The adoption of Artificial Intelligence in Education (AIED) holds the promise of revolutionizing educational practices by offering personalized learning experiences, automating administrative and pedagogical tasks, and reducing the cost of content creation. However, the lack of standardized practices in the development and deployment of AIED solutions has led to fragmented ecosystems, which presents challenges in interoperability, scalability, and ethical governance. This article aims to address the critical need to develop and implement industry standards in AIED, offering a comprehensive analysis of the current landscape, challenges, and strategic approaches to overcome these obstacles. We begin by examining the various applications of AIED in various educational settings and identify key areas lacking in standardization, including system interoperability, ontology mapping, data integration, evaluation, and ethical governance. Then, we propose a multi-tiered framework for establishing robust industry standards for AIED. In addition, we discuss methodologies for the iterative development and deployment of standards, incorporating feedback loops from real-world applications to refine and adapt standards over time. The paper also highlights the role of emerging technologies and pedagogical theories in shaping future standards for AIED. Finally, we outline a strategic roadmap for stakeholders to implement these standards, fostering a cohesive and ethical AIED ecosystem. By establishing comprehensive industry standards, such as those by IEEE Artificial Intelligence Standards Committee (AISC) and International Organization for Standardization (ISO), we can accelerate and scale AIED solutions to improve educational outcomes, ensuring that technological advances align with the principles of inclusivity, fairness, and educational excellence.

翻译：人工智能教育（AIED）的应用有望通过提供个性化学习体验、自动化管理与教学任务、降低内容创建成本，彻底革新教育实践。然而，AIED解决方案在开发与部署过程中缺乏标准化实践，导致生态系统碎片化，从而在互操作性、可扩展性及伦理治理方面面临挑战。本文旨在解决AIED领域亟需制定并实施行业标准的关键需求，通过全面分析当前格局、挑战及应对策略，提出克服障碍的路径。我们首先考察AIED在各类教育场景中的应用，识别标准化缺失的关键领域，包括系统互操作性、本体映射、数据集成、评估及伦理治理。随后，提出构建AIED稳健行业标准的多层级框架。此外，我们探讨了标准的迭代开发与部署方法论，通过整合实际应用中的反馈循环持续优化与调整标准。本文还强调了新兴技术与教学理论在塑造未来AIED标准中的作用。最后，为利益相关方绘制了实施这些标准的战略路线图，以促进形成协同且符合伦理的AIED生态系统。通过建立如IEEE人工智能标准委员会（AISC）及国际标准化组织（ISO）等机构发布的全面行业标准，我们能够加速并规模化AIED解决方案以改善教育成果，确保技术进步与包容性、公平性及教育卓越性原则保持一致。