【作 者】：
肖 君， 白庆春， 陈 沫， 陆 璐
【关 键 词 】：
在线学习； 生成式人工智能； ChatGPT
【栏 目】：
网络教育
【中文摘要】：
生成式人工智能技术通过对大规模数据编码训练，能够依据人类指令自主地生成语言或图像等内容，在不同场景中展现新型的“智慧”和“创造”能力。现阶段在学习场景中直接应用存在诸多风险，需要不断优化和升级。通过探索和研究生成式人工智能辅助个性化学习潜力场景与技术实施路径，提出生成式人工智能应用于在线学习场景需确保三个方面：（1）内容的准确性；（2）过程的可解释性；（3）个性化的联动性。为了保证人工智能的安全性和可靠性，需要建立完善的技术支持系统，以更好地服务于在线学习和教育需求。通过研究分析，以期为在线学习场景中的生成式人工智能技术规范和应用设计提供有益参考。
【英文摘要】：
Generative AI technology, through the training of large-scale data encoding, can autonomously generate content such as language or images according to human instructions, and display new "intelligent" and "creative" abilities in different scenarios. However, there are many risks associated with direct application in learning scenarios, which requires continuous optimization and upgrading. By exploring and researching the potential scenarios and technical implementation paths for generative AI-assisted personalized learning, it is proposed that three aspects must be ensured when applying generative AI in online learning scenarios: (1) content accuracy; (2) process interpretability; and (3) personalized connectivity. In order to ensure the safety and reliability of AI, it is necessary to establish a perfect technical support system to better serve the needs of online learning and education. Through the research and analysis, it is hoped that useful references can be provided for the technical specification and application design of generative AI in online learning scenarios.