CN112465227A - Teaching data acquisition method and device - Google Patents

Teaching data acquisition method and device Download PDF

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CN112465227A
CN112465227A CN202011373941.1A CN202011373941A CN112465227A CN 112465227 A CN112465227 A CN 112465227A CN 202011373941 A CN202011373941 A CN 202011373941A CN 112465227 A CN112465227 A CN 112465227A
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class
data
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王枫
马镇筠
谢恩
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Beijing Love Theory Technology Co ltd
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Beijing Love Theory Technology Co ltd
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    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
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Abstract

The embodiment of the application provides a method and a device for acquiring teaching materials, which relate to the technical field of data processing, and the method for acquiring the teaching materials comprises the following steps: acquiring an initial teaching plan template selected by a target user from a preset teaching plan library; applying the initial teaching plan template to actual teaching of an actual learning class, and acquiring class attendance data of the actual learning class and lecture data of a target user after a preset time period; processing class attendance data and lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class; and acquiring a teaching plan template and teaching data matched with the class grade from a preset teaching plan library, wherein the teaching data comprises the teaching plan template and the teaching data. By implementing the implementation mode, appropriate teaching materials can be obtained according to the actual learning level of the class of teaching, so that the teaching efficiency and teaching efficiency of teachers are improved.

Description

Teaching data acquisition method and device
Technical Field
The application relates to the technical field of data processing, in particular to a teaching data acquisition method and device.
Background
On-line teaching is widely applied to the course preparation and teaching of teachers as a novel teaching mode. The prior teaching material recommending method generally recommends corresponding teaching materials according to teaching subjects for teachers to use in class. However, in practice, it is found that there are many different teaching materials for the same teaching topic, and it is difficult for the teacher to select a suitable teaching material, the efficiency of preparing lessons is low, and the practical learning level of the class of the teaching cannot be considered, and the teaching efficiency of the teacher is reduced.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for obtaining teaching materials, which can obtain suitable teaching materials according to the actual learning level of a class of teaching, thereby improving the efficiency of preparing lessons and the teaching efficiency of teachers.
A first aspect of an embodiment of the present application provides a method for acquiring lecture materials, including:
acquiring an initial teaching plan template selected by a target user from a preset teaching plan library;
applying the initial teaching plan template to actual teaching of an actual learning class, and acquiring class attendance data of the actual learning class and lecture data of the target user after a preset time period;
processing the class attendance data and the lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class;
and acquiring a teaching plan template and teaching data matched with the class grade from the preset teaching plan library, wherein the teaching data comprises the teaching plan template and the teaching data.
In the implementation process, the method can preferentially obtain an initial teaching plan template, and then determines the class condition and the lecture data of an actual learning class according to the actual application of the initial teaching plan template, so that the method can determine the class grade of the class according to the class condition and the lecture data, and can match a more appropriate teaching plan template and teaching data according to the class grade, so that a teacher can determine the teaching mode of each link according to the teaching data and complete the whole lecture process according to the teaching plan template. Therefore, by implementing the implementation mode, the most appropriate teaching materials can be obtained according to the actual situation, so that the teaching materials can better accord with the actual learning level of the class of the teaching, the learning efficiency of the learner is improved, and the teacher can be facilitated to carry out corresponding lesson preparation and teaching.
Further, the method further comprises:
acquiring teaching plan data in a preset teaching time period, and acquiring class data corresponding to the teaching plan data;
constructing a class prediction model according to the class attendance data;
generating teaching plan templates according to the teaching plan data, and determining class grade labels corresponding to the teaching plan templates according to the class lesson data;
and generating a preset teaching plan library according to the teaching plan template and the class grade label.
In the implementation process, before the teaching materials are obtained, the method can preferentially obtain teaching plan data and class data corresponding to the teaching plan data, meanwhile, a class prediction model is built according to the class data, class labels corresponding to the teaching plan template are determined according to the teaching plan data and the teaching class receipts, and a teaching database is further generated according to the teaching plan template and the class labels. Therefore, by implementing the implementation mode, the class prediction model and the teaching database can be established in advance, the class prediction can be performed according to the class prediction model subsequently, and the teaching material can be determined according to the prediction result, so that the acquired teaching material can be more accurate.
Further, the constructing a class prediction model according to the class attendance data comprises:
acquiring an original neural network model;
and training the original neural network model through the class attendance data to obtain a class prediction model.
In the implementation process, the method can construct the level prediction model according to the neural network model, so that the level prediction model has higher prediction precision, and the precision of obtaining the whole teaching data is improved.
Further, the generating a teaching plan template according to the teaching plan data includes:
acquiring teaching knowledge point data in the preset teaching time period and teaching time corresponding to the teaching knowledge point data according to the teaching plan template;
generating an initial template according to the teaching knowledge point data and the teaching time;
and disassembling the initial template according to course units to obtain a teaching plan template comprising independent teaching links.
In the implementation process, the method determines knowledge points and teaching time according to the lesson preparation template, then regenerates an initial template according to the knowledge points and the teaching time, and further disassembles the initial template according to the course units to obtain the teaching plan template comprising independent teaching links. Therefore, by the implementation of the implementation mode, the teaching plan template can be generated in a self-adaptive mode according to the lesson preparation template, and the obtaining effect of the teaching plan template is improved.
Further, the acquiring teaching plan data in a preset teaching time period includes:
determining a template teacher and acquiring teaching knowledge points of the template teacher in a preset teaching time period;
acquiring teaching materials corresponding to the teaching knowledge points;
acquiring use habit data of the template teacher giving lessons by using the teaching materials in the preset teaching time period;
and generating teaching plan data according to the teaching knowledge points, the teaching materials and the use habit data.
In the implementation process, the method can generate teaching plan data according to the teaching data and the teaching habits of the template teachers, so that the teaching plan data is more pertinent, and the whole teaching data is better in obtaining effect.
Further, the acquiring class attendance data corresponding to the teaching plan data includes:
acquiring the target class of teaching taught by the template teacher in the preset teaching time period;
acquiring class learner score information corresponding to the target teaching class;
determining the class grade of each target class according to the grade learner score information;
and generating class attendance data according to the class of the target lecture, the class learner score information and the class grade.
In the implementation process, the method can generate class lesson data according to the class learner score information and the class grade of the target class given by the template teacher, so that the class lesson data correspond to the teaching plan data, and the acquisition accuracy of the class lesson data is improved.
A second aspect of the embodiments of the present application provides a teaching material acquiring apparatus, including:
the first acquisition unit is used for acquiring an initial teaching plan template selected by a target user from a preset teaching plan library;
the second acquisition unit is used for applying the initial teaching plan template to the actual teaching of an actual learning class and acquiring class attendance data of the actual learning class and lecture data of the target user after a preset time period;
the prediction unit is used for processing the class attendance data and the lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class;
and the third acquisition unit is used for acquiring teaching plan templates and teaching materials matched with the class grades from the preset teaching plan library, and the teaching materials comprise the teaching plan templates and the teaching materials.
In the implementation process, the teaching material acquisition device can preferentially acquire the initial teaching plan template, then determines the class condition and the teaching data of an actual learning class according to the actual application of the initial teaching plan template, so that the device can determine the class grade of the actual learning class according to the class condition and the teaching data, and can match a more appropriate teaching plan template and teaching material according to the class grade, so that a teacher can determine the teaching mode of each link according to the teaching material, and complete the whole teaching process according to the teaching plan template. Therefore, by implementing the implementation mode, the most appropriate teaching materials can be obtained according to the actual situation, so that the teaching materials can better accord with the actual learning level of the class of the teaching, the learning efficiency of the learner is improved, and the teacher can be facilitated to carry out corresponding lesson preparation and teaching.
Further, the teaching material obtaining device further comprises:
the fourth acquisition unit is used for acquiring teaching plan data in a preset teaching time period;
a fifth acquiring unit, configured to acquire class attendance data corresponding to the teaching plan data;
the construction unit is used for constructing a class prediction model according to the class attendance data;
the determining unit is used for generating teaching plan templates according to the teaching plan data and determining class grade labels corresponding to the teaching plan templates according to the class attendance data;
and the generating unit is used for generating a preset teaching plan library according to the teaching plan template and the class grade labels.
In the implementation process, the teaching data acquisition device can pre-establish a class prediction model and a teaching database, so that class prediction can be performed according to the class prediction model subsequently, and teaching data can be determined according to a prediction result, so that the acquired teaching data can be more accurate.
A third aspect of the embodiments of the present application provides an electronic device, including a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the method for acquiring lecture materials according to any one of the first aspect of the embodiments of the present application.
A fourth aspect of the present embodiment provides a computer-readable storage medium, which stores computer program instructions, where the computer program instructions, when read and executed by a processor, perform the method for obtaining lecture materials according to any one of the first aspect of the present embodiment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flow chart illustrating a method for acquiring teaching materials according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart illustrating a method for acquiring teaching materials according to a second embodiment of the present application;
fig. 3 is a schematic structural diagram of a teaching material obtaining apparatus according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of a lecture data acquiring apparatus according to a fourth embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a method for obtaining lecture data according to an embodiment of the present application. The method is applied to the process of obtaining teaching materials in a targeted manner. The teaching material acquisition method comprises the following steps:
s101, obtaining an initial teaching plan template selected by a target user from a preset teaching plan library.
In this embodiment, the target user may be a user.
In this embodiment, the preset teaching plan library includes a large number of teaching plan templates.
S102, the initial teaching plan template is applied to actual teaching of an actual learning class, and class attendance data of the actual learning class and lecture data of a target user are obtained after a preset time period.
In the embodiment, the method can determine more accurate class attendance data and lecture data in real time according to the initial teaching plan template, and is favorable for the subsequent steps.
And S103, processing class attendance data and lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class.
In this embodiment, the class level is used to indicate how fast the learning efficiency of the class is.
And S104, acquiring teaching plan templates and teaching data matched with class grades from a preset teaching plan library, wherein the teaching data comprises the teaching plan templates and the teaching data.
In this embodiment, the teaching materials include teaching plan templates and teaching materials.
In this embodiment, the teaching plan template is used to represent the link precedence relationship of teaching that the teacher can use for teaching; the teaching materials can be used to represent the material content of each teaching link in the teaching plan template.
In the embodiment of the present application, the execution subject of the method may be a computing device such as a computer and a server, and is not limited in this embodiment.
In this embodiment, an execution subject of the method may also be an intelligent device such as a smart phone and a tablet computer, which is not limited in this embodiment.
It can be seen that, by implementing the teaching material obtaining method described in this embodiment, an initial teaching plan template can be preferentially obtained, then, the class condition and the teaching data of an actual class to be learned are determined according to the actual application of the initial teaching plan template, so that the method can determine the class level of the class according to the class condition and the teaching data, and can match a more appropriate teaching plan template and teaching material according to the class level, so that a teacher can determine the teaching mode of each link according to the teaching material, and complete the whole teaching process according to the teaching plan template. Therefore, by implementing the implementation mode, the most appropriate teaching materials can be obtained according to the actual situation, so that the teaching materials can better accord with the actual learning level of the class of the teaching, the learning efficiency of the learner is improved, and the teacher can be facilitated to carry out corresponding lesson preparation and teaching.
Example 2
Please refer to fig. 2, fig. 2 is a flowchart illustrating a method for obtaining lecture data according to an embodiment of the present application. As shown in fig. 2, the method for obtaining lecture materials includes:
s201, obtaining teaching plan data in a preset teaching time period, and obtaining class teaching data corresponding to the teaching plan data.
As an optional implementation manner, acquiring teaching plan data in a preset teaching time period includes:
determining a template teacher and acquiring teaching knowledge points of the template teacher in a preset teaching time period;
acquiring teaching materials corresponding to teaching knowledge points;
acquiring use habit data of teaching materials used by template teachers in a preset teaching time period;
and generating teaching plan data according to the teaching knowledge points, the teaching materials and the use habit data.
In the embodiment, the teaching plan data is generated according to the teaching data and the teaching habit of the template teacher, so that the teaching plan data is more pertinent, and the whole teaching data is better in obtaining effect.
In this embodiment, the template teacher may be a celebrity, or may be a preset teacher, specifically, a teacher identifier, and the embodiment of the present application is not limited.
In this embodiment, the celebrity can be through the comprehensive judgement that standards such as title, teaching quality carried out to effectively confirm the celebrity.
In this embodiment, the knowledge points in the teaching plan data in the method have the order of explanation.
In this embodiment, the order of the knowledge point explanation can be determined by big data.
For example, when the knowledge points include a first knowledge point and a second knowledge point, in the process of explaining the first knowledge point and the second knowledge point, 80% of teachers preferentially explain the first knowledge point, and at the moment, the first knowledge point is preferentially explained between the second knowledge points.
As an optional implementation, acquiring class attendance data corresponding to the teaching plan data includes:
acquiring a target class taught by a template teacher in a preset teaching time period;
acquiring grade learner score information corresponding to a target teaching class;
determining the class grade of each target class according to the grade learner score information;
and generating class attendance data according to the class of the target lecture, the grade information of the class learner and the class grade.
S202, constructing a class prediction model according to class attendance data.
As an alternative embodiment, the building of the class prediction model according to class attendance data comprises:
acquiring an original neural network model;
and training the original neural network model through class data to obtain a class prediction model.
In the above embodiment, the level prediction model is constructed according to the neural network model, so that the level prediction model has higher prediction accuracy, and the accuracy of acquiring the whole teaching material is improved.
By implementing the implementation mode, the training of the input data can be completed through the artificial intelligence model, so that the overall teaching data acquisition precision is improved.
S203, generating teaching plan templates according to the teaching plan data, and determining class grade labels corresponding to the teaching plan templates according to the class lesson data.
As an optional implementation, generating a teaching plan template according to the teaching plan data includes:
acquiring teaching knowledge point data in a preset teaching time period and teaching time corresponding to the teaching knowledge point data according to the teaching plan template;
generating an initial template according to the teaching knowledge point data and the teaching time;
and disassembling the initial template according to the course units to obtain a teaching plan template comprising independent teaching links.
In the above embodiment, the knowledge point and the teaching time are determined according to the lesson preparation template, then an initial template is generated again according to the knowledge point and the teaching time, and further the initial template is disassembled according to the course unit, so as to obtain the teaching plan template including the independent teaching link. Therefore, by the implementation of the implementation mode, the teaching plan template can be generated in a self-adaptive mode according to the lesson preparation template, and the obtaining effect of the teaching plan template is improved.
As a further optional implementation, the step of generating an initial template according to the teaching knowledge point data and the teaching time includes:
matching the teaching time stamp and the teaching duration of the knowledge points for each teaching knowledge point according to the teaching time;
determining the teaching sequence of each teaching knowledge point according to the teaching timestamp of each teaching knowledge point;
determining a knowledge point explanation time axis according to the teaching sequence and the teaching duration of the knowledge points;
and generating an initial template according to the knowledge point explanation time axis.
By implementing the implementation mode, the initial template can be determined according to the explanation sequence of the knowledge points and the time for explaining each knowledge point, so that the use effect of the initial template is improved.
And S204, generating a preset teaching plan library according to the teaching plan template and the class grade labels.
In this embodiment, the preset teaching plan library includes a large number of teaching plan templates.
S205, obtaining an initial teaching plan template selected by the target user from a preset teaching plan library.
S206, the initial teaching plan template is applied to actual teaching of the actual learning class, and class attendance data of the actual learning class and lecture data of the target user are obtained after a preset time period.
And S207, processing class attendance data and lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class.
And S208, acquiring a teaching plan template and teaching data matched with the class grade from a preset teaching plan library, wherein the teaching data comprises the teaching plan template and the teaching data.
Therefore, by implementing the method for obtaining teaching materials described in this embodiment, the most suitable teaching materials can be obtained according to the actual situation, so that the teaching materials can better meet the actual learning level of the class of the teaching, the learning efficiency of the learner is improved, and the teacher can perform corresponding lesson preparation and teaching.
Example 3
Please refer to fig. 3, fig. 3 is a schematic structural diagram of a lecture data acquisition device according to an embodiment of the present application. As shown in fig. 3, the lecture material acquiring apparatus includes:
a first obtaining unit 310, configured to obtain an initial teaching plan template selected by a target user from a preset teaching plan library;
a second obtaining unit 320, configured to apply the initial teaching plan template to actual teaching of an actual learning class, and obtain class attendance data of the actual learning class and lecture data of a target user after a preset time period;
the prediction unit 330 is configured to process class attendance data and lecture data through a pre-established class prediction model to obtain a class of an actual learning class;
the third obtaining unit 340 is configured to obtain a teaching plan template and teaching materials matched with the class level from a preset teaching plan library, where the teaching materials include the teaching plan template and the teaching materials.
In the embodiment of the present application, for the explanation of the teaching material obtaining apparatus, reference may be made to the description in embodiment 1 or embodiment 2, and details are not repeated in this embodiment.
The initial teaching plan template is obtained by the first obtaining unit 310, then the second obtaining unit 320 determines the class condition and the lecture data of the actual class according to the actual application of the initial teaching plan template, the prediction unit 330 can determine the class grade of the class according to the class condition and the lecture data, and finally the third obtaining unit 340 can match a more suitable teaching plan template and teaching data according to the class grade, so that a teacher can determine the teaching mode of each link according to the teaching data and complete the whole course according to the teaching plan template.
Therefore, the teaching material acquisition device described in this embodiment can acquire the most appropriate teaching material according to the actual situation, so that the teaching material can better meet the actual learning level of the class of the teaching, thereby improving the learning efficiency of the learner, and facilitating the teacher to perform corresponding lesson preparation and teaching.
Example 4
Referring to fig. 4, fig. 4 is a schematic structural diagram of a lecture data acquisition device according to an embodiment of the present application. The lecture material acquiring apparatus shown in fig. 4 is optimized by the lecture material acquiring apparatus shown in fig. 3. As shown in fig. 4, the lecture material acquiring apparatus further includes:
a fourth obtaining unit 350, configured to obtain teaching plan data in a preset teaching time period;
a fifth obtaining unit 360, configured to obtain class attendance data corresponding to the teaching plan data;
a construction unit 370, configured to construct a class prediction model according to class attendance data;
the determining unit 380 is configured to generate teaching plan templates according to the teaching plan data, and determine a class grade tag corresponding to each teaching plan template according to class attendance data;
the generating unit 390 is configured to generate a preset teaching plan library according to the teaching plan template and the class level tags.
As an alternative embodiment, the building unit 370 includes:
a first constructing subunit 371, configured to obtain an original neural network model;
and a second constructing subunit 372, configured to train the original neural network model through class attendance data to obtain a class prediction model.
As an alternative embodiment, the determining unit 380 includes:
the first determining subunit 381 is configured to obtain teaching knowledge point data in a preset teaching time period and teaching time corresponding to the teaching knowledge point data according to the teaching plan template;
a second determining subunit 382, configured to generate an initial template according to the teaching knowledge point data and the teaching time;
and a third determining subunit 383, configured to disassemble the initial template according to the course units, so as to obtain a teaching plan template including an independent teaching link.
As an optional implementation, the fourth obtaining unit 350 includes:
the first subunit 351 is configured to determine a template teacher, and acquire teaching knowledge points of the template teacher in a preset teaching time period;
a second subunit 352, configured to obtain teaching materials corresponding to the teaching knowledge points;
the third subunit 353 is configured to acquire usage habit data of a template teacher giving lessons by using teaching materials within a preset teaching time period;
the fourth sub-unit 354 is configured to generate teaching plan data according to the teaching knowledge points, the teaching materials, and the usage habit data.
As an optional implementation, the fifth obtaining unit 360 includes:
the fifth subunit 361 is configured to obtain a target class of teaching taught by the template teacher within a preset teaching time period;
a sixth subunit 362, configured to obtain class learner score information corresponding to the target class;
a seventh subunit 363, configured to determine, according to the class learner score information, a class level of each target lecture class;
the eighth subunit 364 is configured to generate class attendance data according to the class of the target lecture, the class learner score information, and the class.
In the embodiment of the present application, for the explanation of the teaching material obtaining apparatus, reference may be made to the description in embodiment 1 or embodiment 2, and details are not repeated in this embodiment.
Therefore, the teaching material acquisition device described in this embodiment can acquire the most appropriate teaching material according to the actual situation, so that the teaching material can better meet the actual learning level of the class of the teaching, thereby improving the learning efficiency of the learner, and facilitating the teacher to perform corresponding lesson preparation and teaching.
An embodiment of the present application provides an electronic device, which includes a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute any teaching material obtaining method in embodiment 1 or embodiment 2 of the present application.
An embodiment of the present application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and executed by a processor, the computer program instructions execute any teaching material obtaining method in embodiment 1 or embodiment 2 of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

Claims (10)

1. A method for obtaining teaching materials is characterized by comprising the following steps:
acquiring an initial teaching plan template selected by a target user from a preset teaching plan library;
applying the initial teaching plan template to actual teaching of an actual learning class, and acquiring class attendance data of the actual learning class and lecture data of the target user after a preset time period;
processing the class attendance data and the lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class;
and acquiring a teaching plan template and teaching data matched with the class grade from the preset teaching plan library, wherein the teaching data comprises the teaching plan template and the teaching data.
2. The method of claim 1, further comprising:
acquiring teaching plan data in a preset teaching time period, and acquiring class data corresponding to the teaching plan data;
constructing a class prediction model according to the class attendance data;
generating teaching plan templates according to the teaching plan data, and determining class grade labels corresponding to the teaching plan templates according to the class lesson data;
and generating a preset teaching plan library according to the teaching plan template and the class grade label.
3. The method for obtaining lecture materials according to claim 2, wherein the constructing a class prediction model according to the class lecture data comprises:
acquiring an original neural network model;
and training the original neural network model through the class attendance data to obtain a class prediction model.
4. The method of claim 2, wherein the step of generating a teaching plan template according to the teaching plan data comprises:
acquiring teaching knowledge point data in the preset teaching time period and teaching time corresponding to the teaching knowledge point data according to the teaching plan template;
generating an initial template according to the teaching knowledge point data and the teaching time;
and disassembling the initial template according to course units to obtain a teaching plan template comprising independent teaching links.
5. The method for obtaining teaching materials according to claim 2, wherein the step of obtaining teaching plan data within a preset teaching time period comprises:
determining a template teacher and acquiring teaching knowledge points of the template teacher in a preset teaching time period;
acquiring teaching materials corresponding to the teaching knowledge points;
acquiring use habit data of the template teacher giving lessons by using the teaching materials in the preset teaching time period;
and generating teaching plan data according to the teaching knowledge points, the teaching materials and the use habit data.
6. The method of claim 5, wherein the step of obtaining class lesson data corresponding to the teaching plan data comprises:
acquiring the target class of teaching taught by the template teacher in the preset teaching time period;
acquiring class learner score information corresponding to the target teaching class;
determining the class grade of each target class according to the grade learner score information;
and generating class attendance data according to the class of the target lecture, the class learner score information and the class grade.
7. An apparatus for acquiring teaching materials, comprising:
the first acquisition unit is used for acquiring an initial teaching plan template selected by a target user from a preset teaching plan library;
the second acquisition unit is used for applying the initial teaching plan template to the actual teaching of an actual learning class and acquiring class attendance data of the actual learning class and lecture data of the target user after a preset time period;
the prediction unit is used for processing the class attendance data and the lecture data through a pre-constructed class prediction model to obtain the class grade of the actual learning class;
and the third acquisition unit is used for acquiring teaching plan templates and teaching materials matched with the class grades from the preset teaching plan library, and the teaching materials comprise the teaching plan templates and the teaching materials.
8. The teaching material obtaining apparatus according to claim 7, further comprising:
the fourth acquisition unit is used for acquiring teaching plan data in a preset teaching time period;
a fifth acquiring unit, configured to acquire class attendance data corresponding to the teaching plan data;
the construction unit is used for constructing a class prediction model according to the class attendance data;
the determining unit is used for generating teaching plan templates according to the teaching plan data and determining class grade labels corresponding to the teaching plan templates according to the class attendance data;
and the generating unit is used for generating a preset teaching plan library according to the teaching plan template and the class grade labels.
9. An electronic device, comprising a memory for storing a computer program and a processor for executing the computer program to make the electronic device execute the teaching material acquisition method according to any one of claims 1 to 6.
10. A readable storage medium, wherein computer program instructions are stored in the readable storage medium, and when the computer program instructions are read and executed by a processor, the method for obtaining lecture materials according to any one of claims 1 to 6 is executed.
CN202011373941.1A 2020-11-27 2020-11-27 Teaching data acquisition method and device Pending CN112465227A (en)

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Application publication date: 20210309