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Paper

Generative AI for Education (GAIED): Advances, Opportunities, and Challenges

MPS-Authors

Denny,  Paul
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

Gulwani,  Sumit
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

Heffernan,  Neil T.
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

Käser,  Tanja
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

Moore,  Steven
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

Rafferty,  Anna N.
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

/persons/resource/persons216578

Singla,  Adish       
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

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arXiv:2402.01580.pdf
(Preprint), 257KB

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Citation

Denny, P., Gulwani, S., Heffernan, N. T., Käser, T., Moore, S., Rafferty, A. N., et al. (2024). Generative AI for Education (GAIED): Advances, Opportunities, and Challenges. Retrieved from https://arxiv.org/abs/2402.01580.


Cite as: https://hdl.handle.net/21.11116/0000-000E-7F7D-9
Abstract
This survey article has grown out of the GAIED (pronounced "guide") workshop
organized by the authors at the NeurIPS 2023 conference. We organized the GAIED
workshop as part of a community-building effort to bring together researchers,
educators, and practitioners to explore the potential of generative AI for
enhancing education. This article aims to provide an overview of the workshop
activities and highlight several future research directions in the area of
GAIED.