CN108074203A - A kind of teaching readjustment method and apparatus - Google Patents
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Abstract
The embodiment of the invention discloses a kind of teaching readjustment method, this method includes：According to the face image of the learner collected, the mood attribute of the learner is determined；It is recorded according to the mood attribute of the learner and the studying history of the learner collected, the content of courses is determined for the learner；According to the mood attribute of the learner, instructional strategies is determined for the learner, the content of courses is pushed to the learner according to the instructional strategies.The embodiment of the present invention further simultaneously discloses a kind of teaching readjustment device.
Description
Technical field
The present invention relates to Web-based instruction technical field more particularly to a kind of teaching readjustment method and apparatus.
Background technology
Now, with the development of internet, favor is received by the education and study mode of network, learner passes through network science
The limitation for being no longer influenced by geographical location is practised, and the knowledge got by e-learning is more comprehensive extensively, then, network science
For exercises for a kind of easily mode of learning, the learning efficiency by e-learning is the emphasis of learner's concern.
In the prior art, in e-learning, network courses are all the experience layouts previously according to instructor, learner
During learning network course, it can only be learnt according to advance programmed network courses, in order to improve learner's
Learning efficiency, generally by the static evaluation and the acquisition of dynamic learning capability behavioral data that learning ability is carried out to learner
Mode obtains learner to mastery of knowledge degree, then, provides to mastery of knowledge degree for learner according to learner
Practise and suggest guidance, however, this method be mainly it is mechanical between learner and computer exchange, and in traditional teaching method
Teacher can compare according to the reaction of student neatly to adjust teaching method, and learner is imitated by the study of Network-based Course Learning
Rate is relatively low.
The content of the invention
In view of this, an embodiment of the present invention is intended to provide a kind of device of teaching readjustment method, to solve in the prior art
Existing learner by Network-based Course Learning learning it is less efficient the technical issues of, improve the Experience Degree of user.
In order to achieve the above objectives, the technical proposal of the invention is realized in this way：
In a first aspect, the embodiment of the present invention provides a kind of teaching readjustment method, including：According to the face of the learner collected
Portion's image determines the mood attribute of the learner；According to the mood attribute of the learner and the learner collected
Studying history record, determine the content of courses for the learner；It is the study according to the mood attribute of the learner
Person determines instructional strategies, and the content of courses is pushed to the learner according to the instructional strategies.
Further, the face image for the learner that the basis collects determines the mood attribute of the learner, bag
It includes：The image information of predeterminable area is extracted from the face image of the learner；Believed according to the image of the predeterminable area
Breath obtains the mood data of the learner；Each feelings in the mood data and presetting database of the learner are calculated respectively
The matching degree of thread data；According to the mood data of the learner and the matching degree of each mood data, determine described
The mood attribute of learner.
Further, the matching degree of the mood data according to the learner and each mood data determines
Go out the mood attribute of the learner, including：It will be in the matching degree of the mood data of the learner and each mood data
The corresponding mood classification of maximum is determined as the mood classification of the learner；It is happiness in the mood classification of the learner
When, the mood attribute for determining the learner is positive mood；When the mood classification of the learner is surprised, determine described
The mood attribute of learner is to need mood；It is sad or angry or frightened or detest in the mood classification of the learner
When, the mood attribute for determining the learner is negative emotions.
Further, the mood attribute according to the learner and the studying history of the learner collected note
Record determines the content of courses for the learner, including：When the mood attribute of the learner is positive mood, according to institute
The studying history record of learner is stated, the learning path for determining the learner is the default learning path for going deep into type；
The mood attribute of the learner is when needing mood, to be recorded according to the studying history of the learner, determine the study
The learning path of person is the learning path of default case type；When the mood attribute of the learner is negative emotions, according to
The studying history record of the learner, the learning path for determining the learner are the learning path of default type of releiving；
According to the learning path of the learner, the content of courses is determined for the learner.
Further, it is described according to the mood attribute, determine instructional strategies for the learner, including：Described
When the mood attribute of learner is positive mood, the instructional strategies determined is default gradual instructional strategies；
The mood attribute of the learner is when needing mood, the instructional strategies determined is the teaching plan of default lively formula
Slightly；When the mood attribute of the learner is negative emotions, the instructional strategies determined is the religion of default light formula
Learn strategy.
Second aspect, the embodiment of the present invention provide a kind of teaching readjustment device, including：First determining module, for basis
The face image of the learner collected determines the mood attribute of the learner；Second determining module, for according to
The mood attribute of habit person and the studying history of the learner collected record, the content of courses is determined for the learner；
Pushing module for the mood attribute according to the learner, determines instructional strategies, according to the teaching for the learner
Strategy pushes the content of courses to the learner.
Further, first determining module includes：Extracting sub-module, for from the face image of the learner
Extract the image information of predeterminable area；Submodule is obtained, for the image information according to the predeterminable area, obtains
The mood data of habit person；Computational submodule, for calculating each in the mood data of the learner and presetting database respectively
The matching degree of mood data；Determination sub-module, for the mood data according to the learner and each mood data
Matching degree determines the mood attribute of the learner.
Further, the determination sub-module, specifically for by the mood data of the learner and each mood data
Matching degree in the corresponding mood classification of maximum, be determined as the mood classification of the learner；In the feelings of the learner
When thread classification is glad, the mood attribute for determining the learner is positive mood；It is frightened in the mood classification of the learner
When strange, the mood attribute of the learner is determined to need mood；The learner mood classification for it is sad or angry,
Or during frightened or detest, the mood attribute for determining the learner is negative emotions.
Further, when second determining module specifically for the mood attribute in the learner is positive mood,
It is recorded according to the studying history of the learner, the learning path for determining the learner is the default study road for going deep into type
Footpath；It when the mood attribute of the learner is needs mood, is recorded, determined described according to the studying history of the learner
The learning path of learner is the learning path of default case type；When the mood attribute of the learner is negative emotions,
It is recorded according to the studying history of the learner, the learning path for determining the learner is the study road of default type of releiving
Footpath；According to the learning path of the learner, the content of courses is determined for the learner.
Further, when the pushing module specifically for the mood attribute in the learner is positive mood, by institute
It states instructional strategies and is determined as default gradual instructional strategies；It, will when the mood attribute of the learner is needs mood
The instructional strategies is determined as the instructional strategies of default lively formula；When the mood attribute of the learner is negative emotions,
The instructional strategies is determined as to the instructional strategies of default light formula.
The teaching readjustment method and apparatus that the embodiment of the present invention is provided first, gather the face image of learner, according to
The face image of the learner collected determines the mood attribute of learner, then, according to the mood attribute of learner and adopts
The studying history record of the learner collected, determines the content of courses for learner, finally, according to the mood attribute of learner,
Determine instructional strategies for learner, and the content of courses pushed to learner according to instructional strategies, so so that the content of courses and
Instructional strategies can be adjusted according to the mood of learner, avoid it is mechanical between learner and computer exchange,
By adjusting the content of courses and instructional strategies, the content of courses and the instructional strategies of oneself are neatly suitble to for learner's push, is had
Beneficial to raising learning efficiency of the learner by Network-based Course Learning.
Description of the drawings
Fig. 1 is the flow diagram of the teaching readjustment method in the embodiment of the present invention；
A kind of optional flow diagram of teaching readjustment method in Fig. 2 embodiment of the present invention；
The optional flow diagram of another kind of teaching readjustment method in Fig. 3 embodiment of the present invention；
Another optional flow diagram of teaching readjustment method in Fig. 4 embodiment of the present invention；
Another optional flow diagram of teaching readjustment method in Fig. 5 embodiment of the present invention；
Fig. 6 is the structure diagram of the teaching readjustment device in the embodiment of the present invention.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes.
The embodiment of the present invention provides a kind of teaching readjustment method, and this method is applied in teaching readjustment device, and Fig. 1 is this hair
The flow diagram of teaching readjustment method in bright embodiment, as shown in Figure 1, the teaching readjustment method includes：
S101：According to the face image of the learner collected, the mood attribute of learner is determined；
Specifically, mood is a kind of inner experience of people, and expression is the external embodiment of mood, passes through learner's expression
Identification can know measured's mental emotion state, so, during learner is learnt by network courses, lead to
Camera acquisition initial pictures are crossed, find out position and the ruler of primary expression regions from the initial pictures using Face datection algorithm
It is very little, the face image of the learner collected, and the face image of learner is sent in above-mentioned teaching readjustment device
Intelligent Human-Machine Interface in, then, teaching readjustment device determines the mood attribute of learner by face image；
Wherein, which can be the part in teaching readjustment device or an independent part, in addition,
Above-mentioned Face datection algorithm can include：Adaboost model algorithms and complexion model algorithm, but the embodiment of the present invention is not limited to
This.
Above-mentioned mood attribute can include positive mood, need mood and negative emotions.
As previously described, face image can reflect impression of the learner to the content of courses currently learnt, so,
Teaching readjustment device need to determine the mood attribute of learner according to the face image of learner, in order to determine the feelings of learner
Thread attribute, in a kind of optional embodiment, S101 can include：
S201：The image information of predeterminable area is extracted from the face image of learner；
S202：According to the image information of predeterminable area, the mood data of learner is obtained；
S203：The matching degree of each mood data in the mood data and presetting database of learner is calculated respectively；
S204：According to the matching degree of the mood data of learner and each mood data, the mood category of learner is determined
Property.
Wherein, above-mentioned predeterminable area can be one or more kinds of in face feature, wherein above-mentioned face feature can wrap
Include eyes, face, eyebrow etc.；
In practical applications, eyes and face can most reflect the emotional state of people, then, below using predeterminable area as
Exemplified by face and face, teaching readjustment device matches (SIFT, Scale Invariant using Scale invariant features transform
Feature Transform) algorithm extracts the image information of eyes and face from the face image of learner, then basis
The image information of face and face obtains learner using Object Request Broker (ORB, Object Request broker) algorithm
Mood data, which can be a specific numerical value, or a vector, here, the embodiment of the present invention
It is not specifically limited.
Above-mentioned presetting database can include JAFFE databases and Cohn-Kanada Facial expression databases, and the present invention is real
It is without being limited thereto to apply example；Below by presetting database by taking JAFFE databases as an example, in JAFFE databases, proposed including Ekman
The corresponding mood data of six kinds of basic emotions, wherein, above-mentioned six kinds of basic emotions include：It is glad, sad, angry, frightened, frightened
Very, detest；In S203, of the mood data mood data corresponding with above-mentioned six kinds of basic emotions of learner is calculated respectively
With in degree, when mood data is a numerical value, then above-mentioned matching degree can be the mood data and each mood of learner
The difference of data, when mood data is a vector, then above-mentioned matching degree can be the mood data of learner and each
The distance of mood data, here, the embodiment of the present invention is not specifically limited.
In S204, in order to determine the mood attribute of learner, to determine the religion for being suitble to learner for learner
Content and instructional strategies are learned, in a kind of optional embodiment, S204 can include：
By the mood data of learner mood classification corresponding with the maximum in the matching degree of each mood data, determine
For the mood classification of learner；When the mood classification of learner is glad, the mood attribute for determining learner is positive mood；
When the mood classification of learner is surprised, the mood attribute of learner is determined to need mood；In the mood classification of learner
To be sad or angry or frightened or when detesting, the mood attribute for determining learner is negative emotions.
It is calculated in S203 in the mood data and presetting database of learner after the matching degree of each mood data,
More obtained matching value determines the maximum in matching value, which corresponds to classification of being in a bad mood, wherein, the mood
Classification can include：Happiness, sad, angry, frightened, surprised, detest；
For learner, during study, the mood of appearance can substantially be divided into three classes, and the first kind is study
The receiving ability that person receives knowledge is good, and emotional state is preferable, can show as happiness etc., then, the mood attribute is just
Face mood；Second class is by learner for, there are part doubtful point, emotional state is not good enough, can show as shying in the knowledge that receives
It is strange etc., at this point, the mood attribute is to need mood；Three classes by learner in the knowledge that receives there are more doubtful point,
Emotional state is poor, can show as sad or angry or frightened or detest etc., at this point, the mood attribute is to need mood；
As known from the above, when the mood classification of learner is glad, illustrate that learner's emotional state is preferable, determine study
The mood attribute of person is positive mood；When the mood classification of learner is surprised, illustrate that learner's emotional state is not good enough, determine
The mood attribute of learner is to need mood；When the mood classification of learner is sad or angry or frightened or detest, say
Bright learner's emotional state is poor, and the mood attribute for determining learner is negative emotions.
So far, the mood attribute of learner is just determined.
S102：It is recorded according to the mood attribute of learner and the studying history of the learner collected, is determined for learner
Go out the content of courses；
Here, it is necessary to which explanation, the studying history record of the above-mentioned learner collected can include：The base of learner
This information, the content of courses record of learner, learners' knowledge grasp situation, and the embodiment of the present invention is without being limited thereto；
Wherein, the essential information of above-mentioned learner can be with name, gender, educational background etc., the content of courses of above-mentioned learner
Record can include the content of courses and corresponding evaluating result etc..
After the mood attribute for determining learner and the studying history for collecting learner record, in order to be learner
Determine the content of courses for being suitble to itself current state, in a kind of optional embodiment, S102 can include：
When the mood attribute of learner is positive mood, is recorded according to the studying history of learner, determine learner
Learning path be the default learning path for going deep into type；When the mood attribute of learner is needs mood, according to learner
Studying history record, determine learner learning path be default case type learning path；In the mood of learner
It when attribute is negative emotions, is recorded according to the studying history of learner, determines that the learning path of learner is releived to be default
The learning path of type；According to the learning path of learner, the content of courses is determined for learner.
In specific implementation process, learning path and learning knowledge point learning object to be used can be regarded as one
Big search space, and individualized learning path is recommended to regard a kind of search strategy as, when there are very more learning objects, search
Rope space can be very huge, and it is infeasible to carry out exhaustion, it is necessary to take a kind of effective search strategy, then, it is above-mentioned can be with
It is searched according to the studying history of learner record using cultural gene (Memetic) algorithm or TABU search (Tabu) algorithm
Rope；
Wherein, when the mood attribute of learner is positive mood, illustrate that the mood attribute of learner is preferable, and according to
The studying history record of learner is scanned for using Memetic algorithms or Tabu algorithms, it may be determined that goes out learner
Habit path is the default learning path for going deep into type, which is directed toward the content of courses from the superficial to the deep, then,
It can determine what the content of courses was determined for the knowledge point grasped based on learner according to the learning path for going deep into type
The content of courses from the superficial to the deep；Learn that the learner has learnt religion using Memetic algorithms or Tabu algorithms for example, working as
Content A and content of courses B is learned, and has grasped content of courses A and content of courses B, then, in the emotional state of learner
It is that the content of courses that learner determines is the teaching using content of courses A and content of courses B as basic knowledge from the superficial to the deep when preferable
Content C；
When the mood attribute of learner is needs mood, illustrate that the mood attribute of learner is not good enough, and according to study
The studying history record of person is scanned for using Memetic algorithms or Tabu algorithms, it may be determined that goes out the study road of learner
Footpath is the learning path of default case type, and the learning path of the case type is directed toward the content of courses based on case, then, root
It can determine that the content of courses is the religion that the knowledge point grasped based on learner is determined according to the learning path of the case type
Learn content；Learn that the learner has learnt content of courses A and religion using Memetic algorithms or Tabu algorithms for example, working as
Content B is learned, which has only grasped content of courses A, then, it is that learner is true when the emotional state of learner is not good enough
The content of courses B that it is basic knowledge based on case using content of courses A that the fixed content of courses, which is,；
When the mood attribute of learner is negative emotions, illustrate that the mood attribute of learner is poor, and according to study
The studying history record of person is scanned for using Memetic algorithms or Tabu algorithms, it may be determined that goes out the study road of learner
Footpath is the learning path of default type of releiving, and the learning path direction of the type of releiving is intercutted in the teaching of music or interruption rest
Hold, then, it can determine that the content of courses is the knowledge point grasped based on learner according to the learning path of the type of releiving
The content of courses determined；Learn that the learner has learnt teaching using Memetic algorithms or Tabu algorithms for example, working as
Content A and content of courses B, the learner have only grasped content of courses A, then, when the emotional state of learner is poor, be
The content of courses that learner determines is the content of courses B that music or interruption rest are intercutted by basic knowledge of content of courses A；
It is above-mentioned to be scanned for according to the study of learner study historical record using Memetic algorithms or Tabu algorithms,
It can determine the learning path of learner, the purpose of learning path real-time update is exactly to know from a variety of learning paths and study
To know in point and choose the content of courses for being most suitable for learner so that learning process disclosure satisfy that the different individual requirement of learner,
Effectively shorten learning time, so as to improve learning efficiency.
So far, the content of courses for being suitble to oneself state is determined for learner.
S103：According to the mood attribute of learner, determine instructional strategies for learner, push and impart knowledge to students according to instructional strategies
Content is to learner.
Wherein, above-mentioned instructional strategies is suitable for pushing the mode of the content of courses to learner, for example, instructional strategies can wrap
The progress of the push content of courses and the explanation mode of the push content of courses etc. are included, the embodiment of the present invention is without being limited thereto.
After the mood attribute of learner is determined, in order to determine the teaching for being suitble to itself current state for learner
Strategy so that learner can be easier to grasp the content of courses of push, and in a kind of optional embodiment, S103 can be wrapped
It includes：
When the mood attribute of learner is positive mood, the instructional strategies determined is default gradual teaching plan
Slightly；When the mood attribute of learner is needs mood, the instructional strategies determined is the instructional strategies of default lively formula；
When the mood attribute of learner is negative emotions, the instructional strategies determined is the instructional strategies of default light formula.
Specifically, when the mood attribute of learner is positive mood, illustrate that the learning state of learner is preferable, then
The instructional strategies determined be default gradual instructional strategies, the gradual instructional strategies can be according to faster into
The degree push content of courses pushes the content of courses to learner to learner and/or using explanation mode prosily；For example, really
When the content of courses made is C, gradual instructional strategies can be disposably by content of courses C according to prosily
Explanation mode is pushed to learner；
When the mood attribute of learner is needs mood, illustrate that the learning state of learner is not good enough, then determine
Instructional strategies is the instructional strategies of default lively formula, and the instructional strategies of the lively formula can be to push religion according to medium progress
It learns content and pushes the content of courses to learner to learner and/or using lively explanation mode；For example, in the teaching determined
Hold for B when, the instructional strategies of lively formula can be content of courses B to be pushed to according to lively explanation mode points for 2 to 3 times
Habit person；
When the mood attribute of learner is negative emotions, illustrate that the learning state of learner is poor, then determine
Instructional strategies is the instructional strategies of default light formula, and the instructional strategies of the light formula can be to push religion according to slower progress
It learns content and pushes the content of courses to learner to learner and/or using easily explanation mode；For example, in the teaching determined
Hold for B when, the instructional strategies of light formula can be content of courses B to be pushed to according to easily explanation mode points for 5 to 6 times
Habit person.
Teaching readjustment method in said one or multiple embodiments illustrated with specific example below.
The optional flow diagram of another kind of teaching readjustment method in Fig. 3 embodiment of the present invention, as shown in figure 3, with
Family (being equivalent to above-mentioned learner) gathers the face image of user by Intelligent Human-Machine Interface, is extracted from the face image of user
Go out the image information of predeterminable area, determine the mood attribute of user according to the image information of predeterminable area, and by the feelings of user
Thread attribute is sent to student model；Another optional flow diagram of teaching readjustment method in Fig. 4 embodiment of the present invention,
As shown in figure 4, the input information of student model includes：The personal information of user and the learning behavior information (personal information of user
Above-mentioned studying history record is equivalent to learning behavior information) and emotional information (being equivalent to above-mentioned mood attribute)；
Then, a comprehensive evaluation is carried out to input information in student model, for example, the user is to existing knowledge
Grasp situation, cognitive ability of the student etc., in practical applications, be to study after in each knowledge point, study terminates
Person is tested, according to the cognitive ability of test result calculations learner, to determine the complexity of next blocks of knowledge, as
Adjust the foundation of knowledge learning order.
Then using the input information of student model and comprehensive evaluation as the input information of personalized model, personalized mould
In type, the mood attribute based on the user determined according to the personal information of user, learning behavior information and comprehensive is commented
Valency determines learning path for user, and then determines the content of courses according to learning path, and by the content of courses of user and use
The mood attribute input teaching mode at family, in teaching mode, personalized is pushed out for user with reference to knowledge base, rule base
Practise content (being equivalent to above-mentioned according to the instructional strategies the determined push content of courses).
Another optional flow diagram of teaching readjustment method in Fig. 5 embodiment of the present invention, as shown in figure 5, being
Flow diagram corresponding with Fig. 3 is, it is necessary to illustrate, when numerology practises path in personalized model in the embodiment of the present invention
Dynamic real-time update, that is to say, that student model after emotional state is received in real time, the dynamic in personalized model
The learning path and learning Content of user is updated, in teaching mode, based on newer emotional state, learning Content and knowledge graph
Spectrum determines the newer instructional strategies of dynamic.
By examples detailed above, the emotional state of learner is detected and analyzed in real time, merges emotional state information and user
The foundation of the student model of learning records and personal essential information, in learning process adaptive regularized learning algorithm strategy in study
An important factor for holding, the foundation of Dynamic recommendation personalized model, learner's emotional state information learnt as influence user, the
Once be introduced into individualized learning recommended technology scheme, emotional state information as learning strategy dynamic adjustment it is crucial because
Element compared with only focusing on learner to acquisition of knowledge degree, traditional on-line study method of learning records information, is more nearly
Habit person really learns scene, can improve the learning effect of learner.
The teaching readjustment method that the embodiment of the present invention is provided first, gathers the face image of learner, according to collecting
The face image of learner determine the mood attribute of learner, then, according to the mood attribute of learner and collect
The studying history record of learner, the content of courses is determined for learner, finally, according to the mood attribute of learner, for study
Person determines instructional strategies, and pushes the content of courses to learner according to instructional strategies, so so that the content of courses and teaching plan
Slightly, can be adjusted according to the mood of learner, avoid it is mechanical between learner and computer exchange, pass through tune
The whole content of courses and instructional strategies are neatly suitble to the content of courses and the instructional strategies of oneself for learner's push, are conducive to carry
The learning efficiency that high learner passes through Network-based Course Learning.
Based on same inventive concept, the present embodiment provides a kind of teaching readjustment device, Fig. 6 is the religion in the embodiment of the present invention
The structure diagram of adjusting apparatus is learned, as shown in fig. 6, the teaching readjustment device includes：First determining module 61, second determines mould
Block 62 and pushing module 63；
Wherein, the first determining module 61, for according to the face image of learner collected, determining the mood of learner
Attribute；Second determining module 62 records for the mood attribute according to learner and the studying history of the learner collected, is
Learner determines the content of courses；For the mood attribute according to learner, teaching plan is determined for learner for pushing module 63
Slightly, the content of courses is pushed to learner according to instructional strategies.
Face image can reflect impression of the learner to the content of courses currently learnt, so, teaching readjustment dress
The mood attribute of learner need to be determined according to the face image of learner by putting, in order to determine the mood attribute of learner,
In a kind of optional embodiment, above-mentioned first determining module 61 includes：Extracting sub-module, for from the face image of learner
Extract the image information of predeterminable area；Submodule is obtained, for the image information according to predeterminable area, obtains the feelings of learner
Thread data；Computational submodule, for calculating of each mood data in the mood data of learner and presetting database respectively
With degree；Determination sub-module for the mood data according to learner and the matching degree of each mood data, determines learner's
Mood attribute.
In order to determine the mood attribute of learner, to determine the content of courses and religion that are suitble to learner for learner
Strategy is learned, in a kind of optional embodiment, above-mentioned determination sub-module, specifically for by the mood data of learner and each feelings
The corresponding mood classification of maximum in the matching degree of thread data is determined as the mood classification of learner；In the mood of learner
When classification is glad, the mood attribute for determining learner is positive mood；When the mood classification of learner is surprised, determine to learn
The mood attribute of habit person is to need mood；It is definite when the mood classification of learner is sad or angry or frightened or detest
The mood attribute of learner is negative emotions.
After the mood attribute for determining learner and the studying history for collecting learner record, in order to be learner
Determine the content of courses for being suitble to itself current state, in a kind of optional embodiment, above-mentioned second determining module 62, specifically
For when the mood attribute of learner is positive mood, being recorded according to the studying history of learner, determining learner
Habit path is the default learning path for going deep into type；When the mood attribute of learner is needs mood, according to learner
Historical record is practised, the learning path for determining learner is the learning path of default case type；In the mood attribute of learner
For negative emotions when, recorded according to the studying history of learner, determine the learning path of learner for default type of releiving
Learning path；According to the learning path of learner, the content of courses is determined for learner.
After the mood attribute of learner is determined, in order to determine the teaching for being suitble to itself current state for learner
Strategy so that learner can be easier to grasp the content of courses of push, in a kind of optional embodiment, above-mentioned pushing module
63, when specifically for the mood attribute in learner being positive mood, instructional strategies is determined as default gradual teaching
Strategy；When the mood attribute of learner is needs mood, instructional strategies is determined as to the instructional strategies of default lively formula；
When the mood attribute of learner is negative emotions, instructional strategies is determined as to the instructional strategies of default light formula.
In practical applications, the first determining module 61, the second determining module 62, pushing module 63, extraction submodule, acquisition
Module, computational submodule, determination sub-module can be by being located at central processing unit (CPU, the Central Processing of terminal
Unit), microprocessor (MPU, Microprocessor Unit), application-specific integrated circuit (ASIC, Application
Specific Integrated Circuit) or field programmable gate array (FPGA, Field-Programmable Gate
The realizations such as Array).
The present embodiment records a kind of computer-readable medium, can be ROM (for example, read-only memory, FLASH memory,
Transfer device etc.), magnetic storage medium (for example, tape, disc driver etc.), optical storage medium is (for example, CD-ROM, DVD-
ROM, paper card, paper tape etc.) and other well-known types program storage；Computer is stored in computer-readable medium to be held
Row instruction when executing an instruction, causes at least one processor execution to include following operation：
According to the face image of the learner collected, the mood attribute of learner is determined；According to the mood category of learner
Property and the learner that collects studying history record, determine the content of courses for learner；According to the mood attribute of learner,
Instructional strategies is determined for learner, and the content of courses is pushed to learner according to instructional strategies.
The teaching readjustment method that the embodiment of the present invention is provided first, gathers the face image of learner, according to collecting
The face image of learner determine the mood attribute of learner, then, according to the mood attribute of learner and collect
The studying history record of learner, the content of courses is determined for learner, finally, according to the mood attribute of learner, for study
Person determines instructional strategies, and pushes the content of courses to learner according to instructional strategies, so so that the content of courses and teaching plan
Slightly, can be adjusted according to the mood of learner, avoid it is mechanical between learner and computer exchange, pass through tune
The whole content of courses and instructional strategies are neatly suitble to the content of courses and the instructional strategies of oneself for learner's push, are conducive to carry
The learning efficiency that high learner passes through Network-based Course Learning.
It need to be noted that be：Apparatus above implements the description of item, is similar with above method description, has same
The identical advantageous effect of embodiment of the method, therefore do not repeat.For the technical detail not disclosed in apparatus of the present invention embodiment,
Those skilled in the art refer to the description of the method for the present invention embodiment and understand, to save length, which is not described herein again.
It need to be noted that be：
It is to be understood that " one embodiment " or " embodiment " that specification is mentioned in the whole text mean it is related with embodiment
A particular feature, structure, or characteristic is included at least one embodiment of the present invention.Therefore, occur everywhere in entire disclosure
" in one embodiment " or " in one embodiment " identical embodiment is not necessarily referred to.In addition, these specific feature, knots
Structure or characteristic can in any suitable manner combine in one or more embodiments.It is to be understood that in the various implementations of the present invention
In example, the size of the sequence number of above-mentioned each process is not meant to the priority of execution sequence, and the execution sequence of each process should be with its work(
It can be determined with internal logic, the implementation process without tackling the embodiment of the present invention forms any restriction.The embodiments of the present invention
Sequence number is for illustration only, does not represent the quality of embodiment.
It should be noted that herein, term " comprising ", "comprising" or its any other variant are intended to non-row
His property includes, so that process, method, article or device including a series of elements not only include those elements, and
And it further includes other elements that are not explicitly listed or further includes as this process, method, article or device institute inherently
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this
Also there are other identical elements in the process of element, method, article or device.
In several embodiments provided herein, it should be understood that disclosed device and method can pass through it
Its mode is realized.Apparatus embodiments described above are only schematical, for example, the division of the unit, is only
A kind of division of logic function can have other dividing mode, such as in actual implementation：Multiple units or component can combine or
It is desirably integrated into another system or some features can be ignored or does not perform.In addition, shown or discussed each composition portion
Point mutual coupling or direct-coupling or communication connection can be the INDIRECT COUPLINGs by some interfaces, equipment or unit
Or communication connection, can be electrical, mechanical or other forms.
The above-mentioned unit illustrated as separating component can be or may not be physically separate, be shown as unit
The component shown can be or may not be physical location；Both a place can be located at, multiple network lists can also be distributed to
In member；Part or all of unit therein can be selected to realize the purpose of this embodiment scheme according to the actual needs.
In addition, each functional unit in various embodiments of the present invention can be fully integrated into a processing unit, also may be used
To be each unit individually as a unit, can also two or more units integrate in a unit；It is above-mentioned
The form that hardware had both may be employed in integrated unit is realized, can also be realized in the form of hardware adds SFU software functional unit.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above method embodiment can pass through
The relevant hardware of program instruction is completed, and foregoing program can be stored in computer read/write memory medium, which exists
During execution, execution the step of including above method embodiment；And foregoing storage medium includes：Movable storage device read-only is deposited
The various media that can store program code such as reservoir (Read Only Memory, ROM), magnetic disc or CD.
If alternatively, the above-mentioned integrated unit of the present invention is realized in the form of software function module and is independent product
Sale in use, can also be stored in a computer read/write memory medium.Based on such understanding, the present invention is implemented
The technical solution of example substantially in other words can be embodied the part that the prior art contributes in the form of software product,
The computer software product is stored in a storage medium, and being used including some instructions (can be with so that computer equipment
It is personal computer, server or network equipment etc.) perform all or part of each embodiment the method for the present invention.
And foregoing storage medium includes：Various Jie that can store program code such as movable storage device, ROM, magnetic disc or CD
Matter.
The above description is merely a specific embodiment, but protection scope of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in change or replacement, should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (10)
- A kind of 1. teaching readjustment method, which is characterized in that including：According to the face image of the learner collected, the mood attribute of the learner is determined；It is recorded according to the mood attribute of the learner and the studying history of the learner collected, is that the learner is true Make the content of courses；According to the mood attribute of the learner, determine instructional strategies for the learner, pushed according to the instructional strategies The content of courses is to the learner.
- 2. according to the method described in claim 1, it is characterized in that, the face image for the learner that the basis collects, really The mood attribute of the fixed learner, including：The image information of predeterminable area is extracted from the face image of the learner；According to the image information of the predeterminable area, the mood data of the learner is obtained；The matching degree of each mood data in the mood data and presetting database of the learner is calculated respectively；According to the matching degree of the mood data of the learner and each mood data, the mood of the learner is determined Attribute.
- 3. according to the method described in claim 2, it is characterized in that, the mood data according to the learner with it is described every The matching degree of kind mood data determines the mood attribute of the learner, including：By the mood data of learner mood classification corresponding with the maximum in the matching degree of each mood data, determine For the mood classification of the learner；When the mood classification of the learner is glad, the mood attribute for determining the learner is positive mood；When the mood classification of the learner is surprised, the mood attribute of the learner is determined to need mood；When the mood classification of the learner is sad or angry or frightened or detest, the mood of the learner is determined Attribute is negative emotions.
- 4. it according to the method described in claim 3, it is characterized in that, the mood attribute according to the learner and collects The learner studying history record, determine the content of courses for the learner, including：When the mood attribute of the learner is positive mood, is recorded according to the studying history of the learner, determine institute The learning path for stating learner is the default learning path for going deep into type；When the mood attribute of the learner is needs mood, recorded according to the studying history of the learner, determine institute The learning path for stating learner is the learning path of default case type；When the mood attribute of the learner is negative emotions, is recorded according to the studying history of the learner, determine institute The learning path for stating learner is the learning path of default type of releiving；According to the learning path of the learner, the content of courses is determined for the learner.
- 5. it is that the learner is true according to the method described in claim 3, it is characterized in that, described according to the mood attribute Instructional strategies is made, including：When the mood attribute of the learner is positive mood, the instructional strategies determined is default gradual religion Learn strategy；When the mood attribute of the learner is needs mood, the instructional strategies determined is the religion of default lively formula Learn strategy；When the mood attribute of the learner is negative emotions, the instructional strategies determined is the religion of default light formula Learn strategy.
- 6. a kind of teaching readjustment device, which is characterized in that including：First determining module, for according to the face image of learner collected, determining the mood attribute of the learner；Second determining module, for the mood attribute according to the learner and the studying history of the learner collected note Record determines the content of courses for the learner；Pushing module for the mood attribute according to the learner, determines instructional strategies, according to described for the learner Instructional strategies pushes the content of courses to the learner.
- 7. device according to claim 6, which is characterized in that first determining module includes：Extracting sub-module, for extracting the image information of predeterminable area from the face image of the learner；Submodule is obtained, for the image information according to the predeterminable area, obtains the mood data of the learner；Computational submodule, for calculating of each mood data in the mood data of the learner and presetting database respectively With degree；Determination sub-module for the mood data according to the learner and the matching degree of each mood data, is determined The mood attribute of the learner.
- 8. device according to claim 7, which is characterized in that the determination sub-module, specifically for by the learner Mood data mood classification corresponding with the maximum in the matching degree of each mood data, be determined as the feelings of the learner Thread classification；When the mood classification of the learner is glad, the mood attribute for determining the learner is positive mood；Institute When the mood classification for stating learner is surprised, the mood attribute of the learner is determined to need mood；The learner's When mood classification is sad or angry or frightened or detest, determine the mood attribute of the learner for negative emotions.
- 9. device according to claim 8, which is characterized in that second determining module, specifically in the study When the mood attribute of person is positive mood, is recorded according to the studying history of the learner, determine the study of the learner Path is the default learning path for going deep into type；When the mood attribute of the learner is needs mood, according to the study The studying history record of person, the learning path for determining the learner are the learning path of default case type；In When the mood attribute of habit person is negative emotions, is recorded according to the studying history of the learner, determine the learner Practise the learning path that path is default type of releiving；According to the learning path of the learner, institute is determined for the learner State the content of courses.
- 10. device according to claim 8, which is characterized in that the pushing module, specifically for the learner's When mood attribute is positive mood, the instructional strategies is determined as default gradual instructional strategies；In the learner Mood attribute for when needing mood, the instructional strategies to be determined as to the instructional strategies of default lively formula；In the study When the mood attribute of person is negative emotions, the instructional strategies is determined as to the instructional strategies of default light formula.
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Application publication date: 20180525 |