CN116012203B - Teaching resource matching system - Google Patents
Teaching resource matching system Download PDFInfo
- Publication number
- CN116012203B CN116012203B CN202211657748.XA CN202211657748A CN116012203B CN 116012203 B CN116012203 B CN 116012203B CN 202211657748 A CN202211657748 A CN 202211657748A CN 116012203 B CN116012203 B CN 116012203B
- Authority
- CN
- China
- Prior art keywords
- subject
- learning
- scheme
- data analysis
- analysis unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to the technical field of computers, in particular to a teaching resource matching system, which comprises an information storage unit, a learning state recording unit, a teaching resource library, a scheme storage unit and a data analysis unit, wherein the information storage unit, the learning state recording unit, the teaching resource library, the scheme storage unit and the data analysis unit are connected with the learning state recording unit and are used for analyzing the learning effect of teaching resources of subjects distributed by a user according to the learning state information of the subjects of the user, the data processing unit is respectively connected with the data analysis unit and the scheme storage unit and is used for adjusting the teaching resource matching scheme of the user according to the analysis result of the data analysis unit, and the teaching resource matching unit is respectively connected with the scheme storage unit and the teaching resource and is used for matching teaching resources of subjects suitable for the user according to the teaching resource matching scheme of the user, so that the learning resource matching precision of the user is ensured, and the learning efficiency of the user is improved.
Description
Technical Field
The application relates to the technical field of computers, in particular to a teaching resource matching system.
Background
On-line teaching becomes a convenient means for the students to learn at present, however, in the process of the students to learn on line, the problem that the teaching content is not matched with the teaching content of the students exists, and the on-line learning efficiency of the students is seriously affected.
Chinese patent publication No.: the application discloses a matching method, device, equipment and medium of online teaching resources, and relates to the field of artificial intelligence. The specific implementation scheme is as follows: identifying and determining candidate training objects and candidate teaching objects according to the watching history record of the user on the multimedia content in the electronic equipment; pushing online teaching matching requests to candidate training objects and candidate teaching objects, and determining formal training objects and formal teaching objects according to feedback results; and carrying out online teaching matching according to the attributes and states of the formal training objects and the formal teaching objects. According to the embodiment of the application, the user performs bidirectional screening on the multimedia watching record in the electronic equipment, the training object and the teaching object are determined and teaching matching is performed, the technical problem that the on-line teaching resources are difficult to match with the required objects is solved, and further the technical effects of automatically matching the teaching resources for the training object and improving the resource matching efficiency and accuracy are achieved.
Disclosure of Invention
Therefore, the application provides a teaching resource matching system, which is used for solving the problem that the teaching resource matching scheme is not adjusted according to the learning effect of students on matched learning resources in the prior art.
In order to achieve the above object, the present application provides a teaching resource matching system, including:
the information storage unit is used for storing basic information of each user, wherein the basic information comprises age, gender and age group information where the user is located;
the learning state recording unit is used for recording learning state information of each user, wherein the learning state information comprises learning duration of each subject teaching content of the user and exercise achievements corresponding to the subject teaching content;
a teaching resource library for storing allocable teaching resource information;
the scheme storage unit is connected with the information storage unit and used for storing teaching resource matching schemes of subjects of the users, wherein the teaching resource matching schemes comprise knowledge point density and learning duration of the subjects;
the data analysis unit is connected with the learning state recording unit and used for analyzing the learning effect of the teaching resources of the subjects distributed by the user according to the learning state information of the subjects;
the data processing unit is respectively connected with the data analysis unit and the scheme storage unit and is used for adjusting the teaching resource matching scheme of the user according to the analysis result of the data analysis unit;
the teaching resource matching unit is respectively connected with the scheme storage unit and the teaching resource and is used for matching teaching resources of proper subjects for the user according to the teaching resource matching scheme of the user;
the data analysis unit is also connected with the scheme storage unit and the information storage unit and is used for determining teaching resource matching schemes of the subjects of the user according to the average knowledge point density and the average learning duration of the subjects in the teaching resource matching schemes of the users with the same basic information;
the data analysis unit determines a scheme adjustment period of the teaching resource matching scheme according to the knowledge point density of each subject in the teaching resource matching scheme of the user and the preset knowledge point density,
wherein the data analysis unit is provided with a first preset knowledge point density D1, a second preset knowledge point density D2, a first scheme adjustment period R1, a second scheme adjustment period R2 and a third scheme adjustment period R3, D1 is less than D2, R1 is more than R2 is more than R3, the knowledge point density of the subject is marked as D,
if D is less than D1, the data analysis unit determines that the scheme adjustment period is R1;
if D1 is less than or equal to D2, the data analysis unit determines that the scheme adjustment period is R2;
if D2 is less than or equal to D, the data analysis unit determines that the scheme adjustment period is R3;
the data analysis unit acquires first learning state information of each subject in a current scheme adjustment period when the user completes teaching contents of one scheme adjustment period Ri, calculates a scheme adjustment parameter Ga according to the following formula,
,
wherein Ta represents a first average learning duration of the subject in the first learning state information, T0 represents a preset learning duration, qt represents an influence weight of the average learning duration of the subject on the first adjustment parameter Ga, wa represents a first average problem score of the subject in the first learning state information, W0 represents a standard problem score of the subject, and Qw represents an influence weight of the first average problem score of the subject on the first adjustment parameter Ga;
the data analysis unit determines whether to adjust the teaching resource matching scheme of the subject according to the comparison result of the first adjustment parameter Ga and the scheme comparison parameter Ga0,
if Ga is less than or equal to Ga0, the data analysis unit determines to adjust the teaching resource matching scheme of the subject;
if Ga is more than Ga0, the data analysis unit determines that the teaching resource matching scheme of the subject is not adjusted.
Further, when determining to adjust the teaching resource scheme of the subject, the data analysis unit calculates a first score difference Δwa between the standard exercise score of the subject and the first average score, Δwa=w0-Wa, and determines to adjust the knowledge point density of the subject according to a comparison result between the first score difference Δwa and a preset score difference,
wherein the data processing unit is provided with a first preset achievement difference DeltaW 1, a second preset achievement difference DeltaW 2, a first knowledge point density adjustment coefficient Kv1 and a second knowledge point density adjustment coefficient Kv2, deltaW 1 < DeltaW2, kv2 < Kv1 < 1,
if DeltaWa < DeltaW1, the data analysis unit determines to adjust the learning duration of the subject;
if DeltaW 1 is less than or equal to DeltaWa < DeltaW2, the data analysis unit determines to adjust the knowledge point density of the subject by using Kv 1;
if DeltaW 2 is less than or equal to DeltaWa, the data analysis unit determines to adjust the knowledge point density of the subject by using Kv 2;
if the data analysis unit determines that the x-th knowledge point density adjustment coefficient Kvx is used to adjust the knowledge point density of the subject, the data processing unit marks the knowledge point density of the subject as V1, marks the adjusted knowledge point density of the subject as V2, and sets v2=v1× Kvx, and x=1, 2.
Further, when the data analysis unit determines to adjust the learning duration of the subject, calculating a first time duration ratio delta Ta of the first average learning duration Ta to the preset learning duration T0, wherein delta ta=ta/T0, determining to adjust the learning duration of the subject according to a comparison result of the first time duration ratio delta Ta to the preset duration ratio,
wherein the data analysis unit is provided with a first preset time length ratio delta T1, a second preset time length ratio delta T2, a first learning time length adjustment coefficient Kt1, a second learning time length adjustment coefficient Kt2 and a third learning time length adjustment coefficient Kt3, delta T1 < [ delta ] T2, kt1 < Kt2 < Kt3 < 1,
if delta Ta < deltaT 1, the data processing unit determines to adjust the learning duration of the subject by adopting Kt 1;
if DeltaT 1 is less than or equal to DeltaTa < DeltaT2, the data processing unit determines to adopt Kt2 to adjust the learning duration of the subject;
if delta T2 is less than or equal to delta Ta, the data processing unit determines to adjust the learning duration of the subject by using Kt 3;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to adjust the learning duration of the subject, the data processing unit marks the learning duration of the subject as T1, marks the adjusted learning duration of the subject as T2, and sets t2=t1× Kty, and y=1, 2, and 3.
Further, the data analysis unit acquires second learning state information of each subject in a current scheme adjustment period and third learning state information of each subject in a previous scheme adjustment period when the user completes teaching contents of one scheme adjustment period Ri, calculates scheme period adjustment parameters Gb according to the following formula,
,
tb represents a second average learning duration of the subject in the second learning state information, tc represents a third average learning duration of the subject in the third learning state information, wb represents a second average problem score of the subject in the second learning state information, and Wc represents a third average problem score of the subject in the third learning state information.
Further, the data analysis unit determines whether to readjust the teaching resource matching scheme of the subject according to the comparison result of the scheme period adjustment parameter Gb and the preset scheme period comparison parameter,
wherein the data analysis unit is provided with a first preset scheme period comparison parameter Gb1, a second preset scheme period comparison parameter Gb2 and a third knowledge point density adjustment coefficient Kv3, kv3 is more than 1 and less than 1.3,
if Gb is smaller than Gb1, the data analysis unit determines that the knowledge point density of the subject is readjusted by adopting Kv 2;
if Gb1 is less than or equal to Gb2, the data analysis unit determines that Kv3 is adopted to readjust the knowledge point density of the subject;
if Gb2 is less than or equal to Gb, the data analysis unit determines to readjust the learning duration of the subject;
if the data analysis unit determines that the x-th knowledge point density adjustment coefficient Kvx is used for readjusting the knowledge point density of the subject, the data processing unit marks the readjusted knowledge point density of the subject as V3, and sets v3=ve× Kvx, e=1, 2, and x=2, 3.
Further, when determining to readjust the learning duration of the subject, the data analysis unit calculates a second duration ratio Δtb of the second average learning duration Tb to the third average learning duration Tc, Δtb=tb/T0, determines to adjust the learning duration of the subject according to a comparison result of the second duration time ratio Δtb to a preset duration ratio,
wherein the data analysis unit is provided with a fourth learning duration adjustment coefficient Kt4, kt4 is more than 1 and less than 1.3,
if DeltaTb < DeltaT1, the data processing unit determines to use Kt2 to readjust the learning duration of the subject;
if DeltaT1 is less than or equal to DeltaTb < DeltaT2, the data processing unit determines to readjust the learning duration of the subject by using Kt 3;
if delta T2 is less than or equal to delta Tb, the data processing unit determines to readjust the learning duration of the subject by adopting Kt 4;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to readjust the learning duration of the subject, the readjusted learning duration of the subject is denoted as T3, and t3=tu× Kty, y=2, 3,4, u=1, 2 are set.
Compared with the prior art, the method has the advantages that the data analysis unit analyzes the learning effect of the teaching resources of the subjects distributed by the user according to the learning state information of the subjects of the user, the data processing unit adjusts the teaching resource matching scheme of the user according to the analysis result of the data analysis unit after the analysis result is obtained, and finally the teaching resource matching unit matches the teaching resources of the subjects suitable for the user according to the teaching resource matching scheme of the user, so that the accuracy of teaching resource matching is ensured, and the learning efficiency of the user is improved.
Further, the data analysis unit is further connected to the scheme storage unit and the information storage unit, and is configured to determine a teaching resource matching scheme of each subject of the user according to an average knowledge point density and an average learning duration of each subject in the teaching resource matching scheme of each user with the same basic information, so that accuracy of preliminary matching of teaching resources for new users is improved.
Further, the data analysis unit determines a scheme adjustment period of the teaching resource matching scheme according to the knowledge point density of each subject in the teaching resource matching scheme of the user and the preset knowledge point density, so that the accuracy of determining the adjustment period of the teaching resource matching scheme is ensured.
Further, the data analysis unit acquires first learning state information of each subject in a current scheme adjustment period when the user completes teaching content of one scheme adjustment period, calculates first adjustment parameters of teaching resource matching schemes of the subjects, and determines whether to adjust the teaching resource matching schemes of the subjects according to comparison results of the first adjustment parameters and preset scheme adjustment comparison parameters, so that accuracy of matching teaching resources for the user is improved.
Further, when the data analysis unit determines to adjust the teaching resource scheme of the subject, a first score difference value between the standard exercise score of the subject and the first average score is calculated, and the density of the knowledge points of the subject is determined to be adjusted according to a comparison result of the first score difference value and a preset score difference value, so that the accuracy of matching teaching resources for users is further improved.
Further, when the data analysis unit determines to adjust the learning duration of the subject, a first time length ratio of the first average learning duration to the preset learning duration is calculated, and the density of knowledge points of the subject is determined to be adjusted according to a comparison result of the first time length ratio and the preset time length ratio, so that the accuracy of matching teaching resources for users is further improved.
Further, the data analysis unit acquires the second learning state information of each subject in the current scheme adjustment period and the third learning state information of each subject in the previous scheme adjustment period when the user completes the teaching content of one scheme adjustment period, and calculates scheme period adjustment parameters, so that scientificity of teaching resource matching effect evaluation is ensured.
Further, the data analysis unit determines whether to readjust the teaching resource matching scheme of the subject according to the comparison result of the scheme period adjustment parameter and the preset scheme period comparison parameter, so that the accuracy of matching the teaching resource for the user is further improved.
Further, when the data analysis unit determines to readjust the learning duration of the subject, a second duration ratio of the second average learning duration to the third average learning duration is calculated, and the readjustment of the learning duration of the subject is determined according to a comparison result of the second duration ratio and a preset duration ratio, so that the accuracy of matching teaching resources of the user is ensured, and the learning efficiency of the user is improved.
Drawings
Fig. 1 is a schematic structural diagram of a teaching resource matching system according to the embodiment of the application.
Detailed Description
In order that the objects and advantages of the application will become more apparent, the application will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Preferred embodiments of the present application are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present application, and are not intended to limit the scope of the present application.
It should be noted that, in the description of the present application, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application.
Furthermore, it should be noted that, in the description of the present application, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a teaching resource matching system according to an embodiment of the application.
The teaching resource matching system provided in this embodiment includes:
the information storage unit is used for storing basic information of each user, wherein the basic information comprises age, gender and year group information;
the learning state recording unit is used for recording learning state information of each user, wherein the learning state information comprises learning duration of each subject teaching content of the user and problem achievements corresponding to the subject teaching content;
a teaching resource library for storing allocable teaching resource information;
the scheme storage unit is connected with the information storage unit and used for storing teaching resource matching schemes of each subject of each user, wherein the teaching resource matching schemes comprise knowledge point density and learning duration of the subject;
the data analysis unit is connected with the learning state recording unit and used for analyzing the learning effect of the teaching resources of the subjects distributed by the user according to the learning state information of the subjects of the user;
the data processing unit is respectively connected with the data analysis unit and the scheme storage unit and is used for adjusting the teaching resource matching scheme of the user according to the analysis result of the data analysis unit;
and the teaching resource matching unit is respectively connected with the scheme storage unit and the teaching resources and is used for matching the teaching resources of the proper subjects for the user according to the teaching resource matching scheme of the user.
Specifically, the data analysis unit is further connected with the scheme storage unit and the information storage unit, and is used for determining the teaching resource matching scheme of each subject of the user according to the average knowledge point density and the average learning duration of each subject in the teaching resource matching scheme of each user with the same or similar basic information.
Specifically, the data analysis unit determines a scheme adjustment period of the teaching resource matching scheme according to the knowledge point density of each subject in the teaching resource matching scheme of the user and the preset knowledge point density,
wherein the data analysis unit is provided with a first preset knowledge point density D1, a second preset knowledge point density D2, a first scheme adjustment period R1, a second scheme adjustment period R2 and a third scheme adjustment period R3, D1 is less than D2, R1 is more than R2 is more than R3, the knowledge point density of subjects is recorded as D,
if D is less than D1, the data analysis unit determines that the scheme adjustment period is R1;
if D1 is less than or equal to D2, the data analysis unit determines that the scheme adjustment period is R2;
if D2 is less than or equal to D, the data analysis unit determines that the scheme adjustment period is R3.
Specifically, the data analysis unit acquires first learning state information of each department in the current scheme adjustment period when the user completes the teaching content of one scheme adjustment period Ri, calculates scheme adjustment parameters Ga of the teaching resource matching scheme of the department according to the following formula,
,
wherein Ta represents a first average learning duration of subjects in the first learning state information, T0 represents a preset learning duration, qt represents an influence weight of the average learning duration of the subjects on the first adjustment parameter Ga, wa represents a first average problem score of the subjects in the first learning state information, W0 represents a standard problem score of the subjects, and Qw represents an influence weight of the first average problem score of the subjects on the first adjustment parameter Ga.
Further, the data analysis unit determines whether to adjust the teaching resource matching scheme of the subject according to the comparison result of the first adjustment parameter Ga and the scheme comparison parameter Ga0,
if Ga is less than or equal to Ga0, the data analysis unit determines to adjust the teaching resource matching scheme of the subject;
if Ga is more than Ga0, the data analysis unit determines that the teaching resource matching scheme of the subject is not adjusted.
Specifically, when determining to adjust the teaching resource scheme of the subject, the data analysis unit calculates a first score difference Δwa between the standard exercise score and the first average score of the subject, Δwa=w0-Wa, and determines to adjust the knowledge point density of the subject according to the comparison result between the first score difference Δwa and the preset score difference,
wherein the data processing unit is provided with a first preset achievement difference DeltaW 1, a second preset achievement difference DeltaW 2, a first knowledge point density adjustment coefficient Kv1 and a second knowledge point density adjustment coefficient Kv2, deltaW 1 < DeltaW2, kv2 < Kv1 < 1,
if DeltaWa < DeltaW1 data analysis unit determines to adjust the learning duration of subjects;
if DeltaW 1 is less than or equal to DeltaWa < DeltaW2, the data analysis unit determines to adjust the density of knowledge points of subjects by using Kv 1;
if DeltaW 2 is less than or equal to DeltaWa, the data analysis unit determines that Kv2 is adopted to adjust the density of knowledge points of subjects;
if the data analysis unit determines that the x-th knowledge point density adjustment coefficient Kvx is used to adjust the knowledge point density of the subject, the data processing unit marks the knowledge point density of the subject as V1, marks the adjusted knowledge point density of the subject as V1, and sets v2=v1× Kvx, and x=1, 2.
Specifically, when determining to adjust the learning duration of the subject, the data analysis unit calculates a first time duration ratio delta Ta of a first average learning duration Ta to a preset learning duration T0, delta ta=ta/T0, determines to adjust the learning duration of the subject according to a comparison result of the first time duration ratio delta Ta to the preset duration ratio,
wherein the data analysis unit is provided with a first preset time length ratio delta T1, a second preset time length ratio delta T2, a first learning time length adjustment coefficient Kt1, a second learning time length adjustment coefficient Kt2 and a third learning time length adjustment coefficient Kt3, delta T1 < [ delta ] T2,0.5 < Kt1 < Kt2 < Kt3 < 1,
if delta Ta < deltaT 1, the data processing unit determines to adopt Kt1 to adjust the learning duration of the subject;
if DeltaT 1 is less than or equal to DeltaTa < DeltaT2, the data processing unit determines to adopt Kt2 to adjust the learning duration of the subjects;
if delta T2 is less than or equal to delta Ta, the data processing unit determines to adopt Kt3 to adjust the learning duration of subjects;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to adjust the learning duration of the subject, the data processing unit marks the learning duration of the subject as T1, marks the adjusted learning duration of the subject as T2, and sets t2=t1× Kty, and y=1, 2, and 3.
Specifically, the data analysis unit acquires second learning state information of each department in the current scheme adjustment period and third learning state information of each department in the previous scheme adjustment period when the user completes the teaching content of one scheme adjustment period Ri, calculates a scheme period adjustment parameter Gb according to the following formula,
,
tb represents a second average learning duration of subjects in the second learning state information, tc represents a third average learning duration of subjects in the third learning state information, wb represents a second average problem score of subjects in the second learning state information, and Wc represents a third average problem score of subjects in the third learning state information.
Specifically, the data analysis unit determines whether to readjust the teaching resource matching scheme of the subject according to the comparison result of the scheme period adjustment parameter Gb and the preset scheme period comparison parameter,
wherein the data analysis unit is provided with a first preset scheme period comparison parameter Gb1, a second preset scheme period comparison parameter Gb2 and a third knowledge point density adjustment coefficient Kv3, kv3 is more than 1 and less than 1.3,
if Gb is smaller than Gb1, the data analysis unit determines that Kv2 is adopted to readjust the knowledge point density of the subject;
if Gb1 is less than or equal to Gb2, the data analysis unit determines that Kv3 is adopted to readjust the knowledge point density of the subject;
if Gb2 is less than or equal to Gb, the data analysis unit determines to readjust the learning duration of the subject;
if the data analysis unit determines that the knowledge point density of the subject is readjusted by using the x-th knowledge point density adjustment coefficient Kvx, the data processing unit marks the readjusted knowledge point density of the subject as V3, and sets v3=ve× Kvx, e=1, 2, and x=2, 3.
Specifically, when determining to readjust the learning duration of the subject, the data analysis unit calculates a second duration ratio delta Tb of a second average learning duration Tb to a third average learning duration Tc, wherein delta tb=tb/T0, determines to adjust the learning duration of the subject according to a comparison result of the second duration time ratio delta Tb to a preset duration ratio,
wherein the data analysis unit is provided with a fourth learning duration adjustment coefficient Kt4, kt4 is more than 1 and less than 1.3,
if DeltaTb < DeltaT1, the data processing unit determines to use Kt2 to readjust the learning duration of the subject;
if DeltaT1 is less than or equal to DeltaTb < DeltaT2, the data processing unit determines to readjust the learning duration of the subject by using Kt 3;
if delta T2 is less than or equal to delta Tb, the data processing unit determines to adopt Kt4 to readjust the learning duration of the subject;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to readjust the learning duration of the subject, the readjusted learning duration of the subject is denoted as T3, and t3=tu× Kty, y=2, 3,4, u=1, 2 are set.
Thus far, the technical solution of the present application has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present application is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present application, and such modifications and substitutions will be within the scope of the present application.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application; various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (6)
1. A teaching resource matching system, comprising:
the information storage unit is used for storing basic information of each user, wherein the basic information comprises age, gender and age group information where the user is located;
the learning state recording unit is used for recording learning state information of each user, wherein the learning state information comprises learning duration of each subject teaching content of the user and exercise achievements corresponding to the subject teaching content;
a teaching resource library for storing allocable teaching resource information;
the scheme storage unit is connected with the information storage unit and used for storing teaching resource matching schemes of subjects of the users, wherein the teaching resource matching schemes comprise knowledge point density and learning duration of the subjects;
the data analysis unit is connected with the learning state recording unit and used for analyzing the learning effect of the teaching resources of the subjects distributed by the user according to the learning state information of the subjects;
the data processing unit is respectively connected with the data analysis unit and the scheme storage unit and is used for adjusting the teaching resource matching scheme of the user according to the analysis result of the data analysis unit;
the teaching resource matching unit is respectively connected with the scheme storage unit and the teaching resource library and is used for matching teaching resources of proper subjects for the user according to the teaching resource matching scheme of the user;
the data analysis unit is also connected with the scheme storage unit and the information storage unit and is used for determining teaching resource matching schemes of the subjects of the user according to the average knowledge point density and the average learning duration of the subjects in the teaching resource matching schemes of the users with the same basic information;
the data analysis unit determines a scheme adjustment period of the teaching resource matching scheme according to the knowledge point density of each subject in the teaching resource matching scheme of the user and the preset knowledge point density,
wherein the data analysis unit is provided with a first preset knowledge point density D1, a second preset knowledge point density D2, a first scheme adjustment period R1, a second scheme adjustment period R2 and a third scheme adjustment period R3, D1 is less than D2, R1 is more than R2 is more than R3, the knowledge point density of the subject is marked as D,
if D is less than D1, the data analysis unit determines that the scheme adjustment period is R1;
if D1 is less than or equal to D2, the data analysis unit determines that the scheme adjustment period is R2;
if D2 is less than or equal to D, the data analysis unit determines that the scheme adjustment period is R3;
the data analysis unit acquires first learning state information of each subject in a current scheme adjustment period when the user completes teaching contents of one scheme adjustment period Ri, calculates a scheme first adjustment parameter Ga according to the following formula,
,
wherein Ta represents a first average learning duration of the subject in the first learning state information, T0 represents a preset learning duration, qt represents an influence weight of the average learning duration of the subject on the first adjustment parameter Ga, wa represents a first average problem score of the subject in the first learning state information, W0 represents a standard problem score of the subject, and Qw represents an influence weight of the first average problem score of the subject on the first adjustment parameter Ga;
the data analysis unit determines whether to adjust the teaching resource matching scheme of the subject according to the comparison result of the first adjustment parameter Ga and the scheme comparison parameter Ga0,
if Ga is less than or equal to Ga0, the data analysis unit determines to adjust the teaching resource matching scheme of the subject;
if Ga is more than Ga0, the data analysis unit determines that the teaching resource matching scheme of the subject is not adjusted.
2. The teaching resource matching system according to claim 1, wherein the data analyzing unit calculates a first achievement difference Δwa of the standard exercise achievement of the subject and the first average exercise achievement when determining to adjust the teaching resource plan of the subject, Δwa=w0-Wa, and determines to adjust the knowledge point density of the subject based on a comparison result of the first achievement difference Δwa with a preset achievement difference,
wherein the data processing unit is provided with a first preset achievement difference DeltaW 1, a second preset achievement difference DeltaW 2, a first knowledge point density adjustment coefficient Kv1 and a second knowledge point density adjustment coefficient Kv2, deltaW 1 < DeltaW2, kv2 < Kv1 < 1,
if DeltaWa < DeltaW1, the data analysis unit determines to adjust the learning duration of the subject;
if DeltaW 1 is less than or equal to DeltaWa < DeltaW2, the data analysis unit determines to adjust the knowledge point density of the subject by using Kv 1;
if DeltaW 2 is less than or equal to DeltaWa, the data analysis unit determines to adjust the knowledge point density of the subject by using Kv 2;
if the data analysis unit determines that the x-th knowledge point density adjustment coefficient Kvx is used to adjust the knowledge point density of the subject, the data processing unit marks the knowledge point density of the subject as V1, marks the adjusted knowledge point density of the subject as V2, and sets v2=v1× Kvx, and x=1, 2.
3. The teaching resource matching system according to claim 2, wherein the data analyzing unit calculates a first time length ratio Δta of the first average learning time length Ta to the preset learning time length T0, Δta=ta/T0, and determines to adjust the learning time length of the subject based on a comparison result of the first time length ratio Δta to the preset time length ratio,
wherein the data analysis unit is provided with a first preset time length ratio delta T1, a second preset time length ratio delta T2, a first learning time length adjustment coefficient Kt1, a second learning time length adjustment coefficient Kt2 and a third learning time length adjustment coefficient Kt3, delta T1 < [ delta ] T2, kt1 < Kt2 < Kt3 < 1,
if delta Ta < deltaT 1, the data processing unit determines to adjust the learning duration of the subject by adopting Kt 1;
if DeltaT 1 is less than or equal to DeltaTa < DeltaT2, the data processing unit determines to adopt Kt2 to adjust the learning duration of the subject;
if delta T2 is less than or equal to delta Ta, the data processing unit determines to adjust the learning duration of the subject by using Kt 3;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to adjust the learning duration of the subject, the data processing unit marks the learning duration of the subject as T1, marks the adjusted learning duration of the subject as T2, and sets t2=t1× Kty, and y=1, 2, and 3.
4. The teaching resource matching system according to claim 3, wherein said data analyzing unit acquires second learning state information of each of said subjects in a current course adjustment period and third learning state information of each of said subjects in a previous course adjustment period when said user completes teaching contents of one course adjustment period Ri, and calculates a course period adjustment parameter Gb according to the following formula,
,
tb represents a second average learning duration of the subject in the second learning state information, tc represents a third average learning duration of the subject in the third learning state information, wb represents a second average problem score of the subject in the second learning state information, and Wc represents a third average problem score of the subject in the third learning state information.
5. The teaching resource matching system according to claim 4, wherein the data analyzing unit determines whether to readjust the teaching resource matching scheme of the subject based on a comparison result of the scheme period adjustment parameter Gb and a preset scheme period comparison parameter,
wherein the data analysis unit is provided with a first preset scheme period comparison parameter Gb1, a second preset scheme period comparison parameter Gb2 and a third knowledge point density adjustment coefficient Kv3, kv3 is more than 1 and less than 1.3,
if Gb is smaller than Gb1, the data analysis unit determines that the knowledge point density of the subject is readjusted by adopting Kv 2;
if Gb1 is less than or equal to Gb2, the data analysis unit determines that Kv3 is adopted to readjust the knowledge point density of the subject;
if Gb2 is less than or equal to Gb, the data analysis unit determines to readjust the learning duration of the subject;
if the data analysis unit determines that the x-th knowledge point density adjustment coefficient Kvx is used for readjusting the knowledge point density of the subject, the data processing unit marks the readjusted knowledge point density of the subject as V3, and sets v3=ve× Kvx, e=1, 2, and x=2, 3.
6. The teaching resource matching system according to claim 5, wherein when determining to readjust the learning duration of the subject, the data analysis unit calculates a second duration ratio Δtb of the second average learning duration Tb to the third average learning duration Tc, Δtb=tb/T0, determines to readjust the learning duration of the subject based on a comparison result of the second duration ratio Δtb to a preset duration ratio,
wherein the data analysis unit is provided with a fourth learning duration adjustment coefficient Kt4, deltaT 1 < DeltaT2, kt4 < 1.3,
if DeltaTb < DeltaT1, the data processing unit determines to use Kt2 to readjust the learning duration of the subject;
if DeltaT1 is less than or equal to DeltaTb < DeltaT2, the data processing unit determines to readjust the learning duration of the subject by using Kt 3;
if delta T2 is less than or equal to delta Tb, the data processing unit determines to readjust the learning duration of the subject by adopting Kt 4;
if the data processing unit determines that the y-th learning duration adjustment coefficient Kty is adopted to readjust the learning duration of the subject, the readjusted learning duration of the subject is denoted as T3, and t3=tu× Kty, y=2, 3,4, u=1, 2 are set.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211657748.XA CN116012203B (en) | 2022-12-22 | 2022-12-22 | Teaching resource matching system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211657748.XA CN116012203B (en) | 2022-12-22 | 2022-12-22 | Teaching resource matching system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116012203A CN116012203A (en) | 2023-04-25 |
CN116012203B true CN116012203B (en) | 2023-09-26 |
Family
ID=86034753
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202211657748.XA Active CN116012203B (en) | 2022-12-22 | 2022-12-22 | Teaching resource matching system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116012203B (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117114940A (en) * | 2023-10-24 | 2023-11-24 | 山东爱书人家庭教育科技有限公司 | Resource matching method, system, device and medium |
CN118153929A (en) * | 2024-05-13 | 2024-06-07 | 山东爱书人家庭教育科技有限公司 | Learning resource allocation method, system, device and readable storage medium |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108647352A (en) * | 2018-05-16 | 2018-10-12 | 深圳市鹰硕技术有限公司 | Teaching is prepared lessons teaching notes generation method and device |
CN109299882A (en) * | 2018-10-11 | 2019-02-01 | 四川生学教育科技有限公司 | A kind of analysis of achievement, diagnosis prediction and pushing learning resource method and platform |
CN110704737A (en) * | 2019-09-29 | 2020-01-17 | 百度在线网络技术(北京)有限公司 | Method, device, equipment and medium for matching online teaching resources |
CN113127731A (en) * | 2021-03-16 | 2021-07-16 | 西安理工大学 | Knowledge graph-based personalized test question recommendation method |
CN113139885A (en) * | 2020-01-16 | 2021-07-20 | 广州致远科教软件有限公司 | Teaching management system and management method thereof |
CN113160009A (en) * | 2021-03-31 | 2021-07-23 | 北京大米科技有限公司 | Information pushing method, related device and computer medium |
CN113222791A (en) * | 2021-04-28 | 2021-08-06 | 泰州学院 | Inorganic chemical course teaching tutoring management method based on big data and artificial intelligence |
CN114282758A (en) * | 2021-11-19 | 2022-04-05 | 珠海读书郎软件科技有限公司 | Recorded and broadcast course learning competition method and device and electronic equipment |
CN114329054A (en) * | 2022-03-09 | 2022-04-12 | 广州华赛数据服务有限责任公司 | Education resource sharing system based on big data |
WO2022082987A1 (en) * | 2020-10-22 | 2022-04-28 | 深圳市鹰硕技术有限公司 | Automatic generation method for multi-subject homework, and apparatus |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7736150B2 (en) * | 2002-06-13 | 2010-06-15 | Pfund Jeffrey A | Module-based education |
-
2022
- 2022-12-22 CN CN202211657748.XA patent/CN116012203B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108647352A (en) * | 2018-05-16 | 2018-10-12 | 深圳市鹰硕技术有限公司 | Teaching is prepared lessons teaching notes generation method and device |
CN109299882A (en) * | 2018-10-11 | 2019-02-01 | 四川生学教育科技有限公司 | A kind of analysis of achievement, diagnosis prediction and pushing learning resource method and platform |
CN110704737A (en) * | 2019-09-29 | 2020-01-17 | 百度在线网络技术(北京)有限公司 | Method, device, equipment and medium for matching online teaching resources |
CN113139885A (en) * | 2020-01-16 | 2021-07-20 | 广州致远科教软件有限公司 | Teaching management system and management method thereof |
WO2022082987A1 (en) * | 2020-10-22 | 2022-04-28 | 深圳市鹰硕技术有限公司 | Automatic generation method for multi-subject homework, and apparatus |
CN113127731A (en) * | 2021-03-16 | 2021-07-16 | 西安理工大学 | Knowledge graph-based personalized test question recommendation method |
CN113160009A (en) * | 2021-03-31 | 2021-07-23 | 北京大米科技有限公司 | Information pushing method, related device and computer medium |
CN113222791A (en) * | 2021-04-28 | 2021-08-06 | 泰州学院 | Inorganic chemical course teaching tutoring management method based on big data and artificial intelligence |
CN114282758A (en) * | 2021-11-19 | 2022-04-05 | 珠海读书郎软件科技有限公司 | Recorded and broadcast course learning competition method and device and electronic equipment |
CN114329054A (en) * | 2022-03-09 | 2022-04-12 | 广州华赛数据服务有限责任公司 | Education resource sharing system based on big data |
Non-Patent Citations (1)
Title |
---|
中学生在线学习行为以及影响因素分析;薛含笑;社会科学二辑;全文 * |
Also Published As
Publication number | Publication date |
---|---|
CN116012203A (en) | 2023-04-25 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN116012203B (en) | Teaching resource matching system | |
CN110929515B (en) | Reading understanding method and system based on cooperative attention and adaptive adjustment | |
US20200380989A1 (en) | Electronic transcription job market | |
US9886956B1 (en) | Automated delivery of transcription products | |
CN107256267A (en) | Querying method and device | |
US9971940B1 (en) | Automatic learning of a video matching system | |
CN116187863B (en) | Online digital teaching plan generation method and system based on big data cloud platform | |
WO2019169795A1 (en) | Attention degree evaluation method and apparatus for network teaching | |
CN111460109B (en) | Method and device for generating abstract and dialogue abstract | |
CN109862062A (en) | Content uploading management method and device, electronic equipment and storage medium | |
US20230137209A1 (en) | Counterfactual Text Stylization | |
CN105100164A (en) | Network service recommendation method and device | |
CN107957988A (en) | For determining the method, apparatus and electronic equipment of data exception reason | |
Huang | Utilizing response times in cognitive diagnostic computerized adaptive testing under the higher‐order deterministic input, noisy ‘and’gate model | |
CN116415059A (en) | Method, electronic device and computer program product for recommending content | |
CN112906376A (en) | Self-adaptive matching user English learning text pushing system and method | |
CN110781929B (en) | Credit prediction model training method, prediction method and device, medium and equipment | |
CN111198669A (en) | Volume adjusting system for computer | |
CN114721326B (en) | Marketing inspection information processing method and device based on deep learning algorithm | |
Wojtak et al. | Consistent extinction model for type Ia supernovae in Cepheid-based calibration galaxies and its impact on H 0 | |
KR102089725B1 (en) | Method and apparatus for mutual learning based on image using learning motivation index | |
CN111626881B (en) | Annuity combined risk management system, annuity combined risk management method, annuity combined risk management server and storage medium | |
US8880823B2 (en) | Information processing system, information processing apparatus, and non-transitory computer readable medium storing information processing program | |
CN107785023A (en) | Voiceprint identification device and voiceprint identification method thereof | |
US11093846B2 (en) | Rating model generation |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |