CN108961453B - Classroom roll call assistant decision-making system - Google Patents
Classroom roll call assistant decision-making system Download PDFInfo
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Abstract
The invention relates to a classroom roll call assistant decision-making system which is provided with a two-dimensional code generation module, a database module, a roll call evaluation module and a roll call decision-making module, and the flow is executed according to the following mode: firstly, establishing student information and course names in a database module, and establishing a plurality of teaching classes by teachers according to own teaching conditions; secondly, the teacher selects a teaching class needing teaching; thirdly, giving out evaluation parameters by a roll call evaluation module; fourthly, the roll call decision module obtains a roll call decision result, and roll call, spot check or no roll call; and fifthly, corresponding subsequent operations are carried out corresponding to different roll call decision results. The invention can actively help the teacher to decide which roll call mode is the best in the classroom, reduce the occupation of excessive classroom time, avoid unnecessary teaching time waste and improve the teaching quality and the enthusiasm of students for learning.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to a computer network technology, in particular to a classroom roll call assistant decision-making system.
[ background of the invention ]
In the modern teaching process, roll calling is an effective method for examining the attendance rate of students, and the attendance rate is one of important bases for evaluation of ordinary achievements of the students. The roll call condition can reflect the individual learning attitude of the students and the whole learning trend of the teaching class while reflecting the attendance times of the students. The teacher can prompt students who are not loving to study, do not like to attend class and are easy to arrive late to attend class on time and carefully study by calling.
However, it cannot be denied that roll calling, as an important method for improving teaching quality, has many advantages and also has some disadvantages, such as occupying a certain classroom teaching time. If the teaching time is reduced, the teaching progress is necessarily influenced, and if too much classroom time is occupied in the roll call process, the learning enthusiasm of students is also influenced. Therefore, some teachers like random spot check or call when the number of the teachers is less, and occupation of teaching time is reduced as much as possible.
Then in the teaching process, is the roll call, or randomly spot check the roll call or not the roll call, how to make a decision? In order to solve the problem, the inventor invents a classroom roll call assistant decision-making system, and the invention is generated by the system.
[ summary of the invention ]
In order to solve the above problems, an object of the present invention is to provide a classroom roll call assistant decision system, which can actively assist a teacher in deciding which roll call mode is the best in the classroom.
In order to achieve the purpose, the invention adopts the technical scheme that:
the classroom roll call assistant decision-making system is provided with a two-dimensional code generation module, a database module, a roll call evaluation module and a roll call decision-making module, and the flow is executed according to the following mode:
firstly, establishing student information and course names in a database module, and establishing a plurality of teaching classes by teachers according to own teaching conditions;
secondly, the teacher selects a teaching class needing teaching;
thirdly, giving out evaluation parameters by a roll call evaluation module;
fourthly, the roll call decision module obtains a roll call decision result, and roll call, spot check or no roll call;
and fifthly, corresponding subsequent operations are carried out corresponding to different roll call decision results.
The invention is further perfected as follows:
the student information stored in the database module is as shown in table 1:
TABLE 1 student basic information Table
| Number learning | Name (I) | Professional | Class of class |
Meanwhile, personal roll call record and evaluation information obtained by the roll call evaluation module are also stored, as shown in table 2:
TABLE 2 personal roll call record and evaluation chart
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
The roll call evaluation module obtains evaluation parameters by carrying out the following steps:
firstly, acquiring information of a teacher selected for teaching;
secondly, calculating the personal evaluation average value of each student in the teaching class, and assuming that n records exist in the table 2 of the students, the personal evaluation average value calculation method comprises the following steps:
the personal evaluation score average value is (evaluation score 1+ evaluation score 2+ … + evaluation score n)/n, and if n is 0, the personal evaluation score average value of the student is set to 100;
thirdly, calculating the overall class evaluation score average value, and assuming that the number of class students is m, determining the class evaluation score average value as (personal evaluation score average value 1+ personal evaluation score average value 2+ … + personal evaluation score average value m)/m;
fourthly, calculating coefficients according to the class evaluation mean value: the coefficient is the class rating average/100.
The roll call decision module obtains a roll call decision result, and the process is as follows:
step 1, designing a hierarchical model: the system comprises three layers, wherein the lowest layer is a scheme layer which is named after a roll, a spot check and a non-named after a roll respectively; the middle layer is a criterion layer and is used for describing the influence caused by the adopted scheme, and the method comprises the following steps: b1 guarantees attendance, B2 improves learning trend and B3 guarantees teaching progress; the top layer is A roll call suggestion which is used for giving a roll call decision;
step 2, judging the matrix design as follows:
decision matrix of B1
| B1 | C1 | C2 | C3 |
| C1 | 1 | 3 | 5 |
| C2 | 1/3 | 1 | 3 |
| C3 | 1/5 | 1/3 | 1 |
Decision matrix of B2
| B2 | C1 | C2 | C3 |
| C1 | 1 | 3 | 6 |
| C2 | 1/3 | 1 | 5 |
| C3 | 1/6 | 1/5 | 1 |
Decision matrix of B3
| B3 | C1 | C2 | C3 |
| C1 | 1 | 1/3 | 1/7 |
| C2 | 3 | 1 | 1/3 |
| C3 | 7 | 3 | 1 |
Judgment matrix of A
| A | B1 | B2 | B3 |
| B1 | 1 | 1/5 | 1/9 |
| B2 | 5 | 1 | 1/ |
| B3 | 9 | 3 | 1 |
Step 3, calculating the maximum eigenvalue, the eigenvector, the deviation consistency index and the satisfaction consistency index of each matrix, and then obtaining a total hierarchical ranking vector:
(a) calculating the maximum eigenvalue lambda of each matrix and the eigenvector W corresponding to the maximum eigenvalue;
λB1，WB1＝(wB11，wB12，wB13)
λB2，WB2＝(wB21，wB22，wB23)
λB3，WB3＝(wB31，wB32，wB33)
λA，WA＝(wA1，wA2，wA3)
(b) calculating the deviation consistency index of each matrix:
(c) calculating a satisfactory consistency index for each matrix
And RI is 0.58, when CR is less than 0.1, satisfactory consistency is met, otherwise, the judgment matrix is redesigned, and the steps 2 and 3 are repeated.
(d) Calculating a total hierarchical ranking vector W (W1, W2, W3), wherein the calculation method comprises the following steps:
step 4, calculating a decision vector:
in case one, if the class evaluation score mean is greater than or equal to 80, the decision vector is (w1 coefficient, w2 coefficient, w3), and the roll is suggested;
in case two, the class evaluation score is less than 80 and greater than or equal to 60, the decision vector is (w1 coefficient, w2, w3 coefficient), and the extraction is suggested;
in case three, when the class evaluation score is less than 60, the decision vector is (w1, w2 coefficient, w3 coefficient), and the suggestion is roll calling;
and 5, selecting the component with the maximum median of the decision vector as the roll call decision result.
The judgment matrix is a pair comparison matrix, wherein (Ci, Ci) is 1, and (Ci, Cj) selects the following typical values: 1,3,5,6,7,9,1/3,1/5,1/6,1/7,1/9, with larger values indicating greater importance of Ci to Cj and smaller values indicating less importance.
The judgment matrix is redesigned by selecting typical values of (Ci, Cj) for redesigning, wherein (Ci, Ci) is 1, and the requirement of satisfactory consistency needs to be met.
And if the decision result is roll calling, entering a roll calling link:
(1) the teacher selects the teaching class of the classroom;
(2) generating a two-dimensional code, starting roll calling, and recording the time t 1;
(3) the system automatically inserts a new piece of data into the personal roll call record and evaluation table of the student related to the roll call, and sets fields of 'study number', 'course name' and 'roll call start time t 1' of the new piece of data, and other fields are blank;
(4) the student sends the number and the course name of the student to a classroom roll call assistant decision system server through mobile phone code scanning, the system records the arrival time T2 of the information, if the time T2-T1 is less than or equal to 60 minutes, the system updates the personal roll call record and the evaluation table of the student according to the information, otherwise, the roll call record is set as absent, namely, the absent mark is set as T;
(5) after 60 minutes from roll calling, the system sets the absence identifier in the roll calling record of the student without code scanning as T, and the evaluation score field calculation method is shown in Table 3:
TABLE 3 evaluation score calculation method
And if the decision result is spot check, entering a spot check link:
(1) the teacher selects the teaching class of the classroom;
(2) randomly generating a random check list S, wherein the random check list S is { S1, S2, …, sk }, and k is less than m;
(3) manually roll the names of the students in the spot check list, and mark the results;
(4) updating a table 2 of students in the selective examination list S, adding a new record in the table, and recording the evaluation score of the students on attendance as 100; for absent students, the absence flag is set to T and the evaluation score is 0.
After the scheme is adopted, the system can actively find out the roll call mode which is most suitable for the teaching class, the occupation of excessive classroom time is reduced, unnecessary teaching time waste is avoided, and the teaching quality and the learning enthusiasm of students are improved.
[ description of the drawings ]
FIG. 1 is a system configuration of a preferred embodiment of the present invention;
FIG. 2 is a roll call evaluation process in accordance with a preferred embodiment of the present invention;
FIG. 3 is a hierarchical model in the roll call decision process in accordance with the preferred embodiment of the present invention;
FIG. 4 is a flow chart of the roll call process according to the preferred embodiment of the present invention;
FIG. 5 is a flow chart of a spot check link according to a preferred embodiment of the present invention.
[ detailed description ] embodiments
Referring to the attached drawings 1 to 5 of the specification, the present invention is composed of four modules, which are respectively: the two-dimensional code generating module 1, the roll call evaluating module 2, the database module 3 and the roll call decision module 4 are shown in fig. 1. The functions of the respective modules are as follows
Two-dimensional code generation module 1, the main function: and generating a two-dimensional code according to the current date and time, the teacher work number, the teaching class name and the course name.
The roll call evaluation module 2 has the main functions: and evaluating roll call according to the roll call condition of students.
Database module 3, main functions: the database module is mainly used for storing a student basic information table and an individual roll call record and evaluation table. The student basic information table is used for recording the basic information of all students, and the format is shown in the table 1; the personal roll call recording and evaluating table is used for recording the roll call condition of students, and the format is shown in table 2.
TABLE 1 student basic information Table
| Number learning | Name (I) | Professional | Class of class |
TABLE 2 personal roll call record and evaluation chart
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
And the roll call decision module 4 has the main functions of: and (4) performing roll call decision according to roll call records and evaluation information of all students in the teaching class.
The invention is mainly executed according to the following sequence:
firstly, establishing student information and course names in a database module, and establishing a plurality of teaching classes by teachers according to teaching;
secondly, the teacher selects a teaching class needing teaching;
thirdly, giving out evaluation parameters by a roll call evaluation module;
fourthly, the roll call decision module obtains a roll call decision result, and roll call, spot check or no roll call;
and fifthly, corresponding subsequent operations are carried out corresponding to different roll call decision results.
The overall working process of the third roll call evaluation module is shown in fig. 2 and is described as follows:
(1) acquiring information of a teacher selected from a teaching class;
(2) and calculating the personal evaluation average value of each student in the teaching class. Assuming that n records exist in the personal roll call record and evaluation table of students, the personal evaluation mean value calculation method comprises the following steps:
personal evaluation score mean value (evaluation score 1+ evaluation score 2+ … + evaluation score n)/n
If n is 0, the personal evaluation score of the student is set to 100.
(3) And calculating the average value of the overall evaluation of the class. Assuming that the number of students in a class is m, the class evaluation average value calculation method comprises the following steps:
the class rating score mean (personal rating score mean 1+ personal rating score mean 2+ … + personal rating score mean m)/m
(4) Calculating coefficients according to the class evaluation mean value: the coefficient is the class rating average/100. If the average value of the class evaluation score is more than 80 scores, the attendance rate is high, the learning wind and the learning gas are good, and the roll call is avoided as much as possible; if the average value of the class evaluation is between 60 and 80, the attendance rate is medium, the learning trend is general, and proper roll calling or spot check is needed; if the class evaluation average value is less than 60, the attendance rate is low and the wind is poor, and the roll call or spot check is performed as far as possible.
And after the roll call evaluation module 2 finishes the work, the roll call decision module 4 works.
(1) The roll call decision adopts an analytic hierarchy process, and a hierarchical model is designed as follows:
step 1, as shown in fig. 3, the hierarchical model includes three layers, and the lowest layer is a scheme layer: the method comprises 3 basic schemes, namely 'roll call', 'spot check' (namely randomly checking whether m students are on duty) and 'no roll call'. The middle layer is a standard layer: for describing the impact caused by the adopted scheme, respectively: guarantee the rate of attendance, improve study wind-force and guarantee teaching progress. The top layer is the roll call suggestion, which is used to give the roll call decision.
Step 2, judging the design of the matrix
The value of the judgment matrix as the parameter of the system can be adjusted according to the actual requirement, but the requirement of satisfying consistency is required to be met. A group of judgment matrixes adopted in the scheme are as follows:
decision matrix of B1
| B1 | C1 | C2 | C3 |
| C1 | 1 | 3 | 5 |
| C2 | 1/3 | 1 | 3 |
| C3 | 1/5 | 1/3 | 1 |
Decision matrix of B2
| B2 | C1 | C2 | C3 |
| C1 | 1 | 3 | 6 |
| C2 | 1/3 | 1 | 5 |
| C3 | 1/6 | 1/5 | 1 |
Decision matrix of B3
| B3 | C1 | C2 | C3 |
| C1 | 1 | 1/3 | 1/7 |
| C2 | 3 | 1 | 1/3 |
| C3 | 7 | 3 | 1 |
Judgment matrix of A
| A | B1 | B2 | B3 |
| B1 | 1 | 1/5 | 1/9 |
| B2 | 5 | 1 | 1/ |
| B3 | 9 | 3 | 1 |
Step 3, calculating the maximum eigenvalue, the eigenvector, the deviation consistency index and the satisfaction consistency index of each matrix, and then obtaining a total hierarchical ranking vector:
(a) calculating the maximum eigenvalue lambda of each matrix and the eigenvector W corresponding to the maximum eigenvalue;
λB1，WB1＝(wB11，wB12，wB13)
λB2，WB2＝(wB21，wB22，wB23)
λB3，WB3＝(wB31，wB32，wB33)
λA，WA＝(wA1，wA2，wA3)
(b) calculating the deviation consistency index of each matrix:
(c) calculating a satisfactory consistency index for each matrix
And RI is 0.58, when CR is less than 0.1, satisfactory consistency is met, otherwise, the judgment matrix is redesigned, and the steps 2 and 3 are repeated.
(d) Calculating a total hierarchical ranking vector W (W1, W2, W3), wherein the calculation method comprises the following steps:
step 4, calculating a decision vector:
in case one, if the class evaluation score mean is greater than or equal to 80, the decision vector is (w1 coefficient, w2 coefficient, w3), and the roll is suggested;
in case two, the class evaluation score is less than 80 and greater than or equal to 60, the decision vector is (w1 coefficient, w2, w3 coefficient), and the extraction is suggested;
in case three, when the class evaluation score is less than 60, the decision vector is (w1, w2 coefficient, w3 coefficient), and the suggestion is roll calling;
and 5, selecting the component with the maximum median of the decision vector as the roll call decision result.
The judgment matrix is a pair comparison matrix, wherein (Ci, Ci) is 1, and (Ci, Cj) selects the following typical values: 1,3,5,6,7,9,1/3,1/5,1/6,1/7,1/9, with larger values indicating greater importance of Ci to Cj and smaller values indicating less importance.
The above-mentioned redesign judgment matrix is a parameter of the adjustment matrix, taking the matrix B1 as an example:
| B1 | C1 | C2 | C3 |
| C1 | 1 | 3 | 5 |
| C2 | 1/3 | 1 | 3 |
| C3 | 1/5 | 1/3 | 1 |
each of the values therein represents the degree of importance of the element of the present layer to the element of the previous layer, such as the value of 1/3 for (C2, C1), meaning that C2 is less important than C1 for criterion B1, and the value of 5 for (C1, C3), indicating that C1 is significantly more important than C2 for criterion B1, (C1, C1) is necessarily 1, since C1 is certainly equally important relative to C1.
Typical values in this embodiment where the element (Ci, Cj) may be selected are as follows: 1,3,5,7,9,1/3,1/5,1/7,1/9. A larger value indicates that Ci is more important than Cj, and a smaller value indicates less important. Redesign is that other values can be selected for this typical value parameter to form the judgment matrix, but where (Ci, Ci) is 1, the requirement of satisfactory consistency must be satisfied.
If the decision result is roll calling, the roll calling link is entered as shown in fig. 4:
(1) the teacher selects the teaching class of the classroom;
(2) generating a two-dimensional code, starting roll calling, and recording the time t 1;
(3) the system automatically inserts a new piece of data into the personal roll call record and evaluation table of the student related to the roll call, and sets fields of 'study number', 'course name' and 'roll call start time t 1' of the new piece of data, and other fields are blank;
(4) the student sends the number and the course name of the student to a classroom roll call assistant decision system server through mobile phone code scanning, the system records the arrival time T2 of the information, if the time T2-T1 is less than or equal to 60 minutes, the system updates the personal roll call record and the evaluation table of the student according to the information, otherwise, the roll call record is set as absent, namely, the absent mark is set as T;
(5) after 60 minutes of roll calling, the system sets the absence mark in the roll calling record of the student without code scanning as T, and calculates the evaluation score of the roll calling of the student, and the evaluation score field calculation method is shown in Table 3:
TABLE 3 evaluation score calculation method
Note: the system uses the Unix time format, in seconds, with each time represented by a numerical value.
If the decision result is spot check, entering a spot check link as shown in fig. 5:
(1) the teacher selects the teaching class of the classroom;
(2) randomly generating a random check list S, wherein the random check list S is { S1, S2, …, sk }, and k is less than m;
(3) manually roll the names of the students in the spot check list, and mark the results;
(4) updating a table 2 of students in the selective examination list S, adding a new record in the table, and recording the evaluation score of the students on attendance as 100; for absent students, the absence flag is set to T and the evaluation score is 0.
Example one
(1) Suppose there are 5 students in a class, and after 3 roll calls, the personal roll call record and evaluation table of 5 students is as follows:
TABLE 4 personal roll call records and evaluation List of student 1
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
| 1 | English language | 1516025577.00 | 1516025677.00 | 86.67 | |
| 1 | High number | 1516025577.00 | 1516025777.00 | 73.33 | |
| 1 | Politics | 1516025577.00 | 1516026077.00 | 60.00 |
TABLE 5 personal roll call records and evaluation List of student 2
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
| 2 | English language | 1516025577.00 | 1516025877.00 | 60.00 | |
| 2 | High number | 1517379180.00 | 1517379530.00 | 60.00 | |
| 2 | Politics | 1519696630.00 | T | 0.00 |
TABLE 6 personal roll call records and evaluation List of student 3
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
| 3 | English language | 1516025577.00 | 1516025800.00 | 70.27 | |
| 3 | High number | 1517379180.00 | 1517379313.00 | 82.27 | |
| 3 | Politics | 1519696630.00 | 1519696640.00 | 98.67 |
TABLE 7 personal roll call records and evaluation List of student 4
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
| 4 | English language | 1516025577.00 | 1516025727.00 | 80.00 | |
| 4 | High number | 1517379180.00 | 1517379630.00 | 60.00 | |
| 4 | Politics | 1519696630.00 | 1519696880.00 | 66.67 |
TABLE 8 personal roll call records and evaluation List of student 5
| Number learning | Course name | Roll call start time t1 | Code scanning time t2 | Absence mark | Evaluation score |
| 5 | English language | 1516025577.00 | 1516025627.00 | 93.33 | |
| 5 | High number | 1517379180.00 | 1517379250.00 | 90.67 | |
| 5 | Politics | 1519696630.00 | 1519696653.00 | 96.93 |
(2) Calculating personal evaluation score
Student 1 personal evaluation score (86.67+73.33+ 60.00)/3-73.33
Student 2 personal evaluation score (60.00+60.00+ 0.00)/3-40
Student 3 personal evaluation score (70.27+82.27+ 98.67)/3-83.73
Student 4 personal evaluation score (80.00+60.00+66.67)/3 68.89
Student 5 personal evaluation score (93.33+90.67+ 96.93)/3-93.64
(3) Calculating the average value of class evaluation:
class rating mean value (73.33+40+83.73+68.89+ 93.64)/5-71.92
(4) Calculating an evaluation score coefficient
Coefficient 71.92/100 0.7192
(5) And calculating a total hierarchical sequencing vector according to the judgment matrix as follows: (0.33333935,0.33334751,0.37489469). Since the class rating mean is greater than 60 and less than 80, the roll call decision vector is:
(0.33333935*0.7192，0.33334751，0.37489469*0.7192)＝(0.239737657018，0.33334751，0.269624260438)
the second value in the decision vector is the largest, and the corresponding scheme is spot check, so the final roll call decision is spot check.
The above embodiments are merely preferred embodiments of the present disclosure, which are not intended to limit the present disclosure, and any modifications, equivalents, improvements and the like, which are within the spirit and principle of the present disclosure, should be included in the scope of the present disclosure.
Claims (5)
1. A classroom roll call assistant decision-making system is characterized in that: the system is provided with a two-dimensional code generation module, a database module, a roll call evaluation module and a roll call decision module, and executes the flow according to the following mode:
firstly, establishing student information and course names in a database module, and establishing a plurality of teaching classes by teachers according to own teaching conditions;
secondly, the teacher selects a teaching class needing teaching;
thirdly, giving out evaluation parameters by a roll call evaluation module;
fourthly, the roll call decision module obtains a roll call decision result, and roll call, spot check or no roll call;
fifthly, corresponding subsequent operations are carried out corresponding to different roll call decision results;
the student information stored in the database module is as shown in table 1:
TABLE 1 student basic information Table
Meanwhile, personal roll call record and evaluation information obtained by the roll call evaluation module are also stored, as shown in table 2:
TABLE 2 personal roll call record and evaluation chart
；
The roll call evaluation module obtains evaluation parameters by carrying out the following steps:
firstly, acquiring information of a teacher selected for teaching;
secondly, calculating the personal evaluation average value of each student in the teaching class, and assuming that n records exist in the table 2 of the students, the personal evaluation average value calculation method is as follows:
personal evaluation score mean value (evaluation score 1+ evaluation score 2+ … + evaluation score n)/n,
if n is 0, setting the personal evaluation score average value of the student as 100;
thirdly, calculating the overall class evaluation score average value, and assuming that the number of class students is m, determining the class evaluation score average value as (personal evaluation score average value 1+ personal evaluation score average value 2+ … + personal evaluation score average value m)/m;
fourthly, calculating coefficients according to the class evaluation mean value: the coefficient is the class evaluation average value/100;
the roll call decision module obtains a roll call decision result, and the process is as follows:
step 1, designing a hierarchical model: the system comprises three layers, wherein the lowest layer is a scheme layer which is named after a roll, a spot check and a non-named after a roll respectively; the middle layer is a criterion layer and is used for describing the influence caused by the adopted scheme, and the method comprises the following steps: b1 guarantees attendance, B2 improves learning trend and B3 guarantees teaching progress; the top layer is A roll call suggestion which is used for giving a roll call decision;
step 2, judging the matrix design as follows:
decision matrix of B1
Decision matrix of B2
Decision matrix of B3
Judgment matrix of A
Step 3, calculating the maximum eigenvalue, the eigenvector, the deviation consistency index and the satisfaction consistency index of each matrix, and then obtaining a total hierarchical ranking vector:
(a) calculating the maximum eigenvalue lambda of each matrix and the eigenvector W corresponding to the maximum eigenvalue;
λB1，WB1＝(wB11，wB12，wB13)
λB2，WB2＝(wB21，wB22，wB23)
λB3，WB3＝(wB31，wB32，wB33)
λA，wW＝(wA1，wA2，wA3)
(b) calculating the deviation consistency index of each matrix:
wherein n is the dimension of the matrix, and n is 3 in the scheme;
(c) calculating a satisfactory consistency index for each matrix
When CR is less than 0.1, satisfying consistency is met, otherwise, a judgment matrix is redesigned, and the steps 2 and 3 are repeated;
(d) calculating a total hierarchical ranking vector W (W1, W2, W3), wherein the calculation method comprises the following steps:
wherein i is 1, 2, 3, and the total rank order vector W is (W1, W2, W3);
step 4, calculating a decision vector:
in case one, if the class evaluation score mean is greater than or equal to 80, the decision vector is (w1 coefficient, w2 coefficient, w3), and the roll is suggested;
in case two, the class evaluation score is less than 80 and greater than or equal to 60, the decision vector is (w1 coefficient, w2, w3 coefficient), and the extraction is suggested;
in case three, when the class evaluation score is less than 60, the decision vector is (w1, w2 coefficient, w3 coefficient), and the suggestion is roll calling;
and 5, selecting the component with the maximum median of the decision vector as the roll call decision result.
2. The classroom roll call aid decision system as claimed in claim 1, wherein: the judgment matrix is a pair comparison matrix, wherein (Ci, Ci) is 1, and (Ci, Cj) selects the following typical values: 1,3,5,6,7,9,1/3,1/5,1/6,1/7,1/9, with larger values indicating greater importance of Ci to Cj and smaller values indicating less importance.
3. The classroom roll call aid decision system as claimed in claim 1, wherein: the judgment matrix is redesigned by selecting typical values of (Ci, Cj) for redesigning, wherein (Ci, Ci) is 1, and the requirement of satisfactory consistency needs to be met.
4. The classroom roll call aid decision system as claimed in claim 1, wherein: and if the decision result is roll calling, entering a roll calling link:
(1) the teacher selects the teaching class of the classroom;
(2) generating a two-dimensional code, starting roll calling, and recording the time t 1;
(3) the system automatically inserts a new piece of data into the personal roll call record and evaluation table of the student related to the roll call, and sets fields of 'study number', 'course name' and 'roll call start time t 1' of the new piece of data, and other fields are blank;
(4) the student sends the number and the course name of the student to a classroom roll call assistant decision system server through mobile phone code scanning, the system records the arrival time T2 of the information, if the time T2-T1 is less than or equal to 60 minutes, the system updates the personal roll call record and the evaluation table of the student according to the information, otherwise, the roll call record is set as absent, namely, the absent mark is set as T;
(5) after 60 minutes of roll calling, the system sets the absence identifier in the roll calling record of the student without code scanning as T, and the evaluation sub-field calculation method is shown in Table 3:
TABLE 3 evaluation score calculation method
5. The classroom roll call aid decision system as claimed in claim 1, wherein: and if the decision result is spot check, entering a spot check link:
(1) the teacher selects the teaching class of the classroom;
(2) randomly generating a random check list S, wherein the random check list S is { S1, S2, …, sk }, and k is less than m;
(3) manually roll the names of the students in the spot check list, and mark the results;
(4) updating a table 2 of students in the selective examination list S, adding a new record in the table, and recording the evaluation score of the students on attendance as 100; for absent students, the absence flag is set to T and the evaluation score is 0.
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