Statistical modelling and quantitative assessment of management reforms in higher education on the enhancement of student employability

Employability of university students is a comprehensive ability, which refers to the ability to get a job and keep it, as well as the ability to develop it further [1-2]. According to the nature of employability, it can be categorized into three types: basic ability, adaptive ability and transformational ability. Basic ability refers to the basic knowledge and skills of work-related specialties acquired by college students during their school years [3-5]. Adaptive ability refers to the ability of college students to express, communicate, coordinate, logic and interpersonal interaction in work practice. Adaptive ability refers to the comprehensive ability of college students to exert their subjective initiative and make use of their analytical decision-making ability, organizational and management ability, innovation ability, etc. to improve their working skills and working methods. Enhancing the employability of college students is an important task of college education [6-9].

In recent years, with the changes of domestic and foreign economic situation and the continuous expansion of higher education institutions, the problem of difficult employment of college students has become more and more prominent [10]. To solve the employment problems of college graduates, for institutions of higher learning, we must update the concept of running schools, we must take students’ employment as the center, deepen the reform of teaching management in colleges and universities: First, we should start from the employment market demand, improve the rationality of the professional and curriculum settings [11-13]. Secondly, we should emphasize the reform of teaching methods and teaching methods, and strive to cultivate the employment ability of college students. Third, we should strengthen the entrepreneurship education of college students and change the concept of employment. Fourthly, we should set up student employment guidance centers to provide students with employment services. Fifth, it is necessary to establish the linkage mechanism among schools, governments, enterprises and students to ensure the long-term effectiveness of college students’ employment [14-17].

Literature [18] emphasizes that in recent years the employability of students in higher education has been constrained by excessive theories. The results of the pilot experience carried out by a university in a joint program of law and business administration, which was aimed at improving the employability of students by remedying the inadequacy of teaching, were demonstrated. Literature [19] specifies that students show a sense of powerlessness in front of the complex and changing labor market. In order to help graduates to overcome the difficulties of employment, solutions are proposed based on the problems faced by universities, such as funding and building capacity. Literature [20], by analyzing as well as comparing multiple employment strategies, found that governance reforms are likely to achieve good expected results because the stakeholders of interest support only a subset of the strategies. Literature [21] used a literature review to develop a study that provides a reference for graduate employment by reviewing the context of the era of mass education and comparing graduates from different periods of time as well as the impact of policy reforms on graduate employment in order to improve their employability. Literature [22] aims to examine the management of college students guided by employability. It points out the deficiencies in student management in current universities and puts forward college student management strategies to promote employment, so as to improve students’ employability and prompt them to better meet the needs of social enterprises for talents. Literature [23] aims to address the issue of employability of Vietnamese graduates by comparing it with developed countries to draw differences. The comparative analysis points out that there is a lack of connection between traditional teaching methods and industrial development in Vietnam, a drawback that prevents students from learning skills and knowledge better. Literature [24] exposed the mismatch between the government’s employability agreement and employment and concluded that graduates were too focused on being employable to meet employers’ requirements, which also showed that graduates were not prepared for employment. Literature [25] explored the attribution of responsibility for students’ employability and measures to improve employability. A survey of students revealed that the attribution of responsibility for employability was seen as a tool for the development of students’ and schools’ employment. In addition, students not only assumed responsibility for their employment, but also continued to work to gain positional advantage in the workplace. Literature [26] reveals the mismatch between the talent development model of universities and the social labor market. Evidence of graduate employment is explored by analyzing the available information, emphasizing the importance of employability in the job market, and providing references for promoting graduate employment. Literature [27] mentions that the solution to students’ employment difficulties lies in improving their employability. A regression analysis of a valid sample from a university yielded the factors that hinder the improvement of students’ employability. The results showed that the students on the ability is affected by many factors, the most important factors are the curriculum teaching and club activities. Literature [28] analyzed and elucidated employability in a higher education environment conceptualized with academic goals by utilizing a multidimensional analysis of employability practices in higher education. The results found that embedding entrepreneurship can effectively drive innovation in teaching and learning in the discipline.

Based on quantitative analysis methods such as Pearson’s correlation coefficient, multiple linear regression and t-test, this paper designs and evaluates the management reform path of colleges and universities oriented to the improvement of students’ employability. Using the questionnaire survey and statistical analysis methods, six dimensions of students’ employability, namely, general vocational skills, core qualities, vocational personality, vocational development potential, leadership qualities and team qualities, as well as eight dimensions of employability influencing factors, namely, goal strategy, professional setting, evaluation and incentive, campus culture, school-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning, are extracted. Taking the dimensions of students’ employability as the dependent variable and the dimensions of factors influencing employability as the independent variable, multiple linear regression was carried out to obtain the influence mechanism between the two, so as to design the path of management reform in colleges and universities in a targeted way, and the t-test was used to confirm the validity of the path.

2

Statistical and quantitative assessment model based on the enhancement of students’ employability

In order to assess the effect of college management reform on the improvement of students’ employability, this paper uses multiple regression analysis to conclude that the factors affecting the improvement of college students’ employability in colleges and universities cover the whole process of talent cultivation, and based on this, it designs the path of college management reform based on the orientation of employability, and finally analyzes the application effect of the path by using the t-test.

2.1

Pearson’s correlation coefficient

Correlation analysis is a statistical analysis method to study the linear relationship between random variables, such as the commonly used Pearson correlation coefficient method [29]. The Pearson correlation coefficient between random variables X and Y is: (1) $r = \frac{\sum_{i = 1}^{n} (x_{i} - \bar{x}) (y_{i} - \bar{y})}{\sqrt{\sum_{i = 1}^{n} {(x_{i} - \bar{x})}^{2}} \cdot \sqrt{\sum_{i = 1}^{n} {(y_{i} - \bar{y})}^{2}}}$

Where: x₁, x₂, ⋯, x_n is the n observations of the random variable X. y₁, y₂, ⋯, y_n is the n observations of the random variable Y. $\bar{x} = \frac{1}{n} \sum_{i = 1}^{n} x_{i}$ and $\bar{y} = \frac{1}{n} \sum_{i = 1}^{n} y_{i}$ denote the sample means.

2.2

Multiple linear regression

When there is a linear correlation between the explanatory variable y and the explanatory variable x₁, x₂, ⋯, x_q, y can be expressed as a linear combination of x₁, x₂, ⋯, x_q s, i.e., a multiple linear regression model [30]. Its general form is: (2) $y_{k} = α_{0} + α_{1} x_{k 1} + α_{2} x_{k 2} + \dots + α_{q} x_{k q} + β_{k}, k = 1, 2, \dots, n$

where x_k1, x_k2, …, x_kq is the observed data of the kth sample. α₀, α₁, α₂, ⋯, α_q is the parameter to be estimated, and the error term β_k is an independently and identically distributed random variable with zero mean and finite variance.

Order: (3) $Y = {(y_{1}, y_{2}, \dots, y_{n})}^{T}$ (4) $X = (\begin{matrix} 1 & x_{11} & \dots & x_{1 q} \\ 1 & x_{21} & \dots & x_{2 q} \\ ⋮ & ⋮ & ⋱ & ⋮ \\ 1 & x_{n 1} & \dots & x_{n q} \end{matrix})$ (5) $β = {(β_{1}, β_{2}, \dots, β_{n})}^{T}$ (6) $α = {(α_{0}, α_{1}, \dots, α_{q})}^{T}$

Then equation (2) can be rewritten in the form of a matrix equation: (7) $Y = X α + β$

Then equation (2) can be rewritten as a matrix equation Multiple linear regression model parameters can be estimated using least squares to take the value, but the point estimate can not reflect the closeness between the estimated value and the true value, usually using t statistics to calculate the parameter at a certain confidence level of confidence intervals (confidence level is generally set to 0.95). The form of the

2.3

Variance inflation factors

If the correlation between explanatory variables is strong, multicollinearity can easily exist. Variance inflation factor (VIF) is a common method to test for multicollinearity between variables [31]. For the q explanatory variables, one of them is sequentially selected as the dependent variable and the remaining q − 1 ones are regressed as independent variables to obtain the goodness of fit $R_{i}^{2} (1 \leq i \leq q)$ , then the variance inflation factor can be calculated by equation (8): (8) $V_{i} = \frac{1}{1 - R_{i}^{2}}$

When 0 < V_i ≤ 5, no multicollinearity is considered to exist. When 5 < V_i ≤ 10, there is weak multicollinearity. When 10 < V_i ≤ 100, there is strong multicollinearity. When V_i > 100, there is severe multicollinearity.

2.4

t-test

A t-test compares the significance of the difference between two means by inferring the probability of the difference occurring using the theory of t-distribution. t-tests are categorized into single overall test and double overall test. In this case, the two-sample t-test tests the significance of the difference between two sample means and the totals they each represent. The double overall t-test is further categorized into two cases, one is the independent samples t-test and the other is the (related samples) paired samples t-test [32].

The independent samples t test statistic is: (9) $t = \frac{{\bar{x}}_{1} - {\bar{x}}_{2}}{\sqrt{\frac{(n_{1} - 1) s_{1}^{2} + (n_{2} - 1) s_{2}^{2}}{n_{1} + n_{2} - 2} (\frac{1}{n_{1}} + \frac{1}{n_{2}})}} = \frac{{\bar{x}}_{1} - {\bar{x}}_{2}}{\sqrt{s^{2} (\frac{1}{n_{1}} + \frac{1}{n_{2}})}}$

Where: ${\bar{x}}_{1}$ , ${\bar{x}}_{2}$ is the mean of the two samples. s₁, s₂ is the standard deviation of the two samples. s₂ is the confluence variance of the two samples, i.e.: (10) $s^{2} = \frac{\sum x_{1}^{2} - {(\sum x_{1})}^{2} / n_{1} + \sum x_{2}^{2} - {(\sum x_{2})}^{2} / n_{2}}{n_{1} + n_{2} - 2}$ (11) $d f = n_{1} + n_{2} - 2$

The paired-sample t test statistic is: (12) $t = \frac{{\bar{x}}_{1} - {\bar{x}}_{2}}{\sqrt{\frac{s_{1}^{2} + s_{2} - 2 r s_{1} s_{2}}{n}}} = \frac{{\bar{x}}_{1} - {\bar{x}}_{2}}{\sqrt{\frac{\sum D^{2} - {(\sum D)}^{2} / n}{n (n - 1)}}}$

Where: ${\bar{x}}_{1}$ , ${\bar{x}}_{2}$ is the mean of the two samples. s₁, s₂ is the standard deviation of the two samples. r is the correlation coefficient of the paired samples D. is the number of data differences i.e., D = x₁ − x₂. df = n − 1.

Double Overall (σ₁, σ₂ Unknown, n ≤ 30 ) t The test steps are:

Step1: Establish the original hypothesis H₀ : μ₁ = μ₂ , alternative hypothesis H₁ : μ₁ ≠ μ₂ , determine the significance level a = 0.05.

Step2: Calculate the test statistic t value.

Step3: Determine the form of the test, the use of two-sided test (the left side of the test, the right side of the test of the original hypothesis, alternative hypothesis and two-sided test is different).

Step4: statistical decision, according to the t-test statistical decision rule to determine whether to accept the original hypothesis or to reject the original hypothesis. When the p-value > 0.05, the difference is not significant (accept the original hypothesis). When the p-value is <0.05, there is a significant difference (accept the alternative hypothesis). When the p-value is <0.01, the difference is extremely significant (accept the alternative hypothesis).

3

Analysis of factors affecting the improvement of students’ employability

3.1

Questionnaire design

The questionnaire of this paper is divided into two parts, which are Self-rating Employability Scale and Employability Influencing Factors.

The first part is the self-assessment scale of employability. This part is designed based on the results of exploratory factor analysis based on 170 valid samples from 180 enterprises, and is finally determined to be composed of 6 dimensions and a total of 33 interpretive indicators, including general vocational skills, core qualities, vocational personality, vocational development potential, leadership qualities and team qualities.

The second part is the influencing factors of employability. Combining the actual situation of graduates, this study, based on interview surveys and literature research, through categorization analysis and expert assessment design, has refined a total of 28 interpretative indicators of the formal questionnaire for employability enhancement consisting of eight dimensions: goal strategy, professional setting, evaluation and incentive, campus culture, school-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning.

In this paper, the Likert 5-point scoring method is adopted in the assessment, i.e., the questionnaire respondents are asked to evaluate the degree of conformity between the actual situation of the individual and the formulation of the question items, with 1=completely non-conformity, 2=mostly non-conformity, 3=partial conformity, 4=mostly conformity, and 5=completely conformity.

3.2

Sample Selection and Statistical Analysis

3.2.1

Sample selection

The survey samples were taken from 64 colleges and universities in 23 municipalities and provinces in China, and the survey was conducted from June to August 2023, and the questionnaires were distributed to fresh undergraduate graduates of colleges and universities in the form of paper and electronic questionnaires. The survey method was a combination of class group administration and individual administration. In this study, the data were statistically analyzed by correlation and regression analysis through SPSS28.0 statistical software.

3.2.2

Descriptive statistics of the sample

A total of 3600 questionnaires were distributed in this survey, and 3347 questionnaires were recovered, with a recovery rate of 92.97%. After excluding invalid questionnaires with missing data, obvious response bias or high repetition rate, 2735 valid questionnaires were obtained, with an effective rate of 81.71%. The description of the valid sample is shown in Table 1.

Table 1.

Descriptive statistics of samples (N=2735)

Variable	Classification	Number	Percentage
Gender	Male	1083	39.6%
Gender	Female	1652	60.4%
School level	Ordinary university	1841	67.3%
	“211” university	479	17.5%
	“985” university	415	15.2%
Hometown	City	1392	50.9%
Hometown	Countryside	1343	49.1%
School area	Northwest China	416	15.2%
	Northeast China	222	8.1%
	North China	353	12.9%
	Central China	678	24.8%
	East China	257	9.4%
	South China	429	15.7%
	Southwest China	380	13.9%
Majors	Polytechnic	358	13.1%
	Finance	351	12.8%
	Management	385	14.1%
	Literary history	307	11.2%
	Medicine	339	12.4%
	Agronomy	344	12.6%
	Art	322	11.8%
	Military	329	12.0%
Total		2735	100%

As can be seen from Table 1, there are 1083 male and 1652 female students in the sample, each accounting for 39.6% and 60.4% of the total sample. The home locations were located in towns and villages with 1392 (50.9%) and 1343 (49.1%) persons, respectively, which were more evenly distributed.

The level of sampled schools includes “985” colleges and universities, “211” colleges and universities and colleges of general undergraduate education, accounting for 67.3%, 17.5% and 15.2% respectively. The sampled schools are distributed according to the administrative region division method, and the regional sampling ratios are in descending order: Central China (24.8%), South China (15.7%), Northwest China (15.2%), Southwest China (13.9%), North China (12.9%), East China (9.4%), Northeast China (8.1%). And the selected majors involve eight major professional categories such as science and technology, finance and economics, management, literature, history and philosophy, medicine, agronomy, art and military. This indicates that the selected samples basically cover the main characteristics of the current group of fresh undergraduates in Chinese universities, and have a good representativeness.

3.3

Reliability test

3.3.1

Reliability and Validity Analysis of Employability Self-Assessment Scale (ESSA)

1)

Reliability analysis

The results of the reliability analysis of the employability self-assessment scale are shown in Table 2. SPSS28.0 was used to test the reliability of the sample data and Cronbach’s alpha coefficient was used to measure the reliability of the dimensions of employability. Table 2.

The results of the analysis of the reliability of the employment ability self-rating scale

Classification	Dimension	Cronbach’s α coefficient	Problem number
Self-rating scale	Professional skills	0.912	6
	Core quality	0.863	6
	Occupational personality	0.807	5
	Occupational potential	0.793	6
	Leadership quality	0.826	5
	Team quality	0.738	5

As can be seen from Table 2, the Cronbach’s α coefficients of the dimensions of employability in occupational general skills, core qualities, occupational personality, occupational development potential, leadership qualities, and team qualities are 0.912, 0.863, 0.807, 0.793, 0.826, and 0.738, respectively, which are greater than 0.7, indicating that the reliability of each dimension of the Self-Assessment Scale of Employability is good.

2)

Validity analysis

In this paper, the structural validity of the Employability Self-Assessment Scale was tested by means of factor analysis, and the KMO test was performed before the factor analysis. It is generally believed that the closer the KMO value is to 1, the more suitable it is for factor analysis, and the KMO value is more than 0.7 suitable for factor analysis, while the KMO value is less than 0.6 is not suitable for factor analysis.

The results of the test showed that the KMO values of the dimensions of employability, such as occupational general skills, core qualities, occupational personality, occupational development potential, leadership qualities, and team qualities, were all greater than 0.7, and the factor loadings of each factor of the subordinate items were all greater than 0.7 (P<0.001), indicating that the convergent validity of the scales was high. The explanations of the cumulative variables were all greater than 50%, indicating that the scale had good construct validity.

3.3.2

Reliability analysis of factors affecting employability

1)

Reliability analysis

The results of reliability analysis of employability influencing factors are shown in Table 3. As can be seen from Table 3, the Cronbach’s α values of the influencing factors of employability, such as goal strategy, specialty setting, evaluation and incentive, campus culture, school-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning, are 0.778, 0.805, 0.857, 0.814, 0.806, 0.829, 0.874 and 0.897 respectively. The Cronbach’s alpha values are all greater than 0.7, which is higher than the minimum standard of 0.6 and within the better standard range of 0.7-0.9, indicating that there is a better internal consistency of the various influencing factors of employability, i.e., the reliability of the various influencing factors of employability is good. Table 3.

The results of the analysis of the factors of employment ability

Classification	Dimension	Cronbach’s α coefficient	Problem number
Influencing factor	Target strategy	0.778	3
	Professional setting	0.805	3
	Evaluation incentive	0.857	3
	Campus culture	0.814	3
	School cooperation	0.806	3
	Innovative entrepreneurship	0.829	3
	Teaching ability	0.874	3
	Career guidance	0.897	3

2)

Validity analysis

The KMO values of the influencing factors of employability, such as goal strategy, professional setting, evaluation and incentive, campus culture, school-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning, are all in the range of 0.738~0.856, greater than 0.7, and the loadings of each factor are all greater than 0.7 (P<0.001), and the explanatory degrees of the cumulative variables are greater than 50%, which indicates that the scale has a better convergent validity and structural validity.

3.4

Correlation analysis

In this paper, starting from the condition of conforming to multiple linear regression analysis, before doing multiple linear regression, we first analyze the Pearson correlation coefficients between the structural elements of college students’ employability, i.e., the dependent variables, and the influencing factors of college students’ employability enhancement, i.e., the independent variables, and the results of the correlation analysis are shown in Table 4. Among them, y1~y6 represent six dimensions of employability, namely, general vocational skills, core qualities, vocational personality, vocational development potential, leadership qualities and team qualities, respectively, and y represents the total score of employability. x1~x8 represent eight influencing factors of employability, namely, goal strategy, professional setting, evaluation and motivation, campus culture, university-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning, respectively, and x represents the total score of the influencing factors of employability. x represents the total score of employability influencing factors.

Table 4.

Correlation analysis results

	y	y₁	y₂	y₃	y₄	y₅	y₆
x	0.262**	0.268**	0.219**	0.246**	0.291**	0.257**	0.162**
x₁	0.192**	0.259**	0.153**	0.249**	0.191**	0.277**	0.186**
x₂	0.201**	0.236**	0.197**	0.313**	0.231**	0.162**	0.149**
x₃	0.257**	0.181**	0.135**	0.215**	0.226**	0.264**	0.197**
x₄	0.237**	0.346**	0.184**	0.165**	0.165**	0.179**	0.156**
x₅	0.254**	0.157**	0.176**	0.144**	0.264**	0.235**	0.125**
x₆	0.174**	0.226**	0.183**	0.129**	0.279**	0.202**	0.137**
x₇	0.213**	0.246**	0.158**	0.145**	0.218**	0.206**	0.128**
x₈	0.173**	0.218**	0.155**	0.166**	0.229**	0.111**	0.288**

As can be seen from Table 4, the correlation between the enhancement of employability and the specific dimensions of employability have reached a significant level, and the correlation coefficients are between 0.111 and 0.346, all of which show a weak correlation, which indicates that the refined influencing factors of each college student’s employability have a greater effect on the level of employability.

3.5

Multiple linear regression analysis

In order to further examine the impact of the refined college students’ employability influencing factors on each specific dimension of employability, on the basis of the relevant analysis, a one-way linear regression of the employability influencing factors on the overall score of employability and its dimensions is first conducted separately to determine the degree of influence of the employability influencing factors on each specific dimension of employability. Then a multiple regression analysis is adopted to examine the role of employment ability improvement and its dimensions in influencing the overall level of employment ability and its specific dimensions, to identify the key influence items, and to further verify the strength of the influence between them.

The results of one-way regression analysis between the total score of college students’ employability and the total score of factors influencing employability are shown in Table 5.

Table 5.

Regression analysis results

	B	β	t	P	R	R²	F
Constants	28.359		40.813	0.000
x	0.019	0.077	2.641	0.014	0.077	0.006	7.645*

As shown in Table 5, the linear relationship between the total score of employability and the total score of factors influencing employability is significant (P<0.05), which is suitable for establishing the one-way linear regression equation. The one-way linear equation that can be established is: y=28.359+0.019x, indicating that employability enhancement has a certain degree of influence on employability and has a predictive effect, and the total score of employability enhancement can explain 0.6% of the total score of employability.

The results of multiple step-by-step regression analysis of total employability score and specific dimensions of employability influencing factors are shown in Table 6.

Table 6.

Multiple step-up regression analysis results

	B	β	t	P	R	R²	Adjusted R²	F
Constants	292.517		71.516	0.000	0.301	0.091	0.090	51.462***
x₂	1.246	0.158	5.327	0.001
x₃	1.285	0.064	3.247	0.015
x₄	2.357	0.098	4.153	0.000
x₇	-1.516	-0.087	-2.948	0.007
x₈	1.244	0.092	3.415	0.004

As shown in Table 6, with the total employability score as the dependent variable and each specific dimension of the influencing factors of employability as the independent variable in the multiple stepwise regression analysis, professional setting, career planning, evaluation and incentives, campus culture, and teaching ability enter into the regression equations, i.e., there is a multivariate linear relationship with the employability, and the multivariate linear regression equations are as follows: y = 292.517+1.246x2+1.285x3+ 2.357x4-1.516x7+1.244x8, together explaining 9.0% of the variance in the total score of employability, indicating that the five dimensions of the influences on employability have a predictive influence on employability and are the key influences.

Through the multiple regression analysis of college students’ employability and employability influencing factors, the results of the model aggregate of each specific dimension of college students’ employability and each specific dimension of employability influencing factors are shown in Table 7. ***, **, and * indicate significantly different from 0 at the 0.01, 0.05, and 0.1 levels, respectively.

Table 7.

Multiple step-up regression analysis results

	y₁	y₂	y₃	y₄	y₅	y₆
x₁						0.201***
x₂	0.132***	0.174***	0.196***	0.415***		0.083***
x₃	0.261***	0.225*		0.473*	0.212***
x₄		0.313*	1.135***			0.179**
x₅				0.326*
x₆	0.163*	0.284**			0.172**
x₇	-0.165**			-0.668***	-0.121*	-0.171***
x₈	0.167**			0.434*	0.271***	0.088**
Constants	42.357	55.247	56.761	114.275	36.241	20.437
Adjusted R²	0.081	0.064	0.124	0.066	0.062	0.074
Sample size	2735

As can be seen from Table 7, the multiple stepwise regression analyses were conducted with the general vocational skills (y1), core qualities (y2), vocational personality (y3), career development potential (y4), leadership qualities (y5), and team qualities (y6) as the dependent variables, and with the specific dimensions of the employability influencing factors as the independent variables, and the resulting regression equations and the related interpretations were: 1)

y1=42.357+0.132x2+0.261x3+0.163x6-0.165x7+0.167x8. Professional setting, evaluation incentives, innovation and entrepreneurship, teaching ability, and career planning together explain 8.1% of the variance in occupational generic skills.

2)

y2=55.247+0.174x2+0.225x3+0.313x4+0.284x6. professional setting, evaluation and motivation, campus culture, innovation and entrepreneurship together explain 6.4% of the variation in core qualities.

3)

y3=56.761+0.196x2+0.135x4. professional setting and campus culture together explain 12.4% of the professional personality.

4)

y4=114.275+0.415x2+0.473x3+0.326x5-0.668x7+0.434x8. Specialization, evaluation incentives, school-enterprise cooperation, teaching competence, and career planning together explain 6.6% of the career development potential.

5)

y5=36.241+0.212x3+0.172x6-0.121x7+0.271x8. Evaluation incentives, innovation and entrepreneurship, teaching ability, and career planning together explain 6.2% of leadership quality.

6)

y6=20.437+0.201x1+0.083x2+0.179x4-0.171x7+0.0881x8. Goal strategy, professionalism, campus culture, teaching ability, and career planning together explain 7.4% of the variation in team quality.

4

Path of management reform of colleges and universities based on employability orientation

4.1

Pathway Design for Higher Education Management Reform

Based on the results of the multiple regression analysis of the influencing factors of students’ employability in the previous section, this paper designs the following management reform paths for colleges and universities from the eight dimensions of goal strategy, professional setting, evaluation and incentive, campus culture, school-enterprise cooperation, innovation and entrepreneurship, teaching ability and career planning: 1)

Based on the school development strategy, adopt an all-round and whole-process synergistic development strategy to build a synergistic nurturing mechanism for the improvement of employability. Colleges and universities need to coordinate and integrate the components of all aspects of talent cultivation, and derive the process of talent cultivation to the social and governmental levels, and establish a collaborative cultivation mechanism with internal and external vertical and horizontal linkages. In addition, it should also make use of modern information technology and the diversification and openness of evaluation methods, take the initiative to establish an information platform for interaction with the external society as well as feedback on the quality of talent cultivation in close contact with the outside world, build an all-round evaluation system for the improvement of students’ employability, and feedback the evaluation results to the teaching and management departments in a timely manner, so as to make adjustments to and optimize the course curriculum, teaching content and teaching methods.

2)

Optimize the curriculum and teaching content. First of all, colleges and universities should adjust the specialties and curriculum settings according to the employment market demand to ensure the timeliness and practicality of the teaching content. This can be achieved through regular market research and cooperation with enterprises to ensure that the curriculum is closely aligned with the needs of the industry.

3)

Build a school-based cultural support system that promotes students’ independent construction of employability. Colleges and universities should attach great importance to the construction of campus culture and incentive evaluation, build a good nurturing environment and service learning system for college students to independently construct employability, encourage students to carry out social practice and public welfare volunteer service, independently improve employability through work experience, create a diversified campus activity culture brand centered on competence development, establish an ecosystem for the improvement of comprehensive vocational qualities, and form a complete personal growth The school will establish a comprehensive career quality improvement ecosystem and form a perfect personal growth incentive and evaluation mechanism in the form of a file bag.

4)

Promote innovation and entrepreneurship education and create a favorable innovation and entrepreneurship environment. First of all, colleges and universities should build an innovation and entrepreneurship education system, integrate innovation and entrepreneurship education into the whole process of talent cultivation, and cultivate students’ innovation consciousness and entrepreneurial spirit. Secondly, colleges and universities should provide students with innovation and entrepreneurship practice platforms and resource support, and encourage students to actively participate in innovation and entrepreneurship activities. Finally, colleges and universities should cooperate deeply with enterprises to provide students with more practice opportunities and employment guidance.

5)

Strengthening the Teaching Staff

According to the results of the analysis of the factors affecting the employability of students, the teaching ability of teachers is one of the important factors affecting the employability of students, therefore, it is urgent to strengthen the construction of the teaching force. First of all, colleges and universities should increase the cultivation of young teachers, introduce relevant policies, encourage them to go abroad for further study, introduce advanced teaching methods and learn cutting-edge scientific research achievements, so that they can complete teaching, scientific research and school management in colleges and universities with more foresight and higher quality in the future. Secondly, we should increase the investment in universities and adopt diversified and flexible forms of employment to target the introduction of excellent teachers with high-level teaching ability and scientific research ability. Finally, the construction of dual-teacher team should be strengthened to enhance the theoretical and knowledge level of college teachers while strengthening the cultivation of their teaching practice ability, and encouraging and guiding the teachers to conduct scientific research in conjunction with teaching, industry, and trade in order to improve their own professional ability and practice ability.

6)

Strengthening career guidance services and helping students clarify their career planning. First of all, colleges and universities should provide personalized career planning services to help students understand their own interests, strengths and potentials, and formulate career planning and development plans in line with their own characteristics, as well as provide students with theoretical knowledge and practical experience in career planning by offering career planning courses and lectures and other activities. Secondly, colleges and universities can carry out employment skills training and job search guidance to help students improve their job search skills and interviewing ability. At the same time, activities such as mock interviews and practical job search drills are carried out to help students understand the job search process and the interview process and improve their ability to deal with interviews. Finally, colleges and universities can set up internship and employment platforms to provide students with internship opportunities and employment information, and provide students with more employment opportunities by organizing activities such as campus job fairs and employment promotion seminars. Through the implementation of the above measures, career guidance services can be effectively strengthened to help students in tertiary institutions to make clear career planning so as to enhance their employability.

4.2

Analysis of path application results

In order to verify the effectiveness of the designed college management reform path oriented to the improvement of students’ employability, this paper designs a teaching control experiment. Sixty college students were randomly selected from the sophomore students of College S of University H, from which 30 students were randomly selected as the experimental group and the other 30 as the control group. The experimental group studied under the reformed college teaching and management mode, and the control group studied under the traditional college teaching and management mode, and the self-assessment scale of students’ employability designed in the previous paper was used, and it was changed into the form of a test to test the employability of the two groups of students before and after the experiment.

4.2.1

Homogeneity test of students’ employability before the experiment

Before the experiment, students in the experimental group and the control group were tested for their employability, and the independent samples t-test was conducted on the tested data. The results of the independent sample t-test before the experiment are shown in Table 8.

Table 8.

Independent sample t test results before the experiment

Test index	Group	N	Mean	Standard deviation	t	p
Professional skills	Experimental group	30	2.5	0.425	0.124	0.875
Professional skills	Control group	30	2.4	0.431	0.124	0.875
Core quality	Experimental group	30	1.9	0.937	-0.132	0.881
Core quality	Control group	30	2.1	0.958	-0.132	0.881
Occupational personality	Experimental group	30	2.6	1.024	0.758	0.614
Occupational personality	Control group	30	2.4	1.135	0.758	0.614
Occupational potential	Experimental group	30	2.5	0.826	1.526	0.208
Occupational potential	Control group	30	2.6	0.839	1.526	0.208
Leadership quality	Experimental group	30	2.2	0.743	0.094	0.957
Leadership quality	Control group	30	2.2	0.752	0.094	0.957
Team quality	Experimental group	30	2.5	1.237	-1.155	0.413
Team quality	Control group	30	2.3	1.305	-1.155	0.413

As can be seen from Table 8, before the experiment, the t-test P-values of the two groups of students in the experimental and control groups in the dimensions of employability in terms of occupational general ability, core qualities, occupational personality, occupational development potential, leadership qualities and team qualities are 0. 875, 0.881, 0.614, 0.208, 0.957 and 0.413, respectively, which are greater than 0.05, which means that there is no significant difference between students in the experimental and control groups in terms of their employability of employability are not significantly different, i.e., there is no significant difference between the employability of students in the experimental group and the control group. There is no significant difference between the employability of students in the experimental group and the control group, i.e., the employability is homogeneous, which is basically in line with the preconditions of the experiment.

4.2.2

Comparative analysis of students’ employability before and after the experiment

1)

Paired T-test comparison of students’ employability before and after the experiment in the control group

In order to understand the changes in the specific dimensions of students’ employability after the experimental group and the control group have carried out a semester-long teaching experiment, this paper adopts the paired samples t-test to compare and analyze the data before and after the experiment in the control group. The results of the paired samples t-test for the control group are shown in Table 9. Table 9.

Matching sample t test results of the control group

Test index	Test time	N	Mean	Standard deviation	t	p
Professional skills	Before the experiment	30	2.4	0.431	-2.084	0.314
Professional skills	After the experiment	30	2.9	0.647	-2.084	0.314
Core quality	Before the experiment	30	2.1	0.958	-1.125	0.041
Core quality	After the experiment	30	3.1	1.246	-1.125	0.041
Occupational personality	Before the experiment	30	2.4	1.135	-0.948	0.085
Occupational personality	After the experiment	30	3.2	1.462	-0.948	0.085
Occupational potential	Before the experiment	30	2.6	0.839	-2.873	0.062
Occupational potential	After the experiment	30	3.4	1.573	-2.873	0.062
Leadership quality	Before the experiment	30	2.2	0.752	-0.617	0.108
Leadership quality	After the experiment	30	2.9	1.461	-0.617	0.108
Team quality	Before the experiment	30	2.3	1.305	-3.435	0.184
Team quality	After the experiment	30	3.1	1.824	-3.435	0.184

As can be seen from Table 9, there is no significant difference between the control group before and after the experiment in the specific dimensions of employability such as vocational general skills, vocational personality, career development potential, leadership qualities, and team qualities (p>0.05), and there is a significant difference in the core quality dimensions (p=0.041<0.05). It indicates that the traditional college teaching management mode has some effect on enhancing students’ employability, but the effectiveness is mostly less significant.

2)

Paired t-test comparison of students’ employability before and after the experiment in the experimental group

The paired-sample t-test results of the experimental groups before and after the experiment are shown in Table 10. Table 10.

Matching sample t test results of the control group

Test index	Test time	N	Mean	Standard deviation	t	p
Professional skills	Before the experiment	30	2.5	0.425	-2.675	0.012
Professional skills	After the experiment	30	3.8	0.769	-2.675	0.012
Core quality	Before the experiment	30	1.9	0.937	-1.324	0.000
Core quality	After the experiment	30	3.9	1.437	-1.324	0.000
Occupational personality	Before the experiment	30	2.6	1.024	-3.861	0.010
Occupational personality	After the experiment	30	4.1	1.543	-3.861	0.010
Occupational potential	Before the experiment	30	2.5	0.826	-2.963	0.008
Occupational potential	After the experiment	30	3.9	1.428	-2.963	0.008
Leadership quality	Before the experiment	30	2.2	0.743	-4.125	0.000
Leadership quality	After the experiment	30	4.2	1.541	-4.125	0.000
Team quality	Before the experiment	30	2.5	1.237	-4.358	0.002
Team quality	After the experiment	30	4.1	1.414	-4.358	0.002

As can be seen from Table 10, the p-values of paired-sample t-tests of the experimental groups before and after the experiment in the specific dimensions of employability such as occupational general skills, core qualities, occupational personality, occupational development potential, leadership qualities, and team qualities are 0.012, 0.000, 0.010, 0.008, 0.000, and 0.002, respectively, which are all less than 0.05, and there is a significant difference. It indicates that the college management reform path designed in this paper can effectively enhance students’ employability.

4.2.3

Comparative analysis of students’ employability after the experiment

The college management reform path designed in this paper can effectively improve students’ employability.

In order to further verify the superiority of the college management reform path designed in this paper, an independent samples t-test was conducted on the indicators of students’ employability in the experimental group and the control group after the experiment. The results of the independent sample t-test after the experiment are shown in Table 11.

Table 11.

Independent sample t test results after the experiment

Test index	Group	N	Mean	Standard deviation	t	p
Professional skills	Experimental group	30	3.8	0.769	1.032	0.028
Professional skills	Control group	30	2.9	0.647	1.032	0.028
Core quality	Experimental group	30	3.9	1.437	0.574	0.035
Core quality	Control group	30	3.1	1.246	0.574	0.035
Occupational personality	Experimental group	30	4.1	1.543	1.144	0.024
Occupational personality	Control group	30	3.2	1.462	1.144	0.024
Occupational potential	Experimental group	30	3.9	1.428	2.352	0.041
Occupational potential	Control group	30	3.4	1.573	2.352	0.041
Leadership quality	Experimental group	30	4.2	1.541	2.146	0.009
Leadership quality	Control group	30	2.9	1.461	2.146	0.009
Team quality	Experimental group	30	4.1	1.414	1.611	0.013
Team quality	Control group	30	3.1	1.824	1.611	0.013

As can be seen from Table 11, after the experiment, there are significant differences (p<0.05) between the two groups of students in the experimental and control groups in the employability dimensions of occupational general skills, core qualities, occupational personality, occupational development potential, leadership qualities, and team qualities, especially in the leadership qualities dimension, which is particularly significant (p<0.01). This indicates that the teaching management mode under the college management reform path designed in this paper has a more significant effect on the enhancement of students’ employability than the traditional college teaching management mode, i.e., the designed college management reform path is effective.

5

Conclusion

Using quantitative analysis methods such as Pearson correlation coefficient, multiple linear regression and t-test as research tools, this paper realizes the design and quantitative assessment of the path of college management reforms oriented to the improvement of students’ employability on the basis of exploring the factors influencing the improvement of students’ employability.

First of all, based on the results of questionnaire survey and literature research, this paper extracts six dimensions of students’ employability and eight dimensions of factors influencing employability. The correlation between the employability influencing factors and the specific dimensions of employability all reach a significant level, and the correlation coefficient ranges from 0.111 to 0.346, presenting a weak correlation, indicating that the refined employability influencing factors can influence the level of students’ employability. The six dimensions of employability and eight dimensions of factors influencing employability were used as the dependent and independent variables, respectively, for multiple linear regression. The regression results show that major setting, career planning, evaluation incentives, campus culture, and teaching ability are the core elements affecting the enhancement of students’ employability.

This paper tests the effectiveness of the designed college management reform path through controlled experiments. The experimental group learns under the reformed college teaching management mode, and the control group learns under the traditional college teaching management mode, both of which are homogeneous before the experiment (p>0.05). The scores of the specific dimensions of employability of the students in the experimental group were significantly different before and after the experiment (p<0.05). Whereas, the control group had significant differences only in the core quality dimension scores (p=0.041<0.05) and not in other dimensions (p>0.05). And after the experiment, the scores of all dimensions of students’ employability in the experimental group and the control group are significantly different (p<0.05). It indicates that the college management reform path designed in this paper can effectively improve students’ employability, and the effect is more significant than the traditional teaching management mode.

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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Statistical modelling and quantitative assessment of management reforms in higher education on the enhancement of student employability

Lifen Wen

Mingxu Zhao

Zhenhua Li

Published Online: Sep 25, 2025

Received: Jan 15, 2025

Accepted: Apr 30, 2025

DOI: https://doi.org/10.2478/amns-2025-1005

KeywordsPearson correlation coefficient, Multiple linear regression, t-test, college management reform, Employability

© 2025 Lifen Wen, Mingxu Zhao and Zhenhua Li, published by Sciendo.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Pearson correlation coefficient, Multiple linear regression, t-test, college management reform, Employability