The recent surge in generative AI technologies, such as large language models and diffusion models, has boosted the development of AI applications in various domains, including science, finance, and education. Concurrently, adaptive learning, a concept that has gained substantial interest in the educational sphere, has proven its efficacy in enhancing students' learning efficiency. In this position paper, we aim to shed light on the intersectional studies of these two methods, which combine generative AI with adaptive learning concepts. By presenting discussions about the benefits, challenges, and potentials in this field, we argue that this union will contribute significantly to the development of the next-stage learning format in education.

翻译：近期，以大规模语言模型和扩散模型为代表的生成式人工智能技术迅猛发展，推动了人工智能在科学、金融及教育等多个领域的应用拓展。与此同时，在教育领域备受关注的自适应学习理念，已被证实能有效提升学生的学习效率。本立场文件旨在聚焦这两种方法的交叉研究，探讨将生成式人工智能与自适应学习理念相结合的路径。通过分析该领域的优势、挑战与潜力，我们认为二者的融合将为下一代教育学习模式的发展作出重要贡献。