# The Performance Evaluation of IEE in Colleges and Universities Based on AHP Model

Authors: Zhenghan Liang
Journal: Discrete Dynamics in Nature and Society
 (2022)

---

## Abstract

At present, the country strongly encourages all walks of life to innovate, especially in the field of education. China's major colleges and universities have increased the encouragement of innovation and entrepreneurship education (IEE) projects in keeping with the pace of the times, so it is particularly important to reasonably evaluate the actual benefits of the project. On the one hand, it can greatly improve the recognition of all walks of life for emerging education projects. On the other hand, it can realize the timely and accurate application of the financial funds of the project. Based on this background, through the analysis and summary of existing theories and comprehensive consideration at all levels, this paper studies the new education projects from the aspects of teaching environment, conditions, quality, satisfaction, and financial capital and then constructs a set of performance evaluation index system for IEE in major colleges and universities. At the same time, this paper analyzes the actual education environment in China and evaluates the IEE in all kinds of colleges and universities by using analytic hierarchy process (AHP). Judging from the assessment results, the current teaching conditions and the quality of teachers in Chinese universities are very good. But the conclusion from the perspective of students is opposite, and the investment ratio of their financial capital is not optimistic. Therefore, this paper puts forward the optimization suggestions.


---

## Body

## 1. Introduction

At present, China's economic development environment has entered a new era that is different from any previous stage. The emphasis on education has also reached a new level and even shoulders the important task of an important engine [1]. In the mid-1990s, China’s major universities gradually launched the research on IEE [2] and make the humanities accomplishment of college students achieve a new leap by gradually cultivating their innovation, entrepreneurship, and practical ability [3–5]. But in recent years for the popularity of IE is still far from enough, it is difficult to deal with the major universities setting a series of innovative talent training objectives [6–8]. The reason for this phenomenon is that there are still many problems in the current IEE in universities, such as the pursuit of short-term achievements while ignoring long-term effects, the unified and rigid supply mode, the single and rigid supply mode, the failure of entrepreneurship education curriculum to integrate into the teaching system, and the shortage of IE practice teaching [9–11].However, domestic colleges and universities are actively studying how to construct a teaching quality monitoring system suitable for their own situation at present [12–14], but there are few theoretical studies and practical explorations on the teaching level monitoring mechanism specifically for IEE [15]. Therefore, it is necessary to construct an IEE evaluation system from the perspective of performance, so as to scientifically evaluate the IEE ability of schools and the entrepreneurial quality of students [16]. It helps really improve students' innovative ability and the key qualities needed for entrepreneurship [17]. And we can provide effective decision-making reference for the government and universities to improve the IEE reform according to the performance evaluation results of IEE [18].Based on the above analysis, this paper analyzes the actual education environment in China and evaluates the implementation performance of IEE projects in Chinese universities, so as to analyze the current actual situation and the parts that need to be improved. It is conducive to providing theoretical basis and practical guidance for optimizing the level of IEE in colleges. There are two main contributions of this paper. On the one hand, this paper designs the performance evaluation target system of IEE in universities from the three aspects of teaching input quality, teaching operation quality, and teaching output quality and confirms the evaluation target. Then the performance evaluation index system of IEE in universities is constructed from five aspects. On the other hand, this paper proposes a comprehensive evaluation method of IEE performance in universities by using analytic hierarchy process (AHP) and puts forward the measures to improve the performance of the government and schools in the future according to the evaluation results.This paper mainly analyzes from the following six aspects. The first part comprehensively analyzes the current domestic and international realistic background and the expected goals of this study. The second part analyzes and summarizes the previous studies. The third part constructs the performance evaluation index system of IEE in colleges and universities from five aspects: teaching environment, teaching condition, financial capital, teaching quality, and teaching satisfaction. The fourth part expounds the reasons for choosing AHP and the process evaluation. The fifth part takes China as an example to empirically test the constructed index system. The sixth part puts forward the IEE performance improvement suggestions according to the research conclusion.


## 2. Related Work

At present, many scholars have realized that the evaluation of IEE is very important. For example, Zhou and Zhou [19] took the quality of IEE as the research content, constructed a complete set of evaluation index system for the quality of IEE of college students, and then evaluated it by using extenics. The index system included the existing educational conditions and channels, reasonable educational curriculum and activities, and the actual results achieved. Finally, taking eight universities as an example, the empirical research was carried out, and the corresponding improvement suggestions were put forward. In addition, Wang et al. [20] also proposed an advanced method to evaluate the quality of IEE in colleges. On the basis of traditional fault tree analysis (FTA), they proposed fuzzy fault tree analysis (FFTA) to evaluate the reliability of IEE for teachers and students. In order to further improve the performance of entrepreneurship education in all kinds of colleges and universities, Mao and Zhang [21] constructed the evaluation index system of IEE in colleges and universities and defined and analyzed various indicators. They also improved the traditional decision tree algorithm and then took several universities as examples to verify the rationality of the index system.When this project is applied to higher vocational colleges, Zhou [22] designed a set of reasonable evaluation system from the aspects of investment proportion, development process, and accurate operation. Then the weight of each was analyzed and compared by AHP. Byun et al. [23] believed that universities not only shoulder the responsibility of traditional education and research, but also need to communicate with the region, so as to make more contributions to social development. Therefore, they established an indicator system for evaluating universities, hoping to improve sustainability by increasing innovative activities with local stakeholders. Gao [24] proposed that the foundation of college students' entrepreneurial success is a good entrepreneurial ecological environment. Based on the above analysis, this paper constructed a set of college students' entrepreneurial ecological environment evaluation index system and used AHP-fuzzy comprehensive evaluation method to evaluate and analyze in Shandong Province. From the results, multiparty cooperation is necessary and plays a decisive role in improving college students' entrepreneurship.


## 3. Design of Performance Evaluation Index System of IEE

### 3.1. Characteristics of the Index System

Based on the research and analysis of previous scholars, this paper conducts a comprehensive analysis from the perspectives of the training objectives of entrepreneurial talents, the practical needs of society, and the domestic and foreign environment, so as to determine the final evaluation goal and then designate a reasonable evaluation and assessment system. The main features are as follows.


#### 3.1.1. Evaluation Content Diversity

There are many contents of innovation and entrepreneurship (IE) assessment, including IE rate of students in colleges, employment rate and entrepreneurship rate of graduates, the quantity and quality of scientific research achievements, guidance of teachers on IE of students, curriculum construction, IE base development, IE project construction, and IE fund investment. Through multiperspective evaluation, the quality of IEE in universities can be fully reflected.


#### 3.1.2. Evaluation Process Persistence

IEE in colleges and universities is a dynamic cycle, progressive, and continuous improvement process. The performance evaluation of IEE aims to monitor and control the whole process and operation results of IEE, so as to form effective feedback and continuously optimize the IEE system. This requires the institutionalization, standardization, and specialization of the performance evaluation process of IEE and the use of scientific methods and modern information technology to promote the sustainable development of the performance evaluation of IEE in all colleges and universities.


#### 3.1.3. Comprehensiveness of Evaluation Objects

In the evaluation process, a comprehensive evaluation is carried out around the following objects, including full-time IE tutors, part-time IE teachers, innovation and entrepreneurship disciplines, IE curriculum and teaching material development, IE of students, and IE project incubation.Therefore, this paper follows the characteristics of the above three innovation and entrepreneurship development evaluation systems and establishes the performance evaluation target system of IEE in all kinds of colleges and universities as shown in Figure1.Figure 1
Performance evaluation target system of IEE in all kinds of colleges and universities.


### 3.2. Index System Establishment

Based on the analysis of previous scholars, this paper has a preliminary understanding of the performance evaluation of IEE in all kinds of colleges and universities. At the same time, it comprehensively considers the AHP and analyzes the correlation between various elements. Finally, according to the specified evaluation objectives and the evaluation of expert professors, the performance evaluation index system of IEE in all kinds of colleges and universities is established (Table1).Table 1
Performance evaluation index system of IEE in all kinds of colleges and universities.
Total indexFirst-level indicatorSecond-level indicatorIEE performanceTeaching environmentIE platform constructionIE information release and publicityQuality, decision-making, and ability of leaderManagement system constructionTeaching conditionNumber of IE disciplinesNumber of IE coursesNumber of IEE practice basesNumber of IE practicesFinancial capitalThe proportion of IEE funds to total teaching fundsAnnual growth rate of investment in IEEThe proportion of students' self-financing in total venture capitalAnnual return on student entrepreneurship projectsTeaching qualityThe proportion of teachers with entrepreneurial experience in all entrepreneurial education teachersThe proportion of teachers with entrepreneurial trainer qualification in all entrepreneurial education teachersThe proportion of off-campus entrepreneurial tutors in all entrepreneurial education teachersNumber of entrepreneurship education teachers conducting entrepreneurship training each yearTeaching satisfactionEntrepreneurial rate of studentsSupport rate of parents for entrepreneurship of studentsEnterprise satisfaction with IE projectsAdoption rate of enterprises of innovative and entrepreneurial projects


## 3.1. Characteristics of the Index System

Based on the research and analysis of previous scholars, this paper conducts a comprehensive analysis from the perspectives of the training objectives of entrepreneurial talents, the practical needs of society, and the domestic and foreign environment, so as to determine the final evaluation goal and then designate a reasonable evaluation and assessment system. The main features are as follows.


### 3.1.1. Evaluation Content Diversity

There are many contents of innovation and entrepreneurship (IE) assessment, including IE rate of students in colleges, employment rate and entrepreneurship rate of graduates, the quantity and quality of scientific research achievements, guidance of teachers on IE of students, curriculum construction, IE base development, IE project construction, and IE fund investment. Through multiperspective evaluation, the quality of IEE in universities can be fully reflected.


### 3.1.2. Evaluation Process Persistence

IEE in colleges and universities is a dynamic cycle, progressive, and continuous improvement process. The performance evaluation of IEE aims to monitor and control the whole process and operation results of IEE, so as to form effective feedback and continuously optimize the IEE system. This requires the institutionalization, standardization, and specialization of the performance evaluation process of IEE and the use of scientific methods and modern information technology to promote the sustainable development of the performance evaluation of IEE in all colleges and universities.


### 3.1.3. Comprehensiveness of Evaluation Objects

In the evaluation process, a comprehensive evaluation is carried out around the following objects, including full-time IE tutors, part-time IE teachers, innovation and entrepreneurship disciplines, IE curriculum and teaching material development, IE of students, and IE project incubation.Therefore, this paper follows the characteristics of the above three innovation and entrepreneurship development evaluation systems and establishes the performance evaluation target system of IEE in all kinds of colleges and universities as shown in Figure1.Figure 1
Performance evaluation target system of IEE in all kinds of colleges and universities.


## 3.1.1. Evaluation Content Diversity

There are many contents of innovation and entrepreneurship (IE) assessment, including IE rate of students in colleges, employment rate and entrepreneurship rate of graduates, the quantity and quality of scientific research achievements, guidance of teachers on IE of students, curriculum construction, IE base development, IE project construction, and IE fund investment. Through multiperspective evaluation, the quality of IEE in universities can be fully reflected.


## 3.1.2. Evaluation Process Persistence

IEE in colleges and universities is a dynamic cycle, progressive, and continuous improvement process. The performance evaluation of IEE aims to monitor and control the whole process and operation results of IEE, so as to form effective feedback and continuously optimize the IEE system. This requires the institutionalization, standardization, and specialization of the performance evaluation process of IEE and the use of scientific methods and modern information technology to promote the sustainable development of the performance evaluation of IEE in all colleges and universities.


## 3.1.3. Comprehensiveness of Evaluation Objects

In the evaluation process, a comprehensive evaluation is carried out around the following objects, including full-time IE tutors, part-time IE teachers, innovation and entrepreneurship disciplines, IE curriculum and teaching material development, IE of students, and IE project incubation.Therefore, this paper follows the characteristics of the above three innovation and entrepreneurship development evaluation systems and establishes the performance evaluation target system of IEE in all kinds of colleges and universities as shown in Figure1.Figure 1
Performance evaluation target system of IEE in all kinds of colleges and universities.


## 3.2. Index System Establishment

Based on the analysis of previous scholars, this paper has a preliminary understanding of the performance evaluation of IEE in all kinds of colleges and universities. At the same time, it comprehensively considers the AHP and analyzes the correlation between various elements. Finally, according to the specified evaluation objectives and the evaluation of expert professors, the performance evaluation index system of IEE in all kinds of colleges and universities is established (Table1).Table 1
Performance evaluation index system of IEE in all kinds of colleges and universities.
Total indexFirst-level indicatorSecond-level indicatorIEE performanceTeaching environmentIE platform constructionIE information release and publicityQuality, decision-making, and ability of leaderManagement system constructionTeaching conditionNumber of IE disciplinesNumber of IE coursesNumber of IEE practice basesNumber of IE practicesFinancial capitalThe proportion of IEE funds to total teaching fundsAnnual growth rate of investment in IEEThe proportion of students' self-financing in total venture capitalAnnual return on student entrepreneurship projectsTeaching qualityThe proportion of teachers with entrepreneurial experience in all entrepreneurial education teachersThe proportion of teachers with entrepreneurial trainer qualification in all entrepreneurial education teachersThe proportion of off-campus entrepreneurial tutors in all entrepreneurial education teachersNumber of entrepreneurship education teachers conducting entrepreneurship training each yearTeaching satisfactionEntrepreneurial rate of studentsSupport rate of parents for entrepreneurship of studentsEnterprise satisfaction with IE projectsAdoption rate of enterprises of innovative and entrepreneurial projects


## 4. Performance Evaluation of IEE

### 4.1. Research Method Selection

Analytic Hierarchy Process (AHP): The various factors that affect decision-making are decomposed, and qualitative and quantitative research and analysis are carried out from the dimensions of objectives, criteria, and schemes to make decisions. This method is mainly applicable to the decision-making of projects with problems on criteria or without structure. Firstly, AHP will decompose complex problems according to different levels and different factors. Secondly, it compares the importance of indicators and then establishes a judgment matrix to calculateλ and corresponding feature vectors. Finally, it will calculate their importance [25]. The index system studied in this paper has a relatively clear hierarchical structure, but the index system is relatively complex. Therefore, after comprehensive consideration, AHP is selected to study the subject, and the proportion of each index is calculated based on the established system, and the targeted suggestions are put forward by experts.


### 4.2. Evaluation Process

#### 4.2.1. Construct Judgment Matrix

In the AHP, the matrix judgment scale is used to make the elements in the matrix quantitatively show their importance. Judgment matrix refers to the degree of importance obtained by comparing different factors with correlation between the two adjacent levels [26]. In the past, there are some subjective factors in the construction of the matrix, which greatly reduces the authenticity of the performance evaluation results. In order to ensure the objectivity of judgment, this paper takes 1–9 as a scale. Then we compare and empower the first-level index and the second-level index on the basis of consulting experts. Assuming that the comparison score between indicator X and indicator Y is α, the comparison score between indicator Y and indicator X is 1/α. Table 2 shows the definition diagram of judgment matrix.Table 2
Definition diagram of judgment matrix.
Comparison of importance between two elementsWeightX and Y are equally important1X is a little more important than Y3X is clearly more important than Y5X is very more important than Y7X is extremely more important than Y9Intermediate value of two adjacent judgments2, 4, 6, 8


#### 4.2.2. Calculate Weight Vector

Firstly, the eigenvector and the maximum eigenvalue of matrix A are defined, which are substituted into formula (1), and finally the weight vector is obtained by normalization.(1)A⋅W=λmax⋅W.In the formula,A is the original judgment matrix, W is the weight, and λmax is the maximum feature vector.


#### 4.2.3. Consistency Test of Judgment Matrix

When carrying out the analytic hierarchy process, it is necessary to analyze the consistency of the matrix and understand the specific value of the maximum feature root, so that the judgment matrix is logically reasonable. The steps for consistency checking are as follows:(2)CI=λmax−nn−1,CR=CIRI.In the formula,n denotes the order of the judgment matrix. CI is the consistency index. CR is the consistency ratio. RI is a random index introduced in the formula. The specific value of RI comes from the average value calculated by judging the consistency of the matrix in random sampling, as shown in Figure 2.Figure 2
Random consistency index.In the process of judgment, when CR < 0.1, the consistency of judgment matrix is acceptable. When CR > 0.1, it is considered that the judgment matrix does not meet the consistency requirement and needs to correct the judgment matrix.


#### 4.2.4. Calculate Weight

According to formula (3) and expert scoring results, final weights of indicators are calculated.(3)W=WiWij.In the formula,W is the total weight of the index, Wi is the first-level index weight, and Wij is the second-level index weight.In summary, the university IEE performance evaluation process is shown in Figure3.Figure 3
Performance evaluation flowchart of IEE in all kinds of colleges and universities.


## 4.1. Research Method Selection

Analytic Hierarchy Process (AHP): The various factors that affect decision-making are decomposed, and qualitative and quantitative research and analysis are carried out from the dimensions of objectives, criteria, and schemes to make decisions. This method is mainly applicable to the decision-making of projects with problems on criteria or without structure. Firstly, AHP will decompose complex problems according to different levels and different factors. Secondly, it compares the importance of indicators and then establishes a judgment matrix to calculateλ and corresponding feature vectors. Finally, it will calculate their importance [25]. The index system studied in this paper has a relatively clear hierarchical structure, but the index system is relatively complex. Therefore, after comprehensive consideration, AHP is selected to study the subject, and the proportion of each index is calculated based on the established system, and the targeted suggestions are put forward by experts.


## 4.2. Evaluation Process

### 4.2.1. Construct Judgment Matrix

In the AHP, the matrix judgment scale is used to make the elements in the matrix quantitatively show their importance. Judgment matrix refers to the degree of importance obtained by comparing different factors with correlation between the two adjacent levels [26]. In the past, there are some subjective factors in the construction of the matrix, which greatly reduces the authenticity of the performance evaluation results. In order to ensure the objectivity of judgment, this paper takes 1–9 as a scale. Then we compare and empower the first-level index and the second-level index on the basis of consulting experts. Assuming that the comparison score between indicator X and indicator Y is α, the comparison score between indicator Y and indicator X is 1/α. Table 2 shows the definition diagram of judgment matrix.Table 2
Definition diagram of judgment matrix.
Comparison of importance between two elementsWeightX and Y are equally important1X is a little more important than Y3X is clearly more important than Y5X is very more important than Y7X is extremely more important than Y9Intermediate value of two adjacent judgments2, 4, 6, 8


### 4.2.2. Calculate Weight Vector

Firstly, the eigenvector and the maximum eigenvalue of matrix A are defined, which are substituted into formula (1), and finally the weight vector is obtained by normalization.(1)A⋅W=λmax⋅W.In the formula,A is the original judgment matrix, W is the weight, and λmax is the maximum feature vector.


### 4.2.3. Consistency Test of Judgment Matrix

When carrying out the analytic hierarchy process, it is necessary to analyze the consistency of the matrix and understand the specific value of the maximum feature root, so that the judgment matrix is logically reasonable. The steps for consistency checking are as follows:(2)CI=λmax−nn−1,CR=CIRI.In the formula,n denotes the order of the judgment matrix. CI is the consistency index. CR is the consistency ratio. RI is a random index introduced in the formula. The specific value of RI comes from the average value calculated by judging the consistency of the matrix in random sampling, as shown in Figure 2.Figure 2
Random consistency index.In the process of judgment, when CR < 0.1, the consistency of judgment matrix is acceptable. When CR > 0.1, it is considered that the judgment matrix does not meet the consistency requirement and needs to correct the judgment matrix.


### 4.2.4. Calculate Weight

According to formula (3) and expert scoring results, final weights of indicators are calculated.(3)W=WiWij.In the formula,W is the total weight of the index, Wi is the first-level index weight, and Wij is the second-level index weight.In summary, the university IEE performance evaluation process is shown in Figure3.Figure 3
Performance evaluation flowchart of IEE in all kinds of colleges and universities.


## 4.2.1. Construct Judgment Matrix

In the AHP, the matrix judgment scale is used to make the elements in the matrix quantitatively show their importance. Judgment matrix refers to the degree of importance obtained by comparing different factors with correlation between the two adjacent levels [26]. In the past, there are some subjective factors in the construction of the matrix, which greatly reduces the authenticity of the performance evaluation results. In order to ensure the objectivity of judgment, this paper takes 1–9 as a scale. Then we compare and empower the first-level index and the second-level index on the basis of consulting experts. Assuming that the comparison score between indicator X and indicator Y is α, the comparison score between indicator Y and indicator X is 1/α. Table 2 shows the definition diagram of judgment matrix.Table 2
Definition diagram of judgment matrix.
Comparison of importance between two elementsWeightX and Y are equally important1X is a little more important than Y3X is clearly more important than Y5X is very more important than Y7X is extremely more important than Y9Intermediate value of two adjacent judgments2, 4, 6, 8


## 4.2.2. Calculate Weight Vector

Firstly, the eigenvector and the maximum eigenvalue of matrix A are defined, which are substituted into formula (1), and finally the weight vector is obtained by normalization.(1)A⋅W=λmax⋅W.In the formula,A is the original judgment matrix, W is the weight, and λmax is the maximum feature vector.


## 4.2.3. Consistency Test of Judgment Matrix

When carrying out the analytic hierarchy process, it is necessary to analyze the consistency of the matrix and understand the specific value of the maximum feature root, so that the judgment matrix is logically reasonable. The steps for consistency checking are as follows:(2)CI=λmax−nn−1,CR=CIRI.In the formula,n denotes the order of the judgment matrix. CI is the consistency index. CR is the consistency ratio. RI is a random index introduced in the formula. The specific value of RI comes from the average value calculated by judging the consistency of the matrix in random sampling, as shown in Figure 2.Figure 2
Random consistency index.In the process of judgment, when CR < 0.1, the consistency of judgment matrix is acceptable. When CR > 0.1, it is considered that the judgment matrix does not meet the consistency requirement and needs to correct the judgment matrix.


## 4.2.4. Calculate Weight

According to formula (3) and expert scoring results, final weights of indicators are calculated.(3)W=WiWij.In the formula,W is the total weight of the index, Wi is the first-level index weight, and Wij is the second-level index weight.In summary, the university IEE performance evaluation process is shown in Figure3.Figure 3
Performance evaluation flowchart of IEE in all kinds of colleges and universities.


## 5. Example Analysis

### 5.1. Determination of Index Weight

#### 5.1.1. Construct Hierarchical Model

According to the hierarchical model and data collection results, as well as the specific conditions of the five evaluation indexes of teaching environment, teaching condition, financial capital, teaching quality, and teaching satisfaction, the first-level indicators are set asR=R1,R2,R3,R4,R5. The second-level indicators are set as R1=R11,R12,R13,R14, R2=R21,R22,R23,R24, R3=R31,R32,R33,R34, R4=R41,R42,R43,R44, R5=R51,R52,R53,R54.


#### 5.1.2. Construct Judgment Matrix

The experts and professors construct judgment matrix based on index score, so as to calculate the weight of evaluation indicators. Then according to the results of matrix operation, we obtain the feature vector and feature root and finally calculate the index weight. Accordingly, the index weights of the first level areW=W1,W2,W3,W4,W5 and ∑Wi=1.


#### 5.1.3. Consistency Test and Weight Calculation

In order to ensure the true reliability of the data source of the judgment matrix, we issued a quantitative indicator table to five experts and 100 college students. On the basis of explaining the filling method in detail, all the respondents filled out the questionnaire seriously and practically, of which 87 were valid. The experts filled in the questionnaire based on their own practical experience, and the students filled in the questionnaire according to their own learning experience and harvest. Finally, we get the judgment matrix by analyzing the questionnaire data and making effective trade-offs based on Delphi method (Tables3–8).Table 3
Weight of the first-level indicators.
UR1R2R3R4R5WiR111/441/220.161R2417260.415R31/41/711/71/20.042R421/27140.301R51/21/621/410.081Total1(4)λmax=5.134,CI=0.033, CR=0.030.Table 4
Weight of teaching environment in second-level indicators.
R1R11R12R13R14WiR1111/61/21/50.067R1261420.465R1321/411/30.128R1451/2310.340Total1(5)λmax=4.066,CI=0.022, CR=0.024.Table 5
Weight of teaching condition in second-level indicators.
R1R21R22R23R24WiR2111/3250.279R2231570.536R231/21/5120.124R241/51/71/210.062Total1(6)λmax=4.099,CI=0.033, CR=0.037.Table 6
Weight of financial capital in second-level indicators.
R1R31R32R33R34WiR3113560.521R321/31340.290R331/51/3120.123R341/61/41/210.067Total1(7)λmax=4.162,CI=0.054, CR=0.060.Table 7
Weight of teaching quality in second-level indicators.
R1R41R42R43R44WiR4111/51/220.132R4251360.537R4321/3140.262R441/21/61/410.069Total1(8)λmax=4.102,CI=0.034, CR=0.038.Table 8
Weight of teaching satisfaction in second-level indicators.
R1R51R52R53R54WiR5116250.501R521/611/41/20.069R531/24130.304R541/521/310.126Total1(9)λmax=4.059,CI=0.020, CR=0.022.


## 5.1. Determination of Index Weight

### 5.1.1. Construct Hierarchical Model

According to the hierarchical model and data collection results, as well as the specific conditions of the five evaluation indexes of teaching environment, teaching condition, financial capital, teaching quality, and teaching satisfaction, the first-level indicators are set asR=R1,R2,R3,R4,R5. The second-level indicators are set as R1=R11,R12,R13,R14, R2=R21,R22,R23,R24, R3=R31,R32,R33,R34, R4=R41,R42,R43,R44, R5=R51,R52,R53,R54.


### 5.1.2. Construct Judgment Matrix

The experts and professors construct judgment matrix based on index score, so as to calculate the weight of evaluation indicators. Then according to the results of matrix operation, we obtain the feature vector and feature root and finally calculate the index weight. Accordingly, the index weights of the first level areW=W1,W2,W3,W4,W5 and ∑Wi=1.


### 5.1.3. Consistency Test and Weight Calculation

In order to ensure the true reliability of the data source of the judgment matrix, we issued a quantitative indicator table to five experts and 100 college students. On the basis of explaining the filling method in detail, all the respondents filled out the questionnaire seriously and practically, of which 87 were valid. The experts filled in the questionnaire based on their own practical experience, and the students filled in the questionnaire according to their own learning experience and harvest. Finally, we get the judgment matrix by analyzing the questionnaire data and making effective trade-offs based on Delphi method (Tables3–8).Table 3
Weight of the first-level indicators.
UR1R2R3R4R5WiR111/441/220.161R2417260.415R31/41/711/71/20.042R421/27140.301R51/21/621/410.081Total1(4)λmax=5.134,CI=0.033, CR=0.030.Table 4
Weight of teaching environment in second-level indicators.
R1R11R12R13R14WiR1111/61/21/50.067R1261420.465R1321/411/30.128R1451/2310.340Total1(5)λmax=4.066,CI=0.022, CR=0.024.Table 5
Weight of teaching condition in second-level indicators.
R1R21R22R23R24WiR2111/3250.279R2231570.536R231/21/5120.124R241/51/71/210.062Total1(6)λmax=4.099,CI=0.033, CR=0.037.Table 6
Weight of financial capital in second-level indicators.
R1R31R32R33R34WiR3113560.521R321/31340.290R331/51/3120.123R341/61/41/210.067Total1(7)λmax=4.162,CI=0.054, CR=0.060.Table 7
Weight of teaching quality in second-level indicators.
R1R41R42R43R44WiR4111/51/220.132R4251360.537R4321/3140.262R441/21/61/410.069Total1(8)λmax=4.102,CI=0.034, CR=0.038.Table 8
Weight of teaching satisfaction in second-level indicators.
R1R51R52R53R54WiR5116250.501R521/611/41/20.069R531/24130.304R541/521/310.126Total1(9)λmax=4.059,CI=0.020, CR=0.022.


## 5.1.1. Construct Hierarchical Model

According to the hierarchical model and data collection results, as well as the specific conditions of the five evaluation indexes of teaching environment, teaching condition, financial capital, teaching quality, and teaching satisfaction, the first-level indicators are set asR=R1,R2,R3,R4,R5. The second-level indicators are set as R1=R11,R12,R13,R14, R2=R21,R22,R23,R24, R3=R31,R32,R33,R34, R4=R41,R42,R43,R44, R5=R51,R52,R53,R54.


## 5.1.2. Construct Judgment Matrix

The experts and professors construct judgment matrix based on index score, so as to calculate the weight of evaluation indicators. Then according to the results of matrix operation, we obtain the feature vector and feature root and finally calculate the index weight. Accordingly, the index weights of the first level areW=W1,W2,W3,W4,W5 and ∑Wi=1.


## 5.1.3. Consistency Test and Weight Calculation

In order to ensure the true reliability of the data source of the judgment matrix, we issued a quantitative indicator table to five experts and 100 college students. On the basis of explaining the filling method in detail, all the respondents filled out the questionnaire seriously and practically, of which 87 were valid. The experts filled in the questionnaire based on their own practical experience, and the students filled in the questionnaire according to their own learning experience and harvest. Finally, we get the judgment matrix by analyzing the questionnaire data and making effective trade-offs based on Delphi method (Tables3–8).Table 3
Weight of the first-level indicators.
UR1R2R3R4R5WiR111/441/220.161R2417260.415R31/41/711/71/20.042R421/27140.301R51/21/621/410.081Total1(4)λmax=5.134,CI=0.033, CR=0.030.Table 4
Weight of teaching environment in second-level indicators.
R1R11R12R13R14WiR1111/61/21/50.067R1261420.465R1321/411/30.128R1451/2310.340Total1(5)λmax=4.066,CI=0.022, CR=0.024.Table 5
Weight of teaching condition in second-level indicators.
R1R21R22R23R24WiR2111/3250.279R2231570.536R231/21/5120.124R241/51/71/210.062Total1(6)λmax=4.099,CI=0.033, CR=0.037.Table 6
Weight of financial capital in second-level indicators.
R1R31R32R33R34WiR3113560.521R321/31340.290R331/51/3120.123R341/61/41/210.067Total1(7)λmax=4.162,CI=0.054, CR=0.060.Table 7
Weight of teaching quality in second-level indicators.
R1R41R42R43R44WiR4111/51/220.132R4251360.537R4321/3140.262R441/21/61/410.069Total1(8)λmax=4.102,CI=0.034, CR=0.038.Table 8
Weight of teaching satisfaction in second-level indicators.
R1R51R52R53R54WiR5116250.501R521/611/41/20.069R531/24130.304R541/521/310.126Total1(9)λmax=4.059,CI=0.020, CR=0.022.


## 6. Results and Discussion

Through the above calculation results, it is not difficult to see that the judgment matrix CR given by experts is less than 0.1; that is, the results are effective by calculating the matrix, and the index weight is as Table9. From the overall analysis of the performance of IEE in all kinds of colleges and universities, we find that the evaluation value of IEE performance indicators is high, indicating that the overall IEE in the school is in good condition and has long-term stable development ability.Table 9
Performance evaluation indicator weight of IEE.
First-level indicatorWeightSecond-level indicatorWeightTotal weightB10.161C10.0670.011C20.4650.075C30.1280.021C40.3400.055B20.415C50.2790.116C60.5360.222C70.1240.051C80.0620.026B30.042C90.5210.022C100.2900.012C110.1230.005C120.0670.003B40.301C130.1320.040C140.5370.161C150.2620.079C160.0690.021B50.081C170.5010.041C180.0690.006C190.3040.025C200.1260.010It can be seen from Table9 that teaching condition and quality account for 72.5% in the first-level indicators, which is good in the performance evaluation of IEE in universities. However, the teaching environment, financial capital, and teaching satisfaction are poor in the performance evaluation of IEE in universities, especially the financial funds, which is only 0.035. It shows that the key to improve the level of IEE in all kinds of colleges and universities is to improve the teaching environment, increase financial investment, and improve social satisfaction with IE teaching.Figure4 can be drawn by calculating and sorting the proportion of each secondary index. It can be seen from the chart that the number of IE courses accounts for the highest proportion, followed by the number of IE disciplines and the proportion of teachers with entrepreneurship training qualification to all entrepreneurship education teachers. However, the support rate of parents for entrepreneurship of students and the proportion of students' self-financing in total venture capital are relatively weak; in particular the weight of the annual return on student entrepreneurship projects is only 0.003. It shows that, in the development process of IEE in all kinds of colleges and universities, more attention is paid to teaching conditions and teachers, and the importance of capital investment and teaching feedback needs to be improved.Figure 4
Total ranking of indicator weights of IEE performance evaluation.


## 7. Conclusions and Suggestions

At present, the country vigorously promotes innovation in major industries including education, and the evaluation requirements of its innovation performance are more stringent. However, the existing performance evaluation of IEE in all kinds of colleges and universities generally lacks objectivity, which has great limitations. Therefore, based on the connotation of IEE, this study establishes the performance evaluation system of IEE in all kinds of colleges and universities. Then this paper uses the advanced AHP to determine the index weight and takes China as an example to verify the rationality of the index system. The evaluation results show that the teaching environment, financial capital, and teaching satisfaction are the key factors to improve the level of IEE in all kinds of colleges and universities in the future. However, the development level of IEE in universities is not high, and the support rate of parents and enterprises for students' entrepreneurship is low. And the annual return rate of students' entrepreneurial projects is far from enough. It shows that the road of IEE in major colleges and universities has a long way to go.In the future, the evaluation index system for the performance of IEE in all kinds of colleges and universities can be constructed from more aspects, and the combination weight can be determined by the weight calculation method combining qualitative and quantitative methods, so as to evaluate the performance of IEE in all kinds of colleges and universities more scientifically.According to the theory of performance management, performance improvement should be carried out according to the actual situation after performance evaluation. Therefore, based on the evaluation and analysis of the performance of IEE in all kinds of colleges and universities, this paper puts forward suggestions to promote the project to be truly implemented from the theoretical level to the practical application. Specifically, the level of IEE can be improved from the following three aspects.


### 7.1. Building a Multichannel IEE Platform

The factors affecting students’ learning effect are multilevel and multiangle. The adaptability of teaching methods and the integrity of teaching platform play a fundamental role in students' learning effect. However, the construction of IEE platform is insufficient, and there is still room for improvement and optimization. In view of this, the IEE platform can be optimized from the following two aspects in the future. First, under the existing resources of colleges and universities, schools can use new media technology to combine modern teaching methods with traditional education contents and methods to build a curriculum system that is more closely related to entrepreneurial practice. When developing students' innovation and entrepreneurship, we invite elites in various fields or authoritative experts in corresponding fields to share in order to achieve the desired results. Second, it is conducive to promoting close communication among many universities by using the Internet to build a national entrepreneurship education platform. The current Internet has been rapidly popularized. We make full use of this platform to develop application software and share high-quality video courses in major universities to students. It can not only realize students’ fragmented learning of IE knowledge, but also realize the general education of IE.


### 7.2. Encouraging and Supporting Policies for Entrepreneurship of College Students

At present, the supporting mechanism for university entrepreneurship is not perfect. For this situation, the government should formulate policies according to the results of the investigation and study and increase the project support of college students' IE, so as to stimulate the enthusiasm of college students’ IE. At the same time, universities should actively cooperate with the government. Specifically, governments and schools can improve the supporting capacity of safeguards from the following three aspects. First, the government’s policies are cleverly combined with the current thriving new media to promote policy popularity, so as to improve the success rate of the implementation of IEE projects in all kinds of colleges and universities. Second, the government should pay more attention to the stimulation of college students' enthusiasm for IE and the support of projects, rather than staying in the theoretical teaching. It should enable entrepreneurial students to obtain practical benefits, such as tax deductions, loan guarantees, guiding services, and subsidies for corresponding start-up funds. In addition, certain financial rewards should be given to enterprises that have achieved certain success. Third, universities should take the initiative to strengthen the contact and docking with relevant government departments, including education, industry and commerce, tax, labor and employment departments. At the same time, universities should also strengthen ties with regional IEE institutions.


### 7.3. Increasing Resources Investment to Improve the Quality of IEE Projects

There are many factors affecting the implementation of IEE projects in all kinds of colleges and universities. The construction of curriculum system and the ability of teachers play a key role. Therefore, educational authorities at all levels and universities should increase investment in resources. On the one hand, universities should invite teachers with rich internal experience or practical business experience of enterprises and professional forces from professional training institutions, so as to systematically discuss the training scheme, curriculum design, teaching content design, teaching material compilation, and teaching form. At the same time, major colleges and universities should strengthen the investigation and communication of students by listening to students’ voice. It is beneficial to promote the goal of education project formulation and the curriculum content is also the condition of students’ actual needs. On the other hand, universities should provide more opportunities for full-time teachers to participate in professional practice in off-campus institutions, so that more teachers can truly participate in the whole process of enterprise operation. And universities can encourage teachers to participate in the entrepreneurial practice of enterprises, so that they can understand the actual needs of students and improve the performance of education projects.


## 7.1. Building a Multichannel IEE Platform

The factors affecting students’ learning effect are multilevel and multiangle. The adaptability of teaching methods and the integrity of teaching platform play a fundamental role in students' learning effect. However, the construction of IEE platform is insufficient, and there is still room for improvement and optimization. In view of this, the IEE platform can be optimized from the following two aspects in the future. First, under the existing resources of colleges and universities, schools can use new media technology to combine modern teaching methods with traditional education contents and methods to build a curriculum system that is more closely related to entrepreneurial practice. When developing students' innovation and entrepreneurship, we invite elites in various fields or authoritative experts in corresponding fields to share in order to achieve the desired results. Second, it is conducive to promoting close communication among many universities by using the Internet to build a national entrepreneurship education platform. The current Internet has been rapidly popularized. We make full use of this platform to develop application software and share high-quality video courses in major universities to students. It can not only realize students’ fragmented learning of IE knowledge, but also realize the general education of IE.


## 7.2. Encouraging and Supporting Policies for Entrepreneurship of College Students

At present, the supporting mechanism for university entrepreneurship is not perfect. For this situation, the government should formulate policies according to the results of the investigation and study and increase the project support of college students' IE, so as to stimulate the enthusiasm of college students’ IE. At the same time, universities should actively cooperate with the government. Specifically, governments and schools can improve the supporting capacity of safeguards from the following three aspects. First, the government’s policies are cleverly combined with the current thriving new media to promote policy popularity, so as to improve the success rate of the implementation of IEE projects in all kinds of colleges and universities. Second, the government should pay more attention to the stimulation of college students' enthusiasm for IE and the support of projects, rather than staying in the theoretical teaching. It should enable entrepreneurial students to obtain practical benefits, such as tax deductions, loan guarantees, guiding services, and subsidies for corresponding start-up funds. In addition, certain financial rewards should be given to enterprises that have achieved certain success. Third, universities should take the initiative to strengthen the contact and docking with relevant government departments, including education, industry and commerce, tax, labor and employment departments. At the same time, universities should also strengthen ties with regional IEE institutions.


## 7.3. Increasing Resources Investment to Improve the Quality of IEE Projects

There are many factors affecting the implementation of IEE projects in all kinds of colleges and universities. The construction of curriculum system and the ability of teachers play a key role. Therefore, educational authorities at all levels and universities should increase investment in resources. On the one hand, universities should invite teachers with rich internal experience or practical business experience of enterprises and professional forces from professional training institutions, so as to systematically discuss the training scheme, curriculum design, teaching content design, teaching material compilation, and teaching form. At the same time, major colleges and universities should strengthen the investigation and communication of students by listening to students’ voice. It is beneficial to promote the goal of education project formulation and the curriculum content is also the condition of students’ actual needs. On the other hand, universities should provide more opportunities for full-time teachers to participate in professional practice in off-campus institutions, so that more teachers can truly participate in the whole process of enterprise operation. And universities can encourage teachers to participate in the entrepreneurial practice of enterprises, so that they can understand the actual needs of students and improve the performance of education projects.



---

*Source: 4616501-2022-05-04.xml*