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Interdisciplinary approaches for deep learning

Permanent lenke
https://hdl.handle.net/10037/18337
DOI
https://doi.org/10.46364/njmlm.v6i1.425
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article.pdf (326.6Kb)
Publisert versjon (PDF)
Dato
2018-08-06
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Holmbukt, Tove Elinor
Sammendrag
The Norwegian national curricula for primary and secondary education are currently undergoing reforms, which will be implemented from 2020. The underlying documents regarding the reform are studied in this article, and conclude that learners should be provided with beneficial conditions to develop values and knowledge to manage their lives well. An essential notion is ‘deep learning’ whose implication seems to be acquisition of more in-depth knowledge and understanding of subject areas. The present article argues that learning is about making connections, whether it be noticing connections between isolated subject areas, or, perhaps, between theoretical concepts and practical tasks. Further, the article argues that interdisciplinary approaches extend knowledge as they typically work across subject areas and support learners in discovering disciplinary connections. Claims are made that interdisciplinary strategies have the capacities to facilitate various learning styles, motivation and variation. Such facilitations are required in education that is democratic and which targets all learners. Hence, the article argues that interdisciplinarity and deep learning are concepts that work together, and in which critical thinking and creativity are core elements. The argumentation is based on the four official documents NOU 2014:7, NOU 2015:8, Report to the Storting 28, The Standing Committee on Education, Research and Church Affairs’ recommendation to the Storting 19 S, as well as, data findings discussed in a master study which discusses teachers’ perceptions of interdisciplinarity and learning.
Forlag
Department of Foreign Languages and Translation, University of Agder
Sitering
Holmbukt TE. Interdisciplinary approaches for deep learning. Nordic Journal of Modern Language Methodology. 2018;6(1):3-24
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  • Artikler, rapporter og annet (lærerutdanning og pedagogikk) [663]
Copyright 2018 The Author(s)

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