Cited by 325Global Educational Policies and ReformsGlobal Education Systems and PoliciesDigital Education and Society

An OECD Learning Framework 2030

OECD·2019·Arts, Research, Innovation and Society

Integrity signals

Registry

Crossref · 10.1007/978-3-030-26068-2_3

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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Claims other papers make about this one

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  • The traditional knowledge-skills-attitudes/values outcomes framework reinforces an acquisition metaphor of learning and is insufficient for capturing the complex, generative processes facilitated by GenAI.

    “Likewise, the traditional knowledge-skills-attitudes/values outcomes framework [55] reinforces an acquisition metaphor of learning. This perspective, which views learning as the accumulation of discrete information, is insufficient for capturing the complex, generative processes facilitated by GenAI.”

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Authors
OECD
Corresponding author
OECD
Venue
Arts, Research, Innovation and Society
Published
2019
Pages
23-35
ISSN
  • 2626-7683 (ISSN-L)
  • 2626-7691
OpenAlex
W4234823775
Cited by
325
References
1
Citations by year
2026: 90 · 2025: 101 · 2024: 52 · 2023: 29 · 2022: 27 · 2021: 18 · 2020: 7 · 2019: 1
FWCI
133.08
Type
book chapter
Language
en
Open access
closed
Locations
Arts, research, innovation and society (publishedVersion)
Topics
  • Social Sciences › Political Science and International Relations › Global Educational Policies and Reforms
  • Social Sciences › Education › Global Education Systems and Policies
  • Physical Sciences › Computer Science › Information Systems › Digital Education and Society
Keywords
Education 2030, learning framework, learner agency, transformative competencies, future skills, curriculum design principles, future of education, youth, OECD

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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