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<p>With the arrival of the “Internet Plus” era, college students are facing new challenges of Employment and entrepreneurship. This study aims to explore an effective guidance course system for Employment and entrepreneurship to meet the current social development needs and enhance students’ entrepreneurial ability and employment competitiveness. Through data mining decision tree algorithm, college students’ employment and entrepreneurship situation and their influencing factors were analyzed to establish an effective guidance course system. It was found that factors such as gender, specialty category, and entrepreneurial experience significantly affect students’ entrepreneurial intention. The results of the decision tree analysis show that factors such as family self-employment situation, entrepreneurial attitude, subjective norms, perceived behavioral control, entrepreneurial self-efficacy and entrepreneurship are closely related to the entrepreneurial intention of college students. Based on this, strategies such as building innovation and entrepreneurship simulation and rehearsal carriers, broadening practical teaching bases, and constructing supportive entrepreneurial entity projects are proposed to promote the enhancement of college students’ entrepreneurial ability and the adaptability of the job market.</p>
</abstract>

With the arrival of the “Internet Plus” era, college students are facing new challenges of Employment and entrepreneurship. This study aims to explore an effective guidance course system for Employment and entrepreneurship to meet the current social development needs and enhance students’ entrepreneurial ability and employment competitiveness. Through data mining decision tree algorithm, college students’ employment and entrepreneurship situation and their influencing factors were analyzed to establish an effective guidance course system. It was found that factors such as gender, specialty category, and entrepreneurial experience significantly affect students’ entrepreneurial intention. The results of the decision tree analysis show that factors such as family self-employment situation, entrepreneurial attitude, subjective norms, perceived behavioral control, entrepreneurial self-efficacy and entrepreneurship are closely related to the entrepreneurial intention of college students. Based on this, strategies such as building innovation and entrepreneurship simulation and rehearsal carriers, broadening practical teaching bases, and constructing supportive entrepreneurial entity projects are proposed to promote the enhancement of college students’ entrepreneurial ability and the adaptability of the job market.

Research on the Construction of College Students’ Employment and Entrepreneurship Guidance Course System under the Background of “Internet+”

Applied Mathematics and Nonlinear Sciences

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

With the arrival of the “Internet Plus” era, college students are facing new challenges of Employment and entrepreneurship. This study aims to explore an...

Research on the Construction of College Students’ Employment and Entrepreneurship Guidance Course System under the Background of “Internet+”

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 15 gen 2024

Accettato: 22 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0649

Parole chiave
Employment and entrepreneurship, Decision tree, Entrepreneurial intention, Regression analysis

© 2023 Min Fang et al., published by Sciendo

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

Research on the Construction of College Students’ Employment and Entrepreneurship Guidance Course System under the Background of “Internet+”

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 15 gen 2024

Accettato: 22 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0649

Parole chiaveEmployment and entrepreneurship, Decision tree, Entrepreneurial intention, Regression analysis

© 2023 Min Fang et al., published by Sciendo

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

Parole chiave
Employment and entrepreneurship, Decision tree, Entrepreneurial intention, Regression analysis