【作 者】：
吴南中， 李少兰， 陈明建
【关 键 词 】：
人工智能； 教师教育； 循证教育； 理论架构； 行动网络
【栏 目】：
理论探讨
【中文摘要】：
教师循证教育由于架构了教师教育理论与实践的桥梁，备受研究者关注。然而，受实践中提问不当、制证不足、取证不力、成证不良和用证不能的桎梏而推进缓慢，亟待突围。文章以人工智能作用于教师循证教育的过程为分析框架，梳理教师循证教育中人、证据和教育教学实践之间的多重关系，发挥人工智能在辅助制证、取证和用证上的作用，以此推动教师循证教育的高质量发展，并建构了基于人工智能平台、证据分类分层逻辑、内容关联管理和进化机制为基础的教师循证教育理论模型。在模型中，人工智能平台通过证据分类和内容管理，作用于教师证据获取、使用和优化的全程，最终通过人机协同的教师教育实现循证价值。要实现人工智能支持的教师教育，需要涵盖人类行动者和非人类行动者的多元行动网络，以利益为“中介点”建构循证教育联盟，在有效利用人工智能促进循证教育系列系统化、推进循证教育正规化以及互动广泛化两个支架上，形成理论与实践的双向演进并逐渐扩散。
【英文摘要】：
Evidence-based education for teachers has attracted much attention from researchers because it has bridged the gap between the theory and practice in teacher education. However, it has been slowly developed due to the shackles of improper questioning, insufficient evidence preparation, ineffective evidence collection, poor evidence preparation and inability to use evidence in practice. Based on the analysis framework of the process of AI acting on teachers' evidence-based education, this paper combs out the multiple relationships between people, evidence and educational teaching practice in teachers' evidence-based education, and gives full play to the role of AI in auxiliary evidence preparation, auxiliary evidence collection and auxiliary evidence use, so as to promote the high-quality development of teachers' evidence-based education. It also constructs a theoretical model of teacher evidence-based education on a basis of the artificial intelligence platform, evidence classification and hierarchical logic, content association management and evolution mechanism. In the model, the AI platform acts on the whole process of teacher evidence acquisition, use and optimization through evidence classification and content management, and finally realizes evidence-based value through human-computer collaborative teacher education. In order to realize teacher education supported by AI, it is necessary to build an evidence-based education alliance with interests as the "intermediary point" through a multi-action network covering human and non-human actors, and form a two-way evolution and gradual diffusion of theory and practice on the basis of effective use of AI to promote the systematization of evidence-based education series and promote the normalization and interaction of evidence-based education.