CN107886451A - Exercise individualized fit method in the Teaching System of mobile terminal - Google Patents
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Abstract
The invention discloses a kind of exercise individualized fit method in mobile terminal Teaching System.By the tutoring system being managed, caused teaching data regards the data source of exercise Matching Model as to this method over the years first, a complete learning cycle is divided into three phases during exercise individualized fit, each stage uses different matching algorithms.In three phases, the exercise difficulty of push gradually increases, and coordinates similar topic clustering algorithm to be that student's push inscribes other the most similar exercises to wrong, consolidates knowledge point.Method provided by the invention, for the most suitable topic of Intelligence of Studentsization push, substantially increase the learning efficiency of student and the efficiency of teaching of teacher.
Description
Technical field
The invention belongs to Computer Applied Technology field, and in particular in a kind of small-scale mobile terminal Teaching System
Exercise individualized fit method.
Background technology
The rapid development of internet, on the one hand make it that information is presented explosive growth, people to the demand of information increasingly
Variation.On the other hand the development also for education provides new platform, expedites the emergence of out such a new industry shape of online education
State.
Information orientated higher education has also obtained huge lifting." internet+" this pattern just enters all trades and professions, online
Industry of imparting knowledge to students is also such.With the comprehensive popularization greatly developed with wireless network of society, and the propulsion of " internet+",
Arise at the historic moment in online teaching classroom.Online teaching classroom is exactly to pass through " internet+education ", the more high-quality education resource of utilization,
Enter row information push, recording learning track using intelligent terminal instrument, carry out learning outcome evaluation；Established and learned by interaction device
Community is practised, is made between instructor and learner and can be effectively interactive between learner and learner；Platform is established simultaneously,
Support is provided for the teaching community of teacher, makes instructor can be with the joint research content of courses, mode of learning, teaching method, study
Resource and learning tool.Long-run development of the online teaching classroom teaching model to colleges and universities has important strategic importance.In campus
In the process of teaching, online teaching classroom is increasingly popularized in college teaching, and all kinds of class teaching platforms extensively should
For in the teaching process of teacher.
At present, instructors can use class teaching platform to complete the thing such as exercise test, homework in roll-call, class before the class
, significantly reduce teaching pressure, improve efficiency of teaching.However, simple class teaching platform can not meet gradually
The high speed development of Informalized teaching.We are just stepping into the big data epoch, and traditional teaching pattern can not adapt to the blast of data
Increase, big data its study situation is accurately diagnosed, the analysis of individualized learning scheme and the decision-making of intelligence learning scheme
All brand-new development is brought to education.Set forth herein small-scale mobile terminal Teaching System in exercise individualized fit
Method is exactly the product under big data education, and big data is combined by it with university researchers education, to classroom instruction with a kind of complete
New mode, it is a change of educational mode.
In small-scale mobile terminal Teaching System application process, the need for pushing exercise exercise to student stage by stage be present
Ask.In general, when student has just begun to use the system, it is necessary to which the process of an adaptive learning, what is mainly practised is basis
Exercise；And as study for wrong topic (corresponding weak knowledge point) deeply, it is necessary to be strengthened；Finally need to carry out difficult point
Tackling key problem, practises some highly difficult exercises generally easily to malfunction.However, how the individual character of exercise is set according to this mode of learning
Change matching process, still occur at present without the technology of simple possible.
The content of the invention
The purpose of the present invention is overcome the deficiencies in the prior art, there is provided the exercise in a kind of mobile terminal Teaching System
Property matching process.
Exercise individualized fit method in the Teaching System of mobile terminal, it comprises the following steps：
1) collect user over the years preserved exercise of random exercise in Exercise Library and test situation data of correcting errors, and led
Enter initial data source of the database as the exercise Matching Model of mobile terminal Teaching System；Meanwhile taught in mobile terminal classroom
During the follow-up use of system, exercise Matching Model constantly records the user and is subordinate to other of same class with the user
The situation of correcting errors of all users each road exercise during exercise exercise, and real-time update is into database；
2) first stage of mobile terminal Teaching System is initially used in user, exercise Matching Model is according to primary data
Source calculates the error rate of per pass exercise, if then selecting exercise push in arterial highway among the workbook from error rate less than first threshold
To user terminal；
3) when user enters second stage at the completion first stage, exercise Matching Model is based on being calculated according to initial data source
The error rate of obtained per pass exercise, from error rate higher than first threshold but less than Second Threshold workbook among, if selection
Arterial highway exercise is pushed to user terminal；Meanwhile using similar topic clustering algorithm, calculate and the user is current or history does wrong exercise
Other similar exercises, and at least select one of most like exercise to be pushed to user terminal from similar workbook；
4) when user's completion second stage enters the phase III, exercise Matching Model is chosen is subordinate to same class with the user
If all users of level error rate highest arterial highway exercise during exercise exercise, and pushed to user terminal.
By the small-scale tutoring system being managed, caused teaching data regards exercise Matching Model as to the present invention over the years
Data source, class's individualized learning model is established by data model analysis.It is complete by one during exercise individualized fit
Learning cycle be divided into three phases, each stage uses different matching algorithms.Exercise individualized fit model can be every
One class establishes class's individualized learning model, helps to each different classes of the teacher according to model content precision
Implement specific aim teaching.
Preferably, described mobile terminal Teaching System is using mobile terminal to rely on, using Cloud Server as backstage
Tutoring system.
Preferably, described first stage, second stage and the switching between the phase III, have been practised by user
Exercise road number reaches predetermined threshold value road number or user has practised number of days and reached predetermined threshold value number of days to trigger.
Preferably, the push of described most like exercise is the push request triggering received according to user terminal.
Preferably, described similar topic clustering algorithm is as follows：
Relative coefficient between any two problem is predisposed to identical numerical value, is then based on described initial data source point
The exercise test of analysis unique user is corrected errors situation data, if the user two problems in test process malfunction simultaneously, to this two
The relative coefficient of problem is done plus 1 processing；The exercise of traversal all users over the years tests situation data of correcting errors, and obtains any twice
Relative coefficient between topic, the correlation and relative coefficient between two problems are proportional.
Preferably, in second stage, exercise Matching Model is during the multiple push of push exercise, except push is wrong
Outside rate is less than the exercise of first threshold by mistake, the exercise ratio that error rate is higher than the Second Threshold is also continuously increased.
The present invention, which for intelligence turns to student and pushes exercise, proposes a kind of habit in small-scale mobile terminal Teaching System
Inscribe individualized fit method.For contemporary classroom instruction equipment control demand, using segmented push and similar topic clustering algorithm,
Realize the purpose of the intelligent push of exercise.Student is divided into three phases and provides different exercises intelligent push side by the present invention
Method, the efficiency of teaching of teacher is substantially increased, meet the demand of small-scale classroom online teaching of new generation.
Brief description of the drawings
Fig. 1 is database data export flow chart；
Fig. 2 is specific presentation mode figure of the similar topic clustering algorithm result in teaching platform system.
Embodiment
The present invention is further elaborated and illustrated with reference to the accompanying drawings and detailed description.
Middle and small scale mobile terminal of the present invention Teaching System is to include by support of mobile terminal with Android and iOS system
Based on all kinds of mobile phone plane plate equipment, the Simple portable personalized teaching system using Cloud Server as backstage, applied to colleges and universities
The small-scale classroom instruction of teacher.Training of Exercises module is wherein built-in with, Exercise Library is built-in with module, can be in a manner of paper
Intelligently exercise is pushed to student to be trained.The push of exercise has both of which, and one kind is random push, and another kind is sublevel
Section push.Under random push mode, a number of exercise is chosen from Exercise Library every time, student is pushed to and carries out test instruction
Practice, and record test result, correct errors situation of each student to per pass exercise, the data are due to sample randomness, therefore
It can be used for statistical analysis.Another push mode stage by stage is the main improvement of the present invention, is mainly used in meeting personalization
The exercise push demand of intelligence.The realization of this method is illustrated in detail below：
Exercise individualized fit method in the Teaching System of small-scale mobile terminal comprises the following steps：
1) database is established, stores the exercise that the student over the years of the small-scale tutoring system obtains under random push mode
Situation data of correcting errors are tested, as the initial data source of the exercise Matching Model of mobile terminal Teaching System, to pass through data
Class's individualized learning model is established in model analysis.The sample size of the data source is sufficiently large, to meet the requirement of statistical analysis.
Meanwhile during the follow-up use of mobile terminal Teaching System, exercise Matching Model, which constantly records this, all to be made
With the information and exercise test result data of the user of the system, and it is recorded in real time in database.Exercise individualized fit
During a complete learning cycle is divided into three phases, each stage uses different matching algorithms.
2) student of first stage is beginner, is recorded without topic is done.Therefore mobile terminal classroom instruction is initially used with user
System is initially as the first stage.Exercise Matching Model computes exercises the error rate of per pass exercise in storehouse according to initial data source,
Then it is divided into multiple difficulty gradients from low to high according to error rate.It is less than the habit of first threshold from error rate in the first stage
If arterial highway exercise is selected to be pushed to user terminal as most easy topic among topic collection.Thus, by the way that this course learning will be received for the first time
Student is classified as the first stage, and model can be student's push low error rate exercise over the years, help students basis of curriculum to know
Know, reach the effect of quick start.
3) when student enters second stage at the completion first stage, exercise Matching Model is based on being calculated according to initial data source
The error rate of obtained per pass exercise, from error rate higher than first threshold but less than Second Threshold workbook among, if selection
Arterial highway exercise is pushed to user terminal as medium topic.Compared to the first stage, the exercise difficulty now pushed starts to be lifted.And
In this stage, deepening continuously with study, exercise Matching Model is during the follow-up push of push exercise, except push
Outside error rate is less than the exercise of first threshold, also constantly gradually increases error rate and (be more difficult to higher than the exercise of Second Threshold
Exercise) ratio.
Further, since correct errors situation of the student in exercise test process has been saved in database, can be preliminary
Recognize the wrong examination question distribution situation of the student.Therefore now need to use similar topic clustering algorithm, calculate and find out with being somebody's turn to do
Other similar exercises of user is current or history does wrong exercise, and one of most like habit is at least selected from similar workbook
Topic is pushed to user terminal.By pushing the similar topic of wrong topic for student, it can help what student's intensified learning was not grasped oneself very well
Knowledge, help student's polishing knowledge point short slab.But the exercise push similar to wrong exercise, can be system automatic push,
It settings button can actively click on for user below wrong exercise, then be pushed according to user's request.
4) when user's completion second stage enters the phase III, exercise Matching Model is chosen is subordinate to same class with the user
If all users of level error rate highest arterial highway exercise during exercise exercise, and pushed to user terminal.Into
Triphasic student, to having done a large amount of exercises and having been supplemented for knowledge point short slab, therefore the student in this stage is
There is good grasp to course all rudimentary knowledge point, now model is the high error rate topic that student pushes Ben Banben terms,
Student is helped to have more preferable deeper understanding to course set point.
In above-mentioned implementation, the switching of different phase can be realized using various ways：
A kind of is the threshold value for having been practised by setting exercise, after student has practised a number of exercise, you can is entered
Next pattern.Another kind is the form by setting the period, can be set into several timing nodes a term, work as arrival
Sometime during node, into next stage.It is of course also possible to by artificial according to the situation of student by administrative staff such as teachers
It is adjusted.
In addition, similar topic clustering algorithm can be realized using modes such as K-means clustering algorithms or semantics recognitions.But
In the present invention, it is contemplated that the word of the None- identifieds such as substantial amounts of formula is there may be in exercise, conventional clustering algorithm is difficult to reality
The now similitude matching feature, therefore another Similarity Algorithm is used, its implementation is：
Relative coefficient between any two problem is predisposed to identical numerical value, is then based on foregoing initial data source point
The exercise test of analysis unique user is corrected errors situation data, if the user two problems in test process malfunction simultaneously, to this two
The relative coefficient of problem is done plus 1 processing；The exercise of traversal all users over the years tests situation data of correcting errors, and obtains any twice
Relative coefficient between topic, the correlation and relative coefficient between two problems are proportional.When be connected to request need push with
During the maximally related exercise of a certain exercise, you can take out another exercise maximum with the relative coefficient of the exercise, push to user
End.
Below based on this method, the specific implementation of the present invention is elaborated in conjunction with the embodiments.Wherein main reality
Existing mode comes exposition details and effect as it was previously stated, repeat no more only in conjunction with accompanying drawing.
Embodiment
Next by taking the C language teaching platform that we are developed as an example, small-scale mobile terminal classroom instruction system is specifically introduced
The embodiment of exercise individualized fit method in system：
We regard the C language teaching platform being managed as the data source of exercise individualized fit model, such as Fig. 1 institutes
Show, by the class for selecting to record with partial data, under the random push mode that will be stored for many years in system history data storehouse
The exercise test data export of student, for establishing database, carries out follow-up exercise individualized fit.
Because education week is 18 weeks, the student of first three weeks is divided into the first stage by model, and the student of three to ten five weeks is divided into
Second stage, the student of ten five to ten eight weeks are divided into the phase III, and exercise individualized fit is automatically imported according to the difference in stage
In three modules corresponding to model.
The student for receiving this course learning for the first time is classified as the first stage by exercise individualized fit method.As shown in table 1,
Statistical module in model will count the accuracy of all topics, by accuracy be ranked up so as to by topic be divided into most easy topic,
Medium topic, secondary problem and most four parts of problem, model is that student pushes most easily inscribing in examination question over the years, side in the first phase
Students basis of curriculum knowledge is helped, reaches the effect of quick start.
The exercise of table 1 is by accuracy classification situation
3rd week, student completed a number of Training of Exercises, i.e., into second stage, now starts to push to student
Medium topic in table 1, increase difficulty.And while model push medium difficulty similar topic, it is gradual according to student's answer situation
The ratio of increase time problem and most problem, reach the purpose of the intelligent weak topic in push knowledge point.In addition, in the process, can
The wrong topic record page is set, and the button of " having a go at similar topic " is set below the wrong topic of per pass of the page, as shown in Figure 2.
When student clicks on, by similar topic clustering algorithm, other exercises similar to the road exercise are calculated, and from similar habit
Topic, which is concentrated, selects one or multi-channel similar exercise to be pushed to user terminal.
In the present embodiment, similar topic clustering algorithm principle is as follows：One student wrong two topics on a paper, then this
Correlation between twice topic adds one, and single student will necessarily have contingency, but more than 100 identical or different grades
The two all simultaneously wrong topics of students, then model is considered as, the examination of the two topics is same knowledge point, accordingly
Model is classified as same class.When the quantity of collection is sufficiently large, exercise individualized fit model can test out arbitrarily completely
Correlation between twice topic, for the wrong topic for inscribing the high degree of correlation of studentization push.Similar topic clustering algorithm in the present embodiment
Implementation be：At the beginning, the relative coefficient between any two problem is predisposed to 0, is then based on foregoing pushing away at random
The exercise for sending the initial data source obtained under pattern to analyze unique user tests situation data of correcting errors, if the user is in an exercise
Two problems malfunction simultaneously in test, then the relative coefficient of two problem are done plus 1 is handled；Travel through the exercise test of all users
Situation of correcting errors data, obtain the relative coefficient between any two problem.Then one maximum of conduct of relative coefficient is selected
Most related exercise, relative coefficient is smaller, and correlation is lower.
We have drawn the correlation between different examination questions eventually through exercise individualized fit model.Such as figure four, works as
It is raw do wrong certain road topic when, model will be that student push its degree of correlation highest topic, reach intelligence and turn to student and push knowledge
The purpose of the weak topic of point.
The student in stage in the end of term is divided into the phase III by exercise individualized fit method, and algorithm model passes through WEKA and SPSS
Statistics is studied the exercise practice result of student, by collecting complete this term of class mistake topic situation, often collects one
Target topic weighted value is carried out for error message plus a processing, draws full class's examination question error rate ranking list, while for student's push most
Problem, reach the effect for review of assaulting fortified position.
The present invention, which for intelligence turns to student and pushes exercise, proposes a kind of habit in small-scale mobile terminal Teaching System
Inscribe individualized fit method.For contemporary classroom instruction equipment control demand, the intelligent purpose pushed of exercise is realized.This hair
It is bright student to be divided into three phases different exercise intellectuality method for pushing is provided, the efficiency of teaching of teacher is substantially increased, it is full
The demand of foot small-scale classroom online teaching of new generation.
Although depicting the present invention by embodiment, it will be appreciated by the skilled addressee that the present invention have it is many deformation and
Change the spirit without departing from the present invention, it is desirable to which appended claim includes these deformations and changed without departing from the present invention's
Spirit.
Claims (6)
1. a kind of exercise individualized fit method in mobile terminal Teaching System, it is characterised in that comprise the following steps：
1) collect user over the years preserved exercise of random exercise in Exercise Library and test situation data of correcting errors, and be conducted into number
According to initial data source of the storehouse as the exercise Matching Model of mobile terminal Teaching System；Meanwhile in mobile terminal classroom instruction system
Unite during follow-up use, exercise Matching Model constantly record the user and with the user be subordinate to same class other are all
The situation of correcting errors of user's each road exercise during exercise exercise, and real-time update is into database；
2) first stage of mobile terminal Teaching System is initially used in user, exercise Matching Model is according to initial data source meter
The error rate of per pass exercise is calculated, if then selection arterial highway exercise is pushed to use among the workbook from error rate less than first threshold
Family end；
3) when user enters second stage at the completion first stage, exercise Matching Model is based on being calculated according to initial data source
Per pass exercise error rate, from error rate higher than first threshold but less than Second Threshold workbook among, if selection arterial highway
Exercise is pushed to user terminal；Meanwhile using similar topic clustering algorithm, find out similar to the exercise that the user is current or history does wrong
Other exercises, and at least select one of most like exercise to be pushed to user terminal from similar workbook；
4) when user's completion second stage enters the phase III, exercise Matching Model is chosen is subordinate to same class with the user
If all users error rate highest arterial highway exercise during exercise exercise, and pushed to user terminal.
2. the exercise individualized fit method in mobile terminal Teaching System as claimed in claim 1, it is characterised in that institute
The mobile terminal Teaching System stated is the tutoring system using Cloud Server as backstage using mobile terminal as support.
3. the exercise individualized fit method in mobile terminal Teaching System as claimed in claim 1, it is characterised in that institute
First stage, second stage and the switching between the phase III stated, it is that the exercise road number practised by user reaches default threshold
Value road number or user have practised number of days and have reached predetermined threshold value number of days to trigger.
4. the exercise individualized fit method in mobile terminal Teaching System as claimed in claim 1, it is characterised in that institute
The push for the most like exercise stated is the push request triggering received according to user terminal.
5. the exercise individualized fit method in mobile terminal Teaching System as claimed in claim 1, it is characterised in that institute
The similar topic clustering algorithm stated is as follows：
Relative coefficient between any two problem is predisposed to identical numerical value, it is single to be then based on described initial data source analysis
The exercise of individual user tests situation data of correcting errors, if the user two problems in test process malfunction, to two problem simultaneously
Relative coefficient do plus 1 processing；The exercise test of traversal all users over the years is corrected errors situation data, obtain any two problem it
Between relative coefficient, the correlation and relative coefficient between two problems be proportional.
6. the exercise individualized fit method in mobile terminal Teaching System as claimed in claim 1, it is characterised in that
Second stage, exercise Matching Model is during the multiple push of push exercise, except push error rate is less than first threshold
Outside exercise, the exercise ratio that error rate is higher than the Second Threshold is also continuously increased.
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| CN109712455A (en) * | 2018-11-22 | 2019-05-03 | 浙江创一信息技术有限公司 | Intelligence learning measure of supervision, storage medium, control device and learning machine |
| CN110096589A (en) * | 2019-03-14 | 2019-08-06 | 杭州笔声智能科技有限公司 | A kind of examination question feedback and recommendation explanation method and system based on image recognition technology |
| CN110704503A (en) * | 2019-09-19 | 2020-01-17 | 上海易点时空网络有限公司 | Question setting method and device and server |
| CN110738883A (en) * | 2019-10-23 | 2020-01-31 | 广西财经学院 | multimedia-based tourism culture resource management and tourist attraction teaching system |
| CN113611172A (en) * | 2021-08-18 | 2021-11-05 | 江苏熙枫教育科技有限公司 | English listening comprehension training method based on deep learning |
| CN116452071A (en) * | 2023-06-16 | 2023-07-18 | 济南科明数码技术股份有限公司 | Intelligent teaching quality evaluation system based on VR and 5G technologies |
| CN116452071B (en) * | 2023-06-16 | 2023-08-18 | 济南科明数码技术股份有限公司 | Intelligent teaching quality evaluation system based on VR and 5G technologies |
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