CN107909285A - A kind of method for student's cooperative learning intelligent packet - Google Patents
A kind of method for student's cooperative learning intelligent packet Download PDFInfo
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- CN107909285A CN107909285A CN201711216325.3A CN201711216325A CN107909285A CN 107909285 A CN107909285 A CN 107909285A CN 201711216325 A CN201711216325 A CN 201711216325A CN 107909285 A CN107909285 A CN 107909285A
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- 230000001419 dependent effect Effects 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 claims description 3
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
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- 238000011156 evaluation Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses in a kind of method for student's cooperative learning intelligent packet, supervised learning student model is established according to the data of science, student is divided into tetra- grades of A, B, C, D by different subjects, realize and be grouped by different subjects, different brackets, and group member can be updated at any time according to data, there is higher flexibility.
Description
Technical field
The present invention relates to Internet technical field, is specially a kind of side for student's cooperative learning intelligent packet
Method.
Background technology
Cooperative learning is exactly using cooperative learning group as citation form, and system is using between dynamic factor in teaching
Interaction, promotes the study of student, using the achievement of group as evaluation criterion, reaches the education activities of instructional objective jointly.
At present, the group mode of existing cooperative learning is：Teacher specifies group member, is determined according to total marks of the examination small
The form such as group membership, student oneself packet, has a defect that the foundation or dumb for being grouped no science data.
The content of the invention
It is above-mentioned to solve it is an object of the invention to provide a kind of method for student's cooperative learning intelligent packet
The problem of being proposed in background technology.
To achieve the above object, the present invention provides following technical solution：
The invention discloses a kind of method for student's cooperative learning intelligent packet, comprise the following steps that：
（1）, data acquisition：Student classroom, Outside Class Studying data are collected using information education instrument, such as：Total marks of the examination, rob
Answer number, recording class notes number, classroom notes access number；
（2）, z-score standardization：Each dimensional feature has 0 average after conversion, and unit variance, also makes z-score standardize（Zero-mean
Standardization）, calculation is that characteristic value is subtracted average, divided by standard deviation；
（3）, feature selecting：The correlation between independent variable and dependent variable is analyzed using Pearson correlation coefficient, according to calculating
Pearson correlation coefficient draws the degree of correlation between independent variable and dependent variable；
（4）, svm classifier model：Subject is divided into tetra- class of A, B, C, D by interest using learn kernel functions.
Preferably, the step（3）With（4）In, it is described（3）Middle Pearson correlation coefficient exists（0.5,1）Between it is right
Should（4）In A groups, it is described（3）In Pearson correlation coefficient exist（0,0.5）Between it is corresponding（4）In B groups, it is described（3）Middle skin
You exist at inferior related coefficient（0, -0.5）Between it is corresponding（4）Middle C groups, it is described（3）Middle Pearson correlation coefficient exists（- 0.5, -1）Between
It is corresponding（4）Middle D groups.
Compared with prior art, the beneficial effects of the invention are as follows：
Of the present invention in the method for student's cooperative learning intelligent packet, being established according to the data of science has prison
Educational inspector practises student model, and student is divided into tetra- grades of A, B, C, D by different subjects, is realized by different subjects, different brackets point
Group, and group member can be updated at any time according to data, there is higher flexibility.
Brief description of the drawings
Fig. 1 is study group packet flow chart.
Embodiment
The invention discloses a kind of method for student's cooperative learning intelligent packet, comprise the following steps that：
（1）, data acquisition：Student classroom, Outside Class Studying data are collected using information education instrument, such as：Total marks of the examination, rob
Answer number, recording class notes number, classroom notes access number；
（2）, z-score standardization：Each dimensional feature has 0 average after conversion, and unit variance, also makes z-score standardize（Zero-mean
Standardization）, calculation is that characteristic value is subtracted average, divided by standard deviation；
（3）, feature selecting：The correlation between independent variable and dependent variable is analyzed using Pearson correlation coefficient, according to calculating
Pearson correlation coefficient draws the degree of correlation between independent variable and dependent variable；
（4）, svm classifier model：Subject is divided into tetra- class of A, B, C, D by interest using learn kernel functions.
Preferably, the step（3）With（4）In, it is described（3）Middle Pearson correlation coefficient exists（0.5,1）Between it is right
Should（4）In A groups, it is described（3）In Pearson correlation coefficient exist（0,0.5）Between it is corresponding（4）In B groups, it is described（3）Middle skin
You exist at inferior related coefficient（0, -0.5）Between it is corresponding（4）Middle C groups, it is described（3）Middle Pearson correlation coefficient exists（- 0.5, -1）Between
It is corresponding（4）Middle D groups.
Teacher by record the total marks of the examination of every class of student, race to be the first to answer a question number, recording class notes number, classroom notes look into
Number is read, and student examination achievement is calculated by z=(x- μ)/σ, races to be the first to answer a question number, recording class notes number, classroom notes
Section's purpose scale corresponding to consulting number, then passes through Pearson came formula
The degree of correlation between independent variable and dependent variable is calculated, further according to the size of Pearson correlation coefficient, by subject by
Raw interest is divided into tetra- class of A, B, C, D.
It can be obtained by above-mentioned student model：
Student 1=[B, A, C, A, B, C, A, D, D]
Student 2=[C, A, D, B, A, C, C, D, C]
Student 3=[A, C, A, A, B, A, A, A, A]
Student 4=[B, A, B, A, A, A, B, B, C]
Student 5=[C, D, D, C, D, D, D, D, D]
Student 6=[D, B, C, D, A, B, B, C, B]
Student 1 { B }, student 2 { C }, student 3 { A }, student 6 { D } are divided into one group by interested in Chinese language now, by mathematics
Interested that student 1 { A }, student 3 { C }, student 5 { D }, student 6 { B } are divided into one group, so we can be student by not
Equal purpose Grasping level is divided into cooperative learning group, while adjusts student grouping at any time according to data.
Although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
Understanding without departing from the principles and spirit of the present invention can carry out these embodiments a variety of changes, modification, replace
And modification, the scope of the present invention is defined by the appended.
Claims (2)
- A kind of 1. method for student's cooperative learning intelligent packet, it is characterised in that：Comprise the following steps that：（1）, data acquisition：Student classroom, Outside Class Studying data are collected using information education instrument, such as：Total marks of the examination, rob Answer number, recording class notes number, classroom notes access number；（2）, z-score standardization：Each dimensional feature has 0 average after conversion, and unit variance, also makes z-score standardize（Zero-mean Standardization）, calculation is that characteristic value is subtracted average, divided by standard deviation；（3）, feature selecting：The correlation between independent variable and dependent variable is analyzed using Pearson correlation coefficient, according to calculating Pearson correlation coefficient draws the degree of correlation between independent variable and dependent variable；（4）, svm classifier model：Subject is divided into tetra- class of A, B, C, D by interest using learn kernel functions.
- A kind of 2. method for student's cooperative learning intelligent packet according to claim 1, it is characterised in that：Institute The step of stating（3）With（4）In, it is described（3）Middle Pearson correlation coefficient exists（0.5,1）Between it is corresponding（4）In A groups, it is described（3） In Pearson correlation coefficient exist（0,0.5）Between it is corresponding（4）In B groups, it is described（3）Middle Pearson correlation coefficient exists（0 ,- 0.5）Between it is corresponding（4）Middle C groups, it is described（3）Middle Pearson correlation coefficient exists（- 0.5, -1）Between it is corresponding（4）Middle D groups.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201711216325.3A CN107909285A (en) | 2017-11-28 | 2017-11-28 | A kind of method for student's cooperative learning intelligent packet |
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| CN201711216325.3A CN107909285A (en) | 2017-11-28 | 2017-11-28 | A kind of method for student's cooperative learning intelligent packet |
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| CN107909285A true CN107909285A (en) | 2018-04-13 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110287331A (en) * | 2019-06-04 | 2019-09-27 | 广州视源电子科技股份有限公司 | Work compound group determines method, apparatus, equipment and storage medium |
| CN113610679A (en) * | 2021-08-06 | 2021-11-05 | 四川牛阶科技有限责任公司 | Online learning method and system based on supervision constraint |
-
2017
- 2017-11-28 CN CN201711216325.3A patent/CN107909285A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110287331A (en) * | 2019-06-04 | 2019-09-27 | 广州视源电子科技股份有限公司 | Work compound group determines method, apparatus, equipment and storage medium |
| CN113610679A (en) * | 2021-08-06 | 2021-11-05 | 四川牛阶科技有限责任公司 | Online learning method and system based on supervision constraint |
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Address after: Room 705, Building 5, Information Road, Songshan Lake Park, Dongguan City, Guangdong Province Applicant after: Guangdong Mozi Education Technology Co.,Ltd. Address before: Room 705, 7th floor, Rongyi Building, No. 5 Information Road, Songshan Lake Hi-tech Industrial Development Zone, Dongguan City, Guangdong Province Applicant before: DONGGUAN YOUSHAN ELECTRONIC TECHNOLOGY CO.,LTD. |
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| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180413 |