  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.
