Welcome to Francis Academic Press

International Journal of New Developments in Education, 2021, 3(3); doi: 10.25236/IJNDE.2021.030306.

A Strategic System of Evaluation and Promotion for Higher Education

Author(s)

Hengyi Zhang, Guanyu Zhao

Corresponding Author:
Hengyi Zhang
Affiliation(s)

School of Automation and Software Engineering, Shanxi University, Taiyuan, Shanxi 030006, China

Abstract

The higher education system is an important factor for a country to provide citizens with basic education and continuing education after secondary education. But looking around the world, countries have different methods of higher education, each with its own advantages and disadvantages. Our team decide to develop a model to determine and evaluate the health and sustainability of a country’s higher education system. Analyze selected countries and formulate a set of feasible policies to improve the current problems in the national higher education system.

Keywords

System of Higher Education, Weighted Rank-Sum Ratio, BP Neural Network, Grey Prediction Method

Cite This Paper

Hengyi Zhang, Guanyu Zhao. A Strategic System of Evaluation and Promotion for Higher Education. International Journal of New Developments in Education (2021) Vol. 3, Issue 3: 22-26. https://doi.org/10.25236/IJNDE.2021.030306.

References

[1] Xu Jiayuan & Li Shuyun, a Study of the Internationa Intelligence Return Based on CES Production Function Model. [J]. Forum on Science and Technology in China, 2012(12): 102-106. 

[2] Zhu Yongdong, Xiang Huaxing,&Ye Jiayu, Comprehensive evaluation of American higher education development level based on factor analysis. [J].Higher Education Exploration, 2014 (5). 

[3] Tao Zhuang, Detailed explanation of classical rank sum ratio method. [J] .Journal of Mathematical Mdeicine, 2007. 

[4] Liu Mengjin, Xu Mingxue, Zong Min, & Yang Bing, Reform of New College Entrance Examination: Problems, Measures and Conditions. [J]. China Educational Technology, 2020, 11(406). 

[5] Yu Shanfu, An economic analysis of the relationship between brain drain and per capita GDP, industrial growth rate and living standard. [J]. Commercial Times, 2014 (5).

[6] Che-Chiang Hsu, & Chia-Yon Chen, Applications of improved grey prediction model for power demand forecasting. [J]. Energy Conversion and Management, 2003.