【作 者】：
李世瑾， 李 睿， 顾小清
【关 键 词 】：
多主体仿真； 人工智能教育； 复杂系统； 理论前瞻； 理论进路
【栏 目】：
理论探讨
【中文摘要】：
人工智能教育是涵括教育主体与社会环境的复杂动态系统。为有序推演人工智能教育生态的内生机理和实践路向，并从根源上规避其风险弊端，研究将多主体仿真引入人工智能教育研究，详尽阐释人工智能教育仿真的思想内核，同时采用案例研究方法，展现人工智能教育仿真的操作过程及重难点。研究发现，系统科学的建模思想、协同演化的动态过程和清晰严密的因果机制是人工智能教育仿真的思想内核，多层次和动态化是人工智能教育仿真的关键抓手，通过引入多元化的仿真数据和探索动态化的仿真规律，能够捕获最优效益的行动方向与干预措施，科学指引人工智能教育变革的理论前瞻，最大限度地保证质量提升。鉴于此，提出人工智能教育仿真的理论进路与发展建议：强化人工智能教育仿真的顶层设计，推动人工智能教育仿真的范式转型，打造人工智能教育仿真的实践系统，避免人工智能教育仿真方法的误用。
【英文摘要】：
Artificial intelligence education is a complex dynamic system that includes educational subjects and social environment. In order to deduce the endogenous mechanism and practical directions of AI education ecology in an orderly manner and avoid its risks and drawbacks from the root, this study introduces multi-subject simulation into AI education research and explains the ideological core of AI education simulation in detail. In addition, this study adopts the case study method to show the operation process and important and difficult points of AI education simulation. This study finds that the idea of system science modelling, the dynamic process of collaborative evolution and the clear and rigorous cause-and-effect mechanism are the ideological core of AI education simulation, and the multi-level and dynamic nature are the key grips of AI education simulation. By introducing diversified simulation data and exploring dynamic simulation laws, it is possible to capture the direction of action and intervention measures with optimal benefits, and scientifically guide the theoretical foresight of AI education reform to maximize the quality of advancement. In view of this, the theoretical progression and development suggestions of AI education simulation are proposed: strengthening the top-level design of AI education simulation, promoting the paradigm transformation of AI education simulation, building a practical system of AI education simulation, and avoiding the misuse of AI education simulation methods.