CN110097099A - A kind of association analysis method based on student classroom performance sexual behaviour and achievement - Google Patents
A kind of association analysis method based on student classroom performance sexual behaviour and achievement Download PDFInfo
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- CN110097099A CN110097099A CN201910317914.3A CN201910317914A CN110097099A CN 110097099 A CN110097099 A CN 110097099A CN 201910317914 A CN201910317914 A CN 201910317914A CN 110097099 A CN110097099 A CN 110097099A
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- 238000012097 association analysis method Methods 0.000 title claims abstract description 9
- 230000007786 learning performance Effects 0.000 claims abstract description 33
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- 238000004458 analytical method Methods 0.000 claims abstract description 18
- 238000012417 linear regression Methods 0.000 claims abstract description 6
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Abstract
The invention discloses a kind of association analysis methods based on student classroom performance sexual behaviour and achievement, acquire the image of all students in classroom by camera first, are analyzed using analysis machine acquired image, obtain the learning performance sexual behaviour of all students;The learning performance sexual behaviour data of all students obtained are subjected to multiple linear regression with the achievement of corresponding student, obtain the regression coefficient of learning performance sexual behaviour and achievement;The classroom participation of each student is found out according to the achievement of the regression coefficient and each student of obtained learning performance sexual behaviour and achievement;Using the classroom participation of each student and corresponding achievement as reference axis, and the mean value line of classroom participation and achievement is drawn out in a coordinate system, obtain four-quadrant scatter plot;All students are divided into four classes based on the four-quadrant scatter plot, realize the association analysis to all students.The classification of student can be presented to automatically teacher in the form of various charts and scale by the above method, facilitated student and taught students in accordance with their aptitude and improve results.
Description
Technical field
The present invention relates to intelligent classroom technical fields, more particularly to a kind of student classroom that is based on to show sexual behaviour and achievement
Association analysis method.
Background technique
Currently, student the participation on classroom be one be difficult to explication the problem of, what teacher can only be subjective pass through
Whether student is active on classroom, whether participates in interaction to judge, or determines the participation of student on merit.Due to learning
Life is multifarious, and the content of courses is ever-changing, and the concern that teacher gives different students is also different, prior art
In, teachers association by more energy concentrate on studying well with poor student, lack it is a kind of scientific and effective and can be objective
Assess the technical solution of student classroom performance and achievement.
Summary of the invention
The object of the present invention is to provide a kind of association analysis method based on student classroom performance sexual behaviour and achievement, the party
The classification of student can be presented to automatically teacher in the form of various charts and scale by method, facilitated student and taught students in accordance with their aptitude and improve
Achievement.
The purpose of the present invention is what is be achieved through the following technical solutions:
A kind of association analysis method based on student classroom performance sexual behaviour and achievement, which comprises
Step 1, the image that all students in classroom are acquired by camera, carry out acquired image using analysis machine
Analysis, obtains the learning performance sexual behaviour of all students;
Step 2, the achievement of the learning performance sexual behaviour data of all students obtained and corresponding student are carried out it is polynary
Linear regression obtains the regression coefficient of learning performance sexual behaviour and achievement;
Step 3 is found out according to the achievement of the regression coefficient and each student of obtained learning performance sexual behaviour and achievement
The classroom participation of each student;
Step 4 draws out the classroom participation of each student and corresponding achievement as reference axis, and in a coordinate system
The mean value line of classroom participation and achievement, obtains four-quadrant scatter plot;
All students are divided into four classes based on the four-quadrant scatter plot by step 5, realize the association point to all students
Analysis.
In step 1, the analysis machine in real time carries out acquired image with sorting technique-rcnn using target positioning
Analysis, obtains the learning performance sexual behaviour of each student, and its position in classroom.
The learning performance sexual behaviour includes following five kinds of behaviors: paying attention to the class, reads and writes, life is interacted, raised one's hand, response.
After step 1 obtains the learning performance sexual behaviour of all students, the method also includes: by all students
Performance sexual behaviour behavior is practised to be presented in front end page in the form of curve, chart.
In step 3, the acquisition process of classroom participation are as follows:
Learning performance sexual behaviour data are denoted as respectively first: paying attention to the class tj, read and write dx, raw interaction ss, raise one's hand js, response
yd;
The regression coefficient of learning performance sexual behaviour and achievement is denoted as respectively: x1- tj, x2- dx, x3- ss, x4- js, x5- yd, with
And degree of fitting R2;
Then classroom participation obtains as follows:
Participation=(x1tj+x2dx+x3ss+x4js+x5yd)+B;
Wherein, x1, x2, x3, x4, x5Indicate that five kinds of behaviors and achievement carry out the coefficient of multiple linear regression, the i.e. power of behavior
Weight values;The displacement of B expression participation.
The detailed process of the step 5 are as follows:
Be divided into all students based on the four-quadrant scatter plot: achievement and participation are all good;Participation is general, achievement
It is good;Participation is high, gets poor results;Participation and achievement are all poor;
Critical life, learning method bad student, study habit bad student are selected according to classifying screen, and navigates to this rank according to demand
The target student that section is paid close attention to.
The method also includes:
By the analysis to particular student multiple stage achievements and participation, moving for particular student achievement and participation is drawn
Move track.
As seen from the above technical solution provided by the invention, the above method can by the classification of student with various charts and
The form of scale is presented to teacher automatically, facilitates student and teaches students in accordance with their aptitude and improve results.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment
Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill in field, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is the association analysis method process provided in an embodiment of the present invention that sexual behaviour and achievement are showed based on student classroom
Schematic diagram;
Fig. 2 is four-quadrant scatterplot schematic diagram provided by the embodiment of the present invention;
Fig. 3 is the traveling locus schematic diagram of student performance and participation provided by the embodiment of the present invention.
Specific embodiment
With reference to the attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on this
The embodiment of invention, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, belongs to protection scope of the present invention.
The embodiment of the present invention is described in further detail below in conjunction with attached drawing, is implemented as shown in Figure 1 for the present invention
The association analysis method flow diagram based on student classroom performance sexual behaviour and achievement that example provides, which comprises
Step 1, the image that all students in classroom are acquired by camera, carry out acquired image using analysis machine
Analysis, obtains the learning performance sexual behaviour of all students;
In step 1, the analysis machine in real time carries out acquired image with sorting technique-rcnn using target positioning
Analysis, obtains the learning performance sexual behaviour of each student, and its position in classroom.
In the specific implementation, the learning performance sexual behaviour may include but unlimited following five kinds of behaviors: paying attention to the class, read and write, give birth to
It is raw interact, raise one's hand, response.
In addition, after the learning performance sexual behaviour for obtaining all students, it can also be by the learning performance of all students
Behavior is presented in front end page in the form of curve, chart, is checked for teacher.
Step 2, the achievement of the learning performance sexual behaviour data of all students obtained and corresponding student are carried out it is polynary
Linear regression obtains the regression coefficient of learning performance sexual behaviour and achievement;
Step 3 is found out according to the achievement of the regression coefficient and each student of obtained learning performance sexual behaviour and achievement
The classroom participation of each student;
In the step, the acquisition process of classroom participation are as follows:
Learning performance sexual behaviour data are denoted as respectively first: paying attention to the class tj, read and write dx, raw interaction ss, raise one's hand js, response
yd;
The regression coefficient of learning performance sexual behaviour and achievement is denoted as respectively: x1- tj, x2- dx, x3- ss, x4- js, x5- yd, with
And degree of fitting R2;
Then classroom participation obtains as follows:
Participation=(x1tj+x2dx+x3ss+x4js+x5yd)+B。
x1, x2, x3, x4, x5Indicate that five kinds of behaviors and achievement carry out the coefficient of multiple linear regression, the i.e. weighted value of behavior;B
Indicate the displacement of participation.
Step 4 draws out the classroom participation of each student and corresponding achievement as reference axis, and in a coordinate system
The mean value line of classroom participation and achievement, obtains four-quadrant scatter plot;
All students are divided into four classes based on the four-quadrant scatter plot by step 5, realize the association point to all students
Analysis.
Specifically, it is illustrated in figure 2 four-quadrant scatterplot schematic diagram provided by the embodiment of the present invention, is based on the four-quadrant
All students are divided by limit scatter plot: achievement and participation are all good;Participation is general, does well in;Participation is high, gets poor results;Ginseng
It is all poor with degree and achievement.In Fig. 2, student 1,2,3 is located at the first quartile of four-quadrant scatter plot, and achievement and participation are below equal
Value, belongs to all poor one kind of participation and achievement.
Critical life, learning method bad student, study habit bad student are selected according to classifying screen, and navigates to this rank according to demand
The target student that section is paid close attention to, then teacher can teach students in accordance with their aptitude to student, improve class's achievement.
Furthermore it is also possible to draw particular student achievement by the analysis to particular student multiple stage achievements and participation
With the traveling locus of participation, it is illustrated in figure 3 the traveling locus of student performance and participation provided by the embodiment of the present invention
Schematic diagram shows factor according to the classroom that the track of Fig. 3 is obtained with student performance variation.
It is worth noting that, the content being not described in detail in the embodiment of the present invention belongs to professional and technical personnel in the field's public affairs
The prior art known.
In conclusion the method for the embodiment of the present invention has the advantages that
(1) by the correlation between analysis student's individual achievement and classroom participation, the student of a class is automatic
Be divided into: achievement and participation are all good;Participation is general, does well in;Participation is high, gets poor results;Participation and all poor four class of achievement,
Facilitate student to teach students in accordance with their aptitude;
(2) filter out critical life, learning method bad student and study habit bad student, and by the classification of student with various charts and
The form of scale is presented to teacher, assists in it and improves results, to improve the achievement of entire class.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Within the technical scope of the present disclosure, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims
Subject to enclosing.
Claims (7)
1. a kind of association analysis method based on student classroom performance sexual behaviour and achievement, which is characterized in that the described method includes:
Step 1, the image that all students in classroom are acquired by camera, divide acquired image using analysis machine
Analysis, obtains the learning performance sexual behaviour of all students;
The learning performance sexual behaviour data of all students obtained are carried out multiple linear with the achievement of corresponding student by step 2
It returns, obtains the regression coefficient of learning performance sexual behaviour and achievement;
Step 3, found out according to the achievement of the regression coefficient and each student of obtained learning performance sexual behaviour and achievement it is each
The classroom participation of student;
Step 4, using the classroom participation of each student and corresponding achievement as reference axis, and draw out classroom in a coordinate system
The mean value line of participation and achievement, obtains four-quadrant scatter plot;
All students are divided into four classes based on the four-quadrant scatter plot by step 5, realize the association analysis to all students.
2. the method for student performance association analysis according to claim 1, which is characterized in that in step 1,
The analysis machine in real time analyzes acquired image with sorting technique-rcnn using target positioning, obtains each
The learning performance sexual behaviour of student, and its position in classroom.
3. the method for student performance association analysis according to claim 1 or claim 2, which is characterized in that
The learning performance sexual behaviour includes following five kinds of behaviors: paying attention to the class, reads and writes, life is interacted, raised one's hand, response.
4. the method for student performance association analysis according to claim 1, which is characterized in that obtain all students in step 1
Learning performance sexual behaviour after, the method also includes: by the learning performance sexual behaviour behavior of all students with curve, chart
Form be presented in front end page.
5. the method for student performance association analysis according to claim 1, which is characterized in that in step 3, classroom participation
Acquisition process are as follows:
Learning performance sexual behaviour data are denoted as respectively first: paying attention to the class tj, read and write dx, raw interaction ss, raise one's hand js, response yd;
The regression coefficient of learning performance sexual behaviour and achievement is denoted as respectively: x1- tj, x2- dx, x3- ss, x4- js, x5- yd, and it is quasi-
Right R2;
Then classroom participation obtains as follows:
Participation=(x1tj+x2dx+x3ss+x4js+x5yd)+B;
Wherein, x1, x2, x3, x4, x5Indicate that five kinds of behaviors and achievement carry out the coefficient of multiple linear regression, the i.e. weighted value of behavior;
The displacement of B expression participation.
6. the method for student performance association analysis according to claim 1, which is characterized in that the detailed process of the step 5
Are as follows:
Be divided into all students based on the four-quadrant scatter plot: achievement and participation are all good;Participation is general, does well in;Ginseng
It is high with degree, it gets poor results;Participation and achievement are all poor;
Critical life, learning method bad student, study habit bad student are selected according to classifying screen, and navigates to this stage weight according to demand
The target student of point concern.
7. the method for student performance association analysis according to claim 1, which is characterized in that the method also includes:
By the analysis to particular student multiple stage achievements and participation, the migration rail of particular student achievement and participation is drawn
Mark.
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CN112528890A (en) * | 2020-12-15 | 2021-03-19 | 北京易华录信息技术股份有限公司 | Attention assessment method and device and electronic equipment |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107609651A (en) * | 2017-08-15 | 2018-01-19 | 华中师范大学 | A kind of design item appraisal procedure based on learner model |
CN108694679A (en) * | 2018-05-15 | 2018-10-23 | 北京中庆现代技术股份有限公司 | A kind of method student's learning state detection and precisely pushed |
CN109636690A (en) * | 2018-12-17 | 2019-04-16 | 中国人民解放军国防科技大学 | Learning effectiveness comprehensive scoring method based on online learning behavior data of learner |
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CN107609651A (en) * | 2017-08-15 | 2018-01-19 | 华中师范大学 | A kind of design item appraisal procedure based on learner model |
CN108694679A (en) * | 2018-05-15 | 2018-10-23 | 北京中庆现代技术股份有限公司 | A kind of method student's learning state detection and precisely pushed |
CN109636690A (en) * | 2018-12-17 | 2019-04-16 | 中国人民解放军国防科技大学 | Learning effectiveness comprehensive scoring method based on online learning behavior data of learner |
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CN112528890A (en) * | 2020-12-15 | 2021-03-19 | 北京易华录信息技术股份有限公司 | Attention assessment method and device and electronic equipment |
CN112528890B (en) * | 2020-12-15 | 2024-02-13 | 北京易华录信息技术股份有限公司 | Attention assessment method and device and electronic equipment |
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Application publication date: 20190806 |