CN114444978A - Big data-based teaching auxiliary system and method - Google Patents
Big data-based teaching auxiliary system and method Download PDFInfo
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Abstract
The invention discloses a teaching auxiliary system and a method based on big data, relating to the technical field of big data analysis; the method comprises the steps of collecting teaching auxiliary data, wherein the teaching auxiliary data comprise examination questions of the high-level examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details, preprocessing the teaching auxiliary data, labeling the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty degree and importance degree, forming a knowledge storage database by using the calibrated teaching auxiliary data, and assisting teaching by using a qualitative reasoning method according to the knowledge storage database.
Description
Technical Field
The invention discloses a system and a method, relates to the technical field of big data analysis, and particularly relates to a teaching auxiliary system and a method based on big data.
Background
Under the era background of big data, the internet promotes the development of education and changes the traditional education mode. The Internet is used as a carrier, and under the holding of big data, the teaching service is provided for a wider audience group in a more convenient and more flexible education form. However, no more perfect method or system is available for teaching assistance in many aspects.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a teaching auxiliary system and a method based on big data, and the specific scheme provided by the invention is as follows:
the invention provides a teaching auxiliary method based on big data, which collects teaching auxiliary data, wherein the teaching auxiliary data comprises examination questions of the higher examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details,
pre-processing is carried out on the teaching assistance data,
labeling the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty degree and importance degree, forming a knowledge storage database by using the labeled teaching auxiliary data,
and (4) assisting teaching by using a qualitative reasoning method according to the knowledge reserve database.
Further, the collecting teaching assistance data in the big data based teaching assistance method includes:
and (4) acquiring the examination questions of the college entrance examination in the each subject in the past year, the simulation examination questions of the subjects in each province and city, the examination question investigation knowledge points and the answer details according to the determined format and the specification.
Further, in the big data-based teaching assistance method, the preprocessing the teaching assistance data includes:
and creating field mapping for the teaching auxiliary data, and carrying out structuring and standardization processing on the teaching auxiliary data according to mapping fields.
Further, in the big data-based teaching assistance method, label calibration is performed on the processed teaching assistance data through a visual interface.
The invention also provides a teaching auxiliary system based on big data, which comprises an acquisition and input module, a preprocessing module, a classification module and a teaching auxiliary module,
the acquisition and input module acquires teaching auxiliary data, wherein the teaching auxiliary data comprises examination questions of the college entrance examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details,
the preprocessing module is used for preprocessing the teaching assistance data,
the classification module carries out label calibration on the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty and importance, forms a knowledge storage database by utilizing the calibrated teaching auxiliary data,
the teaching auxiliary module is used for assisting teaching by using a qualitative reasoning method according to the knowledge storage database.
Further, the teaching assistance system based on big data in the collection input module collects teaching assistance data, including:
and (4) acquiring and recording the examination questions of the college entrance examination in each subject, the simulation examination questions of each subject in each province and city, the examination questions, the investigation knowledge points of the examination questions and the details of answers according to the instant format and the standard.
Further, in the big data based teaching assistance system, the preprocessing module preprocesses the teaching assistance data, including:
and creating field mapping for the teaching auxiliary data, and carrying out structuring and standardization processing on the teaching auxiliary data according to mapping fields.
Further, the big data-based teaching auxiliary system further comprises a visualization module, and the visualization module is used for performing label calibration on the processed teaching auxiliary data through a visualization interface.
The invention has the advantages that:
the invention provides a big data-based teaching assistance method, which is used for collecting the examination questions of the college entrance examination in the past year and the high-quality simulation examination questions of each province and city in each subject, examining the content of the examination questions, investigating knowledge points and answer details, carrying out informationized standardized processing, carrying out label calibration on the examination questions displayed after the processing to form a knowledge storage database of teaching assistance data, assisting in integrating and communicating important knowledge points in teaching of teachers according to a qualitative reasoning method and the knowledge storage database, carrying out side key analysis and key explanation, and achieving the effect of achieving twice the result with half the effort.
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 schematic diagram of the system application of the present invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
The invention provides a teaching auxiliary method based on big data, which collects teaching auxiliary data, wherein the teaching auxiliary data comprises examination questions of the higher examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details,
pre-processing is carried out on the teaching assistance data,
labeling the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty degree and importance degree, forming a knowledge storage database by using the labeled teaching auxiliary data,
and (5) assisting teaching by using a qualitative reasoning method according to the knowledge storage database.
The method can collect, arrange and summarize various knowledge points more quickly and efficiently by utilizing the advantages of the internet big data in data acquisition and processing, collect a large amount of knowledge such as key points more conveniently and efficiently, is more intelligent and more accurate, assists teaching work with key points, improves teaching level and provides powerful guarantee for students to promote the study.
In particular applications, in some embodiments of the method of the present invention, when teaching assistance is performed,
collecting teaching auxiliary data, wherein the teaching auxiliary data comprises the examination questions of the high-level examination in each subject, the simulation examination questions of each subject in each province and city, the examination question investigation knowledge points and the answer details, inputting the information according to the fixed format and the standard to form comprehensive question bank comprehensive data,
preprocessing the teaching auxiliary data, creating field mapping, structuring and standardizing the data according to mapping fields, storing the data for program analysis and processing,
labeling the processed teaching auxiliary data through a data service visualization platform according to knowledge point division, a problem solving thought, a question answering flow, difficulty degree and importance degree, forming a knowledge storage database by using the labeled teaching auxiliary data, labeling the teaching auxiliary data by a qualified teacher user through the visualization platform, selecting an optimal auxiliary scheme according to established flow analysis and comparison after submission is finished, calculating and processing parameters such as grading and the like, labeling the affiliated knowledge point for the test question, calculating a series of parameters such as occurrence times, occurrence forms and values in a large-scale examination in the past year, calculating the importance degree of the knowledge point and the like according to the parameters, finally, taking complete test question, real question and other data associated with the knowledge point label as established standard database data, and continuously updating latest knowledge point associated data in the period, and is presented to all users for use,
and forming a knowledge reserve database by using the calibrated teaching auxiliary data, analyzing the distribution situation and the important situation of the past-year knowledge points, and assisting in combining and communicating important knowledge points in the course of a teacher according to a qualitative reasoning method and the knowledge reserve database, analyzing the emphasis points and explaining the emphasis points to achieve the effect of doubling the result with half the effort.
The invention also provides a teaching auxiliary system based on big data, which comprises an acquisition and input module, a preprocessing module, a classification module and a teaching auxiliary module,
the acquisition and input module acquires teaching auxiliary data, wherein the teaching auxiliary data comprises examination questions of the college entrance examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details,
the preprocessing module is used for preprocessing the teaching auxiliary data,
the classification module carries out label calibration on the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty and importance, forms a knowledge storage database by utilizing the calibrated teaching auxiliary data,
the teaching auxiliary module is used for assisting teaching by using a qualitative reasoning method according to the knowledge storage database.
The information interaction, execution process and other contents between the modules in the system are based on the same concept as the method embodiment of the present invention, and specific contents can be referred to the description in the method embodiment of the present invention, and are not described herein again.
Similarly, the system collects and inputs the examination questions of the high-level examination in each subject, the high-quality simulation examination questions of each province and city, the content of the examination questions, inspects knowledge points and answer details, carries out informationized standardized processing, carries out label calibration on the examination questions displayed after the processing to form a knowledge storage database of teaching auxiliary data, and assists to integrate important knowledge points in the teaching of a teacher according to a qualitative reasoning method, analyze the emphasis and explain the emphasis, thereby achieving the effect of multiplying the result with half the effort.
It should be noted that not all steps and modules in the above flows and system structures are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The system structure described in the above embodiments may be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by a plurality of physical entities, or some components in a plurality of independent devices may be implemented together.
The above-mentioned embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.
Claims (8)
1. A teaching assistance method based on big data is characterized in that teaching assistance data is collected, the teaching assistance data comprises examination questions of the higher level of examination in each subject, simulation examination questions of each subject in each province and city, examination knowledge points of the examination questions and answer details,
pre-processing is carried out on the teaching assistance data,
labeling the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty degree and importance degree, forming a knowledge storage database by using the labeled teaching auxiliary data,
and (4) assisting teaching by using a qualitative reasoning method according to the knowledge reserve database.
2. The big data based instructional aid method of claim 1, wherein said collecting instructional aid data comprises:
and (4) acquiring the examination questions of the college entrance examination in the each subject in the past year, the simulation examination questions of the subjects in each province and city, the examination question investigation knowledge points and the answer details according to the determined format and the specification.
3. The big data based teaching assistance method of claim 1 or 2, wherein said preprocessing said teaching assistance data comprises:
and creating field mapping for the teaching auxiliary data, and carrying out structuring and standardization processing on the teaching auxiliary data according to mapping fields.
4. The big data based teaching assistance method of claim 1, wherein said teaching assistance data after processing is labeled through a visual interface.
5. The teaching auxiliary system based on big data is characterized by comprising an acquisition and input module, a preprocessing module, a classification module and a teaching auxiliary module,
the acquisition and input module acquires teaching auxiliary data, wherein the teaching auxiliary data comprises examination questions of the college entrance examination in each subject, simulation examination questions of each subject in each province and city, examination question investigation knowledge points and answer details,
the preprocessing module is used for preprocessing the teaching auxiliary data,
the classification module carries out label calibration on the processed teaching auxiliary data according to knowledge point division, question solving thinking, question answering flow, difficulty and importance, forms a knowledge storage database by utilizing the calibrated teaching auxiliary data,
the teaching auxiliary module is used for assisting teaching by using a qualitative reasoning method according to the knowledge storage database.
6. The big data based teaching assistance system of claim 5, wherein said collection and entry module collects teaching assistance data, comprising:
and (4) acquiring and recording the examination questions of the college entrance examination in each subject, the simulation examination questions of each subject in each province and city, the examination questions, the investigation knowledge points of the examination questions and the details of answers according to the instant format and the standard.
7. The big data based instructional aid system according to claim 5 or 6, wherein said preprocessing module preprocesses said instructional aid data comprising:
and creating field mapping for the teaching auxiliary data, and carrying out structuring and standardization processing on the teaching auxiliary data according to mapping fields.
8. The big data based teaching assistance system of claim 5, further comprising a visualization module for tagging said processed teaching assistance data through a visualization interface.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115936940A (en) * | 2022-12-26 | 2023-04-07 | 吉林农业科技学院 | Mathematical simulation teaching system and method based on big data |
Citations (3)
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|---|---|---|---|---|
| JP2002215016A (en) * | 2001-01-18 | 2002-07-31 | Eikoh Inc | Method for analyzing exercise of entrance examination question and storage medium for system of the same |
| CN108345593A (en) * | 2017-01-22 | 2018-07-31 | 北京新唐思创教育科技有限公司 | A kind of teaching handout generation method and its device based on problem database system |
| CN112487183A (en) * | 2020-11-10 | 2021-03-12 | 江苏乐易学教育科技有限公司 | Labeled test question knowledge point classification method and system |
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- 2022-03-18 CN CN202210267636.7A patent/CN114444978A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002215016A (en) * | 2001-01-18 | 2002-07-31 | Eikoh Inc | Method for analyzing exercise of entrance examination question and storage medium for system of the same |
| CN108345593A (en) * | 2017-01-22 | 2018-07-31 | 北京新唐思创教育科技有限公司 | A kind of teaching handout generation method and its device based on problem database system |
| CN112487183A (en) * | 2020-11-10 | 2021-03-12 | 江苏乐易学教育科技有限公司 | Labeled test question knowledge point classification method and system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115936940A (en) * | 2022-12-26 | 2023-04-07 | 吉林农业科技学院 | Mathematical simulation teaching system and method based on big data |
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