arXiv Open Access 2024

Bringing Generative AI to Adaptive Learning in Education

Hang Li Tianlong Xu Chaoli Zhang Eason Chen Jing Liang +4 lainnya
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Abstrak

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.

Penulis (9)

H

Hang Li

T

Tianlong Xu

C

Chaoli Zhang

E

Eason Chen

J

Jing Liang

X

Xing Fan

H

Haoyang Li

J

Jiliang Tang

Q

Qingsong Wen

Format Sitasi

Li, H., Xu, T., Zhang, C., Chen, E., Liang, J., Fan, X. et al. (2024). Bringing Generative AI to Adaptive Learning in Education. https://arxiv.org/abs/2402.14601

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓