion, thinking, emotion and consciousness five dimensions respectively.
7. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 6, it is characterized in that, the described original test result to student whole in test sample book group carries out mathematical statistics, the original test result of each student being converted to the derived score for reflecting this student residing level in described test sample book group, comprising:
Respectively mathematical statistics is carried out to the original measurement mark of five dimensions described in each student;
The original measurement mark of described five dimensions of each student is converted to respectively the extroversion of the extroversion for reflecting this student, introversion, thinking, emotion and consciousness five aspects residing level in described test sample book group, the interior derived score to, thinking, emotion and consciousness five dimensions.
8. auxiliary high school student selects the information recommendation method of university's specialty as claimed in claim 7, it is characterized in that, described according to described derived score search set up in advance occupation test norm, before finding out personal characteristic information corresponding to each student and professional recommendation information, also comprise:
The derived score of described five dimensions is divided into multiple numerical intervals respectively, and that sets up that each subclass combines with the numerical intervals of five dimensions associates;
Described according to described derived score search set up in advance occupation test norm, find out personal characteristic information corresponding to each student and professional recommendation information, comprising:
Determine the numerical intervals that the derived score of described five dimensions of each student is affiliated separately respectively;
Determine the numerical intervals combination that described numerical intervals is corresponding;
Search the occupation test norm set up in advance, find out and combine with described numerical intervals the subclass associated;
Obtain the professional recommendation information of personal characteristic information corresponding to this subclass and correspondence.
9. auxiliary high school student selects an information recommendation system for university's specialty, it is characterized in that, comprising:
Data acquisition module, for the personal data of each student in the test sample book group preset by the collection of preset test exam pool, described test sample book group comprises multiple student;
Scoring module, for the score standard of described personal data with the described test exam pool preset being compared, draws the original test result of each student;
Statistical analysis module, for carrying out mathematical statistics to the original test result of student whole in test sample book group, is converted to the derived score for reflecting this student residing level in described test sample book group by the original test result of each student;
Recommending module, for searching the occupation test norm set up in advance according to described derived score, finds out personal characteristic information corresponding to each student and professional recommendation information.
10. auxiliary high school student selects the information recommendation system of university's specialty as claimed in claim 9, it is characterized in that, also comprises:
Study module, for the personal information by the multiple different occupation on-the-job personnel of preset test exam pool collecting test as normal data, builds the score standard of described test exam pool according to described normal data; And for analyzing the record information of described on-the-job personnel, extract the hobby of described on-the-job personnel, character trait, learn specialty and occupation type information architecture occupation test norm; Described occupation test norm comprises the professional recommendation information of personal characteristic information and correspondence;
Module is set, for described occupation test norm is divided into multiple subclass: actual type, survey type, artistic type, social pattern, cause type, conventional type, interpersonal relation management type, responsive type, language ability type, flexible type, curious sexual type, risk sexual type, children 's interests type and achievement type; Each subclass all comprises the professional recommendation information of personal characteristic information and correspondence, and derived score is divided into multiple numerical intervals, sets up associating of each subclass and described numerical intervals.
CN201510003645.5A 2015-01-06 2015-01-06 A kind of auxiliary high school student selects the information recommendation method and system of university's profession Active CN104572989B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510003645.5A CN104572989B (en) 2015-01-06 2015-01-06 A kind of auxiliary high school student selects the information recommendation method and system of university's profession

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510003645.5A CN104572989B (en) 2015-01-06 2015-01-06 A kind of auxiliary high school student selects the information recommendation method and system of university's profession

Publications (2)

Publication Number Publication Date
CN104572989A true CN104572989A (en) 2015-04-29
CN104572989B CN104572989B (en) 2018-09-28

Family

ID=53089051

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510003645.5A Active CN104572989B (en) 2015-01-06 2015-01-06 A kind of auxiliary high school student selects the information recommendation method and system of university's profession

Country Status (1)

Country Link
CN (1) CN104572989B (en)

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105139317A (en) * 2015-08-07 2015-12-09 北京环度智慧智能技术研究所有限公司 Cognitive Index analyzing method for interest orientation value test
CN106168952A (en) * 2015-05-18 2016-11-30 睿智顾问公司 Learn system and select system and method
CN106875028A (en) * 2016-06-17 2017-06-20 江婕 A kind of method for aiding in selecting a school and system
CN107193958A (en) * 2017-05-24 2017-09-22 上海赢帆信息技术有限公司 One kind is used to orientation of student and colleges and universities is presented(Special interest group)With the graphic technique of professional match condition
CN107665612A (en) * 2017-10-16 2018-02-06 江苏金惠甫山软件科技有限公司 A kind of career planning experiencing system
CN108052608A (en) * 2017-12-13 2018-05-18 成都优联苔客数字科技有限公司 A kind of method and device according to senior secondary course intelligent recommendation university specialty
CN108108910A (en) * 2018-01-08 2018-06-01 魏是瞻 A kind of information recommendation method and system that high school student is aided in select university's specialty
CN108320253A (en) * 2018-03-23 2018-07-24 封玲 Subject and specialized education's evaluation system
CN108647294A (en) * 2018-05-07 2018-10-12 韦玮 Information recommendation system
CN108846105A (en) * 2018-06-21 2018-11-20 黄彦辉 Based on Euclidean distance character feature vector profession matching process, computer program
CN109389308A (en) * 2018-10-10 2019-02-26 赵益 A kind of career orientation test system
CN109544414A (en) * 2018-10-23 2019-03-29 平安医疗健康管理股份有限公司 Data processing method, device, server and computer readable storage medium
CN110706139A (en) * 2019-09-27 2020-01-17 广东学苑教育发展有限公司 Method, processor and system beneficial to reporting major of colleges and universities
CN111191914A (en) * 2019-12-27 2020-05-22 广东德诚科教有限公司 Professional recommendation method and device, computer equipment and computer readable storage medium
CN111553646A (en) * 2019-12-16 2020-08-18 曹世保 Method for selecting subjects, specialties and professions by using student characters
CN112070376A (en) * 2020-08-27 2020-12-11 北京国育未来文化发展有限公司 College entrance examination volunteer recommendation method, device, terminal and computer readable storage medium
CN112651862A (en) * 2020-12-24 2021-04-13 成都存时科技有限公司 Student academic development direction planning method, device, equipment and readable storage medium
CN112766647A (en) * 2020-12-30 2021-05-07 广东德诚科教有限公司 Method and device for assessing lifetime planning of junior high school students
CN112883260A (en) * 2021-01-26 2021-06-01 浙江萃文科技有限公司 Occupation tendency matching method based on CAPE characteristics
CN113516372A (en) * 2021-06-18 2021-10-19 广州启德教育科技有限公司 Information matching method and device for assisting study leaving and school selection
CN116500179A (en) * 2023-04-21 2023-07-28 南京品生医疗科技有限公司 Risk prediction system for acute coronary syndrome

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101320447A (en) * 2008-06-27 2008-12-10 广州市盈海文化传播有限公司 Method for recommending dormant matching mate based on psychological traits
US20100010914A1 (en) * 2006-12-15 2010-01-14 Nam-Kyo Park Apparatus and method for recommending lecture tailored to person, and connection terminal thereof
CN101923667A (en) * 2009-06-16 2010-12-22 一零四资讯科技股份有限公司 Method for comprehensively testing recommending position
CN103294816A (en) * 2013-06-09 2013-09-11 广东倍智人才管理咨询有限公司 Method and system for recommending positions for job seeker
CN103714413A (en) * 2013-11-21 2014-04-09 清华大学 Position information-based competence model construction system and method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100010914A1 (en) * 2006-12-15 2010-01-14 Nam-Kyo Park Apparatus and method for recommending lecture tailored to person, and connection terminal thereof
CN101320447A (en) * 2008-06-27 2008-12-10 广州市盈海文化传播有限公司 Method for recommending dormant matching mate based on psychological traits
CN101923667A (en) * 2009-06-16 2010-12-22 一零四资讯科技股份有限公司 Method for comprehensively testing recommending position
CN103294816A (en) * 2013-06-09 2013-09-11 广东倍智人才管理咨询有限公司 Method and system for recommending positions for job seeker
CN103714413A (en) * 2013-11-21 2014-04-09 清华大学 Position information-based competence model construction system and method

Cited By (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106168952A (en) * 2015-05-18 2016-11-30 睿智顾问公司 Learn system and select system and method
CN105139317A (en) * 2015-08-07 2015-12-09 北京环度智慧智能技术研究所有限公司 Cognitive Index analyzing method for interest orientation value test
CN105139317B (en) * 2015-08-07 2018-10-09 北京环度智慧智能技术研究所有限公司 The cognition index analysis method of interest orientation value test
CN106875028A (en) * 2016-06-17 2017-06-20 江婕 A kind of method for aiding in selecting a school and system
CN106875028B (en) * 2016-06-17 2021-02-02 江婕 Information screening method and system for assisting school selection
CN107193958B (en) * 2017-05-24 2020-12-18 上海赢帆信息技术有限公司 Graphic method for presenting student positioning and college (professional group) and professional matching condition
CN107193958A (en) * 2017-05-24 2017-09-22 上海赢帆信息技术有限公司 One kind is used to orientation of student and colleges and universities is presented(Special interest group)With the graphic technique of professional match condition
CN107665612A (en) * 2017-10-16 2018-02-06 江苏金惠甫山软件科技有限公司 A kind of career planning experiencing system
CN108052608A (en) * 2017-12-13 2018-05-18 成都优联苔客数字科技有限公司 A kind of method and device according to senior secondary course intelligent recommendation university specialty
CN108052608B (en) * 2017-12-13 2022-01-04 成都优联苔客数字科技有限公司 Method and device for intelligently recommending university major according to high school course
CN108108910A (en) * 2018-01-08 2018-06-01 魏是瞻 A kind of information recommendation method and system that high school student is aided in select university's specialty
CN108320253A (en) * 2018-03-23 2018-07-24 封玲 Subject and specialized education's evaluation system
CN108647294A (en) * 2018-05-07 2018-10-12 韦玮 Information recommendation system
CN108846105A (en) * 2018-06-21 2018-11-20 黄彦辉 Based on Euclidean distance character feature vector profession matching process, computer program
CN109389308A (en) * 2018-10-10 2019-02-26 赵益 A kind of career orientation test system
CN109544414A (en) * 2018-10-23 2019-03-29 平安医疗健康管理股份有限公司 Data processing method, device, server and computer readable storage medium
CN110706139A (en) * 2019-09-27 2020-01-17 广东学苑教育发展有限公司 Method, processor and system beneficial to reporting major of colleges and universities
CN111553646A (en) * 2019-12-16 2020-08-18 曹世保 Method for selecting subjects, specialties and professions by using student characters
CN111191914A (en) * 2019-12-27 2020-05-22 广东德诚科教有限公司 Professional recommendation method and device, computer equipment and computer readable storage medium
CN112070376A (en) * 2020-08-27 2020-12-11 北京国育未来文化发展有限公司 College entrance examination volunteer recommendation method, device, terminal and computer readable storage medium
CN112651862A (en) * 2020-12-24 2021-04-13 成都存时科技有限公司 Student academic development direction planning method, device, equipment and readable storage medium
CN112766647A (en) * 2020-12-30 2021-05-07 广东德诚科教有限公司 Method and device for assessing lifetime planning of junior high school students
CN112883260A (en) * 2021-01-26 2021-06-01 浙江萃文科技有限公司 Occupation tendency matching method based on CAPE characteristics
CN113516372A (en) * 2021-06-18 2021-10-19 广州启德教育科技有限公司 Information matching method and device for assisting study leaving and school selection
CN116500179A (en) * 2023-04-21 2023-07-28 南京品生医疗科技有限公司 Risk prediction system for acute coronary syndrome
CN116500179B (en) * 2023-04-21 2023-12-26 南京品生医疗科技有限公司 Method and system for calculating and converting original scores of ceramide related factors in blood plasma

Also Published As

Publication number Publication date
CN104572989B (en) 2018-09-28

Similar Documents

Publication Publication Date Title
CN104572989A (en) Information recommendation method and system for assisting senior high school students to choose college majors
Amador et al. Prospective teachers’ noticing: A literature review of methodological approaches to support and analyze noticing
Mao et al. Validation of automated scoring for a formative assessment that employs scientific argumentation
Tlakula et al. The use of electronic resources by undergraduate students at the University of Venda, South Africa
Sanday Anthropology and the public interest: Fieldwork and theory
van de Grift Measuring teaching quality in several European countries
Sheu et al. Testing the choice model of social cognitive career theory across Holland themes: A meta-analytic path analysis
CN105096224B (en) Aspiration recommends method and system
Bruns et al. Mathematics-related competence of early childhood teachers visiting a continuous professional development course: an intervention study.
CN106355530A (en) Automated method for college application analysis and decision after the National Higher Education Entrance Examination
Aksu et al. Development of the pedagogical content knowledge scale for pre-service teachers: The validity and reliability study
CN106997571A (en) A kind of subject study development commending system and method based on data-driven
CN113744101A (en) Intelligent examinee volunteer filling method and device in new high-level examination mode and computer equipment
Hossain Mixed method research: An overview
Phillipson et al. Discovering patterns of achievement in Hong Kong students: An application of the Rasch measurement model
Happ Mixed methods in gerontological research: Do the qualitative and quantitative data “touch”?
Gao et al. A comparison between US and Chinese principal decision-making power: A measurement perspective based on PISA 2015
Hesketh Careers advice and tertiary decision-making “downunder” in Australia
CN113888373A (en) Intelligent AI course selection system for personal occupation planning
Mourgues et al. The role of noncognitive factors in predicting academic trajectories of high school students in a selective private school
CN112685470A (en) Lifelong learning resource intelligent pushing method based on credit bank and big data analysis
Kashan et al. A impact of student leadership on students’ academic achievement in public and private Universities of Pakistan
Miskel Teacher and administrator attitudes toward collective negotiation issues
Lei et al. A study on the influence of psychological capital on job burnout of civil servants in the basic-level industrial and commercial departments
TW201814640A (en) System and implementing method thereof for recommending courses according to career development

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20181022

Address after: Room 1606, Research Building of Yimin Residential Committee and Direction Residential Committee, Yandu District Yanlong Street Office, Yancheng City, Jiangsu Province

Patentee after: Jiangsu Jin Huifu mountain Software Technology Co., Ltd.

Address before: 215200 Wujiang science and Technology Development Park, Wujiang economic and Technological Development Zone, Suzhou, Jiangsu

Patentee before: SUZHOU ZHIZHEN ASSESSMENT TECHNOLOGY SOFTWARE TECHNOLOGY CO., LTD.