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<p>The increasing number of graduates from private colleges and universities creates a great challenge to analyze the factors influencing the employment of graduates and to improve the quality. Based on the structural equation SEM model and combining the data of graduates of private colleges and universities in a city, this paper integrates and selects the factors influencing the employment quality of graduates of private colleges and universities. An evaluation model for the employment quality of graduated students has been established through the LSTM network to further study the degree of influence of each influential factor on graduates’ employment quality. In order to deal with the bidirectional dependence of time series data while considering the inputs before and after the current moment, this paper adds the reverse LSTM layer on top of the LSTM network to form a BiLSTM network, which better captures the correlation between the influencing factors. In the research process, it was found that, except for the first selected factor of graduates’ destination, which needs to be eliminated, the other six influencing factors passed the reliability and validity test and could make the model have a good fitting-out effect. In the algorithm analysis, it was found that the running accuracy of the BiLSTM network could reach 97.01% at the maximum. In comparison, the running accuracy of the LSTM network could only get 91.03% at the maximum.BiLSTM network is more outstanding than the LSTM network both in accuracy and stability.</p>
</abstract>

The increasing number of graduates from private colleges and universities creates a great challenge to analyze the factors influencing the employment of graduates and to improve the quality. Based on the structural equation SEM model and combining the data of graduates of private colleges and universities in a city, this paper integrates and selects the factors influencing the employment quality of graduates of private colleges and universities. An evaluation model for the employment quality of graduated students has been established through the LSTM network to further study the degree of influence of each influential factor on graduates’ employment quality. In order to deal with the bidirectional dependence of time series data while considering the inputs before and after the current moment, this paper adds the reverse LSTM layer on top of the LSTM network to form a BiLSTM network, which better captures the correlation between the influencing factors. In the research process, it was found that, except for the first selected factor of graduates’ destination, which needs to be eliminated, the other six influencing factors passed the reliability and validity test and could make the model have a good fitting-out effect. In the algorithm analysis, it was found that the running accuracy of the BiLSTM network could reach 97.01% at the maximum. In comparison, the running accuracy of the LSTM network could only get 91.03% at the maximum.BiLSTM network is more outstanding than the LSTM network both in accuracy and stability.

Analysis of Influencing Factors on the Improvement of Employment Quality of College Students in Private Colleges and Universities - Based on SEM Model

Applied Mathematics and Nonlinear Sciences

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

The increasing number of graduates from private colleges and universities creates a great challenge to analyze the factors influencing the employment of...

Analysis of Influencing Factors on the Improvement of Employment Quality of College Students in Private Colleges and Universities - Based on SEM Model

Data publikacji: 05 lip 2024

Zakres stron: -

Otrzymano: 06 mar 2024

Przyjęty: 22 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1705

Słowa kluczowe
Employment quality, SEM model, BiLSTM network, Reliability and validity test

© 2024 Fangyuan Li., published by Sciendo

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

Analysis of Influencing Factors on the Improvement of Employment Quality of College Students in Private Colleges and Universities - Based on SEM Model

Data publikacji: 05 lip 2024

Zakres stron: -

Otrzymano: 06 mar 2024

Przyjęty: 22 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1705

Słowa kluczoweEmployment quality, SEM model, BiLSTM network, Reliability and validity test

© 2024 Fangyuan Li., published by Sciendo

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

Słowa kluczowe
Employment quality, SEM model, BiLSTM network, Reliability and validity test