# Construction and Application of Physical Education Teacher Literacy Evaluation System Based on Grey Relational Model

Authors: Xianglong Kong; Daowei Guo
Journal: Journal of Sensors
 (2022)

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## Abstract

With the development of our country, more and more attention is paid to the education of students. However, the issue of teachers’ literacy is the one that has the greatest impact on students in the campus. This paper makes an in-depth study and discussion on the quality evaluation system and application of physical education teachers. Better improving the literacy of physical education teachers also has a more positive impact on student education. The following conclusions are drawn from the research and analysis: (1) The basis of selecting evaluation indicators and the corresponding evaluation process for the evaluation of physical education teachers'literacy are multifaceted, and the evaluation criteria should be fully considered. (2) For the construction of the grey relational model, its algorithms are divided into many categories, and different algorithms are applied to different situations of relational degree. The grey relational model based on point relationship and generalized range is introduced, which provides convenience for subsequent computational research. (3) The difference between the basic information distribution and teaching quality of physical education teachers was obtained through the investigation experiment. The form of questionnaire survey determined the specific indicators of evaluation and the distinction between the first and second grades. Through multiple sets of experiments, the main evaluation indicators and the grey correlation degree of teacher literacy are tested, and the correlation degree between evaluation indicators and teacher literacy is obtained.


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## Body

## 1. Introduction

Public-private integrated circuit production forecasts have important economic value in the world economy. Policy adjustments and portfolio reviews and IC industry development information have important implications for governments, policymakers, and stakeholders. In recent years, many researchers have proposed a series of forecasting techniques suitable for high-tech industries. Most of these methods are based on statistical studies related to the use of univariate time series data. However, these models do not give clear insight into the predicted outcome. Combining grey multivariate model with grey relational analysis, a new forecasting method is proposed. The results show that the planning portfolio method has obvious improvement over traditional methods in terms of forecasting techniques and survey variables. The significance of its management and future research directions was discussed [1]. Aiming at the problem that the uncertainty information cannot be described in the traditional grey relational model, a new grey relational model based on grey sequence is established. Design method: On the basis of the definition of the traditional grey relational model, taking into account the limitations of information and knowledge, the grey number algorithm is combined with the grey relational model. General formulas for grey process and grey distance are defined. According to the definition of grey distance, grey relational model and grey geometric relational model based on grey sequence are proposed. Finally, the parallelism, multiplicity, and system conservation of the model are discussed [2]. Although the problem of diagnosis has been extensively discussed in many studies and applied comprehensively in various fields, the literature indicates that there are certain limitations in practical application. In order to expand the application frontier, a practical expert diagnosis model is proposed, which mainly adopts the grey relational analysis technique, that is, the data analysis method based on the generalized distance function to distinguish normal objects and abnormal objects. The concept of how to map regular objects around reference points in a multidimensional space is presented and explained. Therefore, anomalous objects can be determined by judging that the distance between a given anomalous object and a reference point exceeds a threshold [3]. In order to improve the grey analysis method, and the evaluation accuracy is not high, a new evaluation model is established by integrating physical theory. According to the change of index value, the model reflects the utility of data and information content, implements the evaluation model of regional rain resource development potential, and avoids the influence of subjective factors. The evaluation results show that it is scientific to introduce physical theory into grey correlation analysis. The rationality of the model is put forward to improve the evaluation accuracy of grey scale analysis method [4]. Each item has points, and the total score determines the winner. However, the grading table and the class spacing of its assigned units seem unreasonable. To overcome this shortcoming, a complete and accurate evaluation model is built using the grey relational degree derived from grey theory to determine who is the best all-around athlete in all championships. This approach not only reduces scoring disputes, but also helps teams select the best athletes. Using the grey relational analysis method, numerical analysis was carried out on the ranking of typical decathlon competitions. This approach could provide an improved scoring method for World Games or other sports federations to determine who is the best all-around athlete among all athletes [5]. Aiming at the problem that BP artificial neural network cannot automatically select and optimize the input variables, the BP artificial neural network algorithm (GM-BPANN) is optimized by combining BPANN with grey relational analysis. By comparing the data of grain production in China and the stepwise regression method with the transgenic (1, N) grey method, it can be found that the new model can deal with a large number of input variables, improve the adaptability of BP neural network, and has a better effect without special subjective selection. Good stability and accuracy [6]. Set pair analysis (SPA) is a new systems theory method for analyzing factual ambiguity and uncertainty. Applying similarity and difference expressions can resolve many ambiguities and uncertainties. Aiming at the problem that the existing lake eutrophication evaluation methods are too complicated, a lake eutrophication evaluation method based on grey relational degree is proposed. The evaluation results are consistent with other evaluation methods [7]. As a kind of exhibition industry, convention and exhibition are highly valued by countries all over the world. In INA, the development of this industry is very good. We use the corresponding grey model to determine the uniform effect, and use the grey relational analysis method to analyze the economic development. It objectively reflects the level of economic development [8]. Lantern gearbox is an important part of transmission system. Combining the physical model formed by simulation symbols, the three-step statistical algorithm of evaluating feature selection and grey correlation analysis, an ambitious method for gear blade damage is designed. Firstly, the fault data is tested and analyzed through the training data, and then the validation set is verified. The design results of experimental data are consistent with the actual test records, which prove the value and accuracy of this method. According to the health law and national forecasting methods, characteristics, and trading methods, it provides a new selection method and trade-off method [9]. Improving students’ learning motivation is one of the basic problems faced by physical education teachers. From a goal achievement perspective, guidelines need to be established for more effective use of information in the classroom. This study examines the relationship between the motivational climate created by PE teachers and the intrinsic motivation of precompetition classes, precompetition self-confidence and anxiety, and precompetition and post-competition emotional states. Physical education teachers manipulate the atmosphere of motivation and adjust the strategies of goals. Mastery atmosphere is associated with fun, perception, and effort in physical education class, precompetition physical anxiety, and post-competition vitality [10]. It gets the reasons why people choose sports and studies the reasons for these choices. Self-confidence and excellent athletic ability are the internal and external reasons, respectively. Enrollment is because teaching seems easy and is related to lack of interest. The learning motivation of students with different admission methods is similar, but the intrinsic motivation of girls is higher than that of boys, and the learning motivation of third-grade students is lower than that of other grades [11]. This study aims to explore how service-learning programs shape the cultural competencies of preservice teachers. Questionnaires were used to assess changes in students’ cultural competencies. Reflective journals and interviews are qualitative data sources used to identify important factors in service-learning programs that lead to reflections on the role of cultural competencies in teaching and learning. The research results show that the cultural competence of college students has changed [12]. Physical education in Australian universities has always been a single field of teacher education, but in the past 20 years, it has involved many disciplines related to human movement research, leisure, and sports science. Love sports and sports leisure industry and take a new career path. With the popularization of higher education knowledge and the change of social organization, school education, especially high school education, came into being. With the rapid development and reform of information organization in colleges and universities, physical education has become the basic course of higher education. By analyzing the current policies and practices of physical education in colleges and universities, this paper puts forward some ideas for the future [13]. To explore the relationship between communication skills and levels of self-efficacy in physical education teacher candidates, in this study, random sampling was used to select samples. In the current study, the “Teacher Competency Expectation Inventory” (TCEI) and the personal information form based on the teacher competency indicators in the Higher Education Commission/World Bank National Education Development Program were used as data collection tools [14]. This paper summarizes the research on the socialization of physical education teachers. Many previous studies have mentioned the prominent position of coaching orientation among new recruits; however, it has been suggested that new recruits and experienced teachers show a shift to teaching orientation. This change has triggered a new focus on the socialization of physical education teachers. However, the research since then has not been integrated. Therefore, the purpose of this study is to explore to what extent does the research on the socialization of physical education teachers record the changes in the nature of socialization; why this happens; and the enlightenment to schools and physical education. On the basis of the analysis, some suggestions for future research are put forward [15].


## 2. Literacy Evaluation under Grey Relational

### 2.1. Selection of Indicators for Teaching Literacy Evaluation

The evaluation of teachers’ literacy largely depends on the evaluation of teachers’ teaching level. Teacher evaluation has many contents, complex tasks, and high requirements. How to properly measure educational evaluation, transform qualitative indicators into quantitative indicators, and visually present the results of objective evaluation is the key to avoiding human factors as much as possible and giving full play to evaluation, fairness, and justice. Therefore, the selection of evaluation indicators should cover all aspects of evaluating teachers’ teaching ability. Some of the criteria for assessing teachers’ teaching ability are questioned based on the scientific principles, methods, procedures, and variables that should be followed in developing systems models. To further ensure the validity of the measures used, we revised the initial design measures by developing questionnaires and qualitative research methods to obtain the final analytical framework for the measures of teachers’ teaching skills (see Figure1).Figure 1
Teachers’ teaching quality evaluation index.


### 2.2. Teacher Literacy Evaluation Process

Improve the level of teaching management and teaching talents in colleges and universities, and improve teachers’ teaching skills, scientific research ability, teacher quality, and other indicators. Teachers better understand their own strengths and weaknesses, learn from each other about the strengths and weaknesses of their respective practices, and work together to support learning and development, but the first method and method of evaluation is to fill out the student and teacher evaluation form. The main purpose of evaluation is to evaluate teachers’ professional titles and economic interests. This method often only describes one aspect of teachers’ work, lacks depth and objectivity, and cannot fully evaluate teachers’ work. With the rise of information science and the continuous development of communication technology, the management of the education system is gradually informed. If such a large amount of assessment information can be used for comprehensive assessment of teachers’ competence through scientific data collection methods, the assessment of human factors can be excluded, the uncertainty of assessment can be reduced, and the assessment results can provide honest and very accurate insight, which is essential for school management, teacher long-term development, and improving teacher education. Due to the insurmountable problems of the classical complex evaluation method based on fuzzy transformation, in the process of using the objective function, all indicators are considered equally, and the relationship between the severity of each indicator factor is not considered, so the objective, reasonable, and easy evaluation work cannot be guaranteed. Technical realization elements: The purpose of the present invention is to overcome the deficiencies existing in the above-mentioned prior art, and to provide a method and system for evaluating teacher quality, which solves the problem that in the prior art; the indicators for teacher evaluation are not discriminated; and the importance of each indicator factor is not considered. Relationship, resulting in the lack of objective rationality of the evaluation work, and the influence of human factors is large. In order to achieve the above object, in the first aspect, the present invention provides a teacher quality evaluation method, which includes the following steps: Step 1: Collect multidimensional data samples of teachers, and establish a source data matrix. Step 2: Use the maximum value normalization processing method to standardize the source data matrix to obtain a standard data matrix. Step 3: Determine the weight coefficient of the evaluation factor according to the information entropy, and calculate the weight vector from the standard data matrix. Step 4: Perform clustering processing on the teacher set, and first use the fuzzy relationship. The transitive closure method roughly classifies all data samples and then performs precise classification based on the approximate classification. The process is shown in Figure2.Figure 2
Teacher literacy evaluation process.


### 2.3. Grey Relational Model

Grey correlation analysis is a multifactor statistical method and an important part of grey system theory. Compared with the traditional multifactor statistical method (regression analysis and difference analysis), it requires low sample size, and the calculated results will be consistent with the qualitative analysis results, so it should be divided into broad ones. Its basic idea is to judge the strength, order, and order of the relationship between factors by calculating the grey correlation degree between the main cause sequence and each cause sequence. The more grey correlation between the main cause sequence and the main cause sequence, the closer their relationship, and the more influence the main cause sequence has on the main cause sequence, and vice versa.


## 2.1. Selection of Indicators for Teaching Literacy Evaluation

The evaluation of teachers’ literacy largely depends on the evaluation of teachers’ teaching level. Teacher evaluation has many contents, complex tasks, and high requirements. How to properly measure educational evaluation, transform qualitative indicators into quantitative indicators, and visually present the results of objective evaluation is the key to avoiding human factors as much as possible and giving full play to evaluation, fairness, and justice. Therefore, the selection of evaluation indicators should cover all aspects of evaluating teachers’ teaching ability. Some of the criteria for assessing teachers’ teaching ability are questioned based on the scientific principles, methods, procedures, and variables that should be followed in developing systems models. To further ensure the validity of the measures used, we revised the initial design measures by developing questionnaires and qualitative research methods to obtain the final analytical framework for the measures of teachers’ teaching skills (see Figure1).Figure 1
Teachers’ teaching quality evaluation index.


## 2.2. Teacher Literacy Evaluation Process

Improve the level of teaching management and teaching talents in colleges and universities, and improve teachers’ teaching skills, scientific research ability, teacher quality, and other indicators. Teachers better understand their own strengths and weaknesses, learn from each other about the strengths and weaknesses of their respective practices, and work together to support learning and development, but the first method and method of evaluation is to fill out the student and teacher evaluation form. The main purpose of evaluation is to evaluate teachers’ professional titles and economic interests. This method often only describes one aspect of teachers’ work, lacks depth and objectivity, and cannot fully evaluate teachers’ work. With the rise of information science and the continuous development of communication technology, the management of the education system is gradually informed. If such a large amount of assessment information can be used for comprehensive assessment of teachers’ competence through scientific data collection methods, the assessment of human factors can be excluded, the uncertainty of assessment can be reduced, and the assessment results can provide honest and very accurate insight, which is essential for school management, teacher long-term development, and improving teacher education. Due to the insurmountable problems of the classical complex evaluation method based on fuzzy transformation, in the process of using the objective function, all indicators are considered equally, and the relationship between the severity of each indicator factor is not considered, so the objective, reasonable, and easy evaluation work cannot be guaranteed. Technical realization elements: The purpose of the present invention is to overcome the deficiencies existing in the above-mentioned prior art, and to provide a method and system for evaluating teacher quality, which solves the problem that in the prior art; the indicators for teacher evaluation are not discriminated; and the importance of each indicator factor is not considered. Relationship, resulting in the lack of objective rationality of the evaluation work, and the influence of human factors is large. In order to achieve the above object, in the first aspect, the present invention provides a teacher quality evaluation method, which includes the following steps: Step 1: Collect multidimensional data samples of teachers, and establish a source data matrix. Step 2: Use the maximum value normalization processing method to standardize the source data matrix to obtain a standard data matrix. Step 3: Determine the weight coefficient of the evaluation factor according to the information entropy, and calculate the weight vector from the standard data matrix. Step 4: Perform clustering processing on the teacher set, and first use the fuzzy relationship. The transitive closure method roughly classifies all data samples and then performs precise classification based on the approximate classification. The process is shown in Figure2.Figure 2
Teacher literacy evaluation process.


## 2.3. Grey Relational Model

Grey correlation analysis is a multifactor statistical method and an important part of grey system theory. Compared with the traditional multifactor statistical method (regression analysis and difference analysis), it requires low sample size, and the calculated results will be consistent with the qualitative analysis results, so it should be divided into broad ones. Its basic idea is to judge the strength, order, and order of the relationship between factors by calculating the grey correlation degree between the main cause sequence and each cause sequence. The more grey correlation between the main cause sequence and the main cause sequence, the closer their relationship, and the more influence the main cause sequence has on the main cause sequence, and vice versa.


## 3. Grey Relational Analysis Model

### 3.1. Basic Steps of Grey Relational Analysis Model

The first thing to do is to introduce the reference sequenceX0 affecting the characteristics of the system. The data sequence reflecting the behavior characteristics of the system is the reference sequence as follows:
(1)X0=X01,X02,⋯,X0n.The data series composed of factors affecting the behavior of the system is as follows:(2)X1=X11,X12,⋯,X1n,………(3)Xm=Xm1,Xm2,⋯,Xmn.Step 1: Find the initial value image of each sequence (after dimensionalization), and set(4)X′=XiXi1=Xi′1,Xi′2,⋯,Xi′n,where i=0,1,2,⋯,m gets:
(5)X0′,X1′,⋯,Xm′.Step 3: SolveX0 and Xi.Record as(6)Δik=X0′k−Xi′k,Δi=Δi1,Δi2,⋯,Δini=1,2,⋯,m;k=1,2,..,n.The fourth step is to find the maximum and minimum values ofΔik=X0′k−Xi′k. They are recorded as
(7)Δmin=Δiminkminik,Δmax=Δimaxkmaxik.The fifth step is to find the correlation coefficientξik:
(8)Δmin+pΔmax,ξ0ik=Δik+pΔmax,where P is the resolution coefficient, 0<P<1, and generally P=0.5.The sixth step is to find the correlation degree(9)γ0i=1/n∑k=1nξ0ik.According to the size ofγ0i, distinguish the degree of association. If the value is larger, the degree of association is greater, and vice versa.


### 3.2. Grey Correlation Analysis Model Based on Point Correlation Coefficient

The main models of grey relational analysis are usually based on the degree of similarity. Deng’s grey correlation analysis model illustrates this method. ForX1=x11,x12,⋯,x1n, it is the sequence of system behavior characteristics.
(10)Xm=xm1,xm2,⋯,xmn.For the case of correlation factor sequence, the point correlation coefficientγx1k,xik is defined
(11)γx1k,xik=iminkminx1k−xik+ξimaxkmaxx1k−xikx1k−xik+ξimaxkmaxx1k−xik.And the grey correlation degreeγX1,Xi between Xii=1,2,⋯,m and X1:
(12)γX1,Xi=1n∑k=1nγx1k,xik.Formula (12) is the calculation value of grey correlation degree of X1, which is aimed at the grey correlation analysis model of point correlation. In the specific calculation, the original data can be processed according to two different methods: initial value change and average value change.


#### 3.2.1. Generalized Grey Relational Analysis Model

At the same time, a class of generalized grey relational analysis model is also proposed. Let sequence(13)Xi=xi1,xi2,⋯,xin,Xj=xj1,xj2,⋯,xjn.The starting point annihilation images are(14)Xi0=xi01,xi02,⋯,xi0n,Xj0=xj01,xj02,⋯,xj0n.Among them(15)Xi0=xik−xi1,Xj0=xjk−xj1,k=1,2,⋯,n.The generalized grey relational analysis model constructed by this method has three different forms, which are shown in Formulas (16), (17), and (18).The first expression method:(16)εij=1+si+sj1+si+sj+si−sj,where the meaning of letters in Formula (16) is shown in the following formula:
(17)si=∫1nXi−xi1dt,sj=∫1nXj−xj1dt,si−sj=∫1nXi0−Xj0dt.The second expression method:(18)γij=1+si′+sj′1+si′+sj′+si′−sj′.The third expression method:(19)ρij=θεij+1−θγij.where θ∈0,1.In Formula (16), the basic grey absolute relational analysis model can be used to analyze the relationship between absolute quantities of sequences, and in Formula (18), the grey relative relational analysis model based on the grey absolute relational analysis model and initial value transformation is mainly used to analyze the relationship between the change rate of sequences relative to the starting point. Formula (18) is to change the initial value of Xi first, and then, calculate the grey absolute correlation degree of Xi′ after transformation.


## 3.1. Basic Steps of Grey Relational Analysis Model

The first thing to do is to introduce the reference sequenceX0 affecting the characteristics of the system. The data sequence reflecting the behavior characteristics of the system is the reference sequence as follows:
(1)X0=X01,X02,⋯,X0n.The data series composed of factors affecting the behavior of the system is as follows:(2)X1=X11,X12,⋯,X1n,………(3)Xm=Xm1,Xm2,⋯,Xmn.Step 1: Find the initial value image of each sequence (after dimensionalization), and set(4)X′=XiXi1=Xi′1,Xi′2,⋯,Xi′n,where i=0,1,2,⋯,m gets:
(5)X0′,X1′,⋯,Xm′.Step 3: SolveX0 and Xi.Record as(6)Δik=X0′k−Xi′k,Δi=Δi1,Δi2,⋯,Δini=1,2,⋯,m;k=1,2,..,n.The fourth step is to find the maximum and minimum values ofΔik=X0′k−Xi′k. They are recorded as
(7)Δmin=Δiminkminik,Δmax=Δimaxkmaxik.The fifth step is to find the correlation coefficientξik:
(8)Δmin+pΔmax,ξ0ik=Δik+pΔmax,where P is the resolution coefficient, 0<P<1, and generally P=0.5.The sixth step is to find the correlation degree(9)γ0i=1/n∑k=1nξ0ik.According to the size ofγ0i, distinguish the degree of association. If the value is larger, the degree of association is greater, and vice versa.


## 3.2. Grey Correlation Analysis Model Based on Point Correlation Coefficient

The main models of grey relational analysis are usually based on the degree of similarity. Deng’s grey correlation analysis model illustrates this method. ForX1=x11,x12,⋯,x1n, it is the sequence of system behavior characteristics.
(10)Xm=xm1,xm2,⋯,xmn.For the case of correlation factor sequence, the point correlation coefficientγx1k,xik is defined
(11)γx1k,xik=iminkminx1k−xik+ξimaxkmaxx1k−xikx1k−xik+ξimaxkmaxx1k−xik.And the grey correlation degreeγX1,Xi between Xii=1,2,⋯,m and X1:
(12)γX1,Xi=1n∑k=1nγx1k,xik.Formula (12) is the calculation value of grey correlation degree of X1, which is aimed at the grey correlation analysis model of point correlation. In the specific calculation, the original data can be processed according to two different methods: initial value change and average value change.


### 3.2.1. Generalized Grey Relational Analysis Model

At the same time, a class of generalized grey relational analysis model is also proposed. Let sequence(13)Xi=xi1,xi2,⋯,xin,Xj=xj1,xj2,⋯,xjn.The starting point annihilation images are(14)Xi0=xi01,xi02,⋯,xi0n,Xj0=xj01,xj02,⋯,xj0n.Among them(15)Xi0=xik−xi1,Xj0=xjk−xj1,k=1,2,⋯,n.The generalized grey relational analysis model constructed by this method has three different forms, which are shown in Formulas (16), (17), and (18).The first expression method:(16)εij=1+si+sj1+si+sj+si−sj,where the meaning of letters in Formula (16) is shown in the following formula:
(17)si=∫1nXi−xi1dt,sj=∫1nXj−xj1dt,si−sj=∫1nXi0−Xj0dt.The second expression method:(18)γij=1+si′+sj′1+si′+sj′+si′−sj′.The third expression method:(19)ρij=θεij+1−θγij.where θ∈0,1.In Formula (16), the basic grey absolute relational analysis model can be used to analyze the relationship between absolute quantities of sequences, and in Formula (18), the grey relative relational analysis model based on the grey absolute relational analysis model and initial value transformation is mainly used to analyze the relationship between the change rate of sequences relative to the starting point. Formula (18) is to change the initial value of Xi first, and then, calculate the grey absolute correlation degree of Xi′ after transformation.


## 3.2.1. Generalized Grey Relational Analysis Model

At the same time, a class of generalized grey relational analysis model is also proposed. Let sequence(13)Xi=xi1,xi2,⋯,xin,Xj=xj1,xj2,⋯,xjn.The starting point annihilation images are(14)Xi0=xi01,xi02,⋯,xi0n,Xj0=xj01,xj02,⋯,xj0n.Among them(15)Xi0=xik−xi1,Xj0=xjk−xj1,k=1,2,⋯,n.The generalized grey relational analysis model constructed by this method has three different forms, which are shown in Formulas (16), (17), and (18).The first expression method:(16)εij=1+si+sj1+si+sj+si−sj,where the meaning of letters in Formula (16) is shown in the following formula:
(17)si=∫1nXi−xi1dt,sj=∫1nXj−xj1dt,si−sj=∫1nXi0−Xj0dt.The second expression method:(18)γij=1+si′+sj′1+si′+sj′+si′−sj′.The third expression method:(19)ρij=θεij+1−θγij.where θ∈0,1.In Formula (16), the basic grey absolute relational analysis model can be used to analyze the relationship between absolute quantities of sequences, and in Formula (18), the grey relative relational analysis model based on the grey absolute relational analysis model and initial value transformation is mainly used to analyze the relationship between the change rate of sequences relative to the starting point. Formula (18) is to change the initial value of Xi first, and then, calculate the grey absolute correlation degree of Xi′ after transformation.


## 4. Evaluation Index System of Physical Education Teachers’ Literacy

### 4.1. Evaluation of Physical Education Teachers’ Multifaceted Literacy

#### 4.1.1. Gender Structure

There are differences in gender ratio in physical education teachers’ literacy. The gender structure of physical education teachers reflects the absolute number of men and women in physical education teachers and its relationship with the total number of groups. There are great differences between men and women. It not only refers to the physical differences between men and women, but also refers to the huge gap between men and women in terms of thinking mode. If the share distribution of university teachers is more uniform, it can better supplement and support the development of teaching. In the profession of physical education teachers, male teachers have many advantages in physical condition and physical quality, so physical education teachers are mostly male, and there is an unequal gender balance between men and women. The survey found that the ratio of male to female teachers is roughly 79% for male teachers and 21% for female teachers. At the same time, we also made a survey on the influence of five male and female physical education teachers on teaching satisfaction, as shown in the figure.Figure3 shows the influence of each of the five male and female physical education teachers on the teaching quality in terms of gender. The evaluation of teachers’ literacy is multifaceted, and the difference between men and women will also affect. On the quality of physical education, the average satisfaction of female teachers is about 0.8, while the average satisfaction of male teachers is slightly higher than that of female teachers, reaching 0.87. Because of subjects, male teachers have better physical quality, so their satisfaction is also better. We also calculate the accuracy of the experimental data through the grey relational degree model, and get the satisfaction of each time, as shown by the thick line in the figure, and the linear summary of the grey relational degree for this survey is shown by the thin line in the figure. The average accuracy is 0.88.Figure 3
Investigation on gender satisfaction of physical education teachers to teaching.


#### 4.1.2. Age Structure

Age is a sign of natural aging and an uncontrollable part of people. The age structure of physical education teachers refers to the proportion of each age group in the whole. For teachers of ordinary subjects, the older they are, the richer their teaching experience is, but physical education teachers are quite different. Although teaching experience will increase, physical education is different from others, and teachers need to lead by example to demonstrate actions, which lead to the inability of older teachers. Young teachers are more suitable for physical education teachers, and their youthful vitality will make students participate more actively. The distribution and teaching quality of physical education teachers of all ages are investigated, as shown in Figure4.Figure 4
Age structure of physical education teachers and teaching quality.Figure4 shows the age structure and teaching quality of physical education teachers. We can see that the quality of teaching varies from age to age. In the survey, the teaching quality of physical education teachers aged 25-30 reached nearly 90%, followed by teachers aged 30-35, and the number of teachers in these two ages was also the largest. Teachers in these two ages were not only in good health, but also had a lot of experience in teaching. A good combination of the two is also of obvious help to teaching.


#### 4.1.3. Educational Background Structure

Postgraduates and doctors are very important in physical education. It is very important for the faculty and staff working in colleges and universities and has a far-reaching impact on personal education and other abilities. With the increase of the number of students in China, the number of undergraduate, master’s, and doctoral students has increased, and higher education has shifted from elite to mass. Some schools have national physical education class, and the academic qualifications of coaches and judges of the national team are lowered, but the academic qualifications of teachers are also slowly rising. Through the survey found that the proportion of the structure of education in physical education teachers, the quality of these teachers also carried out a survey found that there are some differences, as shown in the following figure.Figure5 is a summary of data introducing the educational background structure and teachers’ literacy. For the distribution of educational background, with the increasing requirements of teachers, the educational background requirements are also increasing. In the survey of physical education teachers, graduate students are in the majority, among which master students are the most, and doctoral students account for less among physical education teachers because of the small overall number. For the literacy score under the influence of educational background, we have made a survey on various groups of people. The external literacy of doctoral students is the highest, followed by master’s students, undergraduates and junior college students are the lowest, but there is not much difference in external literacy among them. The main gap lies in the internal accomplishment, and the higher the educational background, the more knowledge you learn. Knowledge is rich inside. Therefore, the gap between junior college students and graduate students is obvious, but they can also improve their internal literacy through other studies.Figure 5
Educational background structure and teacher literacy.Figure5 illustrates the educational background structure and teachers’ literacy among the respondents. As shown in the figure, we can clearly see the distribution of educational background structure among the teachers participating in the survey, with graduate students accounting for 62% and doctoral students accounting for 6%. Junior college is at least 2%. There are many influences on teachers’ quality. Here, the total scores of internal literacy and external literacy are 1. There is little difference between internal literacy and external literacy in graduate students, but for junior colleges, because what they learn is only different, there is a big gap between teachers’ personal internal literacy.


### 4.2. Selection and Establishment of Evaluation Index of Physical Education Teachers’ Comprehensive Quality

Physical education teachers need not only the qualities of ordinary teachers, but also the physical qualities of physical education. Combined with the suggestions of experts, we classify the known comprehensive qualities, which are roughly divided into three parts: professional basic qualities, professional standard qualities, and marginal qualities.


#### 4.2.1. Selection of Evaluation Indicators

The personal image, ability, knowledge, and skills embodied by college physical education teachers in college physical education play an exemplary role for students. Therefore, this study conducted an in-depth discussion with the instructor after personally reviewing the learning materials. In the form of interviews, we frequently reflect and solicit expert opinions. The first-level indicators of comprehensive teacher knowledge are divided into professional teachers’ basic knowledge, practical teachers’ knowledge, and neighborhood teachers’ knowledge. In the process of making and completing the expert questionnaire and teacher questionnaire, we solicited the views of experts and teachers on the distribution of indicators, and obtained the following data.According to Table1, we can know that four people agree with the results of expert questionnaire survey, two agree with it, and no one opposes it. In the teacher questionnaire, 6 people agree very much, and 37 people agree relatively. Therefore, it can be seen that the questionnaire is effective, and no one disagrees with the classification, so the second indicator can be subdivided on this basis.Table 1
Statistics of questionnaire survey results for the establishment of first-level indicators.
Total numberVery agreeableCompare and agreeAgreeCompare disagreementDeeply disagreeExpert questionnaire604200Teacher questionnaire43637000When classifying the secondary indicators, the research on the basic professional quality of college physical education teachers thinks that it should be composed of four parts: physical education quality, psychological quality, professional skills, and knowledge structure, which are the most basic qualities in physical education. 16.67% of experts strongly agree, 66.66% agree, and 16.67% generally agree. According to the results of the questionnaire survey, 16.28% of professors strongly agree, and 69.77% of teachers and 13.95% of teachers generally agree. It may be useful to divide the basic knowledge of using first-class symbols into four categories: physical knowledge, conceptual knowledge, functional skills, and organizational knowledge.In terms of professional quality of college teachers, this course should include three aspects: skills, technical training, and research ability. 33.33% of the experts agreed, and 66.67% of the experts agreed. According to the results of teachers’ questions and the opinions of experts’ questions, 16.28% of the experts agreed, 79.07% of the teachers agreed, and another 4.65% of the teachers reached the average level. Admittedly, it is necessary to divide vocational training into the above four intermediate indicators. Nowadays, society is slowly entering the era of everyone’s participation, so teachers’ literacy has become an important part of teacher education. 66.67% of the experts agreed, and 13.33% of the experts generally agreed that competitiveness should not be included in teachers’ marginal education according to the changes of experts’ questionnaires, so this product was excluded from teachers’ survey, 18.60% of teachers agreed, 74.42% of teachers agreed, and 6.98% of teachers’ reports were average. It can be seen that the acceptance of marginal indicators to teachers is divided into the above three parts. By modifying expert questions and teachers’ questionnaire feedback, the first and second level indicators of all good performance of physical education teachers used in this study questionnaire are formulated.


#### 4.2.2. Evaluation Established

After the above analysis and investigation, we can accurately establish the evaluation index so as to make it more convenient to evaluate the quality of physical education teachers. It mainly determines the first-level evaluation standards, such as professional standard literacy, professional basic literacy, and teacher marginal literacy. After evaluating the first-level indicators, it evaluates the second-level indicators more specifically. Professional standard literacy includes teaching ability, training ability, and scientific research ability. Professional basic literacy includes physical literacy, psychological literacy, professional skills, and knowledge structure, while teachers’ marginal literacy includes professional ethics, information literacy, humanistic literacy, and competition adjudication ability. After the evaluation index is determined, the evaluation process and steps need to be determined, as shown in the following figure6:Figure 6
Specific process of teacher literacy evaluation.


### 4.3. Teachers’ Literacy under Grey Correlation Degree

Grey relational model is a model that expresses the degree of correlation with it. For teacher literacy evaluation, it is not only to express the degree of correlation between teacher literacy evaluation index and teacher literacy. Above, we described various indicators for evaluating teachers’ literacy. Grey relational analysis is an effective method to study the relational degree of various factors in the system. Its basic idea is to determine the tightness of the connection between sequences according to the similarity of geometric shapes of behavioral sequence curves. It is realized by calculating the grey correlation degree. For the comprehensive evaluation of teachers’ ability and quality, this paper analyzes the commonly used teacher evaluation indicators and puts forward the data comparison based on grey relational analysis to determine their correlation degree. First, we investigated the influence of teachers’ age, educational background, and gender on teachers’ literacy. The correlation degree is shown in the following figure.Figure7 illustrates the relationship between the basic information of physical education teachers and the grey correlation degree; after many experiments, we can get the grey correlation degree of the curve shown in the figure in each experiment; and we can get the relationship degree between this item and physical education teachers’ literacy by averaging it. The dotted line in the figure is the average value of data obtained after many experiments, which can show the relationship between this index and grey relational degree, and can see the degree of relationship with teachers’ literacy more intuitively. The correlation between teacher literacy and education is the highest, followed by age, and the weakest correlation is gender.Figure 7
Grey correlation degree between basic information and teacher literacy.In Figure7, we have conducted an experimental study on the grey correlation between the basic information of physical education teachers and teachers’ literacy and obtained data. For age, gender and educational background, the grey correlation with teachers’ literacy is not very high, and the educational background is slightly higher among these three, with an average value of about 0.68. The average correlation degree of age is 0.64. The average grey correlation degree of gender is 0.56. It shows that the correlation degree of educational background on teachers’ literacy is slightly higher than the other two. Then, we carry out grey analysis experiment on the first-level index of teacher literacy evaluation and get the data as shown in the figure.Figure8 is the correlation analysis of the first-level indicators to teachers’ literacy. By comparing the three first-level indicators, it can be seen that the professional basic literacy has the highest correlation with teachers’ literacy, while the grey correlation of teachers’ marginal literacy is the lowest, and its correlation degree is also the lowest.Figure 8
Grey correlation degree of first-class index.Figure9 is the grey correlation degree of factors affecting physical education teachers’ literacy. This figure shows the influence of evaluation factors on physical education teachers’ literacy. This paper mainly investigates six aspects: teaching ability, training ability, physical literacy, professional ability, professional ethics, and knowledge structure. We have conducted many experiments to ensure the accuracy of the experiment. We trace the data calculated from each experiment in Figure 9 and then connect them into a line. A dotted line in the figure is the linear relationship value, which clearly shows the selected evaluation index of physical education teachers’ literacy.Figure 9
Grey correlation degree of secondary indicators.Figure9 studies the grey correlation degree of various factors affecting physical education teachers’ literacy in detail. From Table 2, we can see that the grey correlation degree of professional ability is the highest among the evaluation factors, reaching the average value of 0.9. It shows that this evaluation factor is the most important for physical education teachers’ literacy, followed by training ability, and training is very important in sports, so the grey correlation degree of teachers’ training ability is also very high. The lowest is humanistic quality, with an average value of only 0.5. The grey correlation degree is low.Table 2
Statistics of questionnaire survey results for establishing secondary indicators.
IndicatorsCrowdTotal numberVery agreeableAgreeGeneralDisagreeDeeply disagreeProfessional basic accomplishmentExpert questionnaire614100Teacher questionnaire43730600Professional standard accomplishmentExpert questionnaire624000Teacher questionnaire43734200Marginal accomplishment of teachersExpert questionnaire604200Teacher questionnaire43832300


### 4.4. Comprehensive Score of Teacher Literacy

In the analysis and research of teachers’ literacy, we determine the correlation degree of each evaluation index through grey correlation model. Under the analysis of the first and second indicators, the correlation degree of professional professionalism is higher, so his score accounts for the highest proportion, followed by professional standard literacy, and finally by teachers’ marginal literacy. In the score, the score proportion will be divided according to the correlation degree, and then, the score will be divided according to the correlation degree of secondary indicators. The final score of 100 is as follows:For Figure10, which shows the proportion of comprehensive scores in teachers’ literacy, the final comprehensive scores can be obtained by multiplying them by the proportion according to various indicators.Figure 10
Comprehensive scoring system.


## 4.1. Evaluation of Physical Education Teachers’ Multifaceted Literacy

### 4.1.1. Gender Structure

There are differences in gender ratio in physical education teachers’ literacy. The gender structure of physical education teachers reflects the absolute number of men and women in physical education teachers and its relationship with the total number of groups. There are great differences between men and women. It not only refers to the physical differences between men and women, but also refers to the huge gap between men and women in terms of thinking mode. If the share distribution of university teachers is more uniform, it can better supplement and support the development of teaching. In the profession of physical education teachers, male teachers have many advantages in physical condition and physical quality, so physical education teachers are mostly male, and there is an unequal gender balance between men and women. The survey found that the ratio of male to female teachers is roughly 79% for male teachers and 21% for female teachers. At the same time, we also made a survey on the influence of five male and female physical education teachers on teaching satisfaction, as shown in the figure.Figure3 shows the influence of each of the five male and female physical education teachers on the teaching quality in terms of gender. The evaluation of teachers’ literacy is multifaceted, and the difference between men and women will also affect. On the quality of physical education, the average satisfaction of female teachers is about 0.8, while the average satisfaction of male teachers is slightly higher than that of female teachers, reaching 0.87. Because of subjects, male teachers have better physical quality, so their satisfaction is also better. We also calculate the accuracy of the experimental data through the grey relational degree model, and get the satisfaction of each time, as shown by the thick line in the figure, and the linear summary of the grey relational degree for this survey is shown by the thin line in the figure. The average accuracy is 0.88.Figure 3
Investigation on gender satisfaction of physical education teachers to teaching.


### 4.1.2. Age Structure

Age is a sign of natural aging and an uncontrollable part of people. The age structure of physical education teachers refers to the proportion of each age group in the whole. For teachers of ordinary subjects, the older they are, the richer their teaching experience is, but physical education teachers are quite different. Although teaching experience will increase, physical education is different from others, and teachers need to lead by example to demonstrate actions, which lead to the inability of older teachers. Young teachers are more suitable for physical education teachers, and their youthful vitality will make students participate more actively. The distribution and teaching quality of physical education teachers of all ages are investigated, as shown in Figure4.Figure 4
Age structure of physical education teachers and teaching quality.Figure4 shows the age structure and teaching quality of physical education teachers. We can see that the quality of teaching varies from age to age. In the survey, the teaching quality of physical education teachers aged 25-30 reached nearly 90%, followed by teachers aged 30-35, and the number of teachers in these two ages was also the largest. Teachers in these two ages were not only in good health, but also had a lot of experience in teaching. A good combination of the two is also of obvious help to teaching.


### 4.1.3. Educational Background Structure

Postgraduates and doctors are very important in physical education. It is very important for the faculty and staff working in colleges and universities and has a far-reaching impact on personal education and other abilities. With the increase of the number of students in China, the number of undergraduate, master’s, and doctoral students has increased, and higher education has shifted from elite to mass. Some schools have national physical education class, and the academic qualifications of coaches and judges of the national team are lowered, but the academic qualifications of teachers are also slowly rising. Through the survey found that the proportion of the structure of education in physical education teachers, the quality of these teachers also carried out a survey found that there are some differences, as shown in the following figure.Figure5 is a summary of data introducing the educational background structure and teachers’ literacy. For the distribution of educational background, with the increasing requirements of teachers, the educational background requirements are also increasing. In the survey of physical education teachers, graduate students are in the majority, among which master students are the most, and doctoral students account for less among physical education teachers because of the small overall number. For the literacy score under the influence of educational background, we have made a survey on various groups of people. The external literacy of doctoral students is the highest, followed by master’s students, undergraduates and junior college students are the lowest, but there is not much difference in external literacy among them. The main gap lies in the internal accomplishment, and the higher the educational background, the more knowledge you learn. Knowledge is rich inside. Therefore, the gap between junior college students and graduate students is obvious, but they can also improve their internal literacy through other studies.Figure 5
Educational background structure and teacher literacy.Figure5 illustrates the educational background structure and teachers’ literacy among the respondents. As shown in the figure, we can clearly see the distribution of educational background structure among the teachers participating in the survey, with graduate students accounting for 62% and doctoral students accounting for 6%. Junior college is at least 2%. There are many influences on teachers’ quality. Here, the total scores of internal literacy and external literacy are 1. There is little difference between internal literacy and external literacy in graduate students, but for junior colleges, because what they learn is only different, there is a big gap between teachers’ personal internal literacy.


## 4.1.1. Gender Structure

There are differences in gender ratio in physical education teachers’ literacy. The gender structure of physical education teachers reflects the absolute number of men and women in physical education teachers and its relationship with the total number of groups. There are great differences between men and women. It not only refers to the physical differences between men and women, but also refers to the huge gap between men and women in terms of thinking mode. If the share distribution of university teachers is more uniform, it can better supplement and support the development of teaching. In the profession of physical education teachers, male teachers have many advantages in physical condition and physical quality, so physical education teachers are mostly male, and there is an unequal gender balance between men and women. The survey found that the ratio of male to female teachers is roughly 79% for male teachers and 21% for female teachers. At the same time, we also made a survey on the influence of five male and female physical education teachers on teaching satisfaction, as shown in the figure.Figure3 shows the influence of each of the five male and female physical education teachers on the teaching quality in terms of gender. The evaluation of teachers’ literacy is multifaceted, and the difference between men and women will also affect. On the quality of physical education, the average satisfaction of female teachers is about 0.8, while the average satisfaction of male teachers is slightly higher than that of female teachers, reaching 0.87. Because of subjects, male teachers have better physical quality, so their satisfaction is also better. We also calculate the accuracy of the experimental data through the grey relational degree model, and get the satisfaction of each time, as shown by the thick line in the figure, and the linear summary of the grey relational degree for this survey is shown by the thin line in the figure. The average accuracy is 0.88.Figure 3
Investigation on gender satisfaction of physical education teachers to teaching.


## 4.1.2. Age Structure

Age is a sign of natural aging and an uncontrollable part of people. The age structure of physical education teachers refers to the proportion of each age group in the whole. For teachers of ordinary subjects, the older they are, the richer their teaching experience is, but physical education teachers are quite different. Although teaching experience will increase, physical education is different from others, and teachers need to lead by example to demonstrate actions, which lead to the inability of older teachers. Young teachers are more suitable for physical education teachers, and their youthful vitality will make students participate more actively. The distribution and teaching quality of physical education teachers of all ages are investigated, as shown in Figure4.Figure 4
Age structure of physical education teachers and teaching quality.Figure4 shows the age structure and teaching quality of physical education teachers. We can see that the quality of teaching varies from age to age. In the survey, the teaching quality of physical education teachers aged 25-30 reached nearly 90%, followed by teachers aged 30-35, and the number of teachers in these two ages was also the largest. Teachers in these two ages were not only in good health, but also had a lot of experience in teaching. A good combination of the two is also of obvious help to teaching.


## 4.1.3. Educational Background Structure

Postgraduates and doctors are very important in physical education. It is very important for the faculty and staff working in colleges and universities and has a far-reaching impact on personal education and other abilities. With the increase of the number of students in China, the number of undergraduate, master’s, and doctoral students has increased, and higher education has shifted from elite to mass. Some schools have national physical education class, and the academic qualifications of coaches and judges of the national team are lowered, but the academic qualifications of teachers are also slowly rising. Through the survey found that the proportion of the structure of education in physical education teachers, the quality of these teachers also carried out a survey found that there are some differences, as shown in the following figure.Figure5 is a summary of data introducing the educational background structure and teachers’ literacy. For the distribution of educational background, with the increasing requirements of teachers, the educational background requirements are also increasing. In the survey of physical education teachers, graduate students are in the majority, among which master students are the most, and doctoral students account for less among physical education teachers because of the small overall number. For the literacy score under the influence of educational background, we have made a survey on various groups of people. The external literacy of doctoral students is the highest, followed by master’s students, undergraduates and junior college students are the lowest, but there is not much difference in external literacy among them. The main gap lies in the internal accomplishment, and the higher the educational background, the more knowledge you learn. Knowledge is rich inside. Therefore, the gap between junior college students and graduate students is obvious, but they can also improve their internal literacy through other studies.Figure 5
Educational background structure and teacher literacy.Figure5 illustrates the educational background structure and teachers’ literacy among the respondents. As shown in the figure, we can clearly see the distribution of educational background structure among the teachers participating in the survey, with graduate students accounting for 62% and doctoral students accounting for 6%. Junior college is at least 2%. There are many influences on teachers’ quality. Here, the total scores of internal literacy and external literacy are 1. There is little difference between internal literacy and external literacy in graduate students, but for junior colleges, because what they learn is only different, there is a big gap between teachers’ personal internal literacy.


## 4.2. Selection and Establishment of Evaluation Index of Physical Education Teachers’ Comprehensive Quality

Physical education teachers need not only the qualities of ordinary teachers, but also the physical qualities of physical education. Combined with the suggestions of experts, we classify the known comprehensive qualities, which are roughly divided into three parts: professional basic qualities, professional standard qualities, and marginal qualities.


### 4.2.1. Selection of Evaluation Indicators

The personal image, ability, knowledge, and skills embodied by college physical education teachers in college physical education play an exemplary role for students. Therefore, this study conducted an in-depth discussion with the instructor after personally reviewing the learning materials. In the form of interviews, we frequently reflect and solicit expert opinions. The first-level indicators of comprehensive teacher knowledge are divided into professional teachers’ basic knowledge, practical teachers’ knowledge, and neighborhood teachers’ knowledge. In the process of making and completing the expert questionnaire and teacher questionnaire, we solicited the views of experts and teachers on the distribution of indicators, and obtained the following data.According to Table1, we can know that four people agree with the results of expert questionnaire survey, two agree with it, and no one opposes it. In the teacher questionnaire, 6 people agree very much, and 37 people agree relatively. Therefore, it can be seen that the questionnaire is effective, and no one disagrees with the classification, so the second indicator can be subdivided on this basis.Table 1
Statistics of questionnaire survey results for the establishment of first-level indicators.
Total numberVery agreeableCompare and agreeAgreeCompare disagreementDeeply disagreeExpert questionnaire604200Teacher questionnaire43637000When classifying the secondary indicators, the research on the basic professional quality of college physical education teachers thinks that it should be composed of four parts: physical education quality, psychological quality, professional skills, and knowledge structure, which are the most basic qualities in physical education. 16.67% of experts strongly agree, 66.66% agree, and 16.67% generally agree. According to the results of the questionnaire survey, 16.28% of professors strongly agree, and 69.77% of teachers and 13.95% of teachers generally agree. It may be useful to divide the basic knowledge of using first-class symbols into four categories: physical knowledge, conceptual knowledge, functional skills, and organizational knowledge.In terms of professional quality of college teachers, this course should include three aspects: skills, technical training, and research ability. 33.33% of the experts agreed, and 66.67% of the experts agreed. According to the results of teachers’ questions and the opinions of experts’ questions, 16.28% of the experts agreed, 79.07% of the teachers agreed, and another 4.65% of the teachers reached the average level. Admittedly, it is necessary to divide vocational training into the above four intermediate indicators. Nowadays, society is slowly entering the era of everyone’s participation, so teachers’ literacy has become an important part of teacher education. 66.67% of the experts agreed, and 13.33% of the experts generally agreed that competitiveness should not be included in teachers’ marginal education according to the changes of experts’ questionnaires, so this product was excluded from teachers’ survey, 18.60% of teachers agreed, 74.42% of teachers agreed, and 6.98% of teachers’ reports were average. It can be seen that the acceptance of marginal indicators to teachers is divided into the above three parts. By modifying expert questions and teachers’ questionnaire feedback, the first and second level indicators of all good performance of physical education teachers used in this study questionnaire are formulated.


### 4.2.2. Evaluation Established

After the above analysis and investigation, we can accurately establish the evaluation index so as to make it more convenient to evaluate the quality of physical education teachers. It mainly determines the first-level evaluation standards, such as professional standard literacy, professional basic literacy, and teacher marginal literacy. After evaluating the first-level indicators, it evaluates the second-level indicators more specifically. Professional standard literacy includes teaching ability, training ability, and scientific research ability. Professional basic literacy includes physical literacy, psychological literacy, professional skills, and knowledge structure, while teachers’ marginal literacy includes professional ethics, information literacy, humanistic literacy, and competition adjudication ability. After the evaluation index is determined, the evaluation process and steps need to be determined, as shown in the following figure6:Figure 6
Specific process of teacher literacy evaluation.


## 4.2.1. Selection of Evaluation Indicators

The personal image, ability, knowledge, and skills embodied by college physical education teachers in college physical education play an exemplary role for students. Therefore, this study conducted an in-depth discussion with the instructor after personally reviewing the learning materials. In the form of interviews, we frequently reflect and solicit expert opinions. The first-level indicators of comprehensive teacher knowledge are divided into professional teachers’ basic knowledge, practical teachers’ knowledge, and neighborhood teachers’ knowledge. In the process of making and completing the expert questionnaire and teacher questionnaire, we solicited the views of experts and teachers on the distribution of indicators, and obtained the following data.According to Table1, we can know that four people agree with the results of expert questionnaire survey, two agree with it, and no one opposes it. In the teacher questionnaire, 6 people agree very much, and 37 people agree relatively. Therefore, it can be seen that the questionnaire is effective, and no one disagrees with the classification, so the second indicator can be subdivided on this basis.Table 1
Statistics of questionnaire survey results for the establishment of first-level indicators.
Total numberVery agreeableCompare and agreeAgreeCompare disagreementDeeply disagreeExpert questionnaire604200Teacher questionnaire43637000When classifying the secondary indicators, the research on the basic professional quality of college physical education teachers thinks that it should be composed of four parts: physical education quality, psychological quality, professional skills, and knowledge structure, which are the most basic qualities in physical education. 16.67% of experts strongly agree, 66.66% agree, and 16.67% generally agree. According to the results of the questionnaire survey, 16.28% of professors strongly agree, and 69.77% of teachers and 13.95% of teachers generally agree. It may be useful to divide the basic knowledge of using first-class symbols into four categories: physical knowledge, conceptual knowledge, functional skills, and organizational knowledge.In terms of professional quality of college teachers, this course should include three aspects: skills, technical training, and research ability. 33.33% of the experts agreed, and 66.67% of the experts agreed. According to the results of teachers’ questions and the opinions of experts’ questions, 16.28% of the experts agreed, 79.07% of the teachers agreed, and another 4.65% of the teachers reached the average level. Admittedly, it is necessary to divide vocational training into the above four intermediate indicators. Nowadays, society is slowly entering the era of everyone’s participation, so teachers’ literacy has become an important part of teacher education. 66.67% of the experts agreed, and 13.33% of the experts generally agreed that competitiveness should not be included in teachers’ marginal education according to the changes of experts’ questionnaires, so this product was excluded from teachers’ survey, 18.60% of teachers agreed, 74.42% of teachers agreed, and 6.98% of teachers’ reports were average. It can be seen that the acceptance of marginal indicators to teachers is divided into the above three parts. By modifying expert questions and teachers’ questionnaire feedback, the first and second level indicators of all good performance of physical education teachers used in this study questionnaire are formulated.


## 4.2.2. Evaluation Established

After the above analysis and investigation, we can accurately establish the evaluation index so as to make it more convenient to evaluate the quality of physical education teachers. It mainly determines the first-level evaluation standards, such as professional standard literacy, professional basic literacy, and teacher marginal literacy. After evaluating the first-level indicators, it evaluates the second-level indicators more specifically. Professional standard literacy includes teaching ability, training ability, and scientific research ability. Professional basic literacy includes physical literacy, psychological literacy, professional skills, and knowledge structure, while teachers’ marginal literacy includes professional ethics, information literacy, humanistic literacy, and competition adjudication ability. After the evaluation index is determined, the evaluation process and steps need to be determined, as shown in the following figure6:Figure 6
Specific process of teacher literacy evaluation.


## 4.3. Teachers’ Literacy under Grey Correlation Degree

Grey relational model is a model that expresses the degree of correlation with it. For teacher literacy evaluation, it is not only to express the degree of correlation between teacher literacy evaluation index and teacher literacy. Above, we described various indicators for evaluating teachers’ literacy. Grey relational analysis is an effective method to study the relational degree of various factors in the system. Its basic idea is to determine the tightness of the connection between sequences according to the similarity of geometric shapes of behavioral sequence curves. It is realized by calculating the grey correlation degree. For the comprehensive evaluation of teachers’ ability and quality, this paper analyzes the commonly used teacher evaluation indicators and puts forward the data comparison based on grey relational analysis to determine their correlation degree. First, we investigated the influence of teachers’ age, educational background, and gender on teachers’ literacy. The correlation degree is shown in the following figure.Figure7 illustrates the relationship between the basic information of physical education teachers and the grey correlation degree; after many experiments, we can get the grey correlation degree of the curve shown in the figure in each experiment; and we can get the relationship degree between this item and physical education teachers’ literacy by averaging it. The dotted line in the figure is the average value of data obtained after many experiments, which can show the relationship between this index and grey relational degree, and can see the degree of relationship with teachers’ literacy more intuitively. The correlation between teacher literacy and education is the highest, followed by age, and the weakest correlation is gender.Figure 7
Grey correlation degree between basic information and teacher literacy.In Figure7, we have conducted an experimental study on the grey correlation between the basic information of physical education teachers and teachers’ literacy and obtained data. For age, gender and educational background, the grey correlation with teachers’ literacy is not very high, and the educational background is slightly higher among these three, with an average value of about 0.68. The average correlation degree of age is 0.64. The average grey correlation degree of gender is 0.56. It shows that the correlation degree of educational background on teachers’ literacy is slightly higher than the other two. Then, we carry out grey analysis experiment on the first-level index of teacher literacy evaluation and get the data as shown in the figure.Figure8 is the correlation analysis of the first-level indicators to teachers’ literacy. By comparing the three first-level indicators, it can be seen that the professional basic literacy has the highest correlation with teachers’ literacy, while the grey correlation of teachers’ marginal literacy is the lowest, and its correlation degree is also the lowest.Figure 8
Grey correlation degree of first-class index.Figure9 is the grey correlation degree of factors affecting physical education teachers’ literacy. This figure shows the influence of evaluation factors on physical education teachers’ literacy. This paper mainly investigates six aspects: teaching ability, training ability, physical literacy, professional ability, professional ethics, and knowledge structure. We have conducted many experiments to ensure the accuracy of the experiment. We trace the data calculated from each experiment in Figure 9 and then connect them into a line. A dotted line in the figure is the linear relationship value, which clearly shows the selected evaluation index of physical education teachers’ literacy.Figure 9
Grey correlation degree of secondary indicators.Figure9 studies the grey correlation degree of various factors affecting physical education teachers’ literacy in detail. From Table 2, we can see that the grey correlation degree of professional ability is the highest among the evaluation factors, reaching the average value of 0.9. It shows that this evaluation factor is the most important for physical education teachers’ literacy, followed by training ability, and training is very important in sports, so the grey correlation degree of teachers’ training ability is also very high. The lowest is humanistic quality, with an average value of only 0.5. The grey correlation degree is low.Table 2
Statistics of questionnaire survey results for establishing secondary indicators.
IndicatorsCrowdTotal numberVery agreeableAgreeGeneralDisagreeDeeply disagreeProfessional basic accomplishmentExpert questionnaire614100Teacher questionnaire43730600Professional standard accomplishmentExpert questionnaire624000Teacher questionnaire43734200Marginal accomplishment of teachersExpert questionnaire604200Teacher questionnaire43832300


## 4.4. Comprehensive Score of Teacher Literacy

In the analysis and research of teachers’ literacy, we determine the correlation degree of each evaluation index through grey correlation model. Under the analysis of the first and second indicators, the correlation degree of professional professionalism is higher, so his score accounts for the highest proportion, followed by professional standard literacy, and finally by teachers’ marginal literacy. In the score, the score proportion will be divided according to the correlation degree, and then, the score will be divided according to the correlation degree of secondary indicators. The final score of 100 is as follows:For Figure10, which shows the proportion of comprehensive scores in teachers’ literacy, the final comprehensive scores can be obtained by multiplying them by the proportion according to various indicators.Figure 10
Comprehensive scoring system.


## 5. Conclusion

This paper makes a detailed introduction and research on the evaluation index and application of physical education teachers’ literacy under the grey relational model. With the development of society, people pay more attention to their health, and the literacy of physical education teachers is particularly important. As for the evaluation index and application of physical education teachers’ literacy, we analyze the basic conditions of physical education teachers themselves, marginal literacy of teachers, professional standard literacy, and professional basic literacy, and analyze the grey correlation degree of these aspects for physical education teachers’ literacy. Also, the grey correlation degree shows that teachers’ professional ability and teachers’ accomplishment have the greatest correlation degree and also introduce the calculation of grey correlation degree in detail.



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*Source: 5448213-2022-09-06.xml*