Competition type learning evaluation method and system based on multi-weight TOPSIS method

Abstract

The invention relates to a competition type learning evaluation method and system based on a multi-weight TOPSIS method. The method comprises the following steps: establishing a multi-dimensional judgment matrix based on the multi-weight TOPSIS method; dividing the students into proper learning groups according to the matrix; establishing an assessment and evaluation system; constructing an evaluation mechanism; and based on an evaluation mechanism, teachers coordinate student project research. The teacher divides the research into a later stage direction and an early stage direction according to the required professional ability, and groups are divided according to the research; the weights of the divided groups are made, the teachers make corresponding test papers according to the required professional ability, then a multi-weight topsis method is adopted to calculate the scores of the test papers of the students, and evaluation results form a multi-dimensional judgment matrix. The ability of the students in multiple dimensions is analyzed at the same time according to the matrix, and the students are distributed to different groups for learning; in the research, an evaluation mechanism constructed according to an examination evaluation system is adopted to supervise and guide students, and preparation is made for follow-up teachers to coordinate student research projects based on evaluation scores.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent education, and specifically relates to a competitive learning evaluation method and system based on a multi-weighted TOPSIS method. Background Art

[0002] With the development of weighted TOPSIS method, it is becoming more and more common to use weighted TOPSIS method to solve problems. However, the traditional weighted TOPSIS method can only obtain evaluation results under one weight each time the evaluation process is executed. This leads to the grouping method being too single in the traditional case, the grouping between students is not reasonable, and the evaluation system after grouping is not perfect. When it is necessary to obtain the evaluation results of the evaluation object under multiple different weights, it takes a lot of energy, so a more reasonable grouping method and a more complete evaluation system are increasingly valued.

[0003] At present, there are two problems to be solved in domestic higher education teaching: First, when college students are studying for competitions, due to the lack of mutual understanding between teachers and students, the problem of unreasonable grouping of students arises, resulting in the inability of team members to give full play to their abilities and difficulty in completing subsequent multidisciplinary cross-disciplinary projects.

[0004] Second, due to the imperfect evaluation system of each study group after grouping, the teacher is unable to track the effective learning level of students in the study group, resulting in the teacher being unable to provide accurate learning guidance to each group member.

[0005] Although there are some innovations in the existing domestic higher education evaluation methods and systems, there are still some shortcomings. For example, the paper "Evaluation of College Students' Innovation Ability Based on Combined Weighted Fuzzy TOPSIS Method in the Context of Industry-University-Research Cooperation" discloses an evaluation method based on the fuzzy TOPSIS method. The system uses the fuzzy TOPSIS method combined with the matching matrix of colleges and enterprises to obtain a new evaluation model, reconstruct a new evaluation system for college students' innovation ability, and evaluate students' innovation education.

[0006] Although the above evaluation scheme has improved the rationality of the evaluation of student innovation education to a certain extent, this method mainly relies on the requirements of enterprises and does not involve the direction planning, training process and monitoring of students during the learning process. Therefore, there is still room for improvement in the comprehensiveness of student training and the guidance and monitoring of students before and after the evaluation.

[0007] Based on this, there is an urgent need to develop a new competitive learning evaluation method and system to solve the current problems of unreasonable grouping and imperfect learning progress tracking after grouping. Summary of the invention

[0008] The purpose of the present invention is to provide a competition performance evaluation method and system based on the multi-weighted TOPSIS method, so as to solve the problem of using the weighted TOPSIS evaluation method to group projects, and construct an evaluation mechanism using the TOPSIS method to supervise and guide competition students, so as to facilitate subsequent teachers to provide accurate guidance to student projects based on weekly assessment and evaluation scores.

[0009] The objective of the present invention is achieved through the following technical solutions:

[0010] A competitive learning evaluation method based on a multi-weighted TOPSIS method comprises the following steps:

[0011] A. Establish a multi-dimensional judgment matrix based on the multi-weight TOPSIS method;

[0012] B. Divide students into appropriate study groups based on the established multi-dimensional judgment matrix;

[0013] C. Establish an assessment and evaluation system;

[0014] D. Based on the assessment and evaluation system, an evaluation mechanism using the TOPSIS method is established;

[0015] E. Based on the evaluation mechanism, teachers coordinate student project research.

[0016] Furthermore, step A specifically includes the following steps:

[0017] A1. Teachers divide the project research into several research directions according to the professional abilities required for the research, and then divide the research directions into early and late directions according to the difficulty or comprehensiveness required for the research directions; among them, the direction with high difficulty or strong comprehensiveness is defined as the late direction, and the other directions involving only a single subject knowledge are defined as the early direction; research direction = early direction + late direction, assuming that there are n research directions, a early direction, and b late directions, that is, n = a + b; then, analyze and count the number of professional abilities required for these n research directions, assuming that the required professional abilities are m items;

[0018] A2. Divide the groups according to the preliminary directions. Set a corresponding group for each preliminary direction, for a total of a groups. Different weights will be set for the divided groups according to different research directions, and each group corresponds to a weight;

[0019] A3. The teacher prepares m corresponding competency assessment test papers according to the m required professional competencies, and then uses the multi-weighted TOPSIS method to calculate the students' test scores, and then the calculation results are combined into a multi-dimensional judgment matrix.

[0020] Furthermore, in step A3, the student score calculation process is as follows:

[0021] A31. Construct a matrix of each student's test scores as follows:

[0022]

[0023] Among them, a ij represents the score of the jth test paper of the i-th student;

[0024] The matrix is ​​standardized to eliminate the influence of different indicator dimensions. The standardized matrix uses the following formula:

[0025] The normalized matrix is:

[0026] A32. Determine the maximum value B max , and the minimum value B min ;

[0027] B max =[b 1 max , b 2 max ,…b m max ]

[0028] =[max(b 11 , b 21 …b n1 )、max(b 12 , b 22 …b n2 ), …, max(b 1m , b 2m …b nm )]

[0029] B min =[b 1 min , b 2 min ,…b m min ]

[0030] =[min(b 11 , b 21 …b n1 )、min(b 12 , b 22 …b n2 )、…、min(b 1m , b 2m …b nm )]

[0031] Among them, b j max for b 1j ,b2j …b nj The maximum value;

[0032] b j min for b 1j ,b 2j …b nj Minimum value among (j=1,2,…,m);

[0033] A33, get the weight ω a Next score:

[0034] First find the distance D between the i-th (i=1, 2, 3...n) student and the maximum value at weight a ai max The distance D from the minimum value ai min ;

[0035] in,

[0036] Then the score of the i-th (i=1, 2, 3...n) student with weight a is calculated and normalized to obtain:

[0037]

[0038] The evaluation results are combined into a multi-dimensional judgment matrix as follows:

[0039]

[0040] Among them, S ij (i=1, 2, ..., e, j=1, 2, 3...n) represents the score of student j under weight i.

[0041] Furthermore, in step B, the multi-dimensional abilities of students are analyzed simultaneously according to the multi-dimensional judgment matrix, and students are divided into different groups for study. Students with strong abilities in a single dimension are assigned to specialize in a certain direction; students with broad ability dimensions are assigned to be responsible for the connection between various directions, so that each student can be assigned tasks suitable for him / her according to his / her own knowledge system.

[0042] Furthermore, in step C, students report and are assessed periodically. The assessment evaluation system is divided into objective characteristic quantity assessment and subjective characteristic quantity assessment. Among them, objective characteristic quantity is: characteristic quantity that can be reasonably evaluated by objective scoring, including answer quality and work progress; subjective characteristic quantity is: characteristic quantity that can be reasonably evaluated by subjective scoring, including achievements, work summary and project progress.

[0043] Furthermore, in step D, the evaluation mechanism is a mechanism for gradually adjusting the proportion of objective characteristic quantity assessment and subjective characteristic quantity assessment in the evaluation system according to the progress of the project. The objective characteristic quantity assessment adopts the weighted TOPSIS method to evaluate the objective characteristic quantity, and the subjective characteristic quantity assessment adopts the subjective scoring method to evaluate the subjective characteristic quantity. The weights of the objective characteristic quantity assessment and the subjective characteristic quantity assessment are both set by the teacher. As the project progresses, the weight of the subjective characteristic quantity assessment gradually occupies the vast majority of the assessment.

[0044] Further, step E is specifically:

[0045] E1. Students report in groups, and teachers ask questions and give scores around the tasks to evaluate the students’ task completion;

[0046] E2. After the student has finished his report, the teacher and other students will rate the student based on the achievements, work summary, and project progress;

[0047] E3. Bring the objective and subjective characteristic quantities into the assessment weight calculation to obtain the assessment score, and coordinate students' research on new and later directions based on the assessment score.

[0048] A teacher evaluation system adopts the competitive learning evaluation method based on the multi-weighted TOPSIS method, and the evaluation system includes: a matrix evaluation unit, a grouping auxiliary unit, a feature quantity setting unit, a weekly meeting assessment unit and a research auxiliary unit;

[0049] The matrix evaluation unit is used to receive the scores of each student's professional ability test paper, calculate the student's test paper scores based on the multi-weighted TOPSIS method, that is, push m ability evaluation test papers to the student end, and obtain a multi-dimensional judgment matrix based on the student's test paper answer situation on the student end;

[0050] The grouping auxiliary unit is used to obtain the value of each element in the multi-dimensional judgment matrix, that is, the ability value of the students under different weights, generate a line chart based on the element value, and assist teachers in analyzing the ability of students in each dimension and thereby dividing the students into different groups for learning;

[0051] The feature quantity setting unit is used to respond to the setting operation of the user teacher on the teacher side for the subjective feature quantity and the objective feature quantity, and set the inclusion items of the subjective feature quantity and the objective feature quantity in the assessment and evaluation system, so that the evaluation mechanism is established;

[0052] The weekly meeting assessment unit is used to obtain the subjective characteristic quantity and objective characteristic quantity scores of each student on the student side and the teacher side, and output the obtained scores to the research auxiliary unit after processing, so as to provide data support for the research auxiliary unit; the subjective characteristic quantity is evaluated by the subjective scoring method, and the objective characteristic quantity is evaluated by the weighted TOPSIS method, and the weekly meeting assessment unit will adjust the proportion of the subjective characteristic quantity and the objective characteristic quantity in the evaluation mechanism according to the research progress of the project;

[0053] The research auxiliary unit is used to reprocess the data obtained in the weekly assessment, and calculate based on the algorithm in the weekly assessment unit to obtain the total score of each student, and then generate a capability map and various parameters of the project research through the student scores; assist teachers in providing precise guidance to student projects; and display various parameters of the research.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention adopts the weighted TOPSIS method to construct an evaluation mechanism; the teacher first analyzes the professional capabilities required for the project research, and divides the research into several directions according to the required professional capabilities, among which a direction with high difficulty or strong comprehensiveness is defined as the late direction, and the other directions involving only a single subject knowledge are defined as the early direction, and the groups are divided according to the early directions, each early direction corresponds to a group, and weights are set for the divided groups, and then the teacher prepares the corresponding test papers according to the required professional capabilities, and then uses the multi-weight TOPSIS method to calculate the student test paper scores, and then the evaluation results are formed into a multi-dimensional judgment matrix; then refer to the matrix to analyze the students' multi-dimensional capabilities, assign students to different groups for learning, so that each student can be assigned to tasks suitable for him according to his degree of knowledge mastery; thereby, through a specific grouping process, the originally scattered and disordered grouping method tends to be standardized and orderly, so as to solve the current unreasonable grouping problem. In the progress of the project after grouping, weekly assessments are used to obtain the numerical values ​​of students' subjective and objective characteristics, and the evaluation mechanism using the TOPSIS method is constructed according to the evaluation system to obtain students' evaluation scores; this prepares for subsequent teachers to coordinate student research projects based on evaluation scores; thereby solving the current problem that university competition learning has no clear direction and teachers cannot accurately guide students. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0057] Figure 1 Flowchart of the competitive learning evaluation method based on the multi-weighted TOPSIS method;

[0058] Figure 2 Flowchart of group division;

[0059] Figure 3 System architecture diagram;

[0060] Figure 4 System diagram. DETAILED DESCRIPTION

[0061] The present invention will be further described below in conjunction with embodiments:

[0062] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0063] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0064] University competitions are innovative competitions, which are competitions for college students. Participants are required to research and complete a specific project and submit plans, physical objects or papers, etc. The competition focuses on the intersection between disciplines, the cooperation of students' abilities and the innovation of research projects. It can promote communication and cooperation among students and enhance students' ability to learn innovatively. To this end, the present invention aims at the problems that the current grouping method of university competition learning is scattered and disordered, and the assessment and evaluation system after grouping is imperfect. A competitive learning evaluation method and system based on the multi-weighted TOPSIS method is proposed, which aims to add multiple weights when calculating the evaluation results to obtain evaluation results under different weights.

[0065] like Figure 1 As shown, the competitive learning evaluation method based on the multi-weighted TOPSIS method of the present invention comprises the following steps:

[0066] 1. Establish a multi-dimensional judgment matrix based on the multi-weight TOPSIS method;

[0067] 2. Divide students into appropriate study groups based on the established multi-dimensional judgment matrix;

[0068] 3. Establish an assessment and evaluation system;

[0069] 4. Based on the assessment and evaluation system, establish an evaluation mechanism using the TOPSIS method;

[0070] 5. Based on the evaluation mechanism, teachers coordinate student project research.

[0071] Step 1 specifically includes the following steps:

[0072] 11. Teachers analyze the professional capabilities required for project research, and divide the research into several research directions based on the required professional capabilities. Among them, the directions with high difficulty or strong comprehensiveness are defined as late-stage directions, and the other directions that only involve knowledge of a single subject are defined as early-stage directions. Among them, the required professional capabilities are m items, and "research direction" = "early-stage direction" + "late-stage direction", there are a early-stage directions and b late-stage directions.

[0073] 12. Divide the groups according to the preliminary directions. Each preliminary direction corresponds to a group, for a total of a groups. Set weights for the divided groups, and each group corresponds to a weight.

[0074] 13. The teacher prepares m corresponding test papers according to the required m professional abilities, and then uses the multi-weighted TOPSIS method to calculate the student test scores. The calculation process is as follows:

[0075] 131. Construct a matrix of each student's test scores as follows:

[0076]

[0077] Among them, a nm Represents the score of the mth test paper of the nth student.

[0078] The matrix is ​​standardized to eliminate the influence of different indicator dimensions, and the standardized matrix is ​​recorded as B. The standardized matrix uses the following formula:

[0079] The normalized matrix is:

[0080] 132. Determine the maximum value B max , and the minimum value B min .

[0081] B max =[b 1 max , b 2 max ,…b j max ]

[0082] =[max(b 11 , b 21 …b i1 )、max(b12 , b 22 …b i2 ), …, max(b 1j , b 2j …b ij )]

[0083] B min =[b 1 min , b 2 min ,…b j min ]

[0084] =[min(b 11 , b 21 …b i1 )、min(b 12 , b 22 …b i2 )、…、min(b 1j , b 2j …b ij )]

[0085] Among them, b h max for b 1j ,b 2j …b ij The maximum value;

[0086] b h min for b 1j ,b 2j …b ij Minimum value among (h=1,2,…,j);

[0087] 133. The weight ω is obtained a Next score:

[0088] First find the distance D between the i-th (i=1, 2, 3...n) student with weight a and the maximum value ai max and the minimum value distance D ai min .

[0089] in,

[0090] Then the score of the i-th (i=1, 2, 3...n) student with weight a is calculated and normalized to obtain:

[0091]

[0092] The evaluation results are combined into a multi-dimensional judgment matrix as follows:

[0093]

[0094] Among them, Sij (i=a, b, ..., e, j=1, 2, 3...n) represents the score of student j under weight i.

[0095] Step 2: Analyze students' abilities in multiple dimensions based on the matrix, divide students into different groups for study, assign students with strong abilities in a single dimension to specialize in a certain direction; assign students with broad abilities to be responsible for the connection between various directions, so that each student can be assigned tasks that suit him or her according to his or her own knowledge system.

[0096] Step 3: After grouping, the teacher sets a reporting cycle and students report in groups. Students will be assessed during the reporting process. The assessment system is divided into objective feature quantity assessment and subjective feature quantity assessment. Among them, objective feature quantity is: feature quantity that can be reasonably evaluated by objective scoring; subjective feature quantity is: feature quantity that can be reasonably evaluated by subjective scoring.

[0097] Specifically, objective characteristics include answer quality and work progress; subjective characteristics include achievements, work summary and project progress.

[0098] Step 4, the evaluation mechanism is a mechanism for gradually adjusting the proportion of objective characteristic quantity assessment and subjective characteristic quantity assessment in the evaluation system according to the progress of the project. The objective characteristic quantity assessment adopts the weighted TOPSIS method to evaluate the objective characteristic quantity, and the subjective characteristic quantity assessment adopts the subjective scoring method to evaluate the subjective characteristic quantity. The weights of the objective characteristic quantity assessment and the subjective characteristic quantity assessment are set by the teachers. As the project progresses, the weight of the subjective characteristic quantity assessment gradually occupies the vast majority of the assessment.

[0099] Step 5, when the teacher coordinates the research, when the students start reporting in groups, the teacher will ask the students random questions about the task, and the teacher will score the students based on their answers to the questions, and then evaluate the students' task completion. After the students have finished their reports, the teacher and other students will score the students based on the results achieved, work summary, and project progress. Finally, the objective and subjective feature quantity assessments are brought into the assessment weight calculation to obtain the assessment score. The teacher guides students to research the problems encountered by each group during the report. Record the new directions discovered during the study, and subsequently coordinate students' research on new and later directions based on the weekly assessment scores.

[0100] Another aspect of the present invention provides a teacher evaluation system, which adopts the competitive learning evaluation method based on the multi-weighted TOPSIS method, and the evaluation system includes:

[0101] Matrix evaluation unit, grouping assistance unit, characteristic quantity setting unit, weekly meeting assessment unit and research assistance unit.

[0102] The matrix evaluation unit is configured to: receive the scores of each professional ability test paper of each student, calculate the student test paper scores based on the multi-weight TOPSIS method, and obtain a multi-dimensional judgment matrix;

[0103] The grouping auxiliary unit is configured to: obtain the value of each unit in the multi-dimensional judgment matrix, generate a line chart based on the value of each unit, assist the teacher in analyzing the ability of each dimension of the students and divide the students into different groups for learning;

[0104] The feature quantity setting unit is configured to: in response to the user teacher's setting operation of the subjective feature quantity and the objective feature quantity, set the inclusion items of the subjective feature quantity and the objective feature quantity in the assessment and evaluation system, so as to obtain the subjective feature quantity and the objective feature quantity that meet the project;

[0105] The weekly meeting assessment unit is configured to: obtain the subjective feature quantity and objective feature quantity scores of each student on the student side and the teacher side, process the obtained scores and output them to the research auxiliary unit to provide data support for the research auxiliary unit; the subjective feature quantity is evaluated by the subjective scoring method, and the objective feature quantity is evaluated by the weighted TOPSIS method, and the weekly meeting assessment unit will adjust the proportion of the subjective feature quantity and the objective feature quantity in the evaluation mechanism according to the research progress of the project;

[0106] The research auxiliary unit is configured to: process the data after the weekly meeting assessment, and calculate based on the data in the weekly meeting assessment unit to obtain the score of each student, and then generate a capability map through the student scores to assist teachers in providing accurate guidance on student projects;

[0107] Example 1

[0108] This embodiment analyzes the research example of the water environment detection scientific research project of the School of Electrical Engineering of Changchun Institute of Technology, and proposes a competitive learning evaluation method based on the multi-weighted TOPSIS method. The specific steps are as follows:

[0109] First, teachers and students determine a potential and innovative research project based on the theme of the competition. The following is an example of the water environment testing project from the Changchun Institute of Technology’s entry to the College Students’ Innovation and Entrepreneurship Training Program Competition.

[0110] After determining the research topic, through analyzing the professional capabilities required for the water environment testing project, it was concluded that the professional capabilities required for the project are: instrument and equipment use capabilities, experimental method design capabilities, mechanical design capabilities, engineering drawing capabilities, circuit analysis and design capabilities, and based on these required professional capabilities, the project research was preliminarily divided into four directions: environmental engineering, mechanical engineering, electrical engineering, and system integration. In the water environment testing example, the system integration direction involves interconnecting and controlling the circuits, signal processing, and mechanical parts to ensure the normal operation and function realization of each component of the device. The research is difficult when the theoretical knowledge reserve is insufficient in the early stage. Figure 2 As shown, the system integration direction and the problems encountered in the research and the new directions generated are arranged in the later research, and the remaining environmental engineering direction, mechanical engineering direction, and electrical engineering direction only involve single subject knowledge and are suitable for early research.

[0111] The groups were divided according to the previous directions: environmental engineering, mechanical engineering, and electrical engineering. Figure 2 As shown in the figure, each direction corresponds to a group with a total of 3 groups, namely Group 1 studies environmental engineering, Group 2 studies mechanical engineering, and Group 3 studies electrical engineering. Then, weights are set for each group, and the weights of the three groups are w1, w2, and w3 respectively. Then, the teacher prepares 5 corresponding test papers according to the ability to use instruments and equipment required by the project, experimental method design ability, mechanical design ability, engineering drawing ability, circuit analysis and design ability. Test paper 1 examines students' ability to correctly operate and calibrate instruments such as water quality analyzers and dissolved oxygen meters, test paper 2 examines students' ability to choose appropriate experimental methods according to different problems, test paper 3 examines students' ability to plan and manage mechanical manufacturing and processing technology, test paper 4 examines students' engineering drawing ability, and test paper 5 examines circuit analysis and design ability. Finally, the multi-weight TOPSIS method is used to calculate the student test papers. Table 1 is the transcript obtained by the above test for this example.

[0112] Table 1

[0113]

[0114] The specific calculation process is as follows:

[0115] The first step is to construct a matrix of each student's test scores and standardize the matrix as follows:

[0116]

[0117] Among them, a nm It represents the score of the mth test paper of the nth student. In this example, n is 4 and m is 5.

[0118] The second step is to determine the maximum value Bmax , and the minimum value B min .

[0119] B max =[b 1 max , b 2 max ,…b j max ]

[0120] =[max(b 11 , b 21 …b i1 )、max(b 12 , b 22 …b i2 ), …, max(b 1j , b 2j …b ij )]

[0121] =[0.6008,0.6390,0.8206,0.8058,0.6199]

[0122] B min =[b 1 min , b 2 min ,…b j min ]

[0123] =[min(b 11 , b 21 …b i1 )、min(b 12 , b 22 …b i2 )、…、min(b 1j , b 2j …b ij )]

[0124] =[0.4206,0.3652,0.2872,0.2120,0.3409]

[0125] where b h max for b 1j ,b 2j …b ij The maximum value;

[0126] b h min for b 1j ,b 2j …b ij Minimum value among (h=1,2,…,j);

[0127] The third step is to get the weight ω a Next score:

[0128] First find the distance D between the i-th (i=1, 2, 3…n) student with weight a=[0.15, 0.15, 0.05, 0.05, 0.60] and the maximum value ai max and the minimum value distance D ai min .

[0129] in

[0130] D ai max =[0.1637,0.2438,0.1421,0.2518];

[0131] D ai min =[0.2282,0.1800,0.2168,0.0765]

[0132] Then, the score of the i-th (i=1, 2, 3...n) student with weight a is calculated and normalized to obtain:

[0133]

[0134] That is S ai =[0.3158,0.2303,0.3276,0.1263]

[0135] Then, the weight b = [0.10, 0.10, 0.35, 0.35, 0.10] is calculated;

[0136] c = the score under [0.40, 0.40, 0.05, 0.05, 0.10],

[0137] Score: S bi =[0.1632,0.5433,0.2455,0.0480]

[0138] S ci =[0.2603,0.2766,0.3645,0.0987]

[0139] Finally, the multi-dimensional judgment matrix is ​​formed:

[0140]

[0141] Among them, S ij(i=a, b, ..., e, j=1, 2, 3...n) represents the test score of the i-th student under weight j.

[0142] The matrix below is a multi-dimensional judgment matrix of students in the water environment testing project of Changchun Institute of Technology:

[0143]

[0144] Then, referring to the matrix, we analyze the students' abilities in three dimensions: environmental engineering, mechanical engineering, and electrical engineering, and divide the students into different groups for study.

[0145] From the above multi-dimensional judgment matrix, we can conclude that student A is weak in the two dimensions of mechanical engineering and electrical engineering, but is strong in the dimension of environmental engineering; student B is weak in the two dimensions of electrical engineering and environmental engineering, but is strong in the dimension of mechanical engineering; student C is strong in the two dimensions of electrical engineering and environmental engineering, but is weak in the dimension of mechanical engineering; student D is not outstanding in the three dimensions of environmental science, mechanical engineering, and electrical engineering, but is slightly stronger in electrical engineering. Therefore, student A is assigned to group 1 and student B is assigned to group 2. Since groups 1 and 2 already have two students with strong abilities, student A and student B, student C and student D are assigned to group 3.

[0146] After dividing the students into groups for study, the teacher then assigns the most suitable tasks to the students according to their knowledge system. For example, in the above example, in the early stage of the project research, A is arranged to study electrical engineering; B is arranged to study mechanical engineering; C and D are arranged to study environmental engineering. And from the multi-dimensional judgment matrix shown above, it can be seen that student C has strong abilities in both electrical engineering and environmental engineering, so he is responsible for studying environmental engineering and also for connecting with students studying electrical engineering.

[0147] In group learning, teachers set reporting cycles, and students report in groups. Students will be assessed during the reporting, and the assessment and evaluation system is divided into objective feature quantity assessment and subjective feature quantity assessment. Then, an evaluation mechanism is constructed based on the assessment and evaluation system. This mechanism is a mechanism that gradually adjusts the proportion of objective feature quantity assessment and subjective feature quantity assessment in the assessment and evaluation system according to the progress of the project. The objective feature quantity assessment uses the weighted topsis method to evaluate the objective feature quantity, and the subjective feature quantity assessment uses the subjective scoring method to evaluate the subjective feature quantity. The weights of the objective feature quantity assessment and the subjective feature quantity assessment are set by the teacher. As the project progresses, the weight of the subjective feature quantity assessment gradually occupies the vast majority of the assessment.

[0148] In the example of the water environment testing project of Changchun Institute of Technology, the objective characteristic quantities include: answer quality and work progress. "Answer quality" refers to the teacher's random questions to the student based on the task set in advance before the report, and the student's answers to the question; "work progress" refers to the degree to which the student completes the task set in advance by the teacher before the report. Subjective characteristic quantities include: achievements, work summary, and project progress. "Achievements" refers to completing an experiment, completing the design of a part, how to overcome problems and challenges encountered in research, etc.; "Work summary" refers to specific tasks completed within a week; "Project progress" refers to the status and development of the project from the beginning to the present, including completed work, current work in progress, and unfinished tasks.

[0149] At the beginning of the weekly meeting, the teacher will randomly ask the student questions about the task. The teacher will score the student on a percentage basis based on the student's answer to the question, and then use 5 to 1 to evaluate the student's task completion, with 5 to 1 corresponding to very good, good, normal, average, and bad. After the student's report, the teacher and other students will score the student in terms of achievements, work summary, and project progress. The scoring is based on a percentage system. The student and teacher will record the scores in the weekly meeting assessment student table and the weekly meeting assessment teacher table respectively. The data in the student table is processed by cumulative average to obtain the student evaluation table. The student evaluation table and the teacher table are processed by TOPSIS method to obtain the final score of each student in the weekly meeting assessment.

[0150] The following is the 5th weekly report of the water environment testing research project of the School of Electrical Engineering of Changchun Institute of Technology.

[0151] At this time, the project is in the early stage of the research. The teacher focuses on cultivating students' theoretical knowledge. This time, the teacher sets the ratio of subjective characteristics to objective characteristics of this week to be 4:6, focusing on cultivating students' basic knowledge in this stage. Table 2 and Table 4 are the student assessment tables and teacher assessment tables for the 5th weekly meeting.

[0152] Table 3 is the student evaluation form for the 5th weekly meeting.

[0153] Table 2

[0154]

[0155] Table 3

[0156]

[0157] Table 4

[0158]

[0159] The assessment and evaluation system is composed of these objective and subjective characteristic quantities, and then the evaluation mechanism is constructed based on the assessment and evaluation system. The assessment and evaluation system is a way to assess the students' objective and subjective characteristic quantities. The assessment and evaluation mechanism refers to a mechanism by which the proportion of objective and subjective characteristic quantities in the assessment changes as the project progresses. The weights of the objective characteristic quantity assessment and the subjective characteristic quantity assessment are set by the teachers. As the project progresses, the weight of the subjective characteristic quantity assessment gradually occupies the vast majority of the assessment.

[0160] During the report, the objective characteristic scores of the students were statistically obtained to form a matrix and the matrix was standardized as follows:

[0161]

[0162] Among them, k ij Represents the score of the jth objective characteristic quantity of the ith student.

[0163] The second step is to determine the maximum value K max , and the minimum value K min .

[0164] K max =[k 1 max , k 2 max ,…k m max ]

[0165] =[max(k 11 , k 21 …k n1 )、max(k 12 , k 22 …k n2 ), …, max(k 1m , k 2m …k nm )]=[0.5445,0.5774]

[0166] K min =[k 1 min , k 2 min ,…k m min ]

[0167] =[min(k 11 , k 21 …k n1 )、min(k 12 , k 22 …k n2 ),…,min(k 1m , k2m …k nm )]=[0.4719,0.3464]

[0168] Among them, k j max k 1m ,k 2m …k nm Maximum value:

[0169] k j min k 1m ,k 2m …k nm Minimum value among (j=1,2,…,m)

[0170] Step 3: Find D i max ;D i min :

[0171] First find the maximum distance D of the i-th (i=1, 2, 3...n) student i max and the minimum value distance D i min .in, That is, D i max =[0,0.0964,0.0513,0.1653]; D i min =[0.1712,0.0816,0.1633,0.0257] Then, the score of the i-th (i=1, 2, 3…n) student is calculated and normalized to:

[0172]

[0173] Finally, the evaluation score of the objective feature quantity is obtained

[0174] S 客 =[0.4249,0.1948,0.3233,0.0571]

[0175] Among them, S n (n=1, 2, 3, ... n) represents the evaluation score of the objective characteristic quantity of the nth student.

[0176] Then organize students and teachers to evaluate the subjective characteristics using the subjective scoring method:

[0177] The evaluation tables of students' subjective characteristics and teachers' subjective characteristics are obtained respectively;

[0178] When reporting, statistics are drawn up to obtain the student subjective characteristic matrix and the teacher subjective characteristic matrix respectively; among them, the student subjective characteristic matrix is ​​obtained by accumulating the data in the table used by the students and taking the average value.

[0179] The student table matrix is ​​as follows:

[0180]

[0181] Among them, y 生ij It means that the subjective characteristic quantity of Student A's jth item is scored by the i-th student in the student table, and then the subjective characteristic quantity of the student is obtained by adding up the data in the student table and taking the average value.

[0182]

[0183] Then the student subjective characteristic quantity matrix is ​​obtained by calculating the student subjective characteristic quantity using the formula.

[0184] Student subjective characteristic matrix Among them, S 生主ij The subjective characteristic matrix of the teacher represents the score of the jth subjective characteristic of the i-th student in the student subjective evaluation table. Among them, H 教主ij It represents the score of the jth subjective characteristic quantity of the i-th student in the teacher's subjective evaluation table, and then the two matrices are added to get the average value, and finally the value of the subjective characteristic quantity of each student in this weekly meeting assessment is obtained, which is organized into a matrix as follows:

[0185] After obtaining the subjective characteristic matrix, the TOPSIS method is used to sort out the subjective characteristic scores of each student, which is the following S 主 Provide reference data.

[0186]

[0187] S Z =[0.2561,0.2561,0.2465,0.2412]

[0188] Finally, the mean method was used to obtain the final score of each student's subjective characteristic quantity in this weekly meeting assessment.

[0189]

[0190] Among them, Sz 1j (j=1, 2, 3) represents the standardized evaluation score of the j-th subjective characteristic quantity of student A.

[0191] Finally, the final evaluation score is obtained by combining the subjective and objective characteristics of this week. For example, if A's score is S 总 1=(S主1 *0.4+S 客1 *0.6) / 2=(0.4249*0.4+0.2561*0.6) / 2=0.1618. Then the scoring and the report content during the periodic report are recorded, analyzed and archived, in preparation for subsequent research, including the project progress, problems encountered in learning and new directions discovered.

[0192] When the project progresses to the middle and late stages, the archived problems and new directions are combined with the scores obtained from the early and mid-term weekly meetings to coordinate students to research new directions and later directions. The research method is still similar to the research method of the water environment detection scientific research project of the School of Electrical Engineering of Changchun Institute of Technology in the above example.

[0193] Specifically, during the 16th weekly report of the water environment detection research project of the School of Electrical Engineering of Changchun Institute of Technology, the inappropriateness of the originally initially formulated direction gradually emerged as the project progressed. At this time, the project is in the late stage of research, and the teacher has a sufficient understanding of the students. At this time, the teacher directly assigns students to study the remaining problems and directions and correct the original inappropriate directions. At this stage, the main focus is on the cultivation of students' personal abilities. The research at this stage is mainly based on joint discussions between students and teachers. Finally, when all problems are solved and all incorrect directions are corrected, students can be organized to end the project.

[0194] Example 2

[0195] A teacher evaluation system, which in this example specifically includes: a matrix evaluation unit, a grouping assistance unit, a feature quantity setting unit, a weekly meeting assessment unit, and a research assistance unit.

[0196] First, when the project starts, teachers receive the scores of each student's professional ability test paper through the matrix evaluation unit, and calculate the student's test paper scores based on the multi-weighted TOPSIS method to obtain a multi-dimensional judgment matrix;

[0197] Next, the teacher groups the students with the help of the grouping auxiliary unit. The system obtains the values ​​of each unit in the multi-dimensional judgment matrix and generates a line chart based on the unit values ​​to assist the teacher in analyzing the students' abilities in each dimension and dividing the students into different groups for learning.

[0198] After the grouping is completed, the teacher uses the characteristic quantity setting unit to set the subjective characteristic quantities and objective characteristic quantities, and sets the inclusion items of the subjective characteristic quantities and objective characteristic quantities in the assessment and evaluation system, so as to obtain the subjective characteristic quantities and objective characteristic quantities that meet the project; that is, the objective characteristic quantities are set to: answer quality, work progress; the subjective characteristic quantities are set to: achievements, work summary and project progress.

[0199] During the weekly assessment of the project research, students are assessed through the weekly assessment unit. The proportion of subjective and objective characteristics is adjusted according to the progress of the project. It is proposed that subjective characteristics are evaluated by subjective scoring method and objective characteristics are evaluated by weighted TOPSIS method, so as to provide data support for the research auxiliary unit.

[0200] Teachers can guide students during research through the research auxiliary unit. This unit processes the data after the weekly assessment and calculates based on the data in the weekly assessment unit to obtain the score of each student. Then, the ability map is generated through the student scores to assist teachers in providing precise guidance on student projects.

[0201] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A competitive learning evaluation method based on multi-weighted TOPSIS method, characterized in that: The following steps are involved: A. Establish a multi-dimensional judgment matrix based on the multi-weight TOPSIS method; B. Divide students into appropriate study groups based on the established multi-dimensional judgment matrix; C. Establish an assessment and evaluation system; D. Based on the assessment and evaluation system, an evaluation mechanism using the TOPSIS method is established; E. Based on the evaluation mechanism, teachers coordinate student project research.

2. A competitive learning evaluation method based on multi-weighted TOPSIS method according to claim 1, characterized in that: Step A specifically comprises the following steps: A1. Teachers divide the project research into several research directions according to the professional abilities required for the research, and then divide the research directions into early and late directions according to the difficulty or comprehensiveness required for the research directions; among them, the direction with high difficulty or strong comprehensiveness is defined as the late direction, and the other directions involving only a single subject knowledge are defined as the early direction; research direction = early direction + late direction, assuming that there are n research directions, a early direction, and b late directions, that is, n = a + b; then, analyze and count the number of professional abilities required for these n research directions, assuming that the required professional abilities are m items; A2. Divide the groups according to the preliminary directions. Set a corresponding group for each preliminary direction, for a total of a groups. Different weights will be set for the divided groups according to different research directions, and each group corresponds to a weight; A3. The teacher prepares m corresponding competency assessment test papers according to the m required professional competencies, and then uses the multi-weighted TOPSIS method to calculate the students' test scores, and then the calculation results are combined into a multi-dimensional judgment matrix.

3. A competitive learning evaluation method based on multi-weighted TOPSIS method according to claim 2, characterized in that: Step A3, the student score calculation process is as follows: A31. Construct a matrix of each student's test scores as follows: Among them, a ij represents the score of the jth test paper of the i-th student; The matrix is ​​standardized to eliminate the influence of different indicator dimensions. The standardized matrix uses the following formula: The normalized matrix is: A32. Determine the maximum value B max , and the minimum value B min ; B max =[b 1 max 、b 2 max 、…b m max ] =[max(b 11 、b 21 …b n1 )、max(b 12 、b 22 …b n2 )、…、max(b 1m 、b 2m …b nm )] B min =[b 1 min 、b 2 min 、…b m min ] =[min(b 11 、b 21 …b n1 )、min(b 12 、b 22 …b n2 )、…、min(b 1m 、b 2m …b nm )] Among them, b j max for b 1j ,b 2j …b nj The maximum value; b j min for b 1j ,b 2j …b nj Minimum value among (j=1,2,…,m); A33, get the weight ω a Next score: First find the distance D between the i-th (i=1, 2, 3...n) student and the maximum value at weight a ai max The distance D from the minimum value ai min ; in, Then the score of the i-th (i=1, 2, 3...n) student with weight a is calculated and normalized to obtain: The evaluation results are combined into a multi-dimensional judgment matrix as follows: Among them, S ij (i=1, 2, ..., e, j=1, 2, 3...n) represents the score of student j under weight i.

4. The competitive learning evaluation method based on the multi-weighted TOPSIS method according to claim 1, characterized in that: Step B, analyze students' abilities in multiple dimensions simultaneously based on the multi-dimensional judgment matrix, divide students into different groups for study, assign students with strong abilities in a single dimension to specialize in a certain direction; assign students with broad ability dimensions to be responsible for the connection between various directions, so that each student can be assigned tasks that suit him or her according to his or her own knowledge system.

5. The competitive learning evaluation method based on the multi-weighted TOPSIS method according to claim 1, characterized in that: Step C: Students report and are assessed periodically. The assessment system is divided into objective characteristic quantity assessment and subjective characteristic quantity assessment. Objective characteristic quantity refers to the characteristic quantity that can be reasonably evaluated by objective scoring, including answer quality and work progress. Subjective characteristic quantity refers to the characteristic quantity that can be reasonably evaluated by subjective scoring, including achievements, work summary and project progress.

6. A competitive learning evaluation method based on multi-weighted TOPSIS method according to claim 1, characterized in that: Step D, the evaluation mechanism is a mechanism for gradually adjusting the proportion of objective feature quantity assessment and subjective feature quantity assessment in the evaluation system according to the progress of the project. The objective feature quantity assessment adopts the weighted TOPSIS method to evaluate the objective feature quantity, and the subjective feature quantity assessment adopts the subjective scoring method to evaluate the subjective feature quantity. The weights of the objective feature quantity assessment and the subjective feature quantity assessment are both determined by the teacher. As the project progresses, the weight of the subjective feature quantity assessment gradually occupies the vast majority of the assessment.

7. A competitive learning evaluation method based on multi-weighted TOPSIS method according to claim 1, characterized in that: Step E is specifically: E1. Students report in groups, and teachers ask questions and give scores around the tasks to evaluate the students’ task completion; E2. After the student has finished his report, the teacher and other students will rate the student based on the achievements, work summary, and project progress; E3. Bring the objective and subjective characteristic quantities into the assessment weight calculation to obtain the assessment score, and coordinate students' research on new and later directions based on the assessment score.

8. A teacher evaluation system, characterized by: The competitive learning evaluation method based on the multi-weighted TOPSIS method as described in claim 1 is adopted, and the evaluation system includes: a matrix evaluation unit, a grouping auxiliary unit, a feature quantity setting unit, a weekly meeting assessment unit, and a research auxiliary unit; The matrix evaluation unit is used to receive the scores of each student's professional ability test paper, calculate the student's test paper scores based on the multi-weighted TOPSIS method, that is, push m ability evaluation test papers to the student end, and obtain a multi-dimensional judgment matrix based on the student's test paper answer situation on the student end; The grouping auxiliary unit is used to obtain the value of each element in the multi-dimensional judgment matrix, that is, the ability value of the students under different weights, generate a line chart based on the element value, and assist teachers in analyzing the ability of students in each dimension and thereby dividing the students into different groups for learning; The feature quantity setting unit is used to respond to the setting operation of the user teacher on the teacher side for the subjective feature quantity and the objective feature quantity, and set the inclusion items of the subjective feature quantity and the objective feature quantity in the assessment and evaluation system, so that the evaluation mechanism is established; The weekly meeting assessment unit is used to obtain the subjective characteristic quantity and objective characteristic quantity scores of each student on the student side and the teacher side, and output the obtained scores to the research auxiliary unit after processing, so as to provide data support for the research auxiliary unit; the subjective characteristic quantity is evaluated by the subjective scoring method, and the objective characteristic quantity is evaluated by the weighted TOPSIS method, and the weekly meeting assessment unit will adjust the proportion of the subjective characteristic quantity and the objective characteristic quantity in the evaluation mechanism according to the research progress of the project; The research auxiliary unit is used to reprocess the data obtained in the weekly assessment, and calculate based on the algorithm in the weekly assessment unit to obtain the total score of each student, and then generate a capability map and various parameters of the project research through the student scores; assist teachers in providing precise guidance to student projects; and display various parameters of the research.

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