Understanding data-driven decision making approach in Chinese higher education through the lens of Bakers model

Autor: Usama Kalim, Saira Bibi
Rok vydání: 2023
Předmět:
Zdroj: International Journal of Chinese Education. 12:2212585X2311621
ISSN: 2212-5868
2212-585X
DOI: 10.1177/2212585x231162120
Popis: Making decisions based on data is evolving in higher education worldwide. Higher education institutions (HEIs) in China are also adopting this trend of data-driven decision making to improve the quality standards in higher education. However, the data-driven decision making (DDDM) approach has recently evolved in China, and the data based decision-making models are still immature. Therefore, this study investigates the DDDM approach of Chinese HEIs through an established theoretical data model lens to highlight some of its immaturities and weaknesses for improvement. The study analyzes the DDDM approach in Chinese higher education by exploring the data-mining practices of a case study university. A leading Chinese university has been taken as a sample case study. The multiple interviews have been taken at both faculty and university levels to explore the DDDM practices. The results suggest that the Chinese university DDDM approach is consistent with the established Bakers model. However, the scope of data mining is limited in some areas when compared with the theoretical model. The university is also behind in using advanced applications and software required for DDDM. The results of this study highlight the DDDM approach in Chinese higher education and some of its immaturity. The results can be used to improve the DDDM approach in Chinese HEIs further to ensure more effective and efficient decision-making.
Databáze: OpenAIRE