Measurement of sustainable higher education development: Evidence from China

Abstract

This paper constructs the 6E evaluation index system, a comprehensive index including the dimensions of economy, effectiveness, efficiency, equity, earnings and equality, to measure the sustainable higher education development of the 31 provincial regions of China by utilizing the information entropy weight-TOPSIS method. This paper then makes a spatial and temporal analysis of the coupling coordination relationship among the dimensions of sustainable higher education development by using the coupling coordination model. In addition, this paper proposes specific and applicable countermeasures for sustainable higher education development. The results show that the comprehensive degrees of sustainable higher education development in most regions are not high, and the coastal regions and the Central-south China regions have higher grades; in addition, for most regions, the coupling coordination degrees mainly remain stable, with mild growth in the respective classifications, and the gap between the west and other regions is declining. The improved method is applicable to measure the sustainable development of higher education and to propose detailed and appropriate suggestions for further development.

Higher education and science popularization: Can they achieve coordinated growth?

“…In specific, the spatial distributions of the average overall performances of the two systems show slight differences: (1) for the higher education system, the generally believed regions with advantages in education (Sichuan, Hubei, Jiangsu, Shanghai, and Zhejiang) still maintained the competitiveness in higher education. These places enjoyed abundant population and traditionally paid great attention to education, therefore, they enjoy qualified local higher education institutes and college students with quantity, and performs better than other regions, which is supported by previous work [ 7 ]; (2) for the science popularization system, the coastal regions had better average overall performances (Jiangsu, Shanghai, and Zhejiang), mainly because of the convenient transportation and strong fiscal strength so that they were relatively much easier to attract more visitors, construct more science and technology museums, and organize more relevant activities, which is also supported by previous work [ 43 ].…”

“…The higher education system is composed of two aspects, namely higher education input and higher education output. The aspect of higher education input, which reflects the resource devotion into higher education industry, is composed of 5 indices; in detail, the indices of the number of teachers, the number of students, and the annual budget, and the number of higher education institutes reflect the input quantity from the human resources, financial, and existence carrier perspectives [ 3 , 56 ]; the index of the annual budget per student reflects the input quality by evaluating the ratio of financial perspectives [ 7 , 56 ]. The aspect of higher education output, which reflects the outcomes of higher education activities, is composed of 3 indices; in detail, the number of publications, the number of science and technology projects, and the number of scientific papers reflect the overall output of scientific activities from higher education institutes; these indices have been selected in previous highly cited and recognized studies and have been widely accepted to efficiently and effectively to assess higher education output [ 3 , 7 ].…”

The COVID-19 Pandemic as an Opportunity to Foster the Sustainable Development of Teaching in Higher Education

“…The notion of SHED (Sustainable Higher Education Development) is all-inclusive and encompasses, for example, the interaction of higher education with the surrounding environment, economic growth, societal equity, equality, and quality enhancement. Therefore, after the identification of the definition of SHED, it is possible to determine indicators for its measurement [5].…”

Intraocular pressure of adults in a coastal province in southern China: the Fujian cross-sectional eye study

“…Socioeconomic status contains economic development level, population distribution, infrastructure status, public facilities, natural environmental factors and so on. Potential differences in economic level, education level, transportation, environmental and lifestyle factors in coastal areas (17)(18)(19)(20)(21), the higher comprehensive degrees of sustainable education development in coastal regions and the central-south China (22), and the faster economic development in coastal areas (23,24), may be important factors in the development of vision changes. Six out of nine cities in Fujian province are coastal areas, and eighty percent of Fujian Province is in a mountainous area, where transportation is inconvenient and economic and medical resources are limited, so we speculated that IOP may also have potential correlation with socioeconomic factors.…”