CN109545018A - Information processing method and device - Google Patents
Information processing method and device Download PDFInfo
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- CN109545018A CN109545018A CN201811183615.7A CN201811183615A CN109545018A CN 109545018 A CN109545018 A CN 109545018A CN 201811183615 A CN201811183615 A CN 201811183615A CN 109545018 A CN109545018 A CN 109545018A
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- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
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Abstract
This application discloses a kind of information processing method and devices.This method includes obtaining the test answers of per pass examination question and the model answer of per pass examination question in first user's paper, wherein the model answer includes default score content and the corresponding default score score value of the default score content；The test answers of examination question described in per pass and the model answer of the examination question are compared, the correct content and the corresponding score value of the correct content in the test answers of examination question described in per pass are obtained；Label corresponding with the correct content in the test answers of examination question described in per pass is searched in default tag library；The corresponding score value of correct content and label in the test answers of the examination question according to per pass generate the user's evaluation information of the first user paper.It cannot achieve present application addresses the paper evaluation method using the association of knowledge of textbook point and the classification of topic type and the technical issues of fining is screened with diagnosis carried out to paper test result.
Description
Technical field
This application involves computer information processing fields, in particular to a kind of information processing method and device.
Background technique
Global education evaluation experienced examination period, test period, description period, judgement period, result approval period and
Six periods of overall merit period, and China still only pays attention to paper at present substantially also in the test period of second stage
Test score, and the analysis result comprehensive for paper, student and teacher etc. can not be obtained.
The paper test interpretation of result method for mostly using unification in the related technology, by student fill in paper answer and with
Model answer compares to realize the statistics of score value, and to examination question be subject to simply classification (such as gap-filling questions, using topic, calculation question
Deng) and be associated with knowledge of textbook point (such as classic poetry recite, addition, multiplication), to realize the criticism to teaching affairs.
But curricular standard requirement can not effectively be docked using the examination result information processing method of " knowledge of textbook point+topic type "
" objective ", single to paper answer, spot style score value statistics also can not effectively realize student's school work situation and religion
The fining of teacher's teaching affairs is screened and diagnosis.
It cannot achieve for the paper evaluation method for using the association of knowledge of textbook point to classify with topic type in the related technology to examination
Volume test result carries out the problem of fining is screened with diagnosis, and currently no effective solution has been proposed.
Summary of the invention
The main purpose of the application is to provide a kind of information processing method and device, to solve to use class in the related technology
The paper evaluation method that this Knowledge Relation is classified with topic type, which cannot achieve, to carry out fining examination to paper test result and examines
Disconnected problem.
To achieve the goals above, according to the one aspect of the application, a kind of information processing method and device are provided.
Information processing method according to the application includes: the test answers for obtaining per pass examination question in first user's paper, with
And the model answer of per pass examination question, wherein model answer includes that default score content and default score content are corresponding default
Score score value；The test answers of per pass examination question and the model answer of the examination question are compared, the test for obtaining per pass examination question is answered
Correct content and the corresponding score value of correct content in case；It is searched in the test answers with per pass examination question in default tag library
The corresponding label of correct content；According to the corresponding score value of correct content and label in the test answers of per pass examination question, generate
The user's evaluation information of first user's paper.
Further, according to the corresponding score value of correct content and label in the test answers of per pass examination question, first is generated
The evaluation information of user's paper includes: according to the classification for presetting classifying rules acquisition label；To belonging in same category of label
Each of the corresponding score value of correct content carry out adduction, obtain the total score of the category.
It further, further include the user's evaluation information for obtaining each first user paper in default grouping；It generates default
The grouping evaluation information of grouping.
It further, further include the user's evaluation information middle finger calibration label for obtaining each first user paper in default grouping
Corresponding total score；Corresponding total score is signed according to the calibration of the user's evaluation information middle finger of each first user paper to be calculated
The user tag scoring rate of the specified label of the packet label average rate and each first user paper of specified label；Judgement
User tag scoring rate in default grouping with the presence or absence of specified label is tried lower than the first user of packet label average rate
Volume；If the user tag scoring rate that there is specified label in default grouping is lower than the first user examination of average label scoring rate
The user tag scoring rate of specified label is then lower than the evaluation information of first user's paper of packet label average rate by volume
It is sent to second user equipment.
Further, refer to that corresponding total score meter is signed in calibration in the user's evaluation information according to each first user paper
Calculate the user tag score of the specified label of the packet label average rate and each first user paper that obtain specified label
After rate further include: successively calculate the difference between each user tag scoring rate and packet label average rate；It successively will be poor
Value is matched with default attention rate matching condition to obtain the attention rate of each first user paper middle finger calibration label.
Further, according to the corresponding score value of correct content and label in the test answers of per pass examination question, first is generated
The evaluation information of user's paper includes: to the corresponding score value of correct content and label in paper in the test answers of per pass examination question
Carry out the characteristic information collection that statistics obtains paper；Judge to concentrate each spy with the presence or absence of with characteristic information in default prompt information library
Reference ceases matched prompt information；If existing in default prompt information library and concentrating each characteristic information equal with characteristic information
The prompt information matched then will concentrate the matched prompt information of each characteristic information to make with characteristic information in default prompt information library
For user's evaluation information.
To achieve the goals above, according to the another aspect of the application, a kind of information processing unit is provided.
Information processing unit according to the application includes: information acquisition unit, for obtaining per pass in first user's paper
The test answers of examination question and the model answer of per pass examination question, wherein model answer includes default score content and presets
Divide the corresponding default score score value of content；Information comparison unit, for by the standard of the test answers of per pass examination question and the examination question
Answer compares, and obtains the correct content and the corresponding score value of correct content in the test answers of per pass examination question；Label is looked into
Unit is looked for, for searching label corresponding with the correct content in the test answers of per pass examination question in default tag library；User
Evaluation information generation unit is generated for the corresponding score value of correct content and label in the test answers according to per pass examination question
The user's evaluation information of first user's paper.
Further, information acquisition unit includes: taxon, for according to the class for presetting classifying rules acquisition label
Not；Score value adduction unit, for obtaining to the corresponding score value progress adduction of the correct content of each of same category of label is belonged to
To the total score of the category.
It further, further include grouping information acquiring unit, for obtaining each first user paper in default grouping
User's evaluation information；It is grouped evaluation information generation unit, for generating the grouping evaluation information of default grouping.
It further, further include total score acquiring unit, for obtaining the use of each first user paper in default grouping
Corresponding total score is signed in evaluation information middle finger calibration in family；Scoring rate statistic unit, for the use according to each first user paper
The packet label average rate and each that specified label is calculated in corresponding total score is signed in evaluation information middle finger calibration in family
The user tag scoring rate of the specified label of one user's paper；Scoring rate judging unit, for judging whether deposit in default grouping
It is lower than first user's paper of packet label average rate in the user tag scoring rate of specified label；Transmission unit is used for
If the user tag scoring rate that there is specified label in default grouping is lower than first user's paper of average label scoring rate,
Evaluation information by the user tag scoring rate of specified label lower than first user's paper of packet label average rate is sent
Give second user equipment.
In the embodiment of the present application, using being pre-configured with all kinds of labels in default tag library, and per pass examination question is being obtained
Test answers in correct content after match corresponding label for it, and the correct content institute is determined according to model answer
Corresponding score value, the scoring event realized to the labeling classification of test answers and statistics, by counting each label can be right
The examination and diagnosis that test answers are refined solve the paper judge side using the association of knowledge of textbook point and the classification of topic type
Method, which cannot achieve, carries out the problem of fining is screened with diagnosis to paper test result.
Detailed description of the invention
The attached drawing constituted part of this application is used to provide further understanding of the present application, so that the application's is other
Feature, objects and advantages become more apparent upon.The illustrative examples attached drawing and its explanation of the application is for explaining the application, not
Constitute the improper restriction to the application.In the accompanying drawings:
Fig. 1 is a kind of flow diagram of information processing method provided by the present application；
Fig. 2 is the flow diagram of another information processing method provided by the present application；
Fig. 3 is the flow diagram of another information processing method provided by the present application；
Fig. 4 is the flow diagram of another information processing method provided by the present application；
Fig. 5 is the flow diagram of another information processing method provided by the present application；
Fig. 6 is the flow diagram of another information processing method provided by the present application；
Fig. 7 is a kind of structural schematic diagram of information processing unit provided by the present application；
Fig. 8 is the structural schematic diagram of another information processing unit provided by the present application；
Fig. 9 is the structural schematic diagram of another information processing unit provided by the present application；
Figure 10 is the structural schematic diagram of another information processing unit provided by the present application.
Specific embodiment
In order to make those skilled in the art more fully understand application scheme, below in conjunction in the embodiment of the present application
Attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is only
The embodiment of the application a part, instead of all the embodiments.Based on the embodiment in the application, ordinary skill people
Member's every other embodiment obtained without making creative work, all should belong to the model of the application protection
It encloses.
It should be noted that the description and claims of this application and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to embodiments herein described herein.In addition, term " includes " is intended to
In cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units need not
Those of be limited to be clearly listed step or unit, but may include be not clearly listed or for these process, methods,
The other step or units of product or equipment inherently.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
According to the present embodiment, a kind of information processing method is provided, Fig. 1 is a kind of information processing method provided by the present application
Flow diagram, as shown in Figure 1, the method comprising the steps of S101 to step S104:
S101 obtains the test answers of per pass examination question and the model answer of per pass examination question in first user's paper, wherein
The model answer includes default score content and the corresponding default score score value of the default score content.
Specifically, the paper in this step includes in examination question, model answer content corresponding with the examination question and examination question
The total score of per pass examination question and each score content of the model answer and corresponding score value.
For example, illustrating by math problems of examination question, the total score of the math problems is 8 points, corresponding
Model answer includes that there are three default score contents, wherein first default score content be y=4x+5, second it is default
Dividing content to be by y=4 × 2+5, the default score content of third is y=13, and above three presets the default score of score content
Score value is respectively 2 points, 2 points and 4 points.Wherein, the first user is the examination personnel to take an examination, such as in the student in school, enterprise
Employee etc., the application is simultaneously not particularly limited.
It should be noted that the default score content and corresponding default score score value in item colibration answer can bases
The topic type of different examination questions is specifically arranged, and the application is simultaneously not particularly limited.
In addition, in first user's paper the test answers of per pass examination question acquisition modes can for by scanner by first
The paper that user answers questions in writing is scanned into terminal device and person's handwriting is identified as test answers by way of image recognition, can also be led to
Cross full-filling with option answering card mode by the test answers of multiple-choice question through the typing of answering card card reader into terminal device,
Examination personnel can be arranged directly to answer on the terminal device acquisition, the application is not to per pass examination question in first user's paper
The acquisition modes of test answers are specifically limited.
S102 compares the test answers of examination question described in per pass and the model answer of the examination question, obtains examination described in per pass
Correct content and the corresponding score value of the correct content in the test answers of topic.
Specifically, the model answer of the test answers of examination question described in the per pass obtained in step S101 and the examination question is carried out
It compares, is compared default score score value corresponding to default score content in the correct content and model answer that obtain later and carried out
It is corresponding, obtain the corresponding score value of correct content.
Exist still by taking examination question above-mentioned is math problems as an example, in the test answers of the examination question corresponding with model answer
Three test contents, respectively y=4x+5, y=4 × 2+5 and y=12, but obtain afterwards by contrast correct interior in test answers
Holding is y=4 × 2+5 and y=4 × 2+5, and y=12 is wrong content, by the default score content of correct option and model answer
And the corresponding default score score value of default score content is corresponded to, then can get the correct content and correct content is corresponding
Score value, y=4x+5 (2 points) and y=4 × 2+5 (2 points), and since Part III content occurs errors excepted (EE) point, y=12 (0
Point).
It should be noted that the mode compared can be specifically arranged according to different topic types, as obtained by marking answer sheet
The test answers of multiple-choice question, then whether the filled out option in contrast test answer and model answer are consistent, if it is passing through terminal
The test answers of the gap-filling questions of equipment typing, then whether the filled out content in contrast test answer and model answer are consistent, this Shen
Specific alignments are not specifically limited please.
S103 searches label corresponding with the correct content in the test answers of examination question described in per pass in default tag library.
The incidence relation between test answers content and label is provided in advance in default tag library, therefore pre-
It is right to can be obtained the correct content institute for label corresponding to correct content in the test answers of bidding label library lookup per pass examination question
The label answered.
Specifically, there are three level-one labels, respectively knowledge label, Skills tab and ability mark for storage in default tag library
Label, and under each first class index include it is multiple secondary labels, as further include under Skills tab memory, understanding, application, reasoning,
The second levels label such as Resolving probiems and mathematical expression, further include under knowledge label it is several with algebra, figure and geometry, statistics and probability,
Practice and the second levels label such as comprehensive further include the second levels marks such as speech-language, mathematics-logic and visuo-spatial under ability label
Label.
For example, the content of tag library is preset based on this, the survey still by taking math problems above-mentioned as an example, in the examination question
Trying the correct content in answer is y=4x+5 and y=4 × 2+5, searched in default tag library with one corresponding to y=4x+5
Grade label is respectively knowledge label, Skills tab and ability label, and second level label is respectively number and algebra mark under knowledge label
Operation label under label, Skills tab and the logic analysis label under ability label；Similarly lookup and y in default tag library
Level-one label corresponding to=4 × 2+5 is respectively knowledge label, Skills tab and ability label, and second level label is respectively knowledge
Practice under label and the language understanding label deducted under label and ability label under comprehensive label, Skills tab；Together
Level-one label difference corresponding to the wrong content y=12 that can also be searched in default tag library in aforementioned test answers of sample
For knowledge label, Skills tab and ability label, second level label is respectively statistics and probability tag, technical ability mark under knowledge label
That signs calculates the numerical expression reasoning label under label and ability label.
It should be noted that in the specific implementation, the quantity of investigation aspect, label level and label that label is embodied
The content flexible setting corresponding with the corresponding content of courses that can be investigated according to paper, the application do not limit the tool of label specifically
Hold in vivo.
The corresponding score value of correct content and label in the test answers of S104 examination question according to per pass generate described the
The user's evaluation information of one user's paper.
The correct content corresponding label and score value of per pass examination question are associated by correct content, it is correct when per pass examination question
When the corresponding label of content is one, the corresponding score value of the correct content is the score value of the label；It is correct when per pass examination question
When content corresponding label is multiple, can the score value as each label by the score value without weight, can also be by certain weight
Proportional distributes to score value on each label；
For example, still by taking examination question above-mentioned is math problems as an example, to illustrate to work as the correct content pair of per pass examination question
When to answer label be multiple, the score value of such as how correct content distributes to each label without weight.Correct content y=4x+5 is corresponding
Level-one label be respectively knowledge label, Skills tab and ability label, then the score value of each level-one label is respectively knowledge label
(2 points), Skills tab (2 points) and ability label (2 points)；The score value of same second level label is respectively several and algebra label (2
Point), operation label (2 points) and logic analysis label (2 points).
It is corresponding, it is that score value is distributed into each label by certain weight is proportional, for example, equally
By taking examination question above-mentioned is math problems as an example.Correctly the corresponding level-one label of content y=4x+5 is respectively knowledge label, technical ability
Label and ability label, if the weight of each label is identical, the score value of each level-one label be respectively knowledge label (2/3 point),
Skills tab (2/3 point) and ability label (2/3 point), the score value of same second level label are respectively several and algebra label (2/3
Point), operation label (2/3 point) and logic analysis label (2/3 point).
It should be noted that when there are include multiple second level labels under the corresponding level-one label of the correct content of examination question
When, score value can also be distributed into each second level label according to specific score value distribution requirements, the application not to score value and label it
Between the relations of distribution be specifically limited.
It should be noted that content included by user's evaluation information can be in the test answers to per pass examination question just
The true corresponding score value of content and label are counted, as counted the paper label total score of same label or statistics examination in paper
Paper label scoring rate of same label etc. in volume, there are be also possible to carry out statistics total score to labels at different levels when multistage label
Value, scoring rate etc..
In a feasible embodiment, Fig. 2 is the process signal of another information processing method provided by the present application
Figure, as shown in Fig. 2, can be realized by following steps S201 and step S202 when executing step S104:
S201 obtains the classification of the label according to default classifying rules.
By default classifying rules first by level-one labeling, obtain in correct in the test answers of each examination question in paper
The classification results for holding corresponding level-one label, if there are contents correct in the test answers of examination question to be corresponding with three-level in paper
Label then continues after to level-one labeling to second level labeling, that is to say, that when the test in paper there are examination question is answered
When correct content is corresponding with multistage label in case, then classification successively is carried out until afterbody label to labels at different levels；Such as
There are contents correct in the test answers of examination question to be only corresponding with single-stage label in fruit paper, then by above-mentioned label according to identical mark
Label are classified.
S202 carries out adduction to the corresponding score value of each of same category of label correct content is belonged to, and is somebody's turn to do
The total score of classification.
The corresponding label of content correct in the test answers of examination question each in paper is classified in step S201,
Lower included label of all categories and its score value are subjected to adduction later and obtain total score of all categories.By to point of all categories
It is worth progress adduction, in terms of the weakness of analysis examinee that can be three-dimensional and in terms of advantage.
In a feasible embodiment, Fig. 3 is the process signal of another information processing method provided by the present application
Figure, as shown in figure 3, this information processing method further includes step S301 to step S302:
S301 obtains the user's evaluation information of each first user paper in default grouping.
For the grouping evaluation information for obtaining specific cluster, the user of each first user paper in the grouping need to be obtained
Evaluation information, the user's evaluation information include that correct content in the test answers of each examination question and the correct content are corresponding
Score value and label.
It should be noted that default grouping can be class, school, province, city etc., specific packet mode can be according to specific need
Setting is asked, the application is not specifically limited packet mode.
S302 generates the grouping evaluation information of the default grouping.
By obtaining the user's evaluation information of each first user paper in default grouping, available default grouping
In each first user paper user's evaluation information in each label score value, and then obtain the specified label of default grouping
Packet label average rate, median score score value, can also be by setting the passing score of each label and being compared
First user's pass rate of each label or personnel amount of failing etc. are obtained, it can also be by setting the outstanding score of each label simultaneously
Compared the first user's excellent rate for obtaining each label or excellent personnel quantity etc..By the grouping evaluation for generating default grouping
Information can obtain the whole paper test situation of default grouping, such as will be seen that default point by packet label average rate
Which label scoring rate of group is lower, that is to say, bright knowledge content study relevant to this label is bad, it should reinforce teaching,
Personnel amount of failing alternatively bright whole teaching level how.
In a feasible embodiment, Fig. 4 is the process signal of another information processing method provided by the present application
Figure, as shown in figure 4, this information processing method further includes step S401 to step S404:
The user's evaluation information middle finger calibration label that S401 obtains each first user paper in default grouping are corresponding
Total score.
The user's evaluation information middle finger calibration label of each first user paper are corresponding in the default grouping of statistics respectively
Total score, as this is default be grouped into include 30 students class, specifying label is several with algebra label, then obtaining respectively should
Several total scores with algebra label in every student's paper in class.
S402 signs corresponding total score according to the calibration of the user's evaluation information middle finger of each first user paper and calculates
Obtain the use of the packet label average rate of the specified label and the specified label of each first user paper
Family label scoring rate.
By the corresponding total score of specified label of every first user's paper in the default grouping obtained in step S401 according to
The secondary standard total score value with the specified label of model answer is compared, then obtains the finger of each first user paper
Calibrate the user tag scoring rate of label, and the user tag score of the specified label according to each first user paper
Rate obtains packet label average rate.
S403 judges in the default grouping with the presence or absence of the user tag scoring rate of the specified label lower than described point
The first user paper of group label average rate.
Successively the user tag scoring rate of the specified label of every first user's paper and packet label are averagely obtained
Point rate is compared, and when user tag scoring rate is greater than packet label average rate, comparison result is positive number, when user marks
Signing comparison result when scoring rate is equal to packet label average rate is zero, and when user tag scoring rate is flat less than packet label
Comparison result is negative when equal scoring rate.
If there are the user tag scoring rates of the specified label to be lower than the average mark in the S404 default grouping
The first user paper of scoring rate is signed, then is put down the user tag scoring rate of the specified label lower than the packet label
The evaluation information of the first user paper of equal scoring rate is sent to second user equipment.
When there are user tag scoring rates lower than the average label scoring rate for comparison result, i.e., comparison result is negative
When number, then the evaluation information by user tag scoring rate lower than first user's paper of the packet label average rate is sent
Give second user equipment.By successively by the label scoring rate of the specified label of first user's paper in default grouping group and flat
Equal label scoring rate is compared, and realizes the layered shaping for presetting the first user in grouping group, that is to say, that by the
One user is divided into one group higher than average label scoring rate and one group lower than average label scoring rate, and different by setting
Specified label, the layering of corresponding first user of different labels can be obtained as a result, when making teacher at school or training
It flexibly can targetedly stress different students according to different labels, not compared to the whole paper of existing simple acquisition
The student information of passing score, can more comprehensively, and also the weak aspect of more careful understanding student, teaches students in accordance with their aptitude.
It should be noted that second user can be teacher, teaching manager, enterprise administrator etc., the application exists
This is not specifically limited.
In a feasible embodiment, after executing step S402, Fig. 5 is at another information provided by the present application
The flow diagram of reason method, as shown in figure 5, this information processing method further includes step S501 to step S502:
S501 successively calculates the difference between each user tag scoring rate and the packet label average rate.
Successively by the user tag scoring rate of the specified label of the every first user's paper obtained in step S402
It is compared with packet label average rate, and records the specified label and packeting average scoring rate of every first user's paper
Between difference.
For example, the user tag scoring rate of the calculating label of the paper of Xiao Wang is so that the first user is Xiao Wang as an example
78.21%, and the packet label scoring rate of default grouping is 88.46%, the difference for calculating the two is -10.25%.
S502 successively matches the difference with default attention rate matching condition to obtain each first user
The attention rate of examination question is specified described in paper.
Successively by the user tag scoring rate and packet label of the specified label of step S501 every first user obtained
Difference between average rate is matched with default attention rate matching condition.
Specifically, default attention rate matching condition can be three numerical intervals (as -10% to 10% is middle attention rate area
Between, being less than -10% is high attention rate section, and being greater than 10% is low attention rate section), by judging which section is the difference fall in
It can determine the attention rate of the specified label in the corresponding first user paper of the difference.
For example, it is -10.25% that difference is obtained still by taking the first user above-mentioned is Xiao Wang as an example, in step S501,
The numerical intervals to match with -10.25% are high attention rate section less than -10%, therefore the concern of the calculating label of Xiao Ming
Degree is height.By the attention rate of each label of determination, the testing level of each label of the first user can be obtained, that is to say, that Gao Guan
The label of note degree reflects that the user has good learning effect in terms of the label, and the label of low attention rate reflects the user
Learning effect in terms of the label is poor, should pay most time and efforts to learn and train, for middle attention rate
Label illustrates that the user is close with average level, should pay the more time and always be learnt and trained, by understanding each mark
The attention rate of label can the first user of auxiliary of science distribute oneself learning time, make study more rich in efficiency.
It should be noted that default attention rate matching condition can for multiple numerical intervals, be also possible to it is more than one or more
The specific value of a attention rate threshold value, numerical intervals and threshold value can be set according to actual needs, not do specific limit herein
It is fixed.
In a feasible embodiment, Fig. 6 is the process signal of another information processing method provided by the present application
Figure, as shown in fig. 6, this information processing method further includes step S601 to step S603:
S601 in the test answers of examination question described in per pass in the paper the corresponding score value of correct content and label into
Row statistics obtains the characteristic information collection of the paper.
Wherein, characteristic information collection includes multiple characteristic informations, survey of each characteristic information all in accordance with per pass examination question in paper
The corresponding score value of correct content and label in examination answer obtain after being counted.
Specifically, characteristic information may include the scoring rate of each label, the attention rate of each label gross score and each label
Deng.
For example, the gross score of the knowledge label of Xiao Ming is 80 points, and scoring rate is so that the first user is Xiao Ming as an example
80%, attention rate is height.
S602 judges to concentrate each characteristic information to match with the presence or absence of with the characteristic information in default prompt information library
Prompt information.
Default prompt information library is provided in advance corresponding with each characteristic information that characteristic information in step S601 is concentrated
Prompt information type, it is successively opposite in each characteristic information that whether default prompt information library lookup has with characteristic information is concentrated
The prompt information answered is prepared to generate evaluation information for step S603.
Specifically, can be each configured in default prompt information library and label scoring rate, each label gross score and each mark
The matched three kinds of prompt information types of the attention rate of label, matched mode can be using setting score sections, by determining label
The score section that gross score, label scoring rate and attention rate are fallen in obtains corresponding prompt information.
For example, first looking for knowledge label gross score being 80 points still by taking the first user above-mentioned is Xiao Ming as an example
Corresponding prompt information, presetting knowledge label gross score at 80 points to 90 points is a score section, then obtains the area
Between it is preconfigured " gross score of knowledge dimension be good level, continuing with keep " prompt information, similarly search respectively
With knowledge label scoring rate be 80% and attention rate is that respectively " knowledge label scoring rate still has larger high corresponding prompt information
Raising space, should be noted the height of attention rate to determine the study situation of knowledge dimension comprehensively " and " the high declarative knowledge of attention rate
The scoring rate of dimension is lower than average rate, therefore should focus on the study and habit of textbook related to knowledge dimension in daily study
The practice of topic ".
If exist in the default prompt information library S603 concentrates each characteristic information to match with the characteristic information
Prompt information, then will concentrate each matched prompt of characteristic information with the characteristic information in the default prompt information library
Information is as the user's evaluation information.
The prompt information that step S603 is obtained manually is divided as evaluation information without embodying preparation material for training and teacher
Test answers are analysed to obtain the evaluation information of paper, using the corresponding pass between preconfigured prompt information and characteristic information collection
System, evaluation information that is easy, fast and accurately obtaining paper, saves a large amount of cost and time.
For example, still by the first user above-mentioned be Xiao Ming for, by obtained in step S602 " knowledge dimension it is total
Score is good level, continuing with keeping ", " knowledge label scoring rate is still greatly improved space, should be noted the height of attention rate
The low study situation to determine knowledge dimension comprehensively " and " scoring rate of the high declarative knowledge dimension of attention rate lower than average rate,
Therefore should focus on the study of textbook related to knowledge dimension and the practice of exercise in daily study " as Xiao Ming paper use
Family evaluation information.
In embodiment provided by the present application, using being pre-configured with all kinds of labels in default tag library, and it is every obtaining
Corresponding label is matched after correct content in the test answers of road examination question for it, and determines that this is correct according to model answer
Score value corresponding to content is realized to the labeling classification of test answers and statistics, by the scoring event for counting each label
Can solve the paper using the association of knowledge of textbook point and the classification of topic type to the examination and diagnosis that test answers are refined
Evaluation method, which cannot achieve, investigates the problem of result carries out fining examination and diagnosis to paper.
Based on the same technical idea, the embodiment of the present application also provides a kind of structural schematic diagram of information processing unit,
Fig. 7 is a kind of structural schematic diagram of information processing unit provided by the present application, as shown in fig. 7, the device includes:
71 information acquisition devices, for obtaining the test answers and per pass examination question of per pass examination question in first user's paper
Model answer, wherein the model answer includes that default score content and the default score content are corresponding default
Divide score value；
72 information comparison devices, for carrying out pair the model answer of the test answers of examination question described in per pass and the examination question
Than obtaining the correct content and the corresponding score value of the correct content in the test answers of examination question described in per pass；
73 label lookup devices, it is correct in the test answers with examination question described in per pass for being searched in default tag library
The corresponding label of content；
74 user's evaluation information generation devices, it is corresponding for the correct content in the test answers of the examination question according to per pass
Score value and label, generate the user's evaluation information of the first user paper.
In a feasible embodiment, Fig. 8 is the structural representation of another information processing unit provided by the present application
Figure, as shown in figure 8, wherein information acquisition unit includes 711 taxons and 712 score value adduction units:
711 taxons, for obtaining the classification of the label according to default classifying rules；
712 score value adduction units, for belonging to each of same category of label corresponding point of correct content
Value carries out adduction, obtains the total score of the category.
In a feasible embodiment, Fig. 9 is the structural representation of another information processing unit provided by the present application
Figure, as shown in figure 9, the device further include:
81 grouping information acquiring units, for obtaining the user's evaluation letter of each first user paper in default grouping
Breath；
82 grouping evaluation information generation units, for generating the grouping evaluation information of the default grouping.
In a feasible embodiment, Figure 10 is the structural representation of another information processing unit provided by the present application
Figure, as shown in Figure 10, described device further include:
91 total score acquiring units, for obtaining the user's evaluation information of each first user paper in default grouping
Corresponding total score is signed in middle finger calibration；
92 scoring rate statistic units are signed for being calibrated according to the user's evaluation information middle finger of each first user paper
Corresponding total score be calculated the specified label packet label average rate and each first user paper
The user tag scoring rate of the specified label；
93 scoring rate judging units, the user tag for judging to whether there is the specified label in the default grouping
Scoring rate is lower than the first user paper of the packet label average rate；
94 transmission units, if for there are the user tag scoring rates of the specified label to be lower than in the default grouping
The first user paper of the average label scoring rate, then by the user tag scoring rate of the specified label lower than described
The evaluation information of the first user paper of packet label average rate is sent to second user equipment.
In embodiment provided by the present application, test answers, the information ratio of per pass examination question are obtained by information acquisition device
Correct content is obtained to device and corresponding score value, label lookup device search the label and user that the correct content matches
Evaluation information generating means generate the user's evaluation information of first user's paper, realize to the classification of the labeling of test answers with
Statistics, the scoring event by counting each label can solve use to the examination and diagnosis that test answers are refined
Knowledge of textbook point association with topic type classification paper evaluation method cannot achieve to paper investigate result carry out fining screen with
The problem of diagnosis.
Obviously, those skilled in the art should be understood that each module of the above invention or each step can be with general
Computing device realize that they can be concentrated on a single computing device, or be distributed in multiple computing devices and formed
Network on, optionally, they can be realized with the program code that computing device can perform, it is thus possible to which they are stored
Be performed by computing device in the storage device, perhaps they are fabricated to each integrated circuit modules or by they
In multiple modules or step be fabricated to single integrated circuit module to realize.In this way, the present invention is not limited to any specific
Hardware and software combines.
The foregoing is merely preferred embodiment of the present application, are not intended to limit this application, for the skill of this field
For art personnel, various changes and changes are possible in this application.Within the spirit and principles of this application, made any to repair
Change, equivalent replacement, improvement etc., should be included within the scope of protection of this application.
Claims (10)
1. a kind of information processing method characterized by comprising
Obtain the model answer of the test answers of per pass examination question and per pass examination question in first user's paper, wherein the standard
Answer includes default score content and the corresponding default score score value of the default score content；
The test answers of examination question described in per pass and the model answer of the examination question are compared, the test of examination question described in per pass is obtained
Correct content and the corresponding score value of the correct content in answer；
Label corresponding with the correct content in the test answers of examination question described in per pass is searched in default tag library；
The corresponding score value of correct content and label in the test answers of the examination question according to per pass generate the first user examination
The user's evaluation information of volume.
2. information processing method according to claim 1, which is characterized in that the test of the examination question according to per pass is answered
The corresponding score value of correct content and label in case, the evaluation information for generating the first user paper include:
The classification of the label is obtained according to default classifying rules；
Adduction is carried out to the corresponding score value of each of same category of label correct content is belonged to, obtains the total of the category
Score value.
3. information processing method according to claim 1, which is characterized in that the method also includes:
Obtain the user's evaluation information of each first user paper in default grouping；
Generate the grouping evaluation information of the default grouping.
4. information processing method according to claim 1, which is characterized in that the method also includes:
Corresponding total score is signed in the user's evaluation information middle finger calibration for obtaining each first user paper in default grouping；
It is calculated according to the corresponding total score of the user's evaluation information middle finger of each first user paper calibration label described
The user tag of the specified label of the packet label average rate and each first user paper of specified label obtains
Divide rate；
Judge flat lower than the packet label with the presence or absence of the user tag scoring rate of the specified label in the default grouping
The first user paper of equal scoring rate；
If there are the user tag scoring rates of the specified label lower than the average label scoring rate in the default grouping
The first user paper, then by the user tag scoring rate of the specified label be lower than the packet label average rate
The evaluation information of the first user paper be sent to second user equipment.
5. information processing method according to claim 4, which is characterized in that tried described according to each first user
The packet label average that the specified label is calculated in corresponding total score is signed in the user's evaluation information middle finger calibration of volume
After the user tag scoring rate of the specified label of rate and each first user paper further include:
Successively calculate the difference between each user tag scoring rate and the packet label average rate；
Successively the difference is matched with default attention rate matching condition to obtain institute in each first user paper
State the attention rate of specified label.
6. information processing method according to claim 1, which is characterized in that the test of the examination question according to per pass is answered
The corresponding score value of correct content and label in case, the evaluation information for generating the first user paper include:
To in the test answers of examination question described in per pass in the paper the corresponding score value of correct content and label carry out statistics obtain
Obtain the characteristic information collection of the paper；
Judge to concentrate the matched prompt of each characteristic information to believe with the presence or absence of with the characteristic information in default prompt information library
Breath；
The matched prompt of each characteristic information is concentrated to believe with the characteristic information if existed in the default prompt information library
Breath, then will in the default prompt information library with the characteristic information each matched prompt information of characteristic information of concentration as
The user's evaluation information.
7. a kind of information processing unit characterized by comprising
Information acquisition unit, for obtaining the test answers of per pass examination question and the standard of per pass examination question in first user's paper
Answer, wherein the model answer includes default score content and the corresponding default score score value of the default score content；
Information comparison unit is obtained for comparing the test answers of examination question described in per pass and the model answer of the examination question
Correct content and the corresponding score value of the correct content in the test answers of examination question described in per pass；
Label lookup unit, for being searched and the correct content pair in the test answers of examination question described in per pass in default tag library
The label answered；
User's evaluation information generating unit, for the corresponding score value of correct content in the test answers of the examination question according to per pass
And label, generate the user's evaluation information of the first user paper.
8. information processing unit according to claim 7, which is characterized in that the information acquisition unit includes:
Taxon, for obtaining the classification of the label according to default classifying rules；
Score value adduction unit, for adding to belonging to the corresponding score value of each of same category of label correct content
It closes, obtains the total score of the category.
9. information processing unit according to claim 7, which is characterized in that described device further include:
Grouping information acquiring unit, for obtaining the user's evaluation information of each first user paper in default grouping；
It is grouped evaluation information generation unit, for generating the grouping evaluation information of the default grouping.
10. information processing unit according to claim 7, which is characterized in that described device further include:
Total score acquiring unit is specified in the user's evaluation information of each first user paper for obtaining in default grouping
The corresponding total score of label；
Scoring rate statistic unit, for corresponding according to the user's evaluation information middle finger of each first user paper calibration label
The packet label average rate of the specified label and the finger of each first user paper is calculated in total score
Calibrate the user tag scoring rate of label；
Scoring rate judging unit, the user tag scoring rate for judging to whether there is the specified label in the default grouping
Lower than the first user paper of the packet label average rate；
Transmission unit, if for there are the user tag scoring rates of the specified label to be lower than described put down in the default grouping
The first user paper of equal label scoring rate then marks the user tag scoring rate of the specified label lower than the grouping
The evaluation information for signing the first user paper of average rate is sent to second user equipment.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110135692A (en) * | 2019-04-12 | 2019-08-16 | 平安普惠企业管理有限公司 | Intelligence grading control method, device, computer equipment and storage medium |
| CN112785179A (en) * | 2021-01-29 | 2021-05-11 | 北京译泰教育科技有限公司 | Index information generation method |
| CN114238598A (en) * | 2021-12-07 | 2022-03-25 | 北京妙医佳健康科技集团有限公司 | Question-answering system and labeling, auditing and model training method thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1514790A (en) * | 1974-12-24 | 1978-06-21 | Clark S | Electronic device for testing a student's knowledge |
| CN101859338A (en) * | 2009-05-14 | 2010-10-13 | 深圳市海云天科技股份有限公司 | Examination paper reading system and marking implementation method thereof |
| CN107169654A (en) * | 2017-05-12 | 2017-09-15 | 北京航空航天大学 | A kind of method and system for analyzing students'comprehensive ability |
| CN107451711A (en) * | 2017-05-12 | 2017-12-08 | 北京航空航天大学 | A kind of evaluation method of students'comprehensive ability |
| CN108053098A (en) * | 2017-11-24 | 2018-05-18 | 河南大学 | A kind of school grade analysis method based on big data |
-
2018
- 2018-10-11 CN CN201811183615.7A patent/CN109545018A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1514790A (en) * | 1974-12-24 | 1978-06-21 | Clark S | Electronic device for testing a student's knowledge |
| CN101859338A (en) * | 2009-05-14 | 2010-10-13 | 深圳市海云天科技股份有限公司 | Examination paper reading system and marking implementation method thereof |
| CN107169654A (en) * | 2017-05-12 | 2017-09-15 | 北京航空航天大学 | A kind of method and system for analyzing students'comprehensive ability |
| CN107451711A (en) * | 2017-05-12 | 2017-12-08 | 北京航空航天大学 | A kind of evaluation method of students'comprehensive ability |
| CN108053098A (en) * | 2017-11-24 | 2018-05-18 | 河南大学 | A kind of school grade analysis method based on big data |
Non-Patent Citations (1)
| Title |
|---|
| 周敏: "评价学生能力水平的数学模型及其在考试成绩中的应用", 《川北医学院学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110135692A (en) * | 2019-04-12 | 2019-08-16 | 平安普惠企业管理有限公司 | Intelligence grading control method, device, computer equipment and storage medium |
| CN112785179A (en) * | 2021-01-29 | 2021-05-11 | 北京译泰教育科技有限公司 | Index information generation method |
| CN114238598A (en) * | 2021-12-07 | 2022-03-25 | 北京妙医佳健康科技集团有限公司 | Question-answering system and labeling, auditing and model training method thereof |
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