Journal of East China Normal University(Educational Sciences) ›› 2022, Vol. 40 ›› Issue (9): 55-66.doi: 10.16382/j.cnki.1000-5560.2022.09.006

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Governance of Artificial Intelligence Education: Logical Mechanism and Practical Approach

Shijin Li, Chenglong Wang, Xiaoqing Gu   

  1. Department of Education Information Technology, East China Normal University, Shanghai 200062, China
  • Accepted:2022-05-30 Online:2022-09-01 Published:2022-08-24

Abstract:

As an endogenous force leading educational innovation, artificial intelligence not only empowers education, but also generates a series of practical challenges that cannot be ignored. Therefore, in the process of deep integration of artificial intelligence and education, scientific governance is particularly critical, and clarifying Its logical mechanism is a solid foundation for effective governance. In order to find a forward-looking and effective governance logic, it is necessary to fully consider innovative governance actions in multiple contexts. The study used international observation and case study methods, compared 12 strategic actions of artificial intelligence governance around the world, expanded the global thinking of artificial intelligence governance, and took the New Zealand artificial intelligence collaborative supervision practice project as an example to clarify the practical process and educational inspiration of artificial intelligence governance. The study found that the logical mechanism of intelligence education governance was expressed as follows. The open and inclusive system context is the prerequisite; the collaborative edification of the advocacy coalition is the backbone, and the scientific and complete supervision mechanism is the motivation guarantee. In view of this, the practical approach for artificial intelligence education governance in China are proposed. Create open and inclusive governance scenarios to promote the systematization of artificial intelligence education governance; shape diverse and synergistic governance mechanisms to enhance the effectiveness of artificial intelligence education governance; apply dynamic forecasting governance methods to ensure the foresight of artificial intelligence education governance.

Key words: artificial intelligence educational governance, logical mechanism, practical approach, international observation, case study