CN108597285A - A kind of intelligence classification lead learning method, system and device - Google Patents
A kind of intelligence classification lead learning method, system and device Download PDFInfo
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Abstract
The invention discloses a kind of intelligence classification lead learning method, system and device, method includes：Obtain practice data and the teacher's preset practice period of student；According to the rank of the preset practice period Auto-matching student of the practice data of student and teacher；The indication of appropriate level is provided according to the rank of student for student, and student is made to carry out corresponding practice teaching practice according to the indication of appropriate level.The present invention can play the role of substituting teacher, by simulating true teaching operations scene, collect the daily study of student and the data generated in the process that fulfil assignment, in conjunction with the analysis of big data technology, precisely know that situation is grasped in the knowledge point of student, for student's Auto-matching grade and the indication of different stage is provided, without being that student carries out classification by hand and can achieve the purpose that individualized teaching, efficient and intelligence degree are high according to the real training situation of student.It the composite can be widely applied to intelligent tutoring field.
Description
Technical field
The present invention relates to intelligent tutoring field, especially a kind of intelligence classification lead learning method, system and device.
Background technology
In daily teaching simulation training, the resources materials such as explanation and books due to teacher are all the religions to theorize
Pattern is educated, student is not deep to the digestion and cognition of knowledge.With the development of information technology, IT application in education sector is gradual
Trend is universal.Various teaching softwares have played important booster action in the various aspects of education sector.
Existing teaching software generally uses primary, middle rank and advanced three-level practicing model：Primary is students'autonomous study
Level, middle rank is the level of self detection of student, and advanced is the level of student examination, practice-training teaching be one by it is shallow enter
Deep, incremental process.Teacher can control real training level accordingly in teaching software, and different stage pair is arranged
Different levels should be opened, the function of different level can also be configured (as being arranged not for different stage in operation layer
Same suggestion content).The purpose of the above three-level teaching is exactly to allow student oneself to practice by training operation class, and teacher is further according to
The case where raw practice, carries out the upper machine explanation of priority and difficulty.The workload that teacher has training operation class can be mitigated significantly in this way,
School's training operation class class hour insufficient contradiction can effectively be solved.
Elementary, middle and high three layers of various functions teacher can freely control in existing teaching software, and can be according to the religion of teacher
It learns wish and different indication information (being classified indication) is provided to student, to give the different degrees of real training of practitioner
Operation guide allows student that can faster digest the content of courses.By taking the financial teaching software with classification lead learning function as an example,
Its primary level has pressure guidance, helps answer, laws and regulations, exits display answer and to wrong number function；Intermediate level has by force
System guidance is exited and flashes, exits answer help and laws and regulations function；Advanced level, which exits, flashes and method law
Advise function.
However, above-mentioned classification lead learning scheme, teacher needs according to the real training situation of student to be that student carries out by hand
Classification, efficiency is low, and intelligence degree is low.
Invention content
In order to solve the above technical problems, it is an object of the invention to：A kind of efficient and high intelligence of intelligence degree is provided
Lead learning method, system and device can be classified.
The first technical solution for being taken of the present invention is：
A kind of intelligence classification lead learning method, includes the following steps：
Obtain practice data and the teacher's preset practice period of student；
According to the rank of the preset practice period Auto-matching student of the practice data of student and teacher；
The indication of appropriate level is provided according to the rank of student for student, and makes guiding of the student according to appropriate level
Prompt carries out corresponding practice teaching practice.
Further, practice data for obtaining student and the step for teacher's preset practice period, specifically include：
User is carried out to log in and log-on message verification；
Role judgement is carried out to the successful user of login authentication；
Enter student subsystem or teacher's subsystem according to the result of Role judgement；
Practice data and the teacher's preset practice period of student are obtained by student subsystem or teacher's subsystem.
Further, the practice data and the preset white silk of teacher that student is obtained by student subsystem or teacher's subsystem
The step for practising the period, specifically includes：
Intelligence classification guiding management and control is carried out by teacher's subsystem, the intelligence classification guiding management and control includes creating intelligence point
Grade guiding rank and the real training prompt project for configuring appropriate level carry out AI mode settings and corresponding rank evaluation mark are arranged
Standard, create real training case simultaneously import real training case data to database, and for student granting real training voucher and according to real training with
The training operation record data of card are analyzed；
The practice data of student are obtained by student subsystem, and all from the preset practice of teacher's subsystem load teacher
Phase.
Further, it is described according to the practice data of student and teacher it is preset practice period Auto-matching student rank this
One step, specially：
Judge whether AI patterns have turned on, if so, using intelligence classification lead learning pattern come automatic assessment of students'
Rank, conversely, then judging the rank of student manually by teacher using classification lead learning pattern.
Further, described the step for rank of the lead learning pattern come automatic assessment of students' is classified using intelligence, specifically
Including：
Judge T according to the current exercise data of student1-T2Whether >=L is true, if so, next step is executed, conversely, then
Read current evaluation rank of the current level of student as student, wherein T1For current time, T2It was evaluated for student's last time
Time, L are teacher's preset practice period；
Data are recorded according to the training operation of student's real training voucher and calculate student's practice index, and then are referred to according to student's practice
Number carrys out the rank of automatic assessment of students'.
Further, described that data calculating student's practice index, Jin Ergen are recorded according to the training operation of student's real training voucher
The step for practicing the rank of the automatic assessment of students' of index according to student, specifically includes：
Data are recorded according to the training operation of student's real training voucher and calculate student's practice index, and the student practices index K
Calculation formula be：K=(P1*S1+P2*S2+…+Pn*Sn)/n, wherein the formula of P is：Pi=Ii/Ji, IiFor student's real training with
In card quantity, J are answered questions in ith training operation recordiIt is answered for the need in ith training operation record in student's real training voucher
Total quantity, SiFor the total score in ith training operation record in student's real training voucher, n is student's real training summary journal number, i
=1,2 ... n；
Student is practiced into index and the accuracy range values of teacher's subsystem AI mode settings compare, obtains student
Practice current evaluation rank of the corresponding rank of the affiliated accuracy range values of index as student.
Further, the step for the rank of the lead learning pattern to judge student manually by teacher using classification, tool
Body includes：
Teacher's subsystem records the practice data of data acquisition student according to the training operation of real training voucher；
Teacher returns to the cadetcy of manual allocation according to the rank of the practice data manual allocation student of student
Student subsystem.
Further, the rank according to student provides the indication of appropriate level for student, and makes student according to phase
The step for answering the indication of rank to carry out corresponding practice teaching practice, specifically includes：
The indication of appropriate level is provided according to the rank of student for student；
Student subsystem judges whether student needs to read old real training data, if so, reading the student from database
Next step is executed after data existing for current real training, conversely, then directly executing next step；
Student carries out training operation according to the indication of appropriate level；
Submit the training operation record of student；
Data analysis is carried out to the training operation record that student submits according to preset statistical rules；
Real training monitoring data report is generated according to the result of data analysis.
The second technical solution for being taken of the present invention is：
A kind of intelligence classification lead learning system, including：
Data acquisition module, practice data and the teacher preset practice period for obtaining student；
Auto-matching module, for according to the preset practice period Auto-matching student's of the practice data of student and teacher
Rank；
Real training exercise module, the indication for providing appropriate level for student according to the rank of student, and make student
Corresponding practice teaching practice is carried out according to the indication of appropriate level.
The third technical solution taken of the present invention is：
A kind of intelligence classification lead learning device, including：
Memory, for storing program；
Processor, for loading described program to execute a kind of intelligence classification lead learning as described in the first technical solution
Method.
The beneficial effects of the invention are as follows：A kind of intelligence classification lead learning method, system and device of the present invention, according to student
Practice data and the preset practice period Auto-matching student of teacher rank, and then student is made according to the rank of Auto-matching
Corresponding practice teaching practice is carried out according to the indication of appropriate level, can play the role of substituting teacher, it is true by simulating
Real teaching operations scene collects the daily study of student and the data generated in the process that fulfil assignment, in conjunction with big data technology
Analysis precisely knows that situation is grasped in the knowledge point of student, is student's Auto-matching grade and provides the indication of different stage,
It is efficient and intelligent without being that classification can achieve the purpose that individualized teaching to student's progress by hand according to the real training situation of student
Change degree is high.
Description of the drawings
Fig. 1 is a kind of overall flow figure of intelligence classification lead learning method of the present invention；
Fig. 2 is intelligence classification lead learning system structure of the embodiment of the present invention one based on B/S three-layer network service architectures
Block diagram；
Fig. 3 is the schematic diagram that one real training of the embodiment of the present invention practices service logic；
Fig. 4 is the schematic diagram that service logic is arranged in one real training of the embodiment of the present invention；
Fig. 5 is the particular flow sheet of one intelligence classification lead learning method of the embodiment of the present invention.
Specific implementation mode
Referring to Fig.1, a kind of intelligence classification lead learning method of the present invention, includes the following steps：
Obtain practice data and the teacher's preset practice period of student；
According to the rank of the preset practice period Auto-matching student of the practice data of student and teacher；
The indication of appropriate level is provided according to the rank of student for student, and makes guiding of the student according to appropriate level
Prompt carries out corresponding practice teaching practice.
Be further used as preferred embodiment, the practice data for obtaining student and teacher's preset practice period this
One step, specifically includes：
User is carried out to log in and log-on message verification；
Role judgement is carried out to the successful user of login authentication；
Enter student subsystem or teacher's subsystem according to the result of Role judgement；
Practice data and the teacher's preset practice period of student are obtained by student subsystem or teacher's subsystem.
It is further used as preferred embodiment, the practice that student is obtained by student subsystem or teacher's subsystem
It the step for data and teacher's preset practice period, specifically includes：
Intelligence classification guiding management and control is carried out by teacher's subsystem, the intelligence classification guiding management and control includes creating intelligence point
Grade guiding rank and the real training prompt project for configuring appropriate level carry out AI mode settings and corresponding rank evaluation mark are arranged
Standard, create real training case simultaneously import real training case data to database, and for student granting real training voucher and according to real training with
The training operation record data of card are analyzed；
The practice data of student are obtained by student subsystem, and all from the preset practice of teacher's subsystem load teacher
Phase.
Wherein, real training prompt project includes but not limited to Reading-guidance Function, answer prompt, real training help, model answer, score
Statistics, error prompting and service description.
AI mode settings including but not limited to practice period, the accuracy range values of high 3 ranks in junior middle school are (such as primary
0%-60%, middle rank 60%-80%, advanced 80%-100%) etc. settings, enable the system to by the setting according to student practice feelings
Condition for Intelligence of Students allocation level, to mitigate the work load that previous teacher needs manual assignment grade, carry by data analysis
High score stage efficiency.
Be further used as preferred embodiment, it is described according to the practice data of student and the teacher preset practice period from
The step for rank of dynamic matching student, specially：
Judge whether AI patterns have turned on, if so, using intelligence classification lead learning pattern come automatic assessment of students'
Rank, conversely, then judging the rank of student manually by teacher using classification lead learning pattern.
The present invention can be according to the actual needs of teacher flexibly from intelligence classification lead learning pattern and classification lead learning mould
A kind of mode is selected in formula to be classified, it is more convenient and flexible, and compatibility is more preferable.
It is further used as preferred embodiment, it is described that lead learning pattern is classified come automatic assessment of students' using intelligence
The step for rank, specifically includes：
Judge T according to the current exercise data of student1-T2Whether >=L is true, if so, next step is executed, conversely, then
Read current evaluation rank of the current level of student as student, wherein T1For current time, T2It was evaluated for student's last time
Time, L are teacher's preset practice period；
Data are recorded according to the training operation of student's real training voucher and calculate student's practice index, and then are referred to according to student's practice
Number carrys out rank of the automatic assessment of students' as preferred embodiment.
It is further used as preferred embodiment, it is described that data numerology is recorded according to the training operation of student's real training voucher
Raw practice index, and then the step for index is come the rank of assessment of students' automatically is practiced according to student, it specifically includes：
Data are recorded according to the training operation of student's real training voucher and calculate student's practice index, and the student practices index K
Calculation formula be：K=(P1*S1+P2*S2+…+Pn*Sn)/n, wherein the formula of P is：Pi=Ii/Ji, IiFor student's real training with
In card quantity, J are answered questions in ith training operation recordiIt is answered for the need in ith training operation record in student's real training voucher
Total quantity, SiFor the total score in ith training operation record in student's real training voucher, n is student's real training summary journal number, i
=1,2 ... n；
Student is practiced into index and the accuracy range values of teacher's subsystem AI mode settings compare, obtains student
Practice current evaluation rank of the corresponding rank of the affiliated accuracy range values of index as student.
It is further used as preferred embodiment, it is described that student is judged using classification lead learning pattern manually by teacher
Rank the step for, specifically include：
Teacher's subsystem records the practice data of data acquisition student according to the training operation of real training voucher；
Teacher returns to the cadetcy of manual allocation according to the rank of the practice data manual allocation student of student
Student subsystem.
It is further used as preferred embodiment, the guiding that the rank according to student provides appropriate level for student carries
Show, and student is made to carry out the step for corresponding practice teaching is practiced according to the indication of appropriate level, specifically includes：
The indication of appropriate level is provided according to the rank of student for student；
Student subsystem judges whether student needs to read old real training data, if so, reading the student from database
Next step is executed after data existing for current real training, conversely, then directly executing next step；
Student carries out training operation according to the indication of appropriate level；
Submit the training operation record of student；
Data analysis is carried out to the training operation record that student submits according to preset statistical rules；
Real training monitoring data report is generated according to the result of data analysis.
It is corresponding with the method for Fig. 1, a kind of intelligence classification lead learning system of the present invention, including：
Data acquisition module, practice data and the teacher preset practice period for obtaining student；
Auto-matching module, for according to the preset practice period Auto-matching student's of the practice data of student and teacher
Rank；
Real training exercise module, the indication for providing appropriate level for student according to the rank of student, and make student
Corresponding practice teaching practice is carried out according to the indication of appropriate level.
It is corresponding with the method for Fig. 1, a kind of intelligence classification lead learning device of the present invention, including：
Memory, for storing program；
Processor, for loading described program to execute a kind of intelligence classification lead learning method as described in the present invention.
The present invention is further explained and is illustrated with specific embodiment with reference to the accompanying drawings of the specification.
Embodiment one
It needs according to the real training situation of student to be the problem of student carries out classification by hand for existing teaching software teacher, this
Invention proposes a kind of new intelligently guiding Hierarchical Teaching system.The system can play the role of substituting teacher, true by simulating
Real teaching operations scene collects the daily study of student and the data generated in the process that fulfil assignment, in conjunction with big data technology
Analysis precisely knows that situation is grasped in the knowledge point of student, is student's Auto-matching grade and provides the indication of different stage.
The system practices data results using incremental and Auto-matching rank mode, for different of ability according to student
Raw indication and grading function using personalized multigroup conjunction, the existing indication for reducing learning difficulty, is also improved
The indication for practising difficulty, has achieved the purpose that student resource intelligence learning.Teacher can also be by teacher's subsystem on backstage
Administration interface checks the knowledge point of the main practical operation error of student, to can targetedly emphasis be said in teaching process
Solution, to promote quality of instruction.
A kind of intelligence classification guiding training teaching system of the present invention, is the intelligence of a set of B/S structures Internet-based
It is classified lead learning system, supports that multi-user is online simultaneously, supports the function to the preservation of user's operation data, intellectual analysis, it is whole
Set system includes student subsystem and teacher's subsystem.As shown in Fig. 2, the B/S structures use 3 layers based on JAVA databases
Structure, including Business Logic, Data Persistence Layer and database.Business Logic, for providing student subsystem and teacher's
The service logic of system.Data Persistence Layer, for will intelligence classification guiding training teaching system data (training operation data,
The data of analysis, hierarchical data, the AI mode setting data etc. of customized classification guiding) it stores into database.
Wherein, the service logic of student subsystem includes but not limited to operation practice, Course Exercise, examination practice, real training
Monitoring, real training report etc. are mainly used for providing real training practice interface to student, and collect training operation data；
The service logic of teacher's subsystem includes but not limited to the management of real training case, real training setting, real training monitoring, real training report
Accuse etc., it is mainly used for managing real training case, setting real training parameter, analysis student's practice data etc..
The intelligence classification guiding system main business logic include：
(1) real training practices service logic
Real training practice service logic is a set of operation model based on intelligence classification guiding, and operator enters intelligence for the first time
It can select the rank (such as high, medium and low) of practice, different ranks that can provide the instruction preset when classification guiding system practice
Practice prompt message.As shown in figure 3, the rank of student is classified bootstrap technique evaluation by intelligence show that main process is：
Within the practice periods of teacher's AI mode settings, data are recorded according to the training operation of real training voucher and calculate student practice index K,
Then practice index K and the accuracy range values of teacher's AI mode settings are compared, obtains the affiliated accuracy range numbers of K
It is worth corresponding rank, the rank obtained is currently finally evaluated into rank as student.The student practices the calculation formula of index K
For：K=(P1*S1+P2*S2+…+Pn*Sn)/n, wherein P is the accuracy of real training voucher, and the formula of P is：Pi=Ii/Ji, PiDeng
In student's real training voucher quantity I is answered questions in ith training operation recordiDivided by total quantity J need to be answered accordinglyi, SiFor student
Total score in real training voucher in ith training operation record, n are student's real training summary journal number, i=1,2 ... n.
And triggering the precondition that intelligence classification bootstrap technique (pattern) evaluation rank needs is：It must satisfy teacher's setting
Practice cycle T1-T2>=L, wherein T1For current time, T2For the time that student's last time evaluates, L is teacher's preset practice week
Phase.
(2) service logic is arranged in real training
Real training setting service logic includes but not limited to operation layer setting service logic, AI mode setting service logics.
1) service logic is arranged in operation layer
Teacher operation layer be arranged in service logic can self-defined classification guiding rank (it is first that system default classification, which guides,
Middle high 3 ranks, teacher can customize 1-m classification guiding rank), preset each rank included real training prompt project
(can multiselect, such as guiding function, enforcement functionalities, answer prompt, fractional statistics, error prompting, service description).
2) AI mode settings service logic
Enabling can be arranged in AI mode business logics or close AI patterns by teacher：Student's practice changes after closing AI patterns
To be classified lead learning pattern, student practices being changed to intelligence classification lead learning pattern after opening AI patterns, as shown in Figure 4.It opens
Teacher can be according to the different classes of corresponding real training standard of setting when opening AI patterns, such as practice period, high 3 ranks in junior middle school are each
The accuracy range values (such as primary 0%-60%, middle rank 60%-80%, advanced 80%-100%) of rank, make system pass through
The real training standard for Intelligence of Students allocation level, mitigates previous teacher's needs according to student's practice conditions combination big data analysis
The work load of manual assignment grade.
(3) real training case management business logic
Teacher can be by case management business logic come the real training case in voluntarily maintenance system, and the case of this system is
With templated format management, case data is stored in the case data table of system database, and teacher can import, export
Real training case, create case then need to only realize according to case template.First original bill example can be led when teacher changes case
Go out, the former case data of covering is completed and then imported in modification.
(4) real training monitoring business logic
Real training monitoring business logic is that the real training situation of student is checked in order to facilitate teacher, by system background and by right
The Macro or mass analysis of student's training operation data can form class's real training consolidated statement, real training knowledge point grasp situation summarizes, student
The consolidated statements such as personal real training situation table.The information that teacher is shown by consolidated statement grasps handle of each student to knowledge point
Degree is held, to targetedly be imparted knowledge to students.
1) class's real training consolidated statement
It reads the real training not counted in training operation record sheet and records data as record data to be counted, and will be to be counted
Record data are compared with the real training answer information to be counted read from real training answer library, obtain each operation step of each student
Rapid operant score finally obtains class's real training summary sheet, wherein class's real training summary sheet includes but not limited to that entire class is learned
Accuracy, the knowledge point of highest accuracy and the knowledge point information of minimum accuracy of raw knowledge point each in training operation.
2) real training knowledge point is grasped situation and is summarized
It reads the real training not counted in training operation record sheet and records data as record data to be counted, and will be to be counted
Record data are compared with the real training answer information to be counted read from real training answer library, obtain the training operation of each student
Positive exact figures, and using the positive exact figures of the training operation of individual students as Y-axis, using each knowledge point in real training case as X-axis, shape
At student's real training knowledge point accuracy consolidated statement.
3) student individual's real training situation consolidated statement
It reads the real training not counted in training operation record sheet and records data as record data to be counted, and will be to be counted
Record data are compared with the real training answer information to be counted read from real training answer library, one by one remember the operation of each student
Record data are compared with standard operation answer, obtain each knowledge point score of each student's operation, ultimately generate student
People operates real training situation consolidated statement.
As shown in figure 5, the detailed process of the intelligence classification lead learning method of the present embodiment is as follows：
1) logging in system by user 1；
2) user login information 2 is verified；
3) judge the user role type 3 logined successfully；
4) when role is student's type, into student subsystem 4；
5) enter real training case list, select training operation case 40；
6) whether student subsystem judges student's initialized practice rank 41, and pop-up window supplies if not initializing
Student selects practice rank (such as junior middle school's height) 42；
If 7) initialized practice rank, student subsystem judges whether student's practice periods meet the practice period and want
43 are asked, student subsystem reads current evaluation rank 44 of the current rank of student as student if being unsatisfactory for, if full
Sufficient then student subsystem passes through the calculation formula current level 45 of assessment of students' again automatically；
8) in real training case operation interface, " reading data " button is provided, user can choose whether to read old real training
Data 46, if not reading or being not present old real training data 48, student subsystem is remembered new training operation data are automatically created
Record；
9) user can select the real training indication project 48 of appropriate level during training operation, such as " bill "
Deng；
10) training operation record 49 is submitted；
11) the real training monitoring module of system background submits data to carry out data analysis according to preset statistical rules user
6；
12) real training monitoring data report 7 is generated；
13) when role is type of teacher, into teacher's subsystem 5；
14) real training classification guiding rank 51 is created, user can the title of self-defined guiding rank and the level of rank；
15) real training of configuration classification guiding rank prompts project 52, and indication project is when real training case makes
It pre-sets, after setting guiding rank prompt project, in the training operation of student subsystem, so that it may with displaying classification guiding
Rank and prompt project accordingly；
16) real training case 53 is created, the type of case is selected, the attribute (such as whether open etc.) of case is set；
17) it according to the stamp fabrication real training case 54 of real training case, imports in real training case to experience system；
18) teacher is arranged in interface in real training and AI patterns 55 of whether opening is arranged, and opens AI patterns and then needs setting corresponding
Rank evaluation criteria 56, such as practice the period, the high evaluation criteria value range in junior middle school.
In conclusion a kind of intelligence classification lead learning method, system and device of the present invention, according to the practice data of student
With the rank of the preset practice period Auto-matching student of teacher, and then make student according to corresponding stage according to the rank of Auto-matching
Other indication carries out corresponding practice teaching practice, can play the role of substituting teacher, by simulating true teaching industry
Business scene, collects the daily study of student and the data generated in the process that fulfil assignment precisely are known in conjunction with the analysis of big data technology
Situation is grasped in the knowledge point of road student, is student's Auto-matching grade and provides the indication of different stage, without according to
Raw real training situation is that classification can achieve the purpose that individualized teaching, efficient and intelligence degree are high to student's progress by hand.
The program can also flexibly be selected from intelligence classification lead learning pattern and classification lead learning pattern according to the actual needs of teacher
A kind of mode is selected to be classified, it is more convenient and flexible, and compatibility is more preferable；Further, the program makes teacher can also
The knowledge point of the main practical operation error of student is checked at back-stage management interface, by teacher's subsystem thus can in teaching process
It is explained with targetedly emphasis, to promote quality of instruction.The program is led in practice-training teachings softwares such as financial practice-training teaching softwares
Domain has a vast market application prospect.
It is to be illustrated to the preferable implementation of the present invention, but the present invention is not limited to the embodiment above, it is ripe
Various equivalent variations or replacement can also be made under the premise of without prejudice to spirit of that invention by knowing those skilled in the art, this
Equivalent deformation or replacement are all contained in the application claim limited range a bit.
Claims (10)
1. a kind of intelligence classification lead learning method, it is characterised in that：Include the following steps：
Obtain practice data and the teacher's preset practice period of student；
According to the rank of the preset practice period Auto-matching student of the practice data of student and teacher；
The indication of appropriate level is provided according to the rank of student for student, and makes indication of the student according to appropriate level
Carry out corresponding practice teaching practice.
2. a kind of intelligence classification lead learning method according to claim 1, it is characterised in that：The white silk for obtaining student
The step for practising data and teacher's preset practice period, specifically includes：
User is carried out to log in and log-on message verification；
Role judgement is carried out to the successful user of login authentication；
Enter student subsystem or teacher's subsystem according to the result of Role judgement；
Practice data and the teacher's preset practice period of student are obtained by student subsystem or teacher's subsystem.
3. a kind of intelligence classification lead learning method according to claim 2, it is characterised in that：It is described to pass through student's subsystem
System or teacher's subsystem obtain the step for practice data and teacher's preset practice period of student, specifically include：
Intelligence classification guiding management and control is carried out by teacher's subsystem, the intelligence classification guiding management and control includes creating intelligence classification to draw
It leads rank and configures the real training prompt project of appropriate level, carry out AI mode settings and corresponding rank evaluation criteria is set, create
It builds real training case and imports real training case data to database, and for student's granting real training voucher and according to the reality of real training voucher
Instruction record data is analyzed；
The practice data of student are obtained by student subsystem, and load teacher's preset practice period from teacher's subsystem.
4. a kind of intelligence classification lead learning method according to claim 3, it is characterised in that：The white silk according to student
The step for habit data and the rank of the preset practice period Auto-matching student of teacher, specially：
Judge whether AI patterns have turned on, if so, using intelligence classification lead learning pattern come the rank of automatic assessment of students',
Conversely, then judging the rank of student manually by teacher using classification lead learning pattern.
5. a kind of intelligence classification lead learning method according to claim 4, it is characterised in that：It is described to be classified using intelligence
Lead learning pattern carrys out the step for rank of automatic assessment of students', specifically includes：
Judge T according to the current exercise data of student1-T2Whether >=L is true, if so, next step is executed, conversely, then reading
Current evaluation rank of the current level of student as student, wherein T1For current time, T2For the time that student's last time evaluates,
L is teacher's preset practice period；
According to the training operation of student's real training voucher record data calculate student practice index, and then according to student practice index come
The rank of automatic evaluation student.
6. a kind of intelligence classification lead learning method according to claim 5, it is characterised in that：It is described according to student's real training
The training operation record data of voucher calculate student and practice index, and then practice index according to student come the grade of automatic assessment of students'
It the step for other, specifically includes：
Data are recorded according to the training operation of student's real training voucher and calculate student's practice index, and the student practices the meter of index K
Calculating formula is：K=(P1*S1+P2*S2+…+Pn*Sn)/n, wherein the formula of P is：Pi=Ii/Ji, IiFor in student's real training voucher
Quantity, J are answered questions in ith training operation recordiSum is answered for the need in ith training operation record in student's real training voucher
Amount, SiFor in student's real training voucher ith training operation record in total score, n be student's real training summary journal number, i=1,
2,…n；
Student is practiced into index and the accuracy range values of teacher's subsystem AI mode settings compare, show that student practices
Current evaluation rank of the corresponding rank of the affiliated accuracy range values of index as student.
7. a kind of intelligence classification lead learning method according to claim 4, it is characterised in that：It is described to be guided using classification
It the step for rank of the teaching pattern to judge student manually by teacher, specifically includes：
Teacher's subsystem records the practice data of data acquisition student according to the training operation of real training voucher；
The cadetcy of manual allocation is returned to student by teacher according to the rank of the practice data manual allocation student of student
Subsystem.
8. a kind of intelligence classification lead learning method according to claim 4, it is characterised in that：The grade according to student
The indication of appropriate level is not provided for student, and student is made to carry out corresponding teaching in fact according to the indication of appropriate level
The step for training is practised, specifically includes：
The indication of appropriate level is provided according to the rank of student for student；
Student subsystem judges whether student needs to read old real training data, if so, current reading the student from database
Next step is executed after data existing for real training, conversely, then directly executing next step；
Student carries out training operation according to the indication of appropriate level；
Submit the training operation record of student；
Data analysis is carried out to the training operation record that student submits according to preset statistical rules；
Real training monitoring data report is generated according to the result of data analysis.
9. a kind of intelligence classification lead learning system, it is characterised in that：Including：
Data acquisition module, practice data and the teacher preset practice period for obtaining student；
Auto-matching module, for the grade according to the preset practice period Auto-matching student of the practice data of student and teacher
Not；
Real training exercise module, the indication for providing appropriate level for student according to the rank of student, and make student according to
The indication of appropriate level carries out corresponding practice teaching practice.
10. a kind of intelligence classification lead learning device, it is characterised in that：Including：
Memory, for storing program；
Processor, for loading described program to execute such as a kind of intelligence classification guiding religion of claim 1-8 any one of them
Method.
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