The recent surge in generative AI technologies, such as large language models and diffusion models, have 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：近期生成式人工智能技术（如大语言模型与扩散模型）的蓬勃发展，推动了人工智能在科学、金融、教育等领域的应用进程。与此同时，自适应学习作为教育领域备受关注的概念，已被证实能有效提升学生的学习效率。本立场论文旨在阐明这两种方法的交叉研究——即将生成式人工智能与自适应学习理念相结合。通过探讨该领域的优势、挑战与潜力，我们论证这一融合将有力推动教育领域下一阶段学习形态的发展。