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Learning and Expertise in Mineral Exploration Decision-Making: An Ecological Dynamics Perspective

Author

Listed:
  • Rhys Samuel Davies

    (Business School, The University of Western Australia, Perth, WA 6009, Australia)

  • Marianne Julia Davies

    (Centre for Sport & Exercise Science, Sheffield Hallam University, Sheffield S10 2BP, UK)

  • David Groves

    (Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Perth, WA 6009, Australia)

  • Keith Davids

    (Centre for Sport & Exercise Science, Sheffield Hallam University, Sheffield S10 2BP, UK)

  • Eric Brymer

    (Faculty of Health, Gold Coast Campus, Southern Cross University, Gold Coast, QLD 4225, Australia)

  • Allan Trench

    (Business School, The University of Western Australia, Perth, WA 6009, Australia
    Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Perth, WA 6009, Australia)

  • John Paul Sykes

    (Business School, The University of Western Australia, Perth, WA 6009, Australia
    Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Perth, WA 6009, Australia)

  • Michael Dentith

    (School of Earth Sciences, The University of Western Australia, Perth, WA 6009, Australia)

Abstract

The declining discovery rate of world-class ore deposits represents a significant obstacle to future global metal supply. To counter this trend, there is a requirement for mineral exploration to be conducted in increasingly challenging, uncertain, and remote environments. Faced with such increases in task and environmental complexity, an important concern in exploratory activities are the behavioural challenges of information perception, interpretation and decision-making by geoscientists tasked with discovering the next generation of deposits. Here, we outline the Dynamics model, as a diagnostic tool for situational analysis and a guiding framework for designing working and training environments to maximise exploration performance. The Dynamics model is based on an Ecological Dynamics framework, combining Newell’s Constraints model, Self Determination Theory, and including feedback loops to define an autopoietic system. By implication of the Dynamics model, several areas are highlighted as being important for improving the quality of exploration. These include: (a) provision of needs-supportive working environments that promote appropriate degrees of effort, autonomy, creativity and technical risk-taking; (b) an understanding of the wider motivational context, particularly the influence of tradition, culture and other ‘forms of life’ that constrain behaviour; (c) relevant goal-setting in the design of corporate strategies to direct exploration activities; and (d) development of practical, representative scenario-based training interventions, providing effective learning environments, with digital media and technologies presenting decision-outcome feedback, to assist in the development of expertise in mineral exploration targeting.

Suggested Citation

  • Rhys Samuel Davies & Marianne Julia Davies & David Groves & Keith Davids & Eric Brymer & Allan Trench & John Paul Sykes & Michael Dentith, 2021. "Learning and Expertise in Mineral Exploration Decision-Making: An Ecological Dynamics Perspective," IJERPH, MDPI, vol. 18(18), pages 1-18, September.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9752-:d:637112
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    References listed on IDEAS

    as
    1. Guj, Pietro, 2008. "Statistical considerations of progressive value and risk in mineral exploration," Resources Policy, Elsevier, vol. 33(3), pages 150-159, September.
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    3. Kate Crawford & Ryan Calo, 2016. "There is a blind spot in AI research," Nature, Nature, vol. 538(7625), pages 311-313, October.
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