<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper analyzes the factors affecting the efficiency value of human resource management in higher education by using the Tobit regression model, puts forward the hypotheses of the influencing factors, constructs a model of the factors affecting the efficiency of human resource utilization in higher education, and derives the specific correlation coefficients of the influencing factors. After examining the correlation between each dimension of teacher management culture in higher education and teachers’ organizational commitment and its dimensions using Pearson’s product-difference correlation method, the correlation between educational management and teachers’ teaching commitment is verified through the quantitative measurement of correlation analysis and linear regression analysis. Based on the decision tree algorithm and multiple linear regression method to predict the resource allocation of teachers’ positions, we constructed a model of human resource optimization and allocation strategy for college teachers and carried out the actual analysis of the utilization rate of resources for teachers’ positions and teachers’ schedules by genetic algorithm. Analysis obtained shows that selecting different population sizes for test results in teacher positions and teacher scheduling programs results in higher algorithm efficiency for populations between 30-50. When the value of the population is taken in the range of 30-50, the average time of the experiment is 60380.4ms-153199.2ms.</p>
</abstract>

This paper analyzes the factors affecting the efficiency value of human resource management in higher education by using the Tobit regression model, puts forward the hypotheses of the influencing factors, constructs a model of the factors affecting the efficiency of human resource utilization in higher education, and derives the specific correlation coefficients of the influencing factors. After examining the correlation between each dimension of teacher management culture in higher education and teachers’ organizational commitment and its dimensions using Pearson’s product-difference correlation method, the correlation between educational management and teachers’ teaching commitment is verified through the quantitative measurement of correlation analysis and linear regression analysis. Based on the decision tree algorithm and multiple linear regression method to predict the resource allocation of teachers’ positions, we constructed a model of human resource optimization and allocation strategy for college teachers and carried out the actual analysis of the utilization rate of resources for teachers’ positions and teachers’ schedules by genetic algorithm. Analysis obtained shows that selecting different population sizes for test results in teacher positions and teacher scheduling programs results in higher algorithm efficiency for populations between 30-50. When the value of the population is taken in the range of 30-50, the average time of the experiment is 60380.4ms-153199.2ms.

Analysis of Challenges and Countermeasures for Higher Education Management in the Era of Big Data

Applied Mathematics and Nonlinear Sciences

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

This paper analyzes the factors affecting the efficiency value of human resource management in higher education by using the Tobit regression model, puts...

Analysis of Challenges and Countermeasures for Higher Education Management in the Era of Big Data

Data publikacji: 13 gru 2023

Zakres stron: -

Otrzymano: 14 mar 2023

Przyjęty: 23 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01462

Słowa kluczowe
Tobit regression model, Correlation analysis, Decision tree algorithm, Multiple linear regression, Population size, Educational management

© 2023 Feng Chen, published by Sciendo

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

Analysis of Challenges and Countermeasures for Higher Education Management in the Era of Big Data

Data publikacji: 13 gru 2023

Zakres stron: -

Otrzymano: 14 mar 2023

Przyjęty: 23 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01462

Słowa kluczoweTobit regression model, Correlation analysis, Decision tree algorithm, Multiple linear regression, Population size, Educational management

© 2023 Feng Chen, published by Sciendo

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

Słowa kluczowe
Tobit regression model, Correlation analysis, Decision tree algorithm, Multiple linear regression, Population size, Educational management