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Rethinking Situated Learning: Participation and Communities of Practice in the UK Fire and Rescue Service

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  • James Brooks

    (University of Leeds, UK)

  • Irena Grugulis

    (University of Leeds, UK)

  • Hugh Cook

    (University of Leeds, UK)

Abstract

Legitimate peripheral participation is the bedrock of situated learning. It involves the novice or newcomer acquiring skills through work in a community of practice (CoP). It is generally assumed that CoP learning involves novices moving in a centripetal manner from periphery to core, gaining skills and knowledge from established workers before becoming full members of the community. This article draws on qualitative research in Northern Fire, one of the UK’s largest fire and rescue services, to challenge the idea that novices’ learning progression is linear and sequential, highlighting their fundamental importance in CoPs. It argues that learning is radial, with established workers learning from novices, just as novices learn from established workers. The novices contributed to group dynamics passively, simply by being there; and actively, through their own skills and theoretical knowledge. When funding cuts and austerity curtailed recruitment, the absence of novice firefighters hindered CoP learning.

Suggested Citation

  • James Brooks & Irena Grugulis & Hugh Cook, 2020. "Rethinking Situated Learning: Participation and Communities of Practice in the UK Fire and Rescue Service," Work, Employment & Society, British Sociological Association, vol. 34(6), pages 1045-1061, December.
  • Handle: RePEc:sae:woemps:v:34:y:2020:i:6:p:1045-1061
    DOI: 10.1177/0950017020913225
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    References listed on IDEAS

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    1. Alan Felstead & Francis Green & Nick Jewson, 2012. "An analysis of the impact of the 2008–9 recession on the provision of training in the UK," Work, Employment & Society, British Sociological Association, vol. 26(6), pages 968-986, December.
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    3. John Seely Brown & Paul Duguid, 1991. "Organizational Learning and Communities-of-Practice: Toward a Unified View of Working, Learning, and Innovation," Organization Science, INFORMS, vol. 2(1), pages 40-57, February.
    4. I. Gijbels & A. Pope & M. P. Wand, 1999. "Understanding exponential smoothing via kernel regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 39-50.
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    Cited by:

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