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The Scaffolded AI Literacy (SAIL) Framework: Results of a Delphi Study for Equitable AI Literacy Framework Design in Education

aut.relation.articlenumber100584
aut.relation.endpage100584
aut.relation.journalComputers and Education: Artificial Intelligence
aut.relation.startpage100584
dc.contributor.authorMacCallum, Kathryn
dc.contributor.authorParsons, David
dc.contributor.authorMohaghegh, Mahsa
dc.date.accessioned2026-03-30T20:35:55Z
dc.date.available2026-03-30T20:35:55Z
dc.date.issued2026-03-24
dc.description.abstractDevelopments in AI technologies and their increasing use in education have prompted ongoing interest in the development of generally applicable AI literacy frameworks to ensure equity of access to knowledge, skills, and understanding. Researchers have investigated the components of AI literacy, how they can be structured, and how they can be developed in educators and learners. Despite much work in this area, and the opportunities and challenges presented by generative AI technologies, most recent frameworks have been confined to those that simply aggregate older ideas from the literature or those that focus on non-generalisable contexts. Few existing frameworks provide novel perspectives on generic approaches to AI literacy that also support equitable, scaffolded competency development for all learners, regardless of context. In contrast, this article reports on a Delphi study that led to the creation of the Scaffolded AI Literacy (SAIL) framework, which is broadly applicable across contexts but also accessible enough to be easily assimilated into the curriculum. Unlike many other frameworks, it provides a scaffolded pathway through competency levels that can be applied across all ages and stages of education and helps to address second- and third-level digital divides. This article details how the Delphi study unfolded, the key decisions that were made during the process, the resulting framework, and how it may contribute to equitable access to AI literacies.
dc.identifier.citationComputers and Education: Artificial Intelligence, ISSN: 2666-920X (Print), Elsevier BV, 100584-100584. doi: 10.1016/j.caeai.2026.100584
dc.identifier.doi10.1016/j.caeai.2026.100584
dc.identifier.issn2666-920X
dc.identifier.urihttp://hdl.handle.net/10292/20827
dc.languageen
dc.publisherElsevier BV
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S2666920X26000469
dc.rights2026 The Authors. Published by Elsevier Ltd. Note: This article is available under the Creative Commons CC-BY-NC license and permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
dc.rights.accessrightsOpenAccess
dc.subject3904 Specialist studies in education
dc.subject4601 Applied computing
dc.subject4602 Artificial intelligence
dc.subjectArtificial Intelligence
dc.subjectAI Literacy
dc.subjectDigital Divide
dc.subjectEquity
dc.subjectFramework
dc.subjectScaffolding
dc.titleThe Scaffolded AI Literacy (SAIL) Framework: Results of a Delphi Study for Equitable AI Literacy Framework Design in Education
dc.typeJournal Article
pubs.elements-id757393

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