CN108846579B - Knowledge quantity calculation method and system for subject knowledge - Google Patents

Knowledge quantity calculation method and system for subject knowledge Download PDF

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CN108846579B
CN108846579B CN201810622100.6A CN201810622100A CN108846579B CN 108846579 B CN108846579 B CN 108846579B CN 201810622100 A CN201810622100 A CN 201810622100A CN 108846579 B CN108846579 B CN 108846579B
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CN108846579A (en
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徐继宁
李志军
王力
胡敦利
孙德辉
张黎明
姜力
李凯龙
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Beijing Yunjing Zhitong Education Technology Co ltd
North China University of Technology
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The invention relates to a knowledge quantity calculation method and a knowledge quantity calculation system for subject knowledge. With the increase of the achieved users, the calculation of the knowledge amount can realize real-time updating, and the calculation accuracy is improved. The method embodies the educational idea centered on learners, and learners can reasonably carry out time distribution and learning decision-making in the learning process according to the knowledge quantity of different knowledge objects.

Description

Knowledge quantity calculation method and system for subject knowledge
Technical Field
The invention belongs to the field of knowledge quantity calculation, and particularly relates to a knowledge quantity calculation method and system for subject knowledge.
Background
Discipline knowledge is a knowledge network made up of a large number of interrelated knowledge objects. In the existing learning mode, online learning occupies an increasingly important position, and the knowledge quantity of a knowledge object is quantitatively described by using a computer technology, so that on one hand, a data basis can be provided for quantitative research of a knowledge network, on the other hand, a learner can make a reasonable learning decision in the learning process, and the learning efficiency is improved.
There is no clear knowledge quantity measurement standard aiming at subject knowledge in the prior art, and an article published by lysina et al, namely discussion on objective measurement of difficulty of knowledge work based on knowledge quantity, discloses that the knowledge quantity of students increases with the increase of teaching time, a mapping relation exists between the knowledge quantity and learning time, and the knowledge can be measured by taking the social standard teaching time as a measurement unit of the knowledge quantity. However, the above measurement methods are based on expert experience or subjective judgment of the instructor, and it is difficult to give accurate guidance to the learning decision of the student without considering the knowledge acceptance of the learner or the achievement of the learning objective from the perspective of the learner.
Disclosure of Invention
In order to solve the above problems, the present invention provides a knowledge quantity calculation method of subject knowledge, which comprises the following specific steps:
a method for calculating the amount of knowledge of subject knowledge, comprising the steps of:
and S1, dividing the knowledge objects into X levels according to the membership relation among the knowledge objects contained in the subject knowledge, wherein X is 1, 2 and 3 … N. Each X level comprises one or a plurality of knowledge objects, and each knowledge object comprises a description unit, a plurality of X-level knowledge units and a test unit. The knowledge objects with the level X being 1 are the whole subject knowledge and are called parent knowledge objects, and the knowledge objects with the level X being larger than the level 1 are all certain X-1 level knowledge units in certain X-1 level knowledge objects and are called the inherited knowledge of the X-1 level knowledge objects. Unique ID assignment is carried out on the description unit, the knowledge unit and the test unit of each level, and a knowledge object level relation storage file is formed, wherein the ID value comprises an attribute value, a level value and a sequence value;
s2, monitoring user behavior, and when the user enters the description unit S in the knowledge objectaTime, record local time T at the time of entryJAnd completing the test unit F of the same knowledge object at the useraTime, local time T when recording is completedcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
S3, calculating the achievement degree gamma of the user to the corresponding knowledge object, and marking the user as the achieved user of the knowledge object when the achievement degree gamma of the user reaches a preset threshold value mu;
s4, obtaining the learning time T of all the achieved users aiming at the same knowledge object in the preset time periodaCalculating the knowledge quantity Q of the knowledge objecta。
Further, when X is equal to N, learning time T of all achieved users for the same knowledge object in a preset time period is acquiredaCalculating the knowledge quantity of the knowledge object, specifically: the number of all agreed users is mnThe number of the main components is one,
Figure GDA0002804758700000021
wherein
Figure GDA0002804758700000022
The "a" is x, and is expressed as a sequential number value of the knowledge object, and may be expressed as a numerical value of a different number of digits depending on the number of the different knowledge object, or may be expressed in another manner.
Further, when X is less than N, learning time T of all achieved users aiming at the same knowledge object in a preset time period is obtainedaAnd calculating to obtain the knowledge quantity of the corresponding knowledge object, specifically: the number of all agreed users is mwThe current X-level knowledge object comprises t X + 1-level knowledge units, and the knowledge quantity of the X + 1-level knowledge unit is QxIt is shown that,
Figure GDA0002804758700000031
wherein the content of the first and second substances,
Figure GDA0002804758700000032
i represents the sequence number value of the knowledge object, and i can be represented by numerical values with different digits or any representation mode for the hierarchy sequence number values of different knowledge objects. And when the current knowledge object is a primary knowledge object U, replacing i with U for representation.
σ1And σ2Are all coefficients, σ1+σ2＝1。
Further, the achievement degree γ ═ a is defined asx/AmWherein A ismIs the total score of the test unit in the current knowledge object, AxThe test scores obtained in the test cells within the current knowledge object for the current user. Preferably, the predetermined threshold value is 0.6 < mu.ltoreq.1.
On the other hand, the invention also provides a knowledge quantity calculation system of subject knowledge, which comprises a knowledge object marking module, a description unit monitoring module, a test unit monitoring module, a learning time calculation module and a knowledge quantity calculation module;
a knowledge object labeling module: labeling ID values of knowledge contents in the knowledge objects according to the membership between the knowledge objects contained in the subject knowledge, wherein the ID values comprise attribute values, hierarchy values and sequence values; the attribute value defines the attribute of the knowledge unit in the same knowledge object as a description unit S, a knowledge unit Z or a test unit F; the level value is the level X to which the knowledge object belongs, X is 1, 2, 3 … N, the primary knowledge object is a father knowledge object, each X level knowledge unit belongs to the inheritance knowledge of the X level knowledge object, and the level X +1 knowledge object is defined at the angle of the X +1 level; the sequence value is the sequence value of the knowledge units belonging to the same knowledge object;
a description unit monitoring module for monitoring the learning path of the user when the user enters the description unit SaThen, the ID value of the description unit is judged, and the current description unit S is obtainedaAdapted test unit FaThe ID value of the system is sent to a monitoring instruction of the test unit monitoring module, and meanwhile, a learning time calculation module sends a time recording instruction;
a test unit monitoring module for receiving the monitoring instruction and monitoring the test unit F with corresponding ID completed by the useraWhen the learning time is short, a calculation instruction is sent to the learning time calculation module, and a marking instruction is sent to the marking module;
a learning time calculation module for receiving the time recording instruction and recording the description unit S of the user entering the knowledge objectaLocal time of day TJAnd receiving a calculation instruction and recording a test unit F for a user to finish the same knowledge objectaLocal time of day TcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
The marking module is used for receiving a marking instruction and marking users with the achievement degree gamma of the current knowledge object reaching a preset index mu as achieved users;
a knowledge amount calculation module for calling learning time T of all achieved users aiming at the same knowledge object in a preset time periodaCalculating and updating the knowledge quantity Q of the corresponding knowledge objecta。
Furthermore, the marking module comprises a test result acquisition sub-module, an achievement degree calculation sub-module and an achievement marking sub-module;
the test score acquisition submodule is used for receiving the marking instruction and acquiring the test score A acquired by the current user in the test unit in the current knowledge objectxAnd the total test score A of the test unit in the current knowledge objectm；
An achievement calculation operator module for calculating the degree of the target according to the formula gamma ═ Ax/AmCalculating the achievement degree gamma of the current user aiming at the current knowledge object, comparing the gamma with a preset threshold value mu, and sending a marking instruction to an achievement marking submodule when the comparison result is that the gamma is not less than mu;
and the achievement marking sub-module is used for receiving the marking instruction and marking the current user as the achieved user aiming at the current knowledge object.
The knowledge quantity calculation module calculates the knowledge quantity of the knowledge object, and preferably, when X is equal to N, the number of all the achieved users is mnThe number of the main components is one,
Figure GDA0002804758700000051
wherein
Figure GDA0002804758700000052
and a is x and is expressed as the sequence number value of the knowledge object.
When X < N, the number of all the achieved users is mwThe current X-level knowledge object comprises t X + 1-level knowledge units, and the knowledge quantity of the X + 1-level knowledge unit is QxIt is shown that,
Figure GDA0002804758700000053
wherein the content of the first and second substances,
Figure GDA0002804758700000054
a ═ i, expressed as the ordinal number value of the knowledge object, σ1And σ2Are all coefficients.
According to the method and the system for calculating the knowledge quantity of the subject knowledge, the knowledge subjects are set in a layered knowledge object mode, each knowledge object takes the description unit as a learning inlet, the test unit as a learning outlet, and the specific learning time of the same user for learning different subject objects in different levels can be calculated according to the monitoring of the description unit and the test unit which correspond to each other; and then, the knowledge quantity of the knowledge object is obtained through statistical calculation according to the learning time of the achieved user, and the calculation of the knowledge quantity can realize real-time updating along with the increase of the achieved user, so that the calculation accuracy is improved. The method fully embodies the teaching concept of the learner center, and the learner can intuitively judge the knowledge quantity of different knowledge objects and provide guidance for reasonable learning decision and time distribution in the learning process.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart showing a method for calculating the amount of knowledge of subject knowledge in example 1;
FIG. 2 is a schematic diagram of a system for calculating the amount of knowledge of subject knowledge.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
A knowledge amount calculation method of subject knowledge, as shown in fig. 1, includes the steps of:
and S1, dividing the knowledge objects into X levels according to the membership relation among the knowledge objects contained in the subject knowledge, wherein X is 1, 2 and 3 … N. Each X level comprises one or a plurality of X-level knowledge objects, and each X-level knowledge object comprises a description unit S, a plurality of X-level knowledge units Z and a test unit F; the knowledge object with the level X being 1 is the whole subject knowledge and is called a father knowledge object, and the knowledge objects with the level X being larger than the level 1 are all certain X-1 level knowledge units in certain X-1 level knowledge objects and are called inheritance knowledge of the X-1 level knowledge objects; unique ID assignment is carried out on the description unit S, the knowledge unit Z and the test unit F of each level, and a knowledge object level relation storage file is formed, wherein the ID values comprise attribute values, level values and sequence number values;
as an example, the present embodiment establishes three hierarchical relationships, where X is 1, which is the first hierarchical relationship, and includes a parent knowledge object U, and U includes a description unit SuN primary knowledge units ZiAnd a test unit Fu(ii) a The second level when X is 2, contains N secondary knowledge objects, i.e. each primary knowledge unit ZiAre all one secondary knowledge object, each secondary knowledge object ZiEach comprising a pair ZiDescription unit S for carrying out the descriptionZiA test unit FZiAnd M secondary knowledge units Zij(ii) a The third level when X is 3, contains M three-level knowledge objects, namely each two-level knowledge unit ZijAre all three-level knowledge objects, and each two-level knowledge object ZijEach comprising a pair ZijDescription unit for carrying out the description
Figure GDA0002804758700000071
A test unit
Figure GDA0002804758700000072
And P three-level knowledge units
Figure GDA0002804758700000073
And setting the level value and the sequence value according to the attribute values of different knowledge, namely the description attribute, the knowledge unit attribute and the test attribute.
As an example, the three-level knowledge unit in this embodiment is a minimum unit of discipline knowledge, and does not include a description unit and a test unit.
Further by way of example, a description attribute of 001, a knowledge unit attribute of 002, and a test attribute of 003 may be set; the father knowledge object U can be a subject overall profile, the N primary knowledge units are N chapters, each level is expressed by a two-bit integer, and the primary knowledge unit is Z01、Z02And so on; each primary knowledge unit is a secondary knowledge object from the perspective of the second level, Z02The secondary description unit is Sz02(ii) a Test cell is Fz02The second-level knowledge unit is Z0201、Z0202And so on; each secondary knowledge unit is a three-level knowledge object from the perspective of the third level, Z020204Is Z02The 02 th secondary knowledge unit below the primary knowledge unit comprises the 04 th inherited knowledge tertiary knowledge unit.
S2, monitoring user behavior, and when the user enters the description unit S in the knowledge objectaTime, record local time T at the time of entryJAnd completing the test unit F of the same knowledge object at the useraTime, local time T when recording is completedcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
It should be noted that a knowledge object includes a description unit, a plurality of knowledge units and a test unit, after a user enters the knowledge object from the description unit, the user needs to learn the knowledge units, and after monitoring that the learning of the user on the knowledge units reaches a preset degree, for example, all main knowledge units are learned, or after learning 80% of the knowledge units, the user has the right to test the test unit; the knowledge object can be any level knowledge object as long as the test unit and the description unit are ensured to correspond.
S3, calculating the achievement degree gamma of the user to the corresponding knowledge object, and marking the user as the achieved user of the knowledge object when the achievement degree gamma of the user reaches a preset threshold value mu;
s4, obtaining the learning time T of all the achieved users aiming at the same knowledge object in the preset time periodaCalculating to obtain the knowledge quantity Q of the corresponding knowledge objecta。
And carrying out knowledge object grading setting on subject knowledge, wherein each knowledge object is provided with a description unit as a learning inlet and a test unit as a learning outlet, learning time of a user is obtained according to a time difference value of the inlet and the outlet, and the knowledge quantity of the current knowledge object is calculated according to the learning time of all achieved users, so that quantitative representation of the subject knowledge object is obtained.
Example 2
This example provides a method for calculating the amount of knowledge of subject knowledge, which is different from example 1 in that the method is further defined by TaCalculating to obtain knowledge quantity Q of corresponding knowledge objectaThe specific method comprises the following steps:
illustratively, the present embodiment establishes three hierarchical relationships, one parent knowledge object U, U comprising one description unit SuN primary knowledge units ZiAnd a test unit Fu(ii) a N secondary knowledge objects, i.e. each primary knowledge unit ZiFrom a secondary perspective, are secondary knowledge objects, each of which includes a pair ZiDescription unit S for carrying out the descriptionZiA test unit FZiAnd M secondary knowledge units Zij(ii) a M three-level knowledge objects, i.e. each two-level knowledge unit ZijFrom a tertiary perspective, are three-level knowledge objects, each of which includes a pair ZijDescription unit for carrying out the description
Figure GDA0002804758700000091
A test unit
Figure GDA0002804758700000092
And P three-level knowledge units
Figure GDA0002804758700000093
The knowledge quantity calculation method of the secondary knowledge object comprises the following steps: by means of a secondary knowledge unit ZijTest cell in (i.e., three-level knowledge object)
Figure GDA0002804758700000094
Testing students to obtain their score AxAnd the total score A of the testmThe ratio gamma is the student pair ZijAchievement degree of learning.
Knowledge quantity of the second level knowledge unit (i.e. the third level knowledge object): suppose there are n student pairs two-level knowledge units ZijLearning is carried out, tests are carried out, and the learning time and the test results of the n students are recorded. Setting the threshold value of achievement degree for grasping the secondary knowledge unit as muij(0.6≤μijLess than or equal to 1), that is, the achievement degree of a student is not less than muijThis indicates that the student mastered the knowledge unit. If there is mnThe students have mastered the knowledge unit, and the learning time is Tij,1,Tij,2,Tij,3,…,
Figure GDA0002804758700000095
Then the secondary knowledge unit ZijIs defined as:
Figure GDA0002804758700000096
Figure GDA0002804758700000101
wherein QijAnd TijWherein ij are all ZijThe sequence number value of the knowledge unit is reflected on the expression mode of the knowledge unit.
Knowledge quantity of primary knowledge unit (i.e. secondary knowledge object):
achievement degree of the primary knowledge unit: by a primary knowledge unit ZiMeasure inTest cell FZiTesting students, score AxAnd the total score A of the testmThe ratio gamma is the student pair ZiAchievement degree of learning.
Knowledge quantity of the primary knowledge unit: consider a primary knowledge unit ZiAll MiA second level knowledge unit Zi1，Zi2，…,
Figure GDA0002804758700000102
The corresponding knowledge amounts are respectively Qi1，Qi2,…,
Figure GDA0002804758700000103
And (4) showing. On the other hand, assume that there are n students paired with primary knowledge unit ZiLearning is carried out, tests are carried out, and the learning time and the test results of the n students are recorded. Setting the threshold value of achievement degree for grasping the primary knowledge unit as mui(0.6≤μiLess than or equal to 1), that is, the achievement degree of a student is not less than muiThis indicates that the student mastered the knowledge unit. If there is mxThe student grasps the knowledge unit ZiThe corresponding learning time is Ti,1,Ti,2,Ti,3,…,
Figure GDA0002804758700000104
Then the primary knowledge unit ZiIs defined as:
Figure GDA0002804758700000105
wherein the content of the first and second substances,
Figure GDA0002804758700000106
a ═ i, and Q denotes the sequence number of the knowledge objectijKnowledge quantity, σ, of a knowledge object of level X +1 belonging to a current knowledge object of level X1And σ2Are all weight coefficients, σ1i+σ2i＝1。
Knowledge quantity of subject knowledge (i.e. primary knowledge object U):
achievement degree of subject knowledge: through the test unit FuTesting students, score AxAnd the total score A of the testmThe ratio gamma of (a) is the achievement degree of the student on U learning.
Knowledge amount of subject knowledge: consider all N primary knowledge units Z of subject knowledge U1,Z2,…,ZNThe corresponding knowledge amounts are respectively Q1，Q2,…,QNAnd (4) showing. On the other hand, suppose that n students have learned the subject knowledge U and have performed a test, and the learning time and the test results of the students are recorded. The threshold value of the achievement degree for mastering the subject knowledge is set to be mu (mu is more than 0.6 and less than or equal to 1), namely the achievement degree of a certain student is not less than mu, which indicates that the student masters the subject knowledge. If there is meThe student knows the subject knowledge, and the learning time is Tu,1,Tu,2,Tu,3,…,
Figure GDA0002804758700000111
The knowledge quantity of the subject knowledge U is defined as:
Figure GDA0002804758700000112
wherein the content of the first and second substances,
Figure GDA0002804758700000113
a ═ u, expressed as overall discipline knowledge, QiKnowledge quantity, σ, being a knowledge object belonging to the overall subject knowledge1uAnd σ2uAre all weight coefficients, σ1u+σ2u＝1。
Example 3
The embodiment provides a knowledge amount calculating system of subject knowledge, as shown in fig. 2, including a knowledge object labeling module 201, a description unit monitoring module 202, a test unit monitoring module 203, a learning time calculating module 204, a knowledge amount calculating module 205 and a marking module 206;
a knowledge object labeling module 201, labeling the ID values of the knowledge units in the knowledge object according to the membership between the knowledge objects contained in the subject knowledge, where the ID values include an attribute value, a hierarchy value, and a sequence value; the attribute value defines the attribute of the knowledge unit in the same knowledge object as a description unit S, a knowledge unit Z or a test unit F; the level value is the level X to which the knowledge object belongs, X is 1, 2, 3 … N, the knowledge object with X being 1 level is the whole subject knowledge and is called as a father knowledge object, and the X level knowledge objects with X being more than 1 level are all certain X-1 level knowledge units in certain X-1 level knowledge objects and are called as the inheritance knowledge of the X-1 level knowledge objects; the sequence value is the sequence value of the knowledge units belonging to the same knowledge object;
a description unit monitoring module 202 for monitoring the learning path of the user when the user enters the description unit SaThen, the ID value of the description unit is judged, and the current description unit S is obtainedaAdapted test unit FaThe ID value of (1), sends a monitoring instruction to the test unit monitoring module 203, and at the same time, the learning time calculation module 204 sends a time recording instruction;
a test unit monitoring module 203 for receiving the monitoring instruction and monitoring the test unit F with the corresponding ID completed by the useraThen, sending a calculation instruction to the learning time calculation module 204, and sending a marking instruction to the marking module 206;
a learning time calculation module 204 for receiving a time recording instruction and recording the description unit S of the user entering the knowledge objectaLocal time of day TJAnd receiving a calculation instruction and recording a test unit F for a user to finish the same knowledge objectaLocal time of day TcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
The marking module 206 is configured to receive a marking instruction, and mark a user whose achievement degree γ of the current knowledge object reaches a preset index μ as an achieved user;
the knowledge amount calculation module 205 calls learning for all achieved users of the same knowledge object within a preset time periodTime TaCalculating and updating the knowledge quantity Q of the corresponding knowledge objecta。
Further, the marking module 206 includes a test result obtaining sub-module 207, an achievement degree calculation sub-module 208, and an achievement marking sub-module 209;
a test result obtaining sub-module 207 for receiving the marking instruction and obtaining the test score A obtained by the current user in the test unit in the current knowledge objectxAnd the total test score A of the test unit in the current knowledge objectm；
The achievement calculation module 208 calculates ax/AmCalculating the achievement degree gamma of the current user for the current knowledge object, comparing the gamma with a preset threshold value mu, and sending a marking instruction to the achievement marking submodule 209 when the comparison result is that the gamma is not less than mu;
and an achievement marking sub-module 209 for receiving the marking instruction and marking the current user as an achieved user for the current knowledge object.
Since the working principle of the system is similar to that of the method, it is not explained much.
The above detailed description of the knowledge calculation method of subject knowledge provided by the present invention has been provided, and the principle and the embodiments of the present invention are explained herein by using specific examples, and each embodiment is described in a progressive manner. It should be noted that various changes and modifications can be made to the invention by those skilled in the art without departing from the principle of the invention, and these changes and modifications also fall into the protection scope of the claims of the invention.

Claims (5)

1. A method for calculating the amount of knowledge of subject knowledge, comprising the steps of:
s1, dividing the knowledge objects into X levels according to the membership relation among the knowledge objects contained in the subject knowledge, wherein X is 1, 2, 3 … N; each X level comprises one or a plurality of knowledge objects, and each knowledge object comprises a description unit, a plurality of X-level knowledge units and a test unit; the knowledge objects with the level X being 1 are the whole subject knowledge and are called father knowledge objects, and the knowledge objects with the level X being larger than the level 1 are all corresponding knowledge units with the level X-1 in the corresponding knowledge objects with the level X-1 and are called inheritance knowledge of the knowledge objects with the level X-1; unique ID assignment is carried out on the description unit, the knowledge unit and the test unit of each level, and a knowledge object level relation storage file is formed, wherein the ID value comprises an attribute value, a level value and a sequence value;
s2, monitoring user behavior, and when the user enters the description unit S in the knowledge objectaTime, record local time T at the time of entryJAnd completing the test unit F of the same knowledge object at the useraTime, local time T when recording is completedcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
S3, calculating the achievement degree gamma of the user to the corresponding knowledge object, and marking the user as an achieved user aiming at the corresponding knowledge object when the achievement degree gamma of the user reaches a preset threshold value mu;
s4, obtaining the learning time T of all the achieved users aiming at the same knowledge object in the preset time periodaCalculating to obtain the knowledge quantity Q of the corresponding knowledge objecta；
When the knowledge object level X is equal to N, acquiring learning time T of all achieved users aiming at the same knowledge object in a preset time periodaAnd calculating to obtain the knowledge quantity of the corresponding knowledge object, specifically: the number of all agreed users is mnThe number of the main components is one,
Figure FDA0002958831720000011
wherein the content of the first and second substances,
Figure FDA0002958831720000021
a ═ x, which represents the sequence number value of the knowledge object;
when the knowledge object hierarchy X is less than N, acquiring presetLearning time T for all agreed-upon users for the same knowledge object over a period of timeaCalculating to obtain the knowledge quantity Q of the corresponding knowledge objectiThe method specifically comprises the following steps: the number of all agreed users is mwThe current X-level knowledge object comprises t X + 1-level knowledge units, and the knowledge quantity of the X + 1-level knowledge unit is QxIt is shown that,
Figure FDA0002958831720000022
wherein the content of the first and second substances,
Figure FDA0002958831720000023
a ═ i, expressed as the ordinal number value of the knowledge object, σ1And σ2Are all coefficients, σ1+σ2＝1。
2. The method of calculating the amount of knowledge of subject knowledge according to claim 1, wherein the achievement degree γ ═ ax/AmWherein A ismIs the total score of the test unit in the current knowledge object, AxThe test scores obtained in the test cells within the current knowledge object for the current user.
3. The method of calculating the amount of knowledge of subject knowledge according to claim 2, wherein 0.6 < μ ≦ 1.
4. A knowledge quantity calculation system of subject knowledge is characterized by comprising a knowledge object labeling module (201), a description unit monitoring module (202), a test unit monitoring module (203), a learning time calculation module (204), a knowledge quantity calculation module (205) and a marking module (206);
the knowledge object labeling module (201) labels ID values of knowledge contents in the knowledge objects according to the membership relation among the knowledge objects contained in subject knowledge, wherein the ID values comprise attribute values, hierarchy values and sequence values; the attribute value defines the attribute of the knowledge content in the same knowledge object as a description unit S, a knowledge unit Z or a test unit F; the level value is the level X to which the knowledge object belongs, X is 1, 2, 3 … N, the primary knowledge object is a father knowledge object, each X level knowledge unit belongs to the inheritance knowledge of the X level knowledge object, and the level X +1 knowledge object is defined at the angle of the X +1 level; the sequence value is the sequence value of the knowledge units belonging to the same knowledge object;
the description unit monitoring module (202) monitors the learning path of the user, and when the user enters the description unit SaThen, the ID value of the description unit is judged, and the current description unit S is obtainedaAdapted test unit FaThe ID value of (1) sends a monitoring instruction to a test unit monitoring module (203), and a learning time calculation module (204) sends a time recording instruction;
the test unit monitoring module (203) is used for receiving the monitoring instruction and monitoring the test unit F of which the user completes the corresponding IDaWhen the learning time is short, a calculation instruction is sent to a learning time calculation module (204), and a marking instruction is sent to a marking module (206);
the learning time calculation module (204) is used for receiving a time recording instruction and recording the description unit S of the user entering the knowledge objectaLocal time of day TJAnd receiving a calculation instruction and recording a test unit F for a user to finish the same knowledge objectaLocal time of day TcCalculating the learning time T of the user to the corresponding knowledge objecta＝Tc-TJ；
The marking module (206) is used for receiving a marking instruction and marking users with the achievement degree gamma of the current knowledge object reaching a preset index mu as achieved users;
the knowledge amount calculation module (205) calls learning time T for all achieved users of the same knowledge object in a preset time periodaCalculating and updating the knowledge quantity Q of the corresponding knowledge objecta；
When the knowledge object level X is equal to N, acquiring learning time T of all achieved users aiming at the same knowledge object in a preset time periodaCalculating to obtain corresponding knowledge objectsThe knowledge quantity specifically comprises: the number of all agreed users is mnThe number of the main components is one,
Figure FDA0002958831720000031
wherein the content of the first and second substances,
Figure FDA0002958831720000041
a ═ x, which represents the sequence number value of the knowledge object;
when the knowledge object hierarchy X is less than N, acquiring learning time T of all achieved users aiming at the same knowledge object in a preset time periodaCalculating to obtain the knowledge quantity Q of the corresponding knowledge objectiThe method specifically comprises the following steps: the number of all agreed users is mwThe current X-level knowledge object comprises t X + 1-level knowledge units, and the knowledge quantity of the X + 1-level knowledge unit is QxIt is shown that,
Figure FDA0002958831720000042
wherein the content of the first and second substances,
Figure FDA0002958831720000043
a ═ i, expressed as the ordinal number value of the knowledge object, σ1And σ2Are all coefficients, σ1+σ2＝1。
5. The system of knowledge amount computation of disciplinary knowledge according to claim 4, characterized in that said labeling module (206) includes, a test achievement acquisition sub-module (207), an achievement degree operator module (208) and an achievement labeling sub-module (209);
the test result acquisition sub-module (207) is used for receiving the marking instruction and acquiring the test score A acquired by the current user in the test unit in the current knowledge objectxAnd the total test score A of the test unit in the current knowledge objectm；
The achievement degree calculation operator module (208) is used for calculating the achievement degree according to a formula gamma-Ax/AmCalculating the achievement degree gamma of the current user aiming at the current knowledge object, comparing the gamma with a preset threshold value mu, and sending a marking instruction to an achievement marking submodule (209) when the comparison result is that the gamma is not less than mu;
the achievement marking sub-module (209) is used for receiving marking instructions and marking the current user as the achieved user aiming at the current knowledge object.
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