CN112598553A - Service system based on online learning and intelligent evaluation - Google Patents
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Abstract
The invention discloses a service system based on online learning and intelligent evaluation, relates to the technical field of online education, and solves the technical problems that the learning content can not be accurately evaluated and the learning efficiency is low when a user learns online; the invention is provided with a plan making module, and the plan making module is used for making a learning plan by a user according to the self condition, so that the learning plan is more in line with the requirements of the user, and the user is prevented from learning too much irrelevant content; the learning effect evaluation module is arranged, and the learning effect evaluation module generates a test paper according to the knowledge points of the learning resources after the learning of the user is finished, acquires the scores of the user, evaluates the learning effect of the user according to the scores, is beneficial to the user to find out the deficiency in time and ensures the learning efficiency of the user; the efficiency analysis module is arranged, and the efficiency analysis module divides the learning process of the user into small stages, acquires the learning efficiency of the small stages, generates a learning efficiency curve and provides timely and accurate reference for the learning of the user.
Description
Technical Field
The invention belongs to the technical field of online education, and particularly relates to a service system based on online learning and intelligent evaluation.
Background
The on-line education is a novel education mode generated along with the development of modern information technology, is characterized by multimedia and interactive modes, transmits teaching audio and video, pictures and texts and data in a long distance, high speed and high quality mode, breaks through the limitation of the traditional teaching and training on time and space, and can realize real-time and interactive teaching in different places. However, most of the existing online education systems are only used for stacking contents and playing videos, and student interaction is limited to live classroom, so that the defects are very obvious, compared with on-site teaching, the online education has insufficient control strength on students, and no tool or method can ensure the effect of online learning.
The invention patent with publication number CN106453658A discloses an online education platform, which comprises a background courseware storage module, a courseware transcoding uploading module, an information server, a database storage service module, a video service module, a live broadcast service module, a content distribution acceleration module, a data analysis module and a client, wherein the data analysis module, the video service module, the live broadcast service module and the database storage service module are all connected with the information server: the video service module is connected with the client through the content distribution acceleration module; the live broadcast service module is connected with the client through the content distribution acceleration module; the background courseware storage module is connected with the video service module, and the background courseware storage module further comprises a private cloud server and a data server, the private cloud server is connected with the client side, and the information server is connected with the data server.
The scheme provides an online education platform which realizes downloading, live broadcasting and on-demand broadcasting and has high transmission speed; however, the above scheme only provides a learning platform, and cannot evaluate the learning effect of the user; therefore, the above solution still needs further improvement.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides a service system based on online learning and intelligent evaluation.
The purpose of the invention can be realized by the following technical scheme: a service system based on online learning and intelligent evaluation comprises a cloud platform, an efficiency analysis module, an administrator module, a data storage module, a plan making module and a learning effect evaluation module;
the cloud platform is respectively in communication connection with the efficiency analysis module, the administrator module, the data storage module, the plan making module and the learning effect evaluation module; the plan making module and the learning effect evaluation module are in wireless connection with an intelligent terminal of a user; the intelligent terminal comprises an intelligent mobile phone, a tablet computer and a notebook computer;
the plan making module is used for making a learning plan by a user through an intelligent terminal;
the administrator module is used for managing learning resources, and the learning resources comprise video learning files and text learning files of different disciplines;
the learning effect evaluation module is used for analyzing the learning result of the online learning of the user;
the efficiency analysis module is used for analyzing the learning efficiency of the user and generating a learning efficiency curve.
Preferably, the learning effect evaluation module supports the user to learn online and analyzes the learning result, and includes:
a user sends an online learning signal to the cloud platform through the intelligent terminal, the learning plan is obtained through the data storage module, and the user learns through the intelligent terminal;
acquiring the learning completion degree of a user, and marking the learning completion degree as XWD; the learning completion degree is the ratio of the duration of the subject resources which have been learned in the learning plan to the total duration of the subject resources;
when the learning completion degree XWD satisfies 0< XWD <1, it is determined that the learning plan is not completed; when the learning completion degree XWD meets the condition that the XWD is 1, judging that the learning plan is completed, summarizing knowledge points of learning resources in the learning plan, generating a test paper according to the knowledge points, and sending the test paper to an intelligent terminal of a user;
acquiring a test paper score of a user, and marking the test paper score as SD;
when the test paper score SD meets SD < L3, judging that the user test fails, and marking the user as an incomplete user; when the test paper score SD meets the condition that L3 is not more than SD, judging that the user test is passed, and marking the user as a finished user; where L3 is a preset test paper score threshold.
Preferably, the efficiency analysis module is configured to analyze learning efficiency in a user learning process, and includes:
acquiring the learning time length of single learning of a user, and marking the learning time length as XS;
acquiring knowledge points in single learning resources of a user, generating a review test paper according to the knowledge points, and sending the review test paper to an intelligent terminal of the user; obtaining the score of a user reviewing the test paper and marking the score as HDF;
by the formula
Acquiring a learning efficiency coefficient XXX; wherein alpha 1 is a preset proportionality coefficient greater than 0;
acquiring the acquisition time of the learning efficiency coefficient, marking the acquisition time as efficiency time, establishing a learning efficiency curve by taking the efficiency time as an independent variable and the learning efficiency coefficient as a dependent variable, and sending the learning efficiency curve to an intelligent terminal of a user through a cloud platform;
and sending the learning efficiency curve to a data storage module for storage.
Preferably, the plan making module is used for making a learning plan, and comprises:
a user sends a planning signal to a planning module through an intelligent terminal; the planning signals comprise single item improving signals and comprehensive learning signals;
when the plan making module receives the single item improving signal, the cloud platform acquires a list of learning resources, a user clicks the list to select the learning resources, and the single item of the selected learning resources is improved;
when the plan making module receives the comprehensive learning signal, the study resources are searched by using subject keywords, the searched study resources are screened to obtain a screening result, and the screening result is marked as the comprehensive learning resources; the subject keywords comprise Chinese, mathematics and English, the ratio of video learning files to text learning files in the comprehensive learning resources is L1: L2, wherein L1 and L2 are preset proportionality coefficients;
and sending the single item improved resources and the comprehensive learning resources to a data storage module for storage.
Preferably, the administrator manages and updates the learning resources through the administrator module, including:
the administrator performs identity authentication through the administrator terminal; the administrator terminal is in wireless connection with the administrator module and comprises a smart phone and a desktop computer;
after the identity authentication is successful, the administrator uploads the learning resources through the administrator module, and the cloud platform performs virus detection on the learning resources;
and sending the learning resources which do not contain the virus to a data storage module for updating and storing.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with a plan making module, and the plan making module is used for making a learning plan; a user sends a planning signal to a planning module through an intelligent terminal; when the plan making module receives the single item improving signal, the cloud platform acquires a list of learning resources, a user clicks the list to select the learning resources, and the single item of the selected learning resources is improved; when the plan making module receives the comprehensive learning signal, the study resources are searched by using subject keywords, the searched study resources are screened to obtain a screening result, and the screening result is marked as the comprehensive learning resources; sending the single improved resource and the comprehensive learning resource to a data storage module for storage; the plan making module is used for making a learning plan by a user according to the self condition, so that the learning plan is more in line with the requirements of the user, and the user is prevented from learning too much irrelevant content;
2. the invention is provided with a learning effect evaluation module, which supports the online learning of the user and analyzes the learning result; a user sends an online learning signal to a cloud platform through an intelligent terminal; acquiring the learning completion degree of a user, and marking the learning completion degree as XWD; when the learning completion degree XWD satisfies 0< XWD <1, it is determined that the learning plan is not completed; when the learning completion degree XWD meets the condition that the XWD is 1, judging that the learning plan is completed, summarizing knowledge points of learning resources in the learning plan, generating a test paper according to the knowledge points, and sending the test paper to an intelligent terminal of a user; acquiring a test paper score SD of a user; when the test paper score SD meets SD < L3, judging that the user test fails, and marking the user as an incomplete user; when the test paper score SD meets the condition that L3 is not more than SD, judging that the user test is passed, and marking the user as a finished user; the learning effect evaluation module generates a test paper according to the knowledge points of the learning resources after the learning of the user is finished, and obtains the score of the user, so that the learning effect of the user is evaluated, the user can find out the deficiency in time, and the learning efficiency of the user is ensured;
3. the invention is provided with an efficiency analysis module, and the efficiency analysis module is used for analyzing the learning efficiency of the user in the learning process; acquiring the learning duration XS of single learning of a user; acquiring knowledge points in single learning resources of a user, generating a review test paper according to the knowledge points, and sending the review test paper to an intelligent terminal of the user; obtaining the score of a user reviewing the test paper and marking the score as HDF; acquiring a learning efficiency coefficient XXX; acquiring the acquisition time of the learning efficiency coefficient, marking the acquisition time as efficiency time, establishing a learning efficiency curve by taking the efficiency time as an independent variable and the learning efficiency coefficient as a dependent variable, and sending the learning efficiency curve to an intelligent terminal of a user through a cloud platform; the efficiency analysis module divides the learning process of the user into small stages, acquires the learning efficiency of the small stages, generates a learning efficiency curve and provides timely and accurate reference for the learning of the user.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a service system based on online learning and intelligent evaluation includes a cloud platform, an efficiency analysis module, an administrator module, a data storage module, a plan making module and a learning effect evaluation module;
the cloud platform is in communication connection with the efficiency analysis module, the administrator module, the data storage module, the plan making module and the learning effect evaluation module respectively; the plan making module and the learning effect evaluation module are in wireless connection with an intelligent terminal of a user; the intelligent terminal comprises an intelligent mobile phone, a tablet computer and a notebook computer;
the plan making module is used for making a learning plan by a user through the intelligent terminal;
the administrator module is used for managing learning resources, and the learning resources comprise video learning files and text learning files of different disciplines;
the learning effect evaluation module is used for analyzing the learning result of the online learning of the user;
the efficiency analysis module is used for analyzing the learning efficiency of the user and generating a learning efficiency curve.
Further, the learning effect evaluation module supports the user to learn online and analyzes the learning result, and comprises:
a user sends an online learning signal to the cloud platform through the intelligent terminal, a learning plan is obtained through the data storage module, and the user learns through the intelligent terminal;
acquiring the learning completion degree of a user, and marking the learning completion degree as XWD; the learning completion degree is the ratio of the duration of the subject resources which have been learned in the learning plan to the total duration of the subject resources;
when the learning completion degree XWD satisfies 0< XWD <1, it is determined that the learning plan is not completed; when the learning completion degree XWD meets the condition that the XWD is 1, judging that the learning plan is completed, summarizing knowledge points of learning resources in the learning plan, generating a test paper according to the knowledge points, and sending the test paper to an intelligent terminal of a user;
acquiring a test paper score of a user, and marking the test paper score as SD;
when the test paper score SD meets SD < L3, judging that the user test fails, and marking the user as an incomplete user; when the test paper score SD meets the condition that L3 is not more than SD, judging that the user test is passed, and marking the user as a finished user; where L3 is a preset test paper score threshold.
Further, the efficiency analysis module is used for analyzing the learning efficiency in the user learning process, and comprises:
acquiring the learning time length of single learning of a user, and marking the learning time length as XS;
acquiring knowledge points in single learning resources of a user, generating a review test paper according to the knowledge points, and sending the review test paper to an intelligent terminal of the user; obtaining the score of a user reviewing the test paper and marking the score as HDF;
by the formula
Acquiring a learning efficiency coefficient XXX; wherein alpha 1 is a preset proportionality coefficient greater than 0;
acquiring the acquisition time of the learning efficiency coefficient, marking the acquisition time as efficiency time, establishing a learning efficiency curve by taking the efficiency time as an independent variable and the learning efficiency coefficient as a dependent variable, and sending the learning efficiency curve to an intelligent terminal of a user through a cloud platform;
and sending the learning efficiency curve to a data storage module for storage.
Further, the plan making module is used for making a learning plan, and comprises:
a user sends a planning signal to a planning module through an intelligent terminal; the planning signals comprise single item improving signals and comprehensive learning signals;
when the plan making module receives the single item improving signal, the cloud platform acquires a list of learning resources, a user clicks the list to select the learning resources, and the single item of the selected learning resources is improved;
when the plan making module receives the comprehensive learning signal, the study resources are searched by using subject keywords, the searched study resources are screened to obtain a screening result, and the screening result is marked as the comprehensive learning resources; the subject keywords comprise Chinese, mathematics and English, the ratio of the video learning files to the text learning files in the comprehensive learning resources is L1: L2, wherein L1 and L2 are preset proportionality coefficients;
and sending the single item improved resources and the comprehensive learning resources to a data storage module for storage.
Further, the administrator manages and updates the learning resources through the administrator module, including:
the administrator performs identity authentication through the administrator terminal; the administrator terminal is in wireless connection with the administrator module and comprises a smart phone and a desktop computer;
after the identity authentication is successful, the administrator uploads the learning resources through the administrator module, and the cloud platform performs virus detection on the learning resources;
and sending the learning resources which do not contain the virus to a data storage module for updating and storing.
Further, virus detection includes:
acquiring the file size of the learning resource, and marking the file size as WD;
opening the learning resources for multiple times through the cloud platform to obtain an opening speed average value, and marking the opening speed average value as DSZ;
by the formula B ═ delta 1 × e-δ2×DSZ+WDAcquiring a virus detection coefficient B; the delta 1 and the delta 2 are preset proportionality coefficients, the delta 1 and the delta 2 are real numbers larger than 0, and e is a natural constant;
when the virus threat coefficient 0< B ≦ J1, judging that the file does not contain a virus file; when the virus threat coefficient J1 is less than B, the file is judged to contain the virus file, a file danger signal is sent to the administrator module through the cloud platform, and meanwhile, the data access authority of the administrator module to the cloud platform and the data storage module is closed;
and sending the sending record of the file danger signal to a data storage module for storage, and carrying out virus detection on the file in the data storage module.
Further, the authentication specifically includes:
the method comprises the steps that an administrator sends an account and a password to a cloud platform through an administrator terminal, the cloud platform verifies the account and the password, and when verification is successful, a face acquisition signal is sent to an intelligent terminal of the administrator;
the administrator module acquires a facial image of an administrator through an administrator terminal and sends the facial image to the cloud platform;
the cloud platform carries out image preprocessing on the face image and marks the face image after the image preprocessing as a verification image; the image preprocessing comprises image segmentation, image denoising and gray level transformation;
acquiring a preset characteristic image through a data storage platform; the preset characteristic images are pre-stored face images of an administrator, and at least one preset characteristic image is included;
matching the verification image with a preset characteristic image, and opening the authority of the cloud platform and the data storage module to an administrator module when the matching is successful, and generating a log accessed by the administrator, wherein the authority comprises a data reading authority and a data modification authority; when the matching fails, locking the manager module;
and sending the log accessed by the administrator to a data storage module for storage through the cloud platform.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The working principle of the invention is as follows:
a user sends a planning signal to a planning module through an intelligent terminal; when the plan making module receives the single item improving signal, the cloud platform acquires a list of learning resources, a user clicks the list to select the learning resources, and the single item of the selected learning resources is improved; when the plan making module receives the comprehensive learning signal, the study resources are searched by using subject keywords, the searched study resources are screened to obtain a screening result, and the screening result is marked as the comprehensive learning resources; sending the single improved resource and the comprehensive learning resource to a data storage module for storage;
a user sends an online learning signal to a cloud platform through an intelligent terminal; acquiring the learning completion degree of a user, and marking the learning completion degree as XWD; when the learning completion degree XWD satisfies 0< XWD <1, it is determined that the learning plan is not completed; when the learning completion degree XWD meets the condition that the XWD is 1, judging that the learning plan is completed, summarizing knowledge points of learning resources in the learning plan, generating a test paper according to the knowledge points, and sending the test paper to an intelligent terminal of a user; acquiring a test paper score SD of a user; when the test paper score SD meets SD < L3, judging that the user test fails, and marking the user as an incomplete user; when the test paper score SD meets the condition that L3 is not more than SD, judging that the user test is passed, and marking the user as a finished user;
acquiring the learning duration XS of single learning of a user; acquiring knowledge points in single learning resources of a user, generating a review test paper according to the knowledge points, and sending the review test paper to an intelligent terminal of the user; obtaining the score of a user reviewing the test paper and marking the score as HDF; acquiring a learning efficiency coefficient XXX; and acquiring the acquisition time of the learning efficiency coefficient, marking the acquisition time as efficiency time, establishing a learning efficiency curve by taking the efficiency time as an independent variable and the learning efficiency coefficient as a dependent variable, and sending the learning efficiency curve to the intelligent terminal of the user through the cloud platform.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A service system based on online learning and intelligent evaluation is characterized by comprising a cloud platform, an efficiency analysis module, an administrator module, a data storage module, a plan making module and a learning effect evaluation module;
the cloud platform is respectively in communication connection with the efficiency analysis module, the administrator module, the data storage module, the plan making module and the learning effect evaluation module; the plan making module and the learning effect evaluation module are in wireless connection with an intelligent terminal of a user; the intelligent terminal comprises an intelligent mobile phone, a tablet computer and a notebook computer;
the plan making module is used for making a learning plan by a user through an intelligent terminal;
the administrator module is used for managing learning resources, and the learning resources comprise video learning files and text learning files of different disciplines;
the learning effect evaluation module is used for analyzing the learning result of the online learning of the user;
the efficiency analysis module is used for analyzing the learning efficiency of the user and generating a learning efficiency curve.
2. The service system based on online learning and intelligent evaluation according to claim 1, wherein the learning effect evaluation module supports online learning of users and analyzes learning results, and comprises:
a user sends an online learning signal to the cloud platform through the intelligent terminal, the learning plan is obtained through the data storage module, and the user learns through the intelligent terminal;
acquiring the learning completion degree of a user, and marking the learning completion degree as XWD; the learning completion degree is the ratio of the duration of the subject resources which have been learned in the learning plan to the total duration of the subject resources;
when the learning completion degree XWD is more than 0 and less than 1, judging that the learning plan is not completed; when the learning completion degree XWD meets the condition that the XWD is 1, judging that the learning plan is completed, summarizing knowledge points of learning resources in the learning plan, generating a test paper according to the knowledge points, and sending the test paper to an intelligent terminal of a user;
acquiring a test paper score of a user, and marking the test paper score as SD;
when the test paper score SD meets SD < L3, judging that the user test fails, and marking the user as an incomplete user; when the test paper score SD meets the condition that L3 is not more than SD, judging that the user test is passed, and marking the user as a finished user; where L3 is a preset test paper score threshold.
3. The service system based on online learning and intelligent evaluation according to claim 1, wherein the efficiency analysis module is configured to analyze learning efficiency of the user in the learning process, and includes:
acquiring the learning time length of single learning of a user, and marking the learning time length as XS;
acquiring knowledge points in single learning resources of a user, generating a review test paper according to the knowledge points, and sending the review test paper to an intelligent terminal of the user; obtaining the score of a user reviewing the test paper and marking the score as HDF;
by the formula
Acquiring a learning efficiency coefficient XXX; wherein alpha 1 is a preset proportionality coefficient greater than 0;
acquiring the acquisition time of the learning efficiency coefficient, marking the acquisition time as efficiency time, establishing a learning efficiency curve by taking the efficiency time as an independent variable and the learning efficiency coefficient as a dependent variable, and sending the learning efficiency curve to an intelligent terminal of a user through a cloud platform;
and sending the learning efficiency curve to a data storage module for storage.
4. The service system based on online learning and intelligent evaluation according to claim 1, wherein the plan making module is configured to make a learning plan, and comprises:
a user sends a planning signal to a planning module through an intelligent terminal; the planning signals comprise single item improving signals and comprehensive learning signals;
when the plan making module receives the single item improving signal, the cloud platform acquires a list of learning resources, a user clicks the list to select the learning resources, and the single item of the selected learning resources is improved;
when the plan making module receives the comprehensive learning signal, the study resources are searched by using subject keywords, the searched study resources are screened to obtain a screening result, and the screening result is marked as the comprehensive learning resources; the subject keywords comprise Chinese, mathematics and English, the ratio of video learning files to text learning files in the comprehensive learning resources is L1: L2, wherein L1 and L2 are preset proportionality coefficients;
and sending the single item improved resources and the comprehensive learning resources to a data storage module for storage.
5. The service system based on online learning and intelligent evaluation according to claim 1, wherein an administrator manages and updates learning resources through the administrator module, including:
the administrator performs identity authentication through the administrator terminal; the administrator terminal is in wireless connection with the administrator module and comprises a smart phone and a desktop computer;
after the identity authentication is successful, the administrator uploads the learning resources through the administrator module, and the cloud platform performs virus detection on the learning resources;
and sending the learning resources which do not contain the virus to a data storage module for updating and storing.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115116285A (en) * | 2022-06-21 | 2022-09-27 | 浪潮卓数大数据产业发展有限公司 | Online learning system based on WeChat native framework |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115116285A (en) * | 2022-06-21 | 2022-09-27 | 浪潮卓数大数据产业发展有限公司 | Online learning system based on WeChat native framework |
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