Traditional models of skill learning posit that skilled action unfolds in an automatic manner and that control will prove deleterious to movement and performance proficiency. These perspectives assume that automated processes are characterised by low levels of control and vice versa. By contrast, a number of authors have recently put forward hybrid theories of skilled action which have sought to capture the close integration between fine-grained automatic motor routines and intentional states. Drawing heavily on the work of Bebko et al. (2005) and Christensen et al. (2016), we argue that controlled and automated processes must operate in parallel if skilled performers are to address the wide range of challenges that they are faced with in training and competition. More specifically, we show how skilled performers use controlled processes to update and improve motor execution in training contexts and to stabilise performance under pressurised conditions.

传统的技能学习模型假定熟练的动作以自动方式展开，而这种控制将证明对动作和表现能力有害。这些观点假设自动化流程的特点是控制水平低，反之亦然。相比之下，许多作者最近提出了熟练动作的混合理论，试图捕捉细粒度的自动运动程序和有意状态之间的紧密结合。大量借鉴 Bebko 等人的工作。(2005) 和克里斯滕森等。(2016)，我们认为，如果熟练的表演者要解决他们在培训和比赛中面临的广泛挑战，受控和自动化流程必须并行运行。进一步来说，