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

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.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-7F7D-9 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-7F80-3
Genre: Paper

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arXiv:2402.01580.pdf (Preprint), 257KB
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 Creators:
Denny, Paul1, Author
Gulwani, Sumit1, Author
Heffernan, Neil T.1, Author
Käser, Tanja1, Author
Moore, Steven1, Author
Rafferty, Anna N.1, Author
Singla, Adish1, Author                 
Affiliations:
1Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society, ou_2541698              

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Free keywords: Computer Science, Computers and Society, cs.CY,Computer Science, Artificial Intelligence, cs.AI
 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.

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Language(s): eng - English
 Dates: 2024-02-022024-02-062024
 Publication Status: Published online
 Pages: 10 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 2402.01580
URI: https://arxiv.org/abs/2402.01580
BibTex Citekey: Denny2402.01580
 Degree: -

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