The promise and challenges of generative AI in education
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- dc.contributor.author Giannakos, Michail
- dc.contributor.author Azevedo, Roger
- dc.contributor.author Brusilovsky, Peter
- dc.contributor.author Cukurova, Mutlu
- dc.contributor.author Dimitriadis, Yannis
- dc.contributor.author Hernández-Leo, Davinia
- dc.contributor.author Järvelä, Sanna
- dc.contributor.author Mavrikise, Manolis
- dc.contributor.author Rienties, Bart
- dc.date.accessioned 2025-05-16T06:24:17Z
- dc.date.available 2025-05-16T06:24:17Z
- dc.date.issued 2024
- dc.description Data de publicació electrònica: 02-09-2024
- dc.description.abstract Generative artificial intelligence (GenAI) tools, such as large language models (LLMs), generate natural language and other types of content to perform a wide range of tasks. This represents a significant technological advancement that poses opportunities and challenges to educational research and practice. This commentary brings together contributions from nine experts working in the intersection of learning and technology and presents critical reflections on the opportunities, challenges, and implications related to GenAI technologies in the context of education. In the commentary, it is acknowledged that GenAI’s capabilities can enhance some teaching and learning practices, such as learning design, regulation of learning, automated content, feedback, and assessment. Nevertheless, we also highlight its limitations, potential disruptions, ethical consequences, and potential misuses. The identified avenues for further research include the development of new insights into the roles human experts can play, strong and continuous evidence, human-centric design of technology, necessary policy, and support and competence mechanisms. Overall, we concur with the general skeptical optimism about the use of GenAI tools such as LLMs in education. Moreover, we highlight the danger of hastily adopting GenAI tools in education without deep consideration of the efficacy, ecosystem-level implications, ethics, and pedagogical soundness of such practices.
- dc.format.mimetype application/pdf
- dc.identifier.citation Giannakos M, Azevedo R, Brusilovsky P, Cukurova M, Dimitriadis Y, Hernandez-Leo D, et al. The promise and challenges of generative AI in education. Behav Inf Technol. 2024 Sep 2. DOI: 10.1080/0144929X.2024.2394886
- dc.identifier.doi http://dx.doi.org/10.1080/0144929X.2024.2394886
- dc.identifier.issn 0144-929X
- dc.identifier.uri http://hdl.handle.net/10230/70423
- dc.language.iso eng
- dc.publisher Taylor & Francis
- dc.relation.ispartof Behaviour & Information Technology. 2024 Sep 2
- dc.rights © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis GroupThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the AcceptedManuscript in a repository by the author(s) or with their consent.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Generative AI in education
- dc.subject.keyword AI in education
- dc.subject.keyword Large language models
- dc.subject.keyword Commentary
- dc.title The promise and challenges of generative AI in education
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion