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Cited by 386

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

Learning Through Work Experience

Guile, David, Griffiths, Toni·2001·Journal of Education and Work

Abstract

How students learn and develop through work experience is here analysed. We draw upon contemporary learning theory, recent developments in the adult education and curriculum theory in developing a critique of current thinking and explore how far this provides the basis for a new pedagogic model for supporting learning through work experience. We discuss the concept of 'context' and the learning which occurs within and between the different contexts of education and work and argue that most models of work experience have either ignored the influence of context upon learning or have approached this issue mechanistically. New curriculum frameworks are needed to and to allow work in all of its forms to be used as a basis for the development of knowledge, skills and identity. We present a typology of work experience which identifies models of work experience, including a model which embodies the concept of 'connectivity'. We suggest that this may provide the basis for a productive and useful relationship between formal and informal learning.

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Metadata

Authors
Guile, D., & Griffiths, T.
Venue
Journal of Education and Work
Published
2001-02
Volume
14
Issue
1
Pages
113-131
ISSN
  • 1363-9080 (ISSN-L)
  • 1469-9435
OpenAlex
W2101145614
Cited by
386
References
37
FWCI
17.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Learning Through Work Experience. https://app.cochat.ai/papers/10.1080/13639080020028738
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Guile, D., & Griffiths, T. (2001). Learning Through Work Experience. Journal of Education and Work. https://doi.org/10.1080/13639080020028738

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.