Method for quantitatively evaluating completion degree of practical training of students
By integrating multi-dimensional data such as student attendance, discussion, task completion, and fluency in defense, and using the entropy weight method and analytic hierarchy process to evaluate students' completion of practical training, the problem of inaccurate evaluation in existing technologies is solved, and a more scientific and flexible evaluation method is achieved.
Patent Information
- Application Number
- CN202411653166.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-19
- Publication Date
- 2025-03-07
AI Technical Summary
Existing methods for assessing student practical training completion suffer from high subjectivity, low accuracy, strong data dependence, high computational complexity, and unstable assessment results, failing to fully reflect students' true abilities and learning progress.
By acquiring data from multiple dimensions such as student attendance, discussion level, task completion, and fluency in defense, the entropy weight method and analytic hierarchy process are used to calculate students' practical training activity, breadth of mastery, and mastery gain, and to comprehensively evaluate students' practical training completion.
It achieves multi-dimensional, objective, and scientific assessment, dynamically reflects students' learning performance, reduces subjectivity, and improves the accuracy and adaptability of the assessment.
Smart Images
Figure CN119578929A_ABST
Abstract
Description
Technical Field
[0001] This patent relates to the field of educational technology, and specifically to a method for quantitatively evaluating the degree of completion of students' practical training. Background Art
[0002] Existing statistical learning methods are highly subjective. They usually measure students' performance during the training week by building models. The evaluation is based on the following dimensions: students' final submission time, attendance, number of tasks completed, complexity of each task, fluency of defense, and students' innovations. The data of each dimension will be collected and converted into eigenvalues to form a multidimensional vector. The module value of the vector is used to measure the comprehensive performance of students during the entire training process. For example, students who submit tasks earlier will get higher scores in the time dimension; higher attendance indicates that students are more involved; more tasks completed indicate that students have stronger task handling ability; more cumbersome methods reflect students' ability to solve complex problems; fluency of defense shows students' expression and knowledge mastery; and innovations represent students' creative thinking. Vectors are constructed comprehensively through these dimensions, and finally the module value is calculated to evaluate students' performance during the training week. However, this method has certain limitations, which will lead to deviations in students' overall performance, and the accuracy cannot be guaranteed, and it cannot fully reflect students' true abilities.
[0003] The cognitive diagnosis model method has unstable results. Usually, the performance of each dimension is regarded as the performance of multiple "knowledge points". Through the specific algorithm in the cognitive diagnosis model, the performance of students in each dimension is measured: students who complete the task earlier are considered to have a better grasp of the knowledge point of "time management ability"; students with higher attendance indicate that they have mastered the dimension of "learning attitude and participation"; the number of tasks solved and the complexity of the tasks are used to evaluate the knowledge point of "problem-solving ability"; and the fluency and innovation of the defense can reflect the students' mastery of "expression ability" and "creative thinking". Although this method avoids the limitation of traditional cognitive diagnosis methods that over-rely on a single task or knowledge point, and comprehensively evaluates students' performance through multiple dimensions, it also has certain defects. First, this method focuses on some quantifiable data of students in practical training, such as submission time, attendance, number of tasks, etc., but ignores the students' listening to lectures or other soft skills during the practical training process; second, when the number of tasks for students is small, the model is not accurate enough in evaluating the overall mastery of students, because the lack of data will directly lead to instability and volatility of the results. In addition, since the model data feature dimensions are relatively single, if there are no more abundant sources of learning data (such as interactions, discussions, etc.), the final evaluation results will still be biased in comprehensiveness.
[0004] The deep learning modeling method requires a lot of time to pre-collect training data. Stacked autoencoders (SAE) and bidirectional long short-term memory networks (BiLSTM) are usually used for feature extraction and fusion to predict the comprehensive performance of students in the practical training week. Specifically, SAE is used to reduce the dimension and extract features of students' practical training data: extract time management ability from the final submission time and attendance, extract task solving ability from the number and complexity of tasks, etc.; BiLSTM is used to capture the time series information of students in the practical training process: the changes in students' performance in different periods of time to predict their subsequent task completion or defense performance. This model can predict whether students can complete tasks on time and make dynamic predictions about their performance in future practical training tasks. However, this method also has certain disadvantages. First, deep learning models have a high demand for a large amount of high-quality training data. During the practical training week, due to the lack of student data, it will be difficult to achieve the ideal effect of model training. Secondly, the computational complexity is high, especially for the processing of large-scale data sets, which requires powerful computing resources. In addition, this model cannot directly give the quantitative mastery of students in various dimensions, but can only predict the possibility of students' subsequent performance, lacking precise interpretability. In addition, if discrete classification values (such as excellent, good, qualified, and unqualified) are used to evaluate student performance, they usually need to be set manually in advance and rely on supervised learning for training, which is prone to subjectivity and increases the cost of annotation. In general, its high computational complexity and dependence on data limit its wide range of practical applications.
[0005] In summary, the completion of student training is a continuous variable that changes with factors such as the number of tasks completed by students, the difficulty of tasks, the quality of completion, submission time, the duration of task intervals, and the complexity of the tasks themselves. It is not a simple discrete variable and cannot be simply divided into two states: completed and uncompleted. At the same time, it is necessary to avoid large fluctuations in completion when there is less data on student task completion, or almost no change in completion when the cumulative amount of task completion is too much. How to scientifically and accurately quantify the completion of students in training is of great significance to the personalized training and breakthrough of weak links in online education. Summary of the invention
[0006] The purpose of the present invention is to provide a method for quantitatively evaluating the completion of students' practical training. Through various parameters, the completion of students' practical training is calculated and ranked, so as to achieve quantitative evaluation of the completion of students' practical training.
[0007] In order to solve the above technical problems, the technical solution of the present invention is: a method for quantitatively evaluating the completion of students' practical training, characterized in that it includes the following steps:
[0008] S1: Obtain students’ actual attendance, students’ discussion, the number of key points of tasks completed by students, task complexity rating, fluency of students’ defense, number of students’ innovative points, and the final submission time of students’ tasks during the training week;
[0009] S2: Get the student training activity based on the student's actual attendance and student discussion;
[0010] S3: The breadth of students’ mastery is obtained based on the number of key points of the tasks completed by the students, the task complexity rating, and the fluency of the students’ defense;
[0011] S4: Obtain the students’ mastery gain based on the number of students’ innovation points, task complexity rating, and the students’ final task submission time during the training week;
[0012] S5: Obtain the degree of completion of student practical training according to the degree of student practical training activity, the breadth of student mastery and the gain of student mastery, and arrange the degree of completion of student practical training in descending order to complete the rating of the degree of completion of student practical training, which is used to quantitatively evaluate the degree of completion of student practical training.
[0013] Preferably, in step S1, the student discussion degree is calculated by the following formula:
[0014]
[0015] Among them, talk i represents the discussion degree of the i-th student, talk ij It represents the discussion degree of the i-th student on the j-th day, and c represents the attendance required during the practical training week.
[0016] Preferably, step S2 comprises the following steps:
[0017] S201: Obtain the student attendance rate based on the student's actual attendance and the attendance required during the training week;
[0018] S202: Determine the weight of student attendance rate and the weight of student discussion degree using entropy weight method;
[0019] S203: Obtain the student training activity according to the student attendance rate, the student discussion degree, the weight of the student attendance rate and the weight of the student discussion degree.
[0020] Preferably, in step S201, the student attendance rate is calculated as follows:
[0021]
[0022] Among them, at_rate i represents the attendance rate of the i-th student, A i represents the actual attendance of the i-th student, A i∈{0,1,2,3}, c represents the attendance required during the training week;
[0023] In step S202, the weight of the student's attendance rate is calculated as follows:
[0024]
[0025] The weight of the student discussion degree is calculated as follows:
[0026]
[0027] Among them, W1 represents the weight of student attendance rate, W2 represents the weight of student discussion degree, K = ln(M), M represents the total number of students in the class, A ij represents the attendance of the i-th student on the j-th day, s ij2 represents the discussion of the i-th student on the j-th day; in step S203, the student training activity is calculated as follows:
[0028] active i =W1×at_rate i +W2×talk i
[0029] Among them, active i represents the training activity of the i-th student, W1 represents the weight of student attendance, W2 represents the weight of student discussion, at_rate i represents the attendance rate of the i-th student, talk i Represents the discussion degree of the i-th student.
[0030] Preferably, step S3 comprises the following steps:
[0031] S301: Obtaining the student's task completion degree according to the number of task key points completed by the student and the total number of task key points;
[0032] S302: Obtaining the student's relaxation strain index based on the task complexity rating and the fluency of the student's defense;
[0033] S303: Calculate the student's mastery breadth according to the student's task completion and the relaxation strain index.
[0034] Preferably, in step S301, the student's task completion degree is calculated using the following formula:
[0035]
[0036] Among them, work_c i Indicates the task completion of the i-th student, work irepresents the number of key points of the task completed by the i-th student, and H represents the total number of key points of the task;
[0037] In step S302, the relaxation strain index is calculated using the following formula:
[0038]
[0039] Among them, δ i represents the relaxation strain index of the ith student, F i represents the fluency of the defense of the i-th student, F i ∈{1,2,3,4,5},C h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}, H represents the total number of key points of the task; in step S303, the student's mastery breadth is calculated as follows:
[0040] R i =Z×work_c i +δ i
[0041] Among them, R i Indicates the breadth of the i-th student’s mastery, work_c i represents the task completion degree of the i-th student, δ i represents the relaxation strain index of the ith student, and Z is a constant.
[0042] Preferably, in step S4, the student mastery gain is calculated as follows:
[0043]
[0044] Among them, I i represents the mastery gain of the i-th student, X i represents the number of innovation points of the i-th student, H represents the total number of key points of the task, T i represents the final submission time of the task of the i-th student in the training week, C h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}.
[0045] Preferably, step S5 comprises the following steps:
[0046] S501: according to the students' practical training activity, students' mastery breadth and students' mastery gain, the weight of the students' practical training activity, the weight of the students' mastery breadth and the weight of the students' mastery gain are determined by using the hierarchical analysis method;
[0047] S502: Based on the weight of the student's practical training activity, the weight of the student's mastery breadth and the weight of the student's mastery gain, the student's practical training completion is obtained and arranged in descending order, thereby completing the rating of the student's practical training completion.
[0048] Preferably, in step S501, the student training activity, the student mastering breadth and the student mastering gain are used as three indicators, and are compared in pairs to obtain a pairwise comparison matrix, which is expressed as follows:
[0049]
[0050] Normalize the pairwise comparison matrix, find the average value of each row of the normalized matrix, and get the weights of the three indicators. The calculation formula is as follows:
[0051]
[0052] Among them, W a The weight of the student's practical training activity, W R represents the weight of the student’s mastery of the breadth, W I represents the weight of students’ mastery gain, a mn Indicates the importance comparison value between the mth indicator and the nth indicator;
[0053] In step S502, the student training completion degree is calculated as follows:
[0054] finish i =W a ×active i +W R ×R i +W I ×I i
[0055] Among them, finish i represents the training completion degree of the i-th student, W a The weight of the student's practical training activity, W R represents the weight of the student’s mastery of the breadth, W I Indicates the weight of students' mastery gain, active i represents the training activity of the i-th student, R i Indicates the breadth of knowledge mastered by the i-th student, I i represents the mastery gain of the i-th student.
[0056] Compared with the prior art, the beneficial effects of the present invention are: (1) Multi-dimensional evaluation: The present invention integrates multiple dimensions such as students' attendance, discussion degree, task completion, task complexity, and fluency of defense, which can more comprehensively reflect students' actual performance and ability than single-dimensional evaluation; (2) Objectivity and scientificity: The present invention objectively allocates weights through entropy weight method and hierarchical analysis method, reduces the subjectivity of evaluation, and improves the scientificity and accuracy of evaluation; (3) Dynamic evaluation capability: The present invention can dynamically calculate the degree of practical training completion based on students' practical training activity, mastery breadth, and mastery gain, making the evaluation results more flexible and adaptable. BRIEF DESCRIPTION OF THE DRAWINGS
[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the description of the embodiments of the present invention are briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0058] Figure 1 is a schematic diagram of the process of the present invention,
[0059] Figure 2 A schematic diagram of the tasks and key points in the student virtual simulation training week of the experimental example of the present invention. DETAILED DESCRIPTION
[0060] The present invention is further described in detail below in conjunction with the accompanying drawings. The technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0061] The present invention uses 80 students to simulate the Figure 2 Take the practical training week shown as an example.
[0062] like Figure 1 As shown, the present invention discloses a method for quantitatively evaluating the completion of students' practical training, comprising the following steps:
[0063] S1: Obtain students’ actual attendance, students’ discussion degree, the number of key points of tasks completed by students, task complexity rating, fluency of students’ defense, number of students’ innovative points and the final submission time of students’ tasks during the practical training week.
[0064] The task complexity rating is based on the difficulty of the key points of the practical training tasks issued by the teacher, and the students' data are collected by the teacher during class.
[0065] The student discussion degree is calculated as follows:
[0066]
[0067] Among them, talk i represents the discussion degree of the i-th student, that is, the number of questions discussed by the i-th student, talk ij It represents the discussion degree of the i-th student on the j-th day, and c represents the attendance required during the practical training week.
[0068] The calculation results of the discussion degree of 80 students are shown in Table 1:
[0069] Table 1. Student discussion
[0070]
[0071]
[0072] S2: Obtain the student training activity based on the student's actual attendance and student discussion, which specifically includes the following steps:
[0073] S201: Obtain the student attendance rate based on the student's actual attendance and the attendance required during the training week.
[0074] The student attendance rate is calculated as follows:
[0075]
[0076] Among them, at_rate i represents the attendance rate of the i-th student, A i represents the actual attendance of the i-th student, A i ∈{0,1,2,3}, that is, the actual attendance of students is divided into four types, 0 represents absence, 1 represents leave, 2 represents lateness, 3 represents normal attendance, and c represents the attendance required during the practical training week.
[0077] The calculation results of the attendance rate of 80 students are shown in Table 2:
[0078] Table 2 Student attendance rate
[0079]
[0080]
[0081] S202: Determine the weight of student attendance rate and the weight of student discussion degree by using the entropy weight method, specifically: use the entropy weight method to calculate the data discreteness of student attendance rate and student discussion degree to obtain the entropy value of each indicator; then calculate the information utility value of each indicator by the entropy value, and finally calculate the weight of student attendance rate and student discussion degree by the information utility values of the two indicators.
[0082] The weight of the student's attendance rate is calculated as follows:
[0083]
[0084] The weight of the student discussion degree is calculated as follows:
[0085]
[0086] Among them, W1 represents the weight of student attendance rate, W2 represents the weight of student discussion degree, K = ln(M), M represents the total number of students in the class, A ij represents the attendance of the i-th student on the j-th day, s ij2 represents the discussion of the i-th student on the j-th day;
[0087] Substituting M=80 into the above two calculation formulas, we get the weight of student attendance rate W1=0.2725 and the weight of student discussion degree W2=0.7275
[0088] S203: Obtain the student training activity according to the student attendance rate, the student discussion degree, the weight of the student attendance rate and the weight of the student discussion degree.
[0089] The calculation formula for the student training activity is as follows:
[0090] active i =W1×at_rate i +W2×talk i
[0091] Among them, active i represents the training activity of the i-th student, W1 represents the weight of the student's attendance rate, W2 represents the weight of the student's discussion rate, at_rate i represents the attendance rate of the i-th student, talk i Represents the discussion degree of the i-th student.
[0092] The calculation results of the practical training activity of 80 students are shown in Table 3:
[0093] Table 3 Practical training activity
[0094]
[0095]
[0096] S3: The breadth of students' mastery is obtained based on the number of key points of the tasks completed by the students, the task complexity rating, and the fluency of the students' defense. The breadth of students' mastery is relative to the depth of mastery, and refers to the breadth of knowledge products that students are exposed to, understand, and are familiar with. The specific steps include the following:
[0097] S301: Obtain the student's task completion degree according to the number of task key points completed by the student and the total number of task key points.
[0098] The student's task completion degree is calculated as follows:
[0099]
[0100] Among them, work_c i Indicates the task completion of the i-th student, work i represents the number of key points of the task completed by the i-th student, and H represents the total number of key points of the task.
[0101] The calculation results of the task completion of 80 students are shown in Table 4:
[0102] Table 4 Task completion
[0103]
[0104]
[0105] S302: Obtain the student's relaxation strain index based on the task complexity rating and the fluency of the student's defense.
[0106] The Student's relaxation strain index is calculated as follows:
[0107]
[0108] Among them, δ i represents the relaxation strain index of the ith student, F i represents the fluency of the defense of the i-th student, F i ∈{1,2,3,4,5}, that is, the fluency of students' defense is divided into 5 levels, and the fluency increases gradually from 1 to 5. h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}, that is, the complexity rating is divided into 3 levels, and the complexity increases gradually from 1 to 3. H represents the total number of key points of the task.
[0109] The calculation results of the relaxation strain index of 80 students are shown in Table 5:
[0110] Table 5 Relaxation strain index
[0111]
[0112]
[0113] S303: Calculate the student's mastery breadth according to the student's task completion and the relaxation strain index.
[0114] The student's mastery of breadth is calculated as follows:
[0115] R i =Z×work_c i +δ i
[0116] Among them, R i Indicates the breadth of the i-th student’s mastery, work_c i represents the task completion degree of the i-th student, δ i represents the relaxation strain index of the ith student, and Z is a constant.
[0117] The calculation results of the 80 students' mastery of breadth are shown in Table 6:
[0118] Table 6. Mastery breadth
[0119]
[0120]
[0121] S4: The student mastery gain is obtained based on the number of student innovation points, task complexity rating and the final submission time of the student's task within the training week. The student mastery gain refers to the positive changes and improvements in the student's mastery of knowledge within a certain period of time.
[0122] The student mastery gain is calculated as follows:
[0123]
[0124] Among them, I i represents the mastery gain of the i-th student, X i represents the number of innovation points of the i-th student, H represents the total number of key points of the task, T i represents the final submission time of the task of the i-th student in the training week, C h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}.
[0125] The calculation results of the mastery gains of 80 students are shown in Table 7:
[0126] Table 7 Mastery Gain
[0127]
[0128]
[0129] S5: Obtain the degree of completion of student training according to the degree of student training activity, the breadth of student mastery and the gain of student mastery, and arrange the degree of completion of student training in descending order to complete the rating of the degree of completion of student training, which is used to quantitatively evaluate the degree of completion of student training, and specifically includes the following steps:
[0130] S501: According to the students' practical training activity, students' mastery breadth and students' mastery gain, the hierarchical analysis method is used to determine the weight of students' practical training activity, the weight of students' mastery breadth and the weight of students' mastery gain. Specifically, the students' practical training activity, students' mastery breadth and students' mastery gain are used as three indicators, and they are compared in pairs to obtain a pairwise comparison matrix, which is expressed as follows:
[0131]
[0132] Normalize the pairwise comparison matrix, find the average value of each row of the normalized matrix, and get the weights of the three indicators. The calculation formula is as follows:
[0133]
[0134] Among them, W a The weight of the student's practical training activity, W R represents the weight of the student’s mastery of the breadth, W I represents the weight of students’ mastery gain, a mn Indicates the importance comparison value between the mth indicator and the nth indicator;
[0135] From this calculation, we can get: the weight of student training activity W a =0.0882, the weight of students’ mastery of breadth W R =
[0136] 0.6687, the weight of student mastery gain W I =0.2431.
[0137] S502: Based on the weight of the student's practical training activity, the weight of the student's mastery breadth and the weight of the student's mastery gain, the student's practical training completion is obtained and arranged in descending order, thereby completing the rating of the student's practical training completion.
[0138] The calculation formula for the student training completion degree is as follows:
[0139] finish i =W a ×active i+W R ×R i +W I ×I i
[0140] Among them, finish i represents the training completion degree of the i-th student, W a The weight of the student's practical training activity, W R represents the weight of the student’s mastery of the breadth, W I Indicates the weight of students' mastery gain, active i represents the training activity of the i-th student, R i Indicates the breadth of knowledge mastered by the i-th student, I i represents the mastery gain of the i-th student.
[0141] The calculation results of the training completion of 80 students are shown in Table 8:
[0142] Table 8 Completion of practical training
[0143]
[0144]
[0145] The practical training completion rating is divided into five levels: A, B, C, D, and E, as shown in Table 9. M is the total number of students in the class. According to the practical training completion of the class, the students' practical training completion is arranged in descending order.
[0146] Table 9 Rating of practical training completion
[0147]
[0148] The rating results of the 80 students' practical training completion are shown in Table 10:
[0149] Table 10 Rating of practical training completion
[0150] Student ID Rating of training completion 1 B 2 E … … 80 D
[0151] The present invention obtains the student training activity through student attendance and student discussion, obtains the student mastery breadth through the number of key points of the task completed by the student, the task complexity rating and the fluency of the student defense, obtains the student mastery gain through the number of student innovation points, the task complexity rating and the final submission time of the student task in the training week, and obtains the overall completion of the student training week through the student training activity, the student mastery breadth and the student mastery gain, and obtains the training completion rating in descending order, which can be combined with the learning ability of different students to personalize the evaluation of their task completion. In addition, the complexity and innovation of the task are introduced as the threshold for evaluating whether it is completed, enriching the "multi-dimensional evaluation" and being able to more comprehensively reflect the actual performance and ability of the students. The present invention combines the cognitive status of the students and the different characteristics of the tasks, and can accurately quantify and dynamically evaluate the overall performance of the students in completing the tasks in the training week.
[0152] The parts not involved in the present invention are the same as the prior art or are implemented by using the prior art.
[0153] The above contents are further detailed descriptions of the present invention in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field of the present invention, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.
Claims
1. A method for quantitatively evaluating the completion of students' practical training, characterized by: The steps include: S1: Obtain students’ actual attendance, students’ discussion, the number of key points of tasks completed by students, task complexity rating, fluency of students’ defense, number of students’ innovative points, and the final submission time of students’ tasks during the training week; S2: Get the student training activity based on the student's actual attendance and student discussion; S3: The breadth of students’ mastery is obtained based on the number of key points of the tasks completed by the students, the task complexity rating, and the fluency of the students’ defense; S4: Obtain the students’ mastery gain based on the number of students’ innovation points, task complexity rating, and the students’ final task submission time during the training week; S5: Obtain the degree of completion of student practical training according to the degree of student practical training activity, the breadth of student mastery and the gain of student mastery, and arrange the degree of completion of student practical training in descending order to complete the rating of the degree of completion of student practical training, which is used to quantitatively evaluate the degree of completion of student practical training.
2. A method for quantitatively evaluating the completion of student training according to claim 1, characterized in that: In step S1, the student discussion degree is calculated as follows: Among them, talk i represents the discussion degree of the i-th student, talk ij It represents the discussion degree of the i-th student on the j-th day, and c represents the attendance required during the practical training week.
3. A method for quantitatively evaluating the completion of student training according to claim 1, characterized in that: Step S2 includes the following steps: S201: Obtain the student attendance rate based on the student's actual attendance and the attendance required during the training week; S202: Determine the weight of student attendance rate and the weight of student discussion degree using entropy weight method; S203: Obtain the student training activity according to the student attendance rate, the student discussion degree, the weight of the student attendance rate and the weight of the student discussion degree.
4. A method for quantitatively evaluating the completion of student training according to claim 3, characterized in that: In step S201, the student attendance rate is calculated using the following formula: Among them, at_rate i represents the attendance rate of the i-th student, A i represents the actual attendance of the i-th student, A i ∈{0,1,2,3}, c represents the attendance required during the training week; In step S202, the weight of the student's attendance rate is calculated as follows: The weight of the student discussion degree is calculated as follows: Among them, W1 represents the weight of student attendance rate, W2 represents the weight of student discussion degree, K = ln(M), M represents the total number of students in the class, A ij represents the attendance of the i-th student on the j-th day, s ij2 represents the discussion of the i-th student on the j-th day; In step S203, the student training activity is calculated using the following formula: active i =W1×at_rate i +W2×talk i Among them, active i represents the training activity of the i-th student, W1 represents the weight of student attendance, W2 represents the weight of student discussion, at_rate i represents the attendance rate of the i-th student, talk i Represents the discussion degree of the i-th student.
5. A method for quantitatively evaluating the completion of student training according to claim 1, characterized in that: Step S3 includes the following steps: S301: Obtaining the student's task completion degree according to the number of task key points completed by the student and the total number of task key points; S302: Obtaining the student's relaxation strain index based on the task complexity rating and the fluency of the student's defense; S303: Calculate the student's mastery breadth according to the student's task completion and the relaxation strain index.
6. A method for quantitatively evaluating the completion of student training according to claim 5, characterized in that: In step S301, the student's task completion degree is calculated as follows: Among them, work_c i Indicates the task completion degree of the i-th student, work i represents the number of key points of the task completed by the i-th student, and H represents the total number of key points of the task; In step S302, the relaxation strain index is calculated by the following formula: Among them, δ i represents the relaxation strain index of the ith student, F i represents the fluency of the defense of the i-th student, F i ∈{1,2,3,4,5},C h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}, H represents the total number of key points of the task; In step S303, the student's mastery of the breadth is calculated as follows: R i =Z×work_c i +d i Among them, R i Indicates the breadth of knowledge mastered by the i-th student, work_c i represents the task completion degree of the i-th student, δ i represents the relaxation strain index of the ith student, and Z is a constant.
7. A method for quantitatively evaluating the completion of student training according to claim 1, characterized in that: In step S4, the student mastery gain is calculated as follows: Among them, I i represents the mastery gain of the i-th student, X i represents the number of innovation points of the i-th student, H represents the total number of key points of the task, T i represents the final submission time of the task of the i-th student in the training week, C h represents the complexity rating of the h-th task key point, C h ∈{1,2,3}.
8. A method for quantitatively evaluating the completion of student training according to claim 1, characterized in that: Step S5 includes the following steps: S501: according to the students' practical training activity, students' mastery breadth and students' mastery gain, the weight of the students' practical training activity, the weight of the students' mastery breadth and the weight of the students' mastery gain are determined by using the hierarchical analysis method; S502: Based on the weight of the student's practical training activity, the weight of the student's mastery breadth and the weight of the student's mastery gain, the student's practical training completion is obtained and arranged in descending order, thereby completing the rating of the student's practical training completion.
9. A method for quantitatively evaluating the completion of student training according to claim 8, characterized in that: In step S501, the student training activity, student mastering breadth and student mastering gain are used as three indicators and compared in pairs to obtain a pairwise comparison matrix, which is expressed as follows: Normalize the pairwise comparison matrix, find the average value of each row of the normalized matrix, and get the weights of the three indicators. The calculation formula is as follows: Among them, W a The weight of student training activity, W R represents the weight of the student’s mastery of the breadth, W I represents the weight of students’ mastery gain, a mn Indicates the importance comparison value between the mth indicator and the nth indicator; In step S502, the student training completion degree is calculated as follows: finish i =W a ×active i +W R ×R i +W I ×I i Among them, finish i represents the training completion degree of the i-th student, W a The weight of student training activity, W R represents the weight of the student’s mastery of the breadth, W I Indicates the weight of students’ mastery gain, active i represents the training activity of the i-th student, R i Indicates the breadth of knowledge mastered by the i-th student, I i represents the mastery gain of the i-th student.