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生成式人工智能（AIGC）赋能下的师范生教育实训新范式

A New Paradigm for Pre-service Teacher Education and Training Empowered by Generative Artificial Intelligence (AIGC)

Progress in Social Sciences / 2025,7(9): 679-687 / 2025-09-16 6 2

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• Authors: 陈丹凤
• Information:

  上海外国语大学贤达经济人文学院，上海

• Keywords:
  Generative artificial intelligence; Teacher preparation programs in normal universities; Educational practice training
  生成式人工智能; 师范生教育; 教育实训
• Abstract: Based on situated learning theory, this study addresses issues in traditional pre-service teacher practical education—such as one-way knowledge indoctrination, insufficient interaction, and subjective and delayed evaluation— by taking the “Family Education in Kindergarten” course as an example. It explores effective pathways for AIGCenabled reform in pre-service teacher practical education and innovatively constructs a dynamic interactive educational decision-making training paradigm powered by AIGC. This paradigm utilizes AIGC to create educational conflict scenarios and multi-agent roles. Students interact with virtual characters and propose educational decisions in real time, while AIGC dynamically adjusts the scenario based on these decisions until conflicts are resolved. Additionally, AIGC generates expert roles to evaluate students’ decisions and provide personalized suggestions. The study elaborates on a complete closed-loop training process: from jointly building an AI-based family education case repository by teachers and students, to virtual training, human-AI collaborative review, real-group situational acting exercises, and finally returning to AI-generated virtual scenarios to identify and address gaps. This new paradigm offers pre-service teachers an ethically risk-free, dynamically interactive platform for educational decision-making training. It enables immersive practice of educational skills with immediate evaluative feedback, accelerates the transformation and deep application of educational knowledge and skills, and provides valuable insights for the reform of pre-service teacher practical education. Furthermore, it promotes the deep integration of artificial intelligence technology in teacher training and holds significant implications for enhancing the educational practical abilities and professional competence of preservice teachers. 基于情境学习理论，本研究针对传统师范生实践教育中单向灌输、交互不足及评价主观滞后等问题，以“幼儿园家庭教育”课程为例，探索AIGC赋能师范生实践教育改革的有效路径，创新构建基于AIGC的动态交互教育决策实训新范式。该范式利用AIGC创建教育冲突情境与多智能体角色，学生与虚拟角色互动并实时提出教育决策，AIGC依据决策动态调整场景直至冲突解决，还能生成专家角色评价学生决策并提供个性化建议。研究详细阐述了从师生共建AI家庭教育案例素材池，到虚拟实训、人机协同复盘、真人小组情境演绎实训，最后回归AI虚拟情境查漏补缺的完整闭环实训过程。这一新范式为师范生提供无伦理风险、动态互动的教育决策实训平台，使其沉浸式训练教育技能并即时获得评价反馈，加速教育知识与技能的转化及深化应用，为师范生实践教育改革提供有益借鉴，推动人工智能技术在师范教育领域的深度融合，对提升师范生教育实践能力和专业素养意义重大。
• DOI: https://doi.org/10.35534/pss.0709115
• Cite: 陈丹凤．生成式人工智能（AIGC） 赋能下的师范生教育实训新范式［J］．社会科学进展，2025，7（9）：679-687.