CN108984516A - A kind of online course content assessment method and system based on barrage comment cloud data - Google Patents
A kind of online course content assessment method and system based on barrage comment cloud data Download PDFInfo
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Abstract
The invention discloses a kind of online course content assessment methods and system based on barrage comment cloud data, 1) method is comprising steps of be sent to barrage cloud data system by student terminal for the barrage comment data of learner；2) barrage cloud data system receives, stores and verify the barrage comment data, and qualified barrage comment data is sent to screen terminal；3) screen terminal receives and shows barrage comment data, and the big data characteristic value corresponding to it is back to barrage cloud data system；4) data system reception and the history big data characteristic value of barrage comment is handled, and result is pushed into teacher's terminal；5) teacher's terminal receive the processing analysis as a result, judge course content with the presence or absence of extremely, and with visual pattern to the unusual part of course content to teacher with information alert.Present invention realization in real time, overall process is identified and is improved to online course content, promotes the authenticity and accuracy of online course content assessment.
Description
Technical field
The present invention relates to online course content evaluation technology field more particularly to it is a kind of based on barrage comment cloud data
Line course content assessment method and system.
Background technique
Online course content is tested and assessed there are three types of existing mainstream technologys: expert simulates assessment, mechanism checks oneself assessment and
Habit person investigates assessment.It is mainly that online course first stage of construction (not putting into formal teaching or study) utilizes expert that expert, which simulates assessment,
Come simulate pupilage experience with perception online course content, to do bid value judge to its quality.Mechanism checks oneself assessment
Refer to that online course Contents Construction initial stage (not putting into formal teaching or study) training organization, individual or producer is made by oneself using content
Scale is evaluated and is checked on to the rough property that online course content carries out, and its object is to judge which course meets network courses base
This requirement or specification.It is (the formal teaching of investment after completing a certain or certain serial online course to learner that learner, which investigates assessment,
Or study) overall perception or satisfaction investigated, feed back to obtain the quality information of online course content from user perspective.
However, the acquisition or generation of above-mentioned online course content evaluation technology data information are formally learned in online course content
Before habit (expert simulates assessment, mechanism checks oneself assessment), or occur after online course content Formal Learning (learner's investigation), still
Cannot the online course perception of content information data to learner's learning process be acquired, it is difficult to realize to online course content
Overall process, normalization assessment and the monitoring of quality.In addition, current evaluation technology evaluation granularity is bigger, mostly with entire
Course, unit or chapters and sections are assessment unit, and evaluation and its result are lack of pertinence, can not be to online course content microcosmic point
Design problem carries out identification in time and diagnosis, loses the chance of discovery course content design problem and error correction in time, is unfavorable for
The optimization of online course content quality and improvement.In addition, traditional evaluation technology can not also be continuously accurate, authentic and valid recording learning
To the evaluation data of online course content quality in person's learning process, it is difficult to carry out based on online under learner's perception big data
Course content quality analysis and diagnosis.
Summary of the invention
In view of above-mentioned deficiencies of the prior art, the purpose of the present invention is to provide it is a kind of based on barrage comment cloud data
Line course content assessment method and system, it is intended to solve existing assessment method to online course content assessment be lack of pertinence with
And the problem of being difficult to realize overall process and normalization monitoring.
Realizing the specific technical solution of the object of the invention is:
It is a kind of based on barrage comment cloud data online course content assessment method, this method comprising the following specific steps
A. the barrage comment data of learner is transmitted by student terminal and gives barrage cloud data system；
B. barrage cloud data system receives, stores and verify above-mentioned barrage comment data, then will the qualified barrage comment of verification
Data are directly transmitted to screen terminal；
C. screen terminal receives and shows barrage comment data, and big data characteristic value corresponding to the barrage comment data is returned
It is back to barrage cloud data system；
D. barrage cloud data system receives and processes the history big data characteristic value of barrage comment, and processing analysis result is pushed away
It send to teacher's terminal；
E. teacher's terminal receives processing analysis as a result, according to the distribution situation of mood label for labelling point, judges course content
Part or certain segment with the presence or absence of abnormal, and with visual pattern to the unusual part of course content to teacher with information alert.
The online course content assessment method based on barrage comment cloud data, wherein student's bullet described in step A
Curtain comment data is related to two classes: one kind is text comments data, including text comments content, text comments quantity and its relative to
The timing node of course content；Another kind of is mood label data, including mood label classification, mood number of labels and its opposite
In course content timing node.Mood label described here is the emoticon for referring to expression student's learning experience.Wherein,
The setting of mood label is related to the technological transformation to traditional barrage emoticon.Specifically, the characteristic according to on-line study, this
Invention delete to traditional barrage emoticon and handled with classification, is remained and is thumbed up, query and spits slot three classes study expression
Parameter, we are referred to as to be named as study mood label.It is arranged in addition, also sending attribute to the barrage of student terminal, is limited
Accepted opinion opinion content just normally must can effectively be sent simultaneously comprising text and mood label.
The online course content assessment method based on barrage comment cloud data, wherein verification described in step B
Refer to and logical process is carried out to the barrage comment data, its object is to verify the integrality of data and legitimacy.
The online course content assessment method based on barrage comment cloud data, wherein barrage described in step C is commented
By corresponding big data characteristic value include: text comments quantity, every text comments relative to course content timing node,
Mood label classification, mood number of labels, course content timing node corresponding to each mood label etc..
The online course content assessment method based on barrage comment cloud data, wherein processing described in step D
Based on the barrage that analysis specifically refers to receive comments on big data, by mathematical statistics method statistic and analysis barrage comment
History big data obtains the course content quality analysis results that cloud data are commented on based on barrage.
The described online course content assessment method based on barrage comment cloud data, wherein mood described in step E
Label for labelling point refer to be pushed to teacher side visual information prompt in, for substitute and identify mood label classification and its
" point " of the different colours of meaning.Wherein, green mark point representative thumbs up, and orange mark point represents query, red mark
Note point, which represents, spits slot.It should be strongly noted that each mark point is interactivity in Visual Chart, and it is corresponding
Online course content be associated with barrage text reviews content.When clicking certain point, can present automatically and play with it is corresponding
Online course content and its barrage text comments.
A kind of online course content evaluation system based on barrage comment cloud data, the system include:
Student terminal sending module, for the barrage comment data of student to be sent to barrage cloud data system；
The reception of barrage cloud data system, storage and correction verification module, for receiving, storing and verify above-mentioned barrage comment data；
Barrage cloud data system sending module, for the qualified barrage comment data packing of verification to be distributed to screen terminal；
Screen terminal receives and display module, for receiving and showing that the barrage that barrage cloud data system sends over comments on number
According to；
Screen terminal return module, for big data characteristic value corresponding to barrage comment data to be back to barrage cloud data system
System；
The processing of barrage cloud data system and pushing module, for extracting big data characteristic value corresponding to barrage comment data, and
It is for statistical analysis, processing analysis result is then pushed into teacher's terminal；
Teacher's terminal receives and cue module, for receiving the history big data analysis of barrage comment as a result, and by mood label
The distribution situation for marking point, in visual form to teacher with information alert.
The online course content evaluation system based on barrage comment cloud data, wherein in student terminal sending module,
The barrage comment data of the student is related to text comments and mood comments on two class data, including text comments content, text are commented
By quantity, every text comments relative to the timing node of course content, mood label classification, mood number of labels, each feelings
Thread label is relative to course content timing node.Student terminal sending module also relates to the emoticon and hair to traditional barrage
Send the technological transformation of attribute.Traditional barrage expression delete and has been handled with classification, has been remained and is thumbed up, query and spits slot three classes
Bao Qing, i.e. study mood label.It is reset in addition, student terminal also sends attribute to barrage, setting comment content is necessary
It just can normally be sent comprising text with two category information of mood label simultaneously.
The online course content evaluation system based on barrage comment cloud data, wherein the reception of barrage cloud data system,
With correction verification module, verification refers to barrage comment data progress logical process for storage, verifies the integrality and conjunction of data
Method.
The online course content evaluation system based on barrage comment cloud data, wherein described in screen return module
Big data characteristic value include: text comments quantity, course content timing node, mood label corresponding to all text comments
Classification, mood number of labels, course content timing node corresponding to be in a bad mood label.
The online course content evaluation system based on barrage comment cloud data, wherein barrage cloud data system processing
With participated in pushing module statistics barrage comment history big data mainly include text comments quantity, all text comments institute it is right
When the course content timing node answered, mood label classification, mood number of labels, course content corresponding to be in a bad mood label
Intermediate node.
The online course content evaluation system based on barrage comment cloud data, wherein teacher's terminal receives and prompt
Mood label for labelling point described in module refers in the visual information prompt for being pushed to teacher side, for substituting and identifying
" point " of the different colours of mood label classification and its meaning.Each point is interactivity in visual information prompt,
It is associated with corresponding online course content and barrage text comments content.
It is new to be added barrage cloud data system the utility model has the advantages that the present invention is by traditional barrage Commentary Systems framework, and
Technological transformation has been carried out to traditional barrage emoticon and transmission attribute, it is online for identifying to be specially provided with study mood label
Course content information.Rely on the abnormal mark of barrage cloud data technique of the invention and the correcting process of barrage comment data sample
Framework and its operating mechanism, realization in real time, overall process are identified and are improved to online course content, both can be with
It focuses on the course content information of more small particle size, promotes the optimization of online course content design and quality, can also realize pair
Online course content carries out normalization diagnosis, promotes the authenticity and accuracy of online course content assessment.
Detailed description of the invention
Fig. 1 is embodiment of the present invention method flow chart；
Fig. 2 is that student terminal of the present invention comments on surface chart；
Fig. 3 is teacher's end message of the present invention prompt figure；
Fig. 4 is present system example structure block diagram.
Specific embodiment
The present invention provides a kind of online course content assessment method based on barrage comment cloud data, to make mesh of the invention
, technical solution and its effect be more clear, be clear, the present invention is described in more detail below.It should be understood that herein
Described specific implementation is only used to explain the present invention, is not intended to limit the present invention.
Refering to fig. 1, Fig. 1 is that a kind of online course content assessment method for commenting on cloud data based on barrage of the present invention is preferably real
Apply the flow chart of example comprising step:
S001. the barrage comment data of learner is transmitted by student terminal and gives barrage cloud data system；
S002. barrage cloud data system receives, stores and verify above-mentioned barrage comment data, then comments the qualified barrage of verification
It directly transmits by data to screen terminal；
S003. screen terminal receives and shows barrage comment data, and by big data feature corresponding to the barrage comment data
Value is back to barrage cloud data system；
S004. barrage cloud data system receives and processes the history big data characteristic value of barrage comment, and processing analysis is tied
Fruit pushes to teacher's terminal；
S005. teacher's terminal receives processing analysis as a result, according to the distribution situation of mood label for labelling point, judges course content
Certain part or certain segment are mentioned with the presence or absence of exception with unusual part of the visual pattern to course content to teacher with information
Show.
The present invention is by being newly added barrage cloud data system, and to traditional bullet in traditional barrage Commentary Systems framework
Curtain emoticon and transmission attribute have carried out technological transformation, are specially provided with mood label for identifying online course content letter
Breath.Rely on the abnormal mark of barrage cloud big data technology of the invention and the correcting process framework of barrage comment data sample and its
Operating mechanism, realization in real time, overall process online course content is identified and is improved, can both focus on more
The course content information of small particle size promotes the optimization of online course content design and quality, can also realize to online course
Content carries out normalization diagnosis, promotes the authenticity and accuracy of online course content assessment.
In the step S001, when carrying out online course learning, each student for participating in assessment can pass through oneself
Student terminal to barrage cloud data system send barrage comment data.Specifically, the barrage comment data of the student is related to
Two class of text comments data and mood comment data, including text comments content, text comments quantity, every text comments are opposite
In the timing node of course content, mood label classification, mood number of labels and each mood label relative to course content
Timing node.A kind of online course content assessment method student terminal based on barrage comment cloud data of the present invention comments on interface,
As shown in Figure 2.For example, when learning online course content, each student can be by the student terminal of oneself by text comments
Content, every text comments are relative to the timing node of course content, mood label classification, mood number of labels, each mood
Label is sent to barrage cloud data system relative to the timing node of course content.Wherein, the mood label classification can be with
To thumb up, query or spit slot any one.For example, student feels certain a part of class during an online course learning
Journey content is not allowed readily understood very much, and at this moment student can illustrate that this part course content is not allowed by student terminal in text comments
Intelligible place, and the contents of the section is identified with query mood label.At the same time, learning terminal can automatic collection
The barrage comment data of student, and send it to barrage cloud data system.
In the step S002, after barrage cloud data system receives and stores the barrage comment data that all students send,
The integrality of the barrage comment data is verified with legitimacy, the qualified barrage comment data of verification is then packaged hair
It send to screen terminal.The integrality and legitimacy verifies of above-mentioned barrage comment data mainly check whether all kinds of comment datas are complete
It is whole, data are complete and data-link is clear.For example, due to learning terminal shutdown, falling net, network in course content learning process
Barrage comment data caused by the abnormal environments such as delay is abnormal, and at this moment barrage cloud data system will be from data target missing, data
The indexs such as chain self checking are verified, to ensure the integrality and legitimacy of barrage comment data.
In the step S003, screen terminal receives and shows above-mentioned barrage comment data, and by the barrage comment data
Corresponding big data characteristic value is back to barrage cloud data system.Specifically, the big data characteristic value of return includes: that text is commented
By course content timing node corresponding to quantity, all text comments, mood label classification, mood number of labels, own
Course content timing node corresponding to mood label.
In the step S004, barrage cloud data system receives and processes the history big data characteristic value of barrage comment,
And processing analysis result is pushed into teacher's terminal.The history big data characteristic value specifically handled mainly includes text comments number
Course content timing node, mood label classification, mood number of labels corresponding to amount, all text comments, are in a bad mood
Course content timing node corresponding to label.
The step S004 further includes step process analytical procedure: based on the barrage comment big data received, being borrowed
Mathematical statistics method statistic and analysis barrage comment history big data are helped, the course content matter for commenting on cloud data based on barrage is obtained
Amount analysis result.This is because student terminal can acquire each student in each online course learning by student terminal to class
The evaluation information of journey content, the evaluation information are the barrage comment data in the present invention, then will be in each student's text comments
Timing node relative to course content of appearance, text comments quantity, all text comments, mood label classification, mood number of tags
Amount, be in a bad mood label are sent in barrage comment cloud data system relative to the barrages comment information such as course content timing node
And it stores.By the data accumulation of daily online course content learning process, every can be formed in barrage cloud data system
The historical review data of online course.Barrage cloud data system of the invention, which realizes, learnt normalization online course content
Student's comment data in journey carries out consecutive quantized acquisition, and can record student in detail truly and effectively to the barrage of every subject
Comment information data form student and comment on big data to the history barrage of every subject.Further, the present invention can be united using mathematics
Meter method carries out statistics calculating to history barrage comment big data, to obtain the text comments quantity of every subject, all texts
Class corresponding to course content timing node, mood label classification, mood number of labels, be in a bad mood label corresponding to commenting on
The big datas characteristic values such as journey content time node.Barrage cloud data system of the invention is commented on by the history barrage to every subject
Data are for statistical analysis, consequently facilitating teacher monitors course content state, optimization and improvement online course content design, improve
Course content learning efficiency.
The present invention will be directed to mood number of labels, mood label classification and its corresponding course content timing node below
It is illustrated.For example, calculating the mood number of tags of every subject according to the history barrage comment data of every subject of formation
Course content timing node corresponding to amount, mood label classification and be in a bad mood label, can be obtained every subject content
Mood label distribution situation on each timing node.It, can be generally by the classification and distributed number situation of mood label
Judge the content quality design conditions of course content a part or a certain segment.If be distributed in certain part course content
To thumb up mood label relatively more and concentrate, illustrate that student is relatively good to the learning experience of the part course content, course content
Design is good；If the query mood label being distributed in certain part course content is relatively more and concentrates, illustrate student to the portion
Point course content less understands that course content design comparison is advanced, exceeds student's cognitive development area；If in certain part course
Be distributed in appearance to spit slot mood label relatively more and concentrate, illustrate that student compares slot to the learning experience of the part course content
Cake, there are serious problems for course content design, teacher should be caused to pay special attention to.At this moment teacher's terminal can issue course teacher pre-
Alert prompt, so that teacher improves in time and optimizes online course content, to improve course content learning efficiency.
In the step S005, teacher's terminal receives the barrage comment big data processing analysis of barrage cloud data system push
As a result, identifying on course content timing node according to mood label and distribution situation, course content part or certain piece are judged
Section is with the presence or absence of abnormal.When judging course content exception, to abnormal course content part to teacher with information alert.I.e.
When the query mood label of certain part course content distribution is relatively more and concentrates, teacher side will prompt teacher: student is to this
Part course content less understands that course content design may be relatively more advanced；Slot mood is spat when the distribution of certain part course content
Label is relatively more and concentrates, and teacher's terminal will prompt teacher: student compares cakes with moulded designs to the learning experience of the part course content,
Course content is designed there are serious problems, should cause to pay special attention to.Mood label ratio is thumbed up when the distribution of certain part course content
More and concentration, teacher's terminal will prompt teacher: student is relatively good to the learning experience of the part course content, course content
Design is good.A kind of online course content assessment method teacher's end message based on barrage comment cloud data of the present invention prompts figure
Example, as shown in Figure 3.
The present invention is illustrated information alert below in conjunction with Fig. 3.For example, when teacher's terminal receives barrage cloud number
According to system push barrage comment big data processing analysis the result is that: certain a part of course content student's spits slot mood label ratio
More and concentration, the corresponding red mark point of this partial content just compares more and concentrates in the information alert of teacher side；Work as religion
Teacher's terminal receive barrage cloud data system push barrage comment big data processing analysis the result is that: certain a part of course content
Raw query mood label is relatively more and concentrates, and the corresponding orange mark point of this partial content is just in the information alert of teacher side
Compare more and concentrates；When teacher's terminal receive barrage cloud data system push barrage comment big data processing analysis the result is that:
Certain a part of course content student to thumb up mood label relatively more and concentrate, this partial content in the information alert of teacher side
Corresponding green mark point is just relatively more and concentrates.In the information alert of teacher's terminal, main mark point generation in different colors
The different mood label substance of table and its meaning.The mark point representative of green thumbs up, and orange mark point represents query, red
Mark point, which represents, spits slot.
Based on the above method, the present invention also provides a kind of online course content evaluation system based on barrage cloud data is preferable
The structural block diagram of embodiment, as shown in figure 4, comprising:
Student terminal sending module 100, for the barrage comment data of student to be sent to barrage cloud data system；
The reception of barrage cloud data system, storage and correction verification module 200, for receiving, storing and verify above-mentioned barrage comment data；
Barrage cloud data system sending module 300, for the qualified barrage comment data packing of verification to be distributed to screen terminal；
Screen terminal receives the barrage comment sended over for receiving and showing barrage cloud data system with display module 400
Data；
Screen terminal return module 500, for big data characteristic value corresponding to barrage comment data to be back to barrage cloud number
According to system；
The processing of barrage cloud data system and pushing module 600, for extracting big data characteristic value corresponding to barrage comment data,
And it is for statistical analysis, processing analysis result is then pushed into teacher's terminal；
Teacher's terminal receive with cue module 700, for receiving the history big data analysis of barrage comment as a result, and by mood mark
The distribution situation of label mark point, in visual form to teacher with information alert.
In the student terminal sending module 100, the barrage comment data of the student specifically include text comments content,
Text comments quantity, every text comments relative to the timing node of course content, mood label classification, mood number of labels,
Each mood label is relative to course content timing node.In addition, student terminal sending module is also related to traditional barrage
Emoticon and the technological transformation for sending attribute.
The barrage cloud data system receives, storage is with correction verification module 200, and verification refers to the barrage comment data
Logical process is carried out, its object is to verify the integrality of barrage comment data and legitimacy.
In the screen return module 500, the big data characteristic value includes: that text comments quantity, all texts are commented
By course corresponding to corresponding course content timing node, mood label classification, mood number of labels, be in a bad mood label
Content time node.
The barrage cloud data system processing and the barrage comment history big data master in pushing module 600, participating in statistics
It will be including course content timing node, mood label classification, mood label corresponding to text comments quantity, all text comments
Course content timing node corresponding to quantity, be in a bad mood label.
Teacher's terminal is received with cue module 700, and the mood label for labelling point, which refers to, is being pushed to teacher
In the visual information prompt at end, " point " of the different colours for substituting and identifying mood label classification and its meaning.Wherein,
The mark point representative of green thumbs up, and orange mark point represents query, and slot is spat in red mark point representative.In addition, each point
It is all interactivity, with corresponding online course content and text comments information association.
It is new to be added barrage cloud data system in conclusion the present invention is by traditional barrage Commentary Systems framework, and
Technological transformation has been carried out to traditional barrage emoticon and transmission attribute, it is online for identifying to be specially provided with study mood label
Course content information.Rely on the abnormal mark of barrage cloud data technique of the invention and the correcting process of barrage comment data sample
Framework and its operating mechanism, realization in real time, overall process are identified and are improved to online course content, both can be with
It focuses on the course content information of more small particle size, promotes the optimization of online course content design and quality, can also realize pair
Online course content carries out normalization diagnosis, promotes the authenticity and accuracy of online course content assessment.
It should be understood that application of the present invention is not limited to above-mentioned case, it for those of ordinary skills, can root
It is improved or converted according to above description, all these modifications and variations all should belong to the protection model of appended claims of the present invention
It encloses.
Claims (14)
1. a kind of online course content assessment method based on barrage comment cloud data, which is characterized in that this method includes following
Specific steps:
A. the barrage comment data of learner is transmitted by student terminal and gives barrage cloud data system；
B. barrage cloud data system receives, stores and verify the barrage comment data, then will the qualified barrage comment of verification
Data are directly transmitted to screen terminal；
C. screen terminal receives and shows barrage comment data, and big data characteristic value corresponding to the barrage comment data is returned
It is back to barrage cloud data system；
D. barrage cloud data system receives and processes the history big data characteristic value of barrage comment, and processing analysis result is pushed away
It send to teacher's terminal；
E. teacher's terminal receives processing analysis as a result, according to the distribution situation of mood label for labelling point, judges course content
Part or certain segment with the presence or absence of abnormal, and with visual pattern to the unusual part of course content to teacher with information alert.
2. the online course content assessment method according to claim 1 based on barrage comment cloud data, which is characterized in that
In step A, the barrage comment data of the learner is two classes: one kind is text comments data, including text comments content,
Text comments quantity and its timing node relative to course content；Another kind of is mood label data, including mood tag class
Not, mood number of labels and its relative to course content timing node；Limiting comment content must include text and mood simultaneously
Label normally can effectively be sent.
3. the online course content assessment method according to claim 2 based on barrage comment cloud data, which is characterized in that
The mood label refer to expression student's learning experience emoticon, including thumb up, query and spit slot three classes study expression
Parameter.
4. the online course content assessment method according to claim 1 based on barrage comment cloud data, which is characterized in that
In step B, the verification, which refers to, carries out logical process to the barrage comment data, and its object is to verify the integrality of data
And legitimacy.
5. the online course content assessment method according to claim 1 based on barrage comment cloud data, which is characterized in that
In step C, big data characteristic value corresponding to the barrage comment data includes: text comments quantity, every text comments
Relative in course corresponding to the timing node of course content, mood label classification, mood number of labels, each mood label
Hold timing node.
6. the online course content assessment method according to claim 1 based on barrage comment cloud data, which is characterized in that
In step D, the processing analysis specifically refers to unite based on the barrage comment big data received by mathematical statistics method
Meter comments on history big data with analysis barrage, obtains the course content quality analysis results that cloud data are commented on based on barrage.
7. the online course content assessment method according to claim 1 based on barrage comment cloud data, which is characterized in that
In step E, the mood label for labelling point refers in the visual information prompt for being pushed to teacher side, for substituting and knowing
" point " of the different colours of sorrow of separation thread label classification and its meaning；Wherein, green mark point representative thumbs up, orange mark point
Query is represented, slot is spat in red mark point representative；Each mark point is interactivity in Visual Chart, and corresponding
Online course content be associated with barrage text reviews content；When clicking certain point, can present automatically and play with it is corresponding
Online course content and its barrage text comments.
8. a kind of system for implementing claim 1 the method, which is characterized in that the system includes:
Student terminal sending module, for the barrage comment data of student to be sent to barrage cloud data system；
The reception of barrage cloud data system, storage and correction verification module, for receiving, storing and verify above-mentioned barrage comment data；
Barrage cloud data system sending module, for the qualified barrage comment data packing of verification to be distributed to screen terminal；
Screen terminal receives and display module, for receiving and showing that the barrage that barrage cloud data system sends over comments on number
According to；
Screen terminal return module, for big data characteristic value corresponding to barrage comment data to be back to barrage cloud data system
System；
The processing of barrage cloud data system and pushing module, for extracting big data characteristic value corresponding to barrage comment data, and
It is for statistical analysis, processing analysis result is then pushed into teacher's terminal；
Teacher's terminal receives and cue module, for receiving the history big data analysis of barrage comment as a result, and by mood label
The distribution situation for marking point, in visual form to teacher with information alert.
9. system according to claim 8, which is characterized in that in student terminal sending module, the bullet of the learner
Curtain comment data is two classes: one kind is text comments data, including text comments content, text comments quantity and its relative to class
The timing node of journey content；Another kind of is mood label data, including mood label classification, mood number of labels and its relative to
Course content timing node；Limiting comment content must include simultaneously text and mood label, normally can effectively send.
10. system according to claim 9, which is characterized in that the mood label refers to expression student's learning experience
Emoticon, including thumb up, query and spit slot three classes study expression parameter.
11. system according to claim 8, which is characterized in that the reception of barrage cloud data system, storage and correction verification module
In, the verification, which refers to, carries out logical process to the barrage comment data, verifies the integrality and legitimacy of data.
12. system according to claim 8, which is characterized in that in screen return module, the big data characteristic value packet
It includes: course content timing node corresponding to text comments quantity, all text comments, mood label classification, mood number of tags
Course content timing node corresponding to amount, be in a bad mood label.
13. system according to claim 8, which is characterized in that the processing of barrage cloud data system is participated in pushing module
Segmentum intercalaris when the barrage comment history big data of statistics includes text comments quantity, course content corresponding to all text comments
Point, mood label classification, mood number of labels, course content timing node corresponding to be in a bad mood label.
14. system according to claim 8, which is characterized in that in the reception of teacher's terminal and cue module, the mood
Label for labelling point refer to be pushed to teacher side visual information prompt in, for substitute and identify mood label classification and its
" point " of the different colours of meaning；Each point is interactivity in visual information prompt, with corresponding online class
Journey content is associated with barrage text comments content.
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