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

<p>This paper first established a multiple linear regression model and estimated the model parameters using the least squares estimation method. Then, it analyzes the employment and entrepreneurship abilities of college students in higher vocational colleges and universities and analyzes the differences in the level of employment and entrepreneurship ability of students in different grades. Then, the impact of artificial intelligence technology on employment and entrepreneurship ability was analyzed in combination with relevant measurement indexes at home and abroad, and finally, based on the results of the analysis, the strategies for improving the employment and entrepreneurship ability of college students in higher vocational colleges were proposed from multiple aspects. The results show that for every 1% increase in the level of AI technology, the total number of people employed in the labor employment market rises by 0.48, and the employment income rises by 6.56. This study has certain reference significance for balancing the “positive effect” and “negative effect” brought by the development of artificial intelligence on labor and employment, and provides realistic and feasible basis for the introduction of employment policy and talent development policy adapted to the development of artificial intelligence.</p>
</abstract>

This paper first established a multiple linear regression model and estimated the model parameters using the least squares estimation method. Then, it analyzes the employment and entrepreneurship abilities of college students in higher vocational colleges and universities and analyzes the differences in the level of employment and entrepreneurship ability of students in different grades. Then, the impact of artificial intelligence technology on employment and entrepreneurship ability was analyzed in combination with relevant measurement indexes at home and abroad, and finally, based on the results of the analysis, the strategies for improving the employment and entrepreneurship ability of college students in higher vocational colleges were proposed from multiple aspects. The results show that for every 1% increase in the level of AI technology, the total number of people employed in the labor employment market rises by 0.48, and the employment income rises by 6.56. This study has certain reference significance for balancing the “positive effect” and “negative effect” brought by the development of artificial intelligence on labor and employment, and provides realistic and feasible basis for the introduction of employment policy and talent development policy adapted to the development of artificial intelligence.

Improvement of Employment and Entrepreneurship Ability of College Students in Higher Vocational Colleges and Universities under the New Situation of Artificial Intelligence

Applied Mathematics and Nonlinear Sciences

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

This paper first established a multiple linear regression model and estimated the model parameters using the least squares estimation method. Then, it analyzes...

Improvement of Employment and Entrepreneurship Ability of College Students in Higher Vocational Colleges and Universities under the New Situation of Artificial Intelligence

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 04 kwi 2024

Przyjęty: 21 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2082

Słowa kluczowe
Least squares estimation, Multiple linear regression, Analysis of variance, Artificial intelligence, Employment and entrepreneurship

© 2024 Ri’an Huang et al., published by Sciendo

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

Improvement of Employment and Entrepreneurship Ability of College Students in Higher Vocational Colleges and Universities under the New Situation of Artificial Intelligence

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 04 kwi 2024

Przyjęty: 21 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2082

Słowa kluczoweLeast squares estimation, Multiple linear regression, Analysis of variance, Artificial intelligence, Employment and entrepreneurship

© 2024 Ri’an Huang et al., published by Sciendo

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

Słowa kluczowe
Least squares estimation, Multiple linear regression, Analysis of variance, Artificial intelligence, Employment and entrepreneurship