CN112052327A - Method of knowledge point mastering condition analysis system - Google Patents
Method of knowledge point mastering condition analysis system Download PDFInfo
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Abstract
The invention relates to the field of big data, and particularly provides a method for a knowledge point mastering condition analysis system. Compared with the prior art, the intelligent student recommendation system can be used for students to study at any time and any place, is more intelligent, points out the defects of mastering of knowledge points of the students more accurately, and intelligently recommends the students to study comprehensively. Let the mr fully understand the student knowledge point and master the condition, have the key point of the side to do up the teaching work, promote the teaching level, provide the powerful guarantee for the student rises to learn.
Description
Technical Field
The invention relates to the field of big data, and particularly provides a method of a knowledge point mastering condition analysis system.
Background
Under the era background of big data, online education promotes the development of education and changes the traditional education mode. The Internet is used as a carrier, online education provides teaching service for wider audience groups in a more convenient and flexible education form, the Internet + education is rapidly developed, the development of education in China is gradually promoted, the existing education mode and teaching experience in China are changed, the online education is not limited by places, time and courses to a certain extent, and students can select to master infirm knowledge to customize and learn in an online practice mode. How to intelligently customize learning becomes a problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides a method of a knowledge point mastering condition analysis system with strong practicability aiming at the defects of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method for a knowledge point mastering condition analysis system is characterized in that acquired standardized data fields of raw data are mapped, analyzed and standardized, a platform self-defined algorithm is used for processing data, score analysis and comparison are carried out on knowledge points through grading rules and answers of various subjects, scores are calculated, the scores are converted into the grades according to the preset knowledge point grades, the grades are associated with users through a data processing system and stored in a system database, and the grades are intelligently recommended to students and teachers for assisting teaching and learning.
Further, the method specifically comprises the following steps:
s1, analyzing data characteristics;
s2, performing standard data visualization display;
s3, establishing standard database data;
and S4, forming a data report and a teaching guidance report.
Further, in step S1, the platform inputs the subjects and the real question questions of each level according to the established format and standard, simulates the self-organized test questions of the examination questions and the subject matters of various styles, analyzes the data characteristics by using the big data quality and the data management method, classifies and evaluates to form a comprehensive subject database comprehensive test question, performs field creation mapping on the data, and stores the data into the system data after the data is structured and standardized according to the mapping fields.
Further, in step S2, the standard data is displayed to the user group for use through the data service visualization platform, the user group forms a unique identifier after registration and login, and the unique identifier is stored in the database user information table, the stored user data are all structured standard data, and the data are processed by the system framework and used for preparing for association between the user and the test question in the future.
Further, in step S3, the test questions are opened to the students for practice through the platform, and after submission is completed, the system framework will analyze and compare according to the established flow to complete the scoring system, and the learning conditions of the students on the knowledge points are calculated by using bayesian probability statistics.
Preferably, the bayesian probability is that bayesian theorem starts from a conditional probability, which is defined as:
on the premise that the event B occurs, the probability of the event a occurring is represented by P (a | B).
Furthermore, after the knowledge point mastering conditions of the students are calculated, scores of the students are obtained, the obtained results are compared with actual conditions and analyzed, data capable of comparing user request behaviors are obtained, and data related to the knowledge point mastering conditions of the students are used as set standard database data.
Preferably, the latest user knowledge point associated data will be continuously updated in step S3.
Further, a user knowledge mastering degree database is obtained through step S3, and is used for analyzing the knowledge point mastering situation, and the data processing system is used as a request analysis layer to request a system platform product service layer, so as to perform intelligent recommendation operation and analysis of user behaviors in the process of using system products, and form a user knowledge point mastering data report and a teaching guidance report.
Compared with the prior art, the method of the knowledge point mastering condition analysis system has the following outstanding beneficial effects:
the intelligent student knowledge point recommendation system can be used for students to study at any time and any place, is more intelligent, points out the defect of mastering of the knowledge points of the students more accurately, and intelligently recommends the students to study comprehensively. Let the mr fully understand the student knowledge point and master the condition, have the key point of the side to do up the teaching work, promote the teaching level, provide the powerful guarantee for the student rises to learn.
Drawings
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 introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart diagram of a method of a knowledge point grasp condition analysis system.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments in order to better understand the technical solutions of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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.
A preferred embodiment is given below:
as shown in fig. 1, in the method of the knowledge point mastering situation analysis system in this embodiment, the obtained standardized data field of the raw data is mapped, analyzed and standardized, the data is processed by using a platform custom algorithm, the score of the knowledge point is analyzed and compared by splitting the scoring rule and the answer of each subject, the score is calculated, the score is converted into a rating according to the rating of the preset knowledge point, the rating is associated with the user through the data processing system and is stored in the system database, and the rating is intelligently recommended to students and teachers for assisting teaching and learning.
The method comprises the following steps:
s1, analyzing data characteristics;
the system platform inputs various subjects, true test questions of various levels, simulated test questions and self-editing test questions of various types of subject matters according to the established format and the specification, is beneficial to the quality of big data and a data management method, analyzes data characteristics, classifies and evaluates to form comprehensive subject database comprehensive data, carries out field creation mapping on the data taken by people, and stores the data into system data after the data is structured and standardized according to mapping fields so as to be convenient for program analysis and processing.
S2, performing standard data visualization display;
in step S1, the standard data is displayed to the user group for use through the data service visualization platform, the user group forms a unique identifier after registration and login, and stores the unique identifier in the database user information table, and the stored user data are all structured standard data, which are processed by the system framework, to prepare for association of the user with the test question in the future.
S3, establishing standard database data;
in step S2, we obtain normalized user data. The test questions are submitted to the students for practice through the platform, after the submission is completed, the system framework analyzes and compares the test questions according to the set flow, a scoring system is completed, and the learning condition of the students on the knowledge points is calculated by means of Bayesian probability statistics.
The derivation of bayesian theorem starts with conditional probabilities. The conditional probability may be defined as: probability of occurrence of event a, on the premise of occurrence of event B. This conditional probability is mathematically represented by P (a | B). In our example, that is, "the probability that the student does not know the knowledge point B" is equal to "the probability that the knowledge point a is not known and the knowledge point B is not known" divided by "the probability that the knowledge point a is not known". The left and right sides of this equation are simultaneously multiplied by P (B) to obtain P (B) P (a | B) ═ P (a ═ B).
And in the second period, the obtained student scores are compared with the actual conditions, so that data capable of comparing the user request behaviors can be obtained, and finally the associated data of the students and the knowledge point mastering conditions are used as established standard database data (in the second period, the latest user knowledge point associated data are continuously updated.
S4, forming a data report and a teaching guidance report:
through the step S3, a user knowledge mastery degree database is obtained for analyzing knowledge point mastery conditions, and the module is integrated into a system, namely, in the data processing system mentioned above, the system is taken as a request analysis layer (C terminal) to request a system platform product service layer (S layer) for carrying out intelligent recommendation operation in the process of using system products and analyzing user behaviors to form a user knowledge point mastery data report and a teaching guidance report.
The invention provides a method of a knowledge point mastering condition analysis system. The system platform is used for inputting and collecting various test questions such as standardized test paper test questions and the like, including test question contents, investigation knowledge points, answer details, test question difficulty rating and other fields, the system is used for carrying out informationized standardized processing, the grading rules of various subjects and answer setting rules are matched with answers, the grasping degree between a user and a question including but not limited to question serial number, question score, answer time and affiliated knowledge point is formed, standardized warehousing storage is carried out, preset question score is used, a plurality of threshold values are set according to the number of questions made by the knowledge point, the grades are divided into unsophisticated, mastered and infirm, and the like, after triggering, the question of difficulty degree of knowledge is carried out according to the ladder knowledge grasping condition, the questions comprise cognitive classification of course knowledge, cognitive modification of question bank, and framework knowledge representation and field knowledge bank suitable for student reasoning models, the intelligent recommendation of basic exercise, diagnosis exercise and supplementary exercise to students can be realized according to qualitative reasoning, so that the learning improvement of the students and the teaching focus analysis of teachers are assisted.
The above embodiments are only specific ones of the present invention, and the scope of the present invention includes but is not limited to the above embodiments, and any method claims conforming to a point of knowledge learning situation analysis system of the present invention and any appropriate changes or substitutions made by those skilled in the art shall fall within the scope of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A method for a knowledge point mastering condition analysis system is characterized in that acquired standardized data fields of raw data are mapped, analyzed and standardized, a platform self-defined algorithm is used for processing data, score analysis and comparison are carried out on knowledge points through grading rules and answers of various subjects, scores are calculated, the scores are converted into the grades according to the preset knowledge point grades, the grades are associated with users through a data processing system and stored in a system database, and the grades are intelligently recommended to students and teachers for assisting teaching and learning.
2. The method of a knowledge point mastering situation analyzing system as claimed in claim 1, characterized by comprising the steps of:
s1, analyzing data characteristics;
s2, performing standard data visualization display;
s3, establishing standard database data;
and S4, forming a data report and a teaching guidance report.
3. The method of claim 2, wherein in step S1, the subject, the true test questions of each level are input through the platform according to the predetermined format and standard, the examination questions and the self-organized test questions of the subject matters of various styles are simulated, the data characteristics are analyzed by using the big data quality and data management method, the classification and evaluation are performed, the comprehensive test questions of the subject library are formed, the data are mapped by field creation, and the data are structured and standardized according to the mapping fields and then stored in the system data.
4. The method for analyzing knowledge point mastering conditions of claim 3, wherein in step S2, standard data are displayed to the user group through the data service visualization platform, the user group forms a unique identifier after registration and login, and the unique identifier is stored in the database user information table, the stored user data are all structured standard data, and the data are processed by the system framework for preparing the association of the user and the test question in the future.
5. The method of claim 4, wherein in step S3, the test questions are opened to students for practice, and after submission, the system framework will analyze and compare according to the established process to complete the scoring system, and calculate the knowledge points mastery status of the students by using Bayesian probability statistics.
6. The method of claim 5, wherein the Bayesian probability is that Bayesian theorem starts with a conditional probability, and the conditional probability is defined as:
on the premise that the event B occurs, the probability of the event a occurring is represented by P (a | B).
7. The method of claim 6, wherein the learning of the knowledge points by the students is calculated, the scores of the students are obtained, the obtained results are compared with the actual situation, so as to obtain data that can be used for comparing the user request behavior, and the data associated with the learning of the knowledge points by the students are used as the predetermined standard database data.
8. The method of claim 7, wherein the latest user knowledge point associated data is continuously updated in step S3.
9. The method of claim 8, wherein a user knowledge mastery degree database is obtained in step S3 for analyzing the knowledge point mastery, and the data processing system is used as a request analysis layer to request a system platform product service layer, so as to perform intelligent recommendation operation and analyze user behavior during the process of using system products, thereby forming a user knowledge point mastery data report and a teaching guidance report.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113192371A (en) * | 2021-04-29 | 2021-07-30 | 上海天好信息技术股份有限公司 | Learning training method based on block chain |
| CN114743440A (en) * | 2022-04-29 | 2022-07-12 | 长沙酷得网络科技有限公司 | Intelligent programming training environment construction method and device based on application disassembly |
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2020
- 2020-09-09 CN CN202010938940.0A patent/CN112052327A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113192371A (en) * | 2021-04-29 | 2021-07-30 | 上海天好信息技术股份有限公司 | Learning training method based on block chain |
| CN114743440A (en) * | 2022-04-29 | 2022-07-12 | 长沙酷得网络科技有限公司 | Intelligent programming training environment construction method and device based on application disassembly |
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Application publication date: 20201208 |