【摘要】 在教育数字化转型持续推进的背景下,人工智能正深度重构个性化教学的实现机制。该研究以美国、英国和芬兰三国的主要政策和实践为主要分析对象,围绕基本思路、实践行动和典型项目进行文献分析。跨案例综合分析表明,三国的主要推进路径表现为教育政策引领、学习路径重构、教育资源适配、教师专业赋能、学生素养培育与公平普惠保障等六方面。基于上述研究发现,考量我国国情与发展现状,提出优化顶层设计与多部门协同、深化行为档案驱动机制、完善智能资源生成与适配体系、系统强化师生数字能力与AI素养、构建协同治理的数字公平生态等五项针对性的实施策略,以期为我国AI赋能大规模因材施教的本土化路径探索提供比较视野与实践启示。更多还原

【Abstract】 Against the backdrop of the ongoing educational digital transformation, Artificial Intelligence(AI) is fundamentally reconstructing the operational mechanisms of personalized instruction. This study takes the major policies and practices of the United States, the United Kingdom, and Finland as its primary analytical objects, conducting document-analysis centered on their fundamental approaches, practical actions, and representative projects. Cross-case synthesis reveals that the principal advancement pathways in these three countries manifest in six key dimensions:educational policy leadership, learning pathway reconstruction, educational resource adaptation, teacher professional empowerment, student competency cultivation, and equity and universal benefit safeguards. Building upon these research findings and considering China’ s national context and developmental status, this study proposes five targeted strategic recommendations: optimizing top-level design and multidepartmental coordination; deepening learner-profile-driven mechanisms; refining intelligent resource generation and adaptation systems; systematically strengthening the digital capabilities and AI literacy of both teachers and students; and constructing a collaboratively governed digital equity ecosystem. These recommendations aim to provide comparative perspectives and practical insights for exploring localized pathways for AIenabled personalized instruction in China.更多还原