An Empirical Study on National Scholarship for Postgraduate Performance Based on Negative Binomial Regression Model
Taking a Provincial University of Science and Engineering as an Example
- 10.2991/978-94-6463-024-4_36How to use a DOI?
- national scholarship for postgraduate; the Negative Binomial Regression model; science and engineering postgraduates; liberal arts postgraduates; performance
In the new era, education information has become a booster for the modernization of education in China. An essential part of education informatization is to cultivate the information ability of students and colleges. As an important direction in the field of higher education research, the National Scholarship for Postgraduate is of great significance to the cultivation of postgraduates. This paper takes scholarship for postgraduate recipients from a provincial science and technology university from 2019 to 2021 as the research objects, takes the information of the “National Scholarship for Postgraduate Approval form” as the primary data source. Stata and Negative Binomial Regression model were used to analyze the differences in the output of scientific research achievements of the winners under different discipline backgrounds, and the regression model was used for significance analysis. The research shows that: the overall performance of national scholarship for postgraduate is significant, and the implementation of national postgraduate scholarships for liberal arts postgraduates is better than that for science and engineering postgraduate. However, there are differences in the type and quantity of scientific research results between different disciplines, and the differences in the discipline categories of the winners significantly affect the output of their scientific research results.
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Cite this article
TY - CONF AU - Anqi Li AU - Huali Hu PY - 2022 DA - 2022/12/12 TI - An Empirical Study on National Scholarship for Postgraduate Performance Based on Negative Binomial Regression Model BT - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022) PB - Atlantis Press SP - 339 EP - 348 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-024-4_36 DO - 10.2991/978-94-6463-024-4_36 ID - Li2022 ER -