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Cognitive control, intentions, and problem solving in skill learning
Wayne Christensen1, Kath Bicknell2
1Philosophy, University of Barcelona, Barcelona, Spain.
Synthese
|November 7, 2022
Summary
Inexperienced individuals demonstrate complex on-the-fly problem-solving in skilled action, challenging traditional skill theories. The Mesh theory explains this adaptability through developing cognitive abilities and interplay between cognitive and automatic mechanisms.
Area of Science:
- Cognitive Psychology
- Motor Skill Acquisition
- Human-Computer Interaction
Background:
- Classical theories struggle to explain rapid, complex adjustments in skilled action.
- Existing models inadequately account for on-the-fly problem-solving in dynamic environments.
Purpose of the Study:
- To investigate flexibility and problem-solving in skilled action using a mountain biking study.
- To further develop and explain the Mesh theory of skill acquisition and control.
- To examine the role of cognitive and automatic mechanisms in adapting to new conditions.
Main Methods:
- Field study involving a learner mountain bike rider adapting to technique and equipment changes.
- Analysis of 'on-the-fly' problem-solving capabilities in response to novel situations.
- Theoretical development of the Mesh model, incorporating causal representation and metacognitive awareness.
Main Results:
- Inexperienced individuals exhibited significant on-the-fly problem-solving abilities.
- Adjustments made were too complex and rapid for purely automatic or traditional cognitive processes.
- The Mesh theory provides a viable explanation for observed adaptive behaviors in skilled action.
Conclusions:
- Skill learning involves developing specific cognitive abilities and an interplay between cognitive and automatic control.
- Intentions in high-risk situations can be more labile than previously modeled.
- Social and cultural learning are critical for developing complex skills and adaptive problem-solving.
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