Hard Transition of Decision-making Models in HEIs of China: The Lack of Data Culture

Year: 2019

Author: Zhang, Junchao, Lu, Mengqi

Type of paper: Abstract refereed

Over the past 20 years, China's higher education has undergone tremendous development. The enrollment rate of higher education was 15% in 2002 and it reached 48.1% in 2018.With the rapid expansion of student scale as well as the enlargement of university autonomy, how can universities promote the rational allocation of resources through scientific decision-making to ensure the education quality and orderly development is becoming the focus of attention.
To improve the quality and efficiency of university decision-making, the transformation from the traditional bureaucracy to evidence-based decision-making model becoming an urgent need,but this transition seems particularly difficult in China.In order to investigate the difficulties and reasons,a survey about decision-making models in HEIs was conducted in 854 4-year HEIs in China in 2015, and the relevant leaders of 64 universities were interviewed during 2013-2018 which focused on the process and problems of decision-making in HEIs of China. On the basis of questionnaire and interviews, this study analyses the current situation of decision-making models in China's HEIs, and then tries to explore the possibilities and countermeasures for the transition from the bureaucracy to the evidence-based model.
It is found that the lack of data awareness of decision-makers, the lack of comprehensive validity and authenticity of data collection, the lack of data mining and analytic technology for institutional research are the status quo of decision-making in HEIs. The government-led resource allocation, as well as the inertia of bureaucratic tradition are the main reasons which hinders the transformation of decision-making mode in HEIs.However, with the government and society increasing strengthened accountability to universities,as well as the rapid development of information technology in China, it has become possible to cultivate a good data culture in HEIs. The study puts forward relevant countermeasures to help the transition of decision-making model such as accelerating the construction of different levels of databases, encouraging third-party evaluation agencies’ development, improving data mining and analysis techniques for institutional research practitioners etc.. But how to solve the specific problems faced by different universities is still worth further discussion.