CN109840261A - A kind of educational data analysis system and method based on active expression type - Google Patents
A kind of educational data analysis system and method based on active expression type Download PDFInfo
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Abstract
The present invention provides a kind of educational data analysis system and method that active expression type is constructed based on active expression type, and it further includes with lower module that wherein system, which includes data acquisition module and display module: the data cleansing module arranged for demand to data；Data mining and analysis module for being excavated and being analyzed to data by machine learning or statistical analysis technique；Categorization module for being classified according to the excavation and analysis result to the ability of learner.The present invention proposes a kind of educational data analysis system and method that active expression type is constructed based on active expression type, it can integrate and actively express data, the ability for encouraging educatee that not only there is professional knowledge and application, and it promoted for knowledge, transform into the ability of innovation and innovation and creation, and provide important evidence as school work examination standard.
Description
Technical field
The present invention relates to the technical field of education and instruction, especially one kind building based on active expression type is actively expressed
The educational data analysis system of type.
Background technique
Along with the fast development of scientific and technological information technology, human society comes into big data era, and big data affects
The every aspect of human society life.Same education big data, also brings great development power and application to education sector
Prospect.Educational data concept is actively expressed in this patent proposition, and illustrates that it is applied in fields such as education and instruction, management, decisions, interior
Hold includes actively expressing educational data concept meaning, meaning, collection method and analysis application system.
Traditional student education big data, it is usually ignorant or unconscious lower collection obtains, big number in student
According to the main journal file including on interactive computer of collection, online Open Course operation log and submit content, teacher
Attendance, the operation of record, and the usually students such as card using information, monitoring record daily behavior information etc..Actively expression education number
According to being a kind of data for educating big data middle school student behavior, result from students'learning, feature be student carry out initiative thinking,
And it states and comes out, have a mind to the data being collected.Data content also wraps other than data are submitted in student's daily work, test etc.
Include student usually to the enquirement of learning Content, answer a question, discuss issues, summarize summarize gains in depth of comprehension, to education resource or
Environment query etc. content is practised, is presented mostly with language expression or text narrating mode, is compared with traditional data and is more difficult to obtain
It takes, so that present education big data seldom includes such data.
The patent of invention of Publication No. CN107563677A discloses a kind of business datum analysis system and its analysis method,
It uses the electronic equipment that can carry out recording and step counting, and voice data and step counting data are transmitted to server, by server
Music data is converted to lteral data, by lteral data and remembers step count data domain business by server or third-party server
Data combine analysis, and can export the analysis of relevant business datum analysis indexes as a result, analyzing by business datum
The combinatory analysis of index may be implemented the quantization tracking for grasping situation to business personnel's proactive and product know-how, realize
To business personnel terminal Whole Course Management.Although this method can obtain the whole lteral data of business personnel, to data
It is not screened, does not separate and actively express data.
Summary of the invention
In order to solve the above technical problems, the present invention proposes that one kind constructs active expression type based on active expression type
Educational data analysis system and method, can integrate and actively express data, encourage educatee not only there is professional knowledge
It with the ability of application, and promoted for knowledge, transform into the ability of innovation and innovation and creation, and mentioned as school work examination standard
Important evidence is supplied.
An object of the present disclosure is to provide a kind of educational data that active expression type is constructed based on active expression type point
Analysis system, including data acquisition module and display module, further include with lower module:
Data cleansing module: educational data is arranged for demand；
Data mining and analysis module: for data to be excavated and analyzed by machine learning or statistical analysis technique；
Categorization module: for being classified according to the excavation and analysis result to the ability of learner；
The data acquisition module, which is used to reasonably select, obtains the significant educational data of learner's learning process.
Preferably, the educational data includes that learner actively expresses data, passive submission data and passively acquires number
At least one of according to.
In any of the above-described scheme preferably, the learner actively expresses data and is all collected.
In any of the above-described scheme preferably, the passive submission data are checked, described check includes looking into
Weight and/or label are plagiarized.
In any of the above-described scheme preferably, the passive acquisition data take selective collection mode.
In any of the above-described scheme preferably, wish difference is collected to three classes educational data according to learner, to three
Different weights are arranged in class data, and setting rule: the learner actively expresses data weighting and is set as h, the passive submission data
Weight is set as m, the passive acquisition data weighting is set as l, wherein h > m > l > 0, to have arrived different role in data mining.
In any of the above-described scheme preferably, the educational data includes classroom or online question and answer and discussion group's number
At least one of data data are identified according to the attend class lower monitoring of, test and examination data, operation and attendance data, class
In any of the above-described scheme preferably, the data cleansing module is used to collect various systems inspection, the letter of data
It ceases incomplete and/or wrong data supplement and/or deletes, and/or standardization unitized to data.
In any of the above-described scheme preferably, the ability of the learner includes knowledge hierarchy, demand tendency and thinking
At least one of mode.
In any of the above-described scheme preferably, the classification standard includes that the memory of knowledge understands the stage, learns instruction
At least one stage in application stage, the evaluation phase of knowledge, innovation stage and innovation and creation stage.
In any of the above-described scheme preferably, the display module is used to that study to be presented in the form of statistical report or achievement
Person is to ' Current Knowledge Regarding.
In any of the above-described scheme preferably, the display module is for stressing to show individualized learning guidance, school work
At least one of early warning, Analysis on development, the acquisition of knowledge degree statistical result.
In any of the above-described scheme preferably, the result includes at least one of the following contents:
1) Instant Help and suggestion provided for learner；
2) analysis result is provided at least one of student, teacher and manager；
3) it helps teacher to understand student and learns situation；
4) suggestion for improving academic environment and improving performance is provided to manager.
Second purpose of the invention is to provide a kind of educational data that active expression type is constructed based on active expression type point
Analysis method, further comprising the steps of including collecting the data in database:
Step 1: data being arranged according to demand；
Step 2: data being excavated and analyzed by machine learning or statistical analysis technique；
Step 3: learning outcome hierarchical classification；
Step 4: learner being presented in the form of statistical report or achievement to ' Current Knowledge Regarding；
Educational data in the collection database, which refers to, obtains the significant religion of learner's learning process to reasonable selection
Educate data.
Preferably, the educational data includes that learner actively expresses data, passive submission data and passively acquires number
At least one of according to.
In any of the above-described scheme preferably, the learner actively expresses data and is all collected.
In any of the above-described scheme preferably, the passive submission data take assisted collection mode.
In any of the above-described scheme preferably, the passive acquisition data take selective collection mode.
In any of the above-described scheme preferably, wish difference is collected to three classes educational data according to learner, to three
Different weights are arranged in class data, and setting rule: the learner actively expresses data weighting and is set as h, the passive submission data
Weight is set as m, the passive acquisition data weighting is set as l, wherein h > m > l > 0, to have arrived different role in data mining.
In any of the above-described scheme preferably, the educational data includes classroom or online question and answer and discussion group's number
At least one of data data are identified according to the attend class lower monitoring of, test and examination data, operation and attendance data, class.
In any of the above-described scheme preferably, the step 1 includes that various systems are collected with the inspection of data, to information
Incomplete and/or wrong data supplement and/or deletion, and/or standardization unitized to data.
In any of the above-described scheme preferably, the ability of the learner includes knowledge hierarchy, demand tendency and thinking
At least one of mode.
In any of the above-described scheme preferably, the classification standard includes that the memory of knowledge understands the stage, learns instruction
At least one stage in application stage, the evaluation phase of knowledge, innovation stage and innovation and creation stage.
In any of the above-described scheme preferably, the result includes at least one of the following contents:
1) Instant Help and suggestion provided for learner；
2) analysis result is provided at least one of student, teacher and manager；
3) it helps teacher to understand student and learns situation；
4) suggestion for improving academic environment and improving performance is provided to manager.
The invention proposes a kind of based on active expression type construct active expression type educational data analysis system and
Method is advocated student's initiative thinking, excavation, the acquired knowledge of tissue, wisdom and potential and is formed, and actively states out,
Have a mind to the data listened, analyze or handled to other people.Learner is taught collected data wish according to learner by the present invention
It educates data and is divided into passive statement type, passive submission type and passive acquisition type three types.Learner's education is inquired into based on this
Meaningful data in data.Passive acquisition type data refer to journal file on learner's online interaction computer, usually swipe the card
Information and class are attended class students' daily behavior information such as lower monitoring record etc., have unconscious, ignorant collected data；Passively
Submission type data refer to attendance, operation, total marks of the examination and online platform test and submit information, and feature is required according to some problems
With the learning data material submitted under frame.Active statement type data include that class is attended class down, on-line off-line learner puts question to, returns
It the data informations such as answers, query, summarizing, discussing, designing, suggesting, there is initiative thinking, tissue statement, have a mind to open or received
The data of collection are compared with other types data and are more difficult to collect.
Detailed description of the invention
Fig. 1 is the educational data analysis system according to the invention that active expression type is constructed based on active expression type
The structure chart of one preferred embodiment.
Fig. 2 is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
The flow chart of one preferred embodiment.
Fig. 3 is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
The flow chart for another embodiment that autonomous expression data system is collected.
Fig. 4 is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
Student actively expresses the flow chart of another embodiment of data mining analysis.
Fig. 5 is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
From the flow chart for another embodiment for actively expressing data.
Fig. 5 A is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
Embodiment as shown in Figure 5 screening technique flow chart.
Fig. 5 B is the educational data analysis method according to the invention that active expression type is constructed based on active expression type
Embodiment as shown in Figure 5 analysis method flow chart.
Specific embodiment
The present invention is further elaborated with specific embodiment with reference to the accompanying drawing.
Embodiment one
As shown in Figure 1, a kind of educational data analysis system for constructing active expression type based on active expression type includes data
Obtain module 100, data cleansing module 110, data mining and analysis module 120, categorization module 130 and display module 140.
Data acquisition module 100 is used for the data collected from active expression.Educational data includes that learner actively expresses number
According to, it is passive submit at least one of data and passive acquisition data, learner actively expresses data and is all collected, and passively mentions
Intersection number is according to being checked, described check includes that duplicate checking and/or label are plagiarized, and the passive data that acquire take selective collection side
Formula, is collected wish difference to three classes educational data according to learner, and different weights, setting rule: institute is arranged to three classes data
It states learner and actively expresses that data weighting is set as h, the passive submission data weighting is set as m, the passive acquisition data weighting
It is set as l, wherein h > m > l > 0, to have arrived different role in data mining.Educational data includes classroom or online question and answer and begs for
It attends class at least one of lower monitoring identification data data by small set of data, test and examination data, operation and attendance data, class.
Data cleansing module 110 is used for that the inspections of data, information not to be complete and/or wrong data for collecting to various systems
It supplements and/or deletes, at and/or standardization unitized to data.
Data mining and analysis module 120 are for being excavated and being divided to data by machine learning or statistical analysis technique
Analysis；
Categorization module 130 is used to classify to the ability of learner according to the excavation and analysis result.The ability of learner
Including at least one of knowledge hierarchy, demand tendency and mode of thinking.Classification standard includes that the memory of knowledge understands the stage, learned
At least one stage in instruction application stage, the evaluation phase of knowledge, innovation stage and innovation and creation stage；Utilize class indication
Data, be based on supervision mechanism, repetition training and Machine self-learning carried out to system, in trained system, to it is above-mentioned with
The educational data collected based on learner's active expression type is excavated, and statistic of classification obtains knowledge locating for Learner behavior
Level and the ability for using knowledge.
Display module 140 is used to present learner in the form of statistical report or achievement to ' Current Knowledge Regarding, stresses to show
At least one of individualized learning guidance, academic warning, Analysis on development, the acquisition of knowledge degree statistical result.The result includes
At least one of the following contents: the 1) Instant Help and suggestion provided for learner；2) in student, teacher and manager at least
A kind of offer analysis result；3) it helps teacher to understand student and learns situation；4) providing to manager improves academic environment and improvement
The suggestion of performance.
Embodiment two
As shown in Fig. 2, a kind of educational data analysis method for constructing active expression type based on active expression type, executes step
200, the educational data in database is collected, i.e., the significant education number of learner's learning process is obtained to reasonable selection
According to.Educational data includes that learner actively expresses at least one of data, passive submission data and passive acquisition data, learner
It actively expresses data all to be collected, passive that data is submitted to take assisted collection mode, the passive data that acquire take selective receipts
Mode set.Wish difference is collected to three classes educational data according to learner, different weights, setting rule are arranged to three classes data
Then: the learner actively expresses that data weighting is set as h, the passive submission data weighting is set as m, the passive acquisition data
Weight is set as l, wherein h > m > l > 0, to have arrived different role in data mining.Educational data includes classroom or online question and answer
With discuss that small set of data, test and examination data, operation and attendance data, class at least one of lower monitoring identification data of attending class are several
According to.
Step 210 is executed, data are arranged according to demand, various systems are collected with the inspection of data, not to information
Complete and/or wrong data supplement and/or deletion, and/or standardization unitized to data.
Step 220 is executed, data are excavated and analyzed by machine learning or statistical analysis technique.
Step 230 is executed, is classified according to the excavation and analysis result to the ability of learner, the ability of learner
Including at least one of knowledge hierarchy, demand tendency and mode of thinking.Classification standard includes that the memory of knowledge understands the stage, learned
At least one stage in instruction application stage, the evaluation phase of knowledge, innovation stage and innovation and creation stage；Utilize class indication
Data, be based on supervision mechanism, repetition training and Machine self-learning carried out to system, in trained system, to it is above-mentioned with
The educational data collected based on learner's active expression type is excavated, and statistic of classification obtains knowledge locating for Learner behavior
Level and the ability for using knowledge.
Step 240 is executed, learner is presented in the form of statistical report or achievement to ' Current Knowledge Regarding, stresses to show individual character
Change at least one of learning guide, academic warning, Analysis on development, the acquisition of knowledge degree statistical result, as a result includes the following contents
At least one of: 1) Instant Help and suggestion that for learner provide；2) at least one of student, teacher and manager are provided
Analyze result；3) it helps teacher to understand student and learns situation；4) providing to manager improves academic environment and improves building for performance
View.
Embodiment three
In daily teaching or life, actively expresses data and mainly exist with voice or written form.This patent independently expresses number
According to system, voice and lteral data are collected by system platform and wechat, then by modes such as speech recognition and Text regions, obtain
It obtains and initially actively expresses data information, and be stored in system database, it is autonomous to express data gathering system flow chart, such as Fig. 3
It is shown.
Education big data analysis, the meaning of excavation are to study and construct the system model of education process.Utilize
Raw study big data is mainly used to establish learner's system model.Student actively expresses data mining, analysis process, such as Fig. 4 institute
Show, comprising:
1) database information is collected, collected from the data for actively expressing collection system storage；
2) " data cleansing ", first according to demand arranges data, is usually to routinize and standardization.
3) data are excavated and is analyzed by machine learning or statistical analysis technique.
4) learning outcome hierarchical classification.It excavates and analysis result is to learners' knowledge level, demand tendency, mode of thinking etc.
Carry out hierarchical classification.It is divided into memory, the understanding stage of knowledge；The knowledge application stage；The evaluation phase of knowledge；Innovate rank
Section；Five stages of innovation and creation stage.
5) result is presented in the form of report or achievement.It learns survivor and actively expresses the excavation of educational data model and analysis, in addition to
The information such as the existing knowledge of learner, learning motivation, previous experience, individualized content recommendation are captured, are provided immediately for learner
It helps and suggests, and can also mainly carry out analysis and provide analysis as a result, the person of encouraging learning to student, teacher and manager
Autonomous positive learning state is kept, helps teacher to understand student and learns situation, providing to manager improves academic environment and change
Into the suggestion etc. of performance.
In conclusion the personnel training to student, society, educator or education administrators want people-oriented, are with student
Center.Data are actively expressed, teacher will be fundamentally solved and only use " spoon-feed " professor " dead knowledge ", with fixation problem or examination
Template test examines student, and the existing situation of the final result as student, can just be truly realized education student-oriented model,
Cultivate educatee's creativity.The ability that data encourage educatee not only to have professional knowledge and application is actively expressed, and
And it promoted for knowledge, transform into the ability of innovation and innovation and creation, and provide important evidence as school work examination standard.
Example IV
From actively expressing data, including unasked problem or the divergent thinking data according to derived from other problems.
As shown in figure 5, execute step 500, construct from active expression database, include actively express keyword (such as: it is assorted
, how, whether, question mark etc.), meaningless word etc..Step 510 is executed, the related data in information database is obtained.Execute step
Rapid 520, garbled data removes useless data.Screening technique is as shown in Figure 5A: execute step 5201, judge in sentence whether
Including meaningless word (including modal particle: such as breathing out, breathe out, emoticon), if comprising and sentence in only meaningless word, sequence
Step 5202 and step 5204 are executed, the sentence is deleted.If comprising meaningless word and the sentence is there are also other content, then
Sequence executes step 5203 and step 5204, deletes meaningless word.If not including meaningless word, step is directly executed
5204, judge whether sentence length is greater than M character, M is preset character length threshold value.If statement length be less than etc.
In M character, then sequence executes step 5205 and step 5206, deletes the sentence.If statement length is greater than M character, then
Step 5206 is executed, whether is judged in sentence comprising determining word (such as good, yes, permissible).If comprising and sentence in only
There is determining word, then sequence executes step 5207 and step 5209, the sentence is deleted, if comprising determining word and there are also it for the sentence
His content, then sequence executes step 5208 and step 5209, marks and determines word.Word is determined if do not included, and is thened follow the steps
5209, judge whether there is specific word in sentence, specific word includes appellation word (such as: so-and-so, certain teacher, certain classmate), prompts certain
People (such as@so-and-so), mail address, telephone number, student number, identification card number, address, postcode.There is specific word in if statement, then
Sequence executes step 5210 and step 5211, and deleting related content and screening terminates.There is no specific word in if statement, then executes
Step 5211, deleting related content and screening terminates.Step 530 is executed, related data is analyzed, analysis method is as shown in Figure 5 B.
Step 5301 is executed, judges whether the sentence includes actively expressing keyword.If executing step including actively expressing keyword
Rapid 5306, confirm that the sentence is actively to express sentence.If not including and actively expressing keyword, 5302 are thened follow the steps, judgement
Whether the sentence and previous sentence are relevant, and (whether emphasis word is same or similar, 70%) degree of association is more than.If with previous
Sentence is not associated with, and thens follow the steps 5306, confirms that the sentence is actively to express sentence.If relevant with previous sentence,
Execute step 5303, judge the sentence and lower N sentence it is whether relevant (whether emphasis word same or similar, the degree of association surpass
It crosses 70%), N is amount threshold.If not being associated with lower N sentence and thening follow the steps 5304, which enters library to be selected.Such as
Fruit is relevant with lower N sentence to then follow the steps 5305, judge the sentence whether include divergent thinking word.If comprising
The word of divergent thinking, thens follow the steps 5306, confirms that the sentence is actively to express sentence.If not including divergent thinking
Word, then follow the steps 5307, abandon the sentence.Step 540 is executed, postsearch screening is carried out to data.Step 550 is executed,
Judge whether to require supplementation with the content from active expression database.It is added to if necessary from the interior of active expression database
Hold, then re-execute the steps 500, supplements from active expression database.If do not required supplementation with from active expression database
Content, then re-execute the steps 560, judge whether screening finish.It is finished if do not screened, re-execute the steps 510,
Obtain the related data in information database.If screening is completed, 570 are thened follow the steps, saves data to active expression letter certainly
Cease database.
For a better understanding of the present invention, the above combination specific embodiments of the present invention are described in detail, but are not
Limitation of the present invention.Any simple modification made to the above embodiment according to the technical essence of the invention, still belongs to
In the range of technical solution of the present invention.In this specification the highlights of each of the examples are it is different from other embodiments it
Locate, the same or similar part cross-reference between each embodiment.For system embodiments, due to itself and method
Embodiment corresponds to substantially, so being described relatively simple, the relevent part can refer to the partial explaination of embodiments of method.
Claims (10)
1. a kind of educational data analysis system for constructing active expression type based on active expression type, including data acquisition module
And display module, which is characterized in that further include with lower module:
Data cleansing module: educational data is arranged for demand；
Data mining and analysis module: for data to be excavated and analyzed by machine learning or statistical analysis technique；
Categorization module: for being classified according to the excavation and analysis result to the ability of learner；
The data acquisition module, which is used to reasonably select, obtains the significant educational data of learner's learning process.
2. the educational data analysis system of active expression type is constructed based on active expression type as described in claim 1,
Be characterized in that: the educational data includes that learner actively expresses in data, passive submission data and passive acquisition data at least
It is a kind of.
3. the educational data analysis system of active expression type is constructed based on active expression type as claimed in claim 2,
Be characterized in that: the learner actively expresses data and is all collected.
4. the educational data analysis system of active expression type is constructed based on active expression type as claimed in claim 2,
Be characterized in that: the passive submission data are checked that described check includes that duplicate checking and/or label are plagiarized.
5. the educational data analysis system of active expression type is constructed based on active expression type as claimed in claim 2,
Be characterized in that: the passive acquisition data take selective collection mode.
6. the educational data analysis system of active expression type is constructed based on active expression type as claimed in claim 2,
It is characterized in that: wish difference is collected to three classes educational data according to learner, different weights, setting rule are arranged to three classes data
Then: the learner actively expresses that data weighting is set as h, the passive submission data weighting is set as m, the passive acquisition data
Weight is set as l, wherein h > m > l > 0, to have arrived different role in data mining.
7. the educational data analysis system of active expression type is constructed based on active expression type as claimed in claim 2,
Be characterized in that: the educational data includes classroom or online question and answer and discussion small set of data, test and examination data, operation and examines
Diligent data, class are attended class at least one of lower monitoring identification data data.
8. the educational data analysis system of active expression type is constructed based on active expression type as described in claim 1,
Be characterized in that: the inspection of data, information is not complete and/or wrong data is mended for collecting to various systems for the data cleansing module
It fills and/or deletes, and/or standardization unitized to data.
9. the educational data analysis system of active expression type is constructed based on active expression type as described in claim 1,
Be characterized in that: the ability of the learner includes at least one of knowledge hierarchy, demand tendency and mode of thinking.
10. a kind of educational data analysis method that active expression type is constructed based on active expression type, including collect database
In educational data, which is characterized in that it is further comprising the steps of:
Step 1: the educational data being arranged according to demand；
Step 2: data being excavated and analyzed by machine learning or statistical analysis technique；
Step 3: being classified according to the excavation and analysis result to the ability of learner；
Step 4: learner being presented in the form of statistical report or achievement to ' Current Knowledge Regarding；
Educational data in the collection database, which refers to, obtains the significant religion of learner's learning process to reasonable selection
Educate data.
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| US20110065082A1 (en) * | 2009-09-17 | 2011-03-17 | Michael Gal | Device,system, and method of educational content generation |
| CN104657567A (en) * | 2013-11-15 | 2015-05-27 | 镇江润欣科技信息有限公司 | Student learning capacity evaluating method and system |
| CN106203635A (en) * | 2016-06-29 | 2016-12-07 | 北京师范大学 | A kind of on-line study behavior puts into data collection and transmission and method |
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