Shuggi Isabelle M, Oh Hyuk, Wu Helena, Ayoub Maria J, Moreno Arianna, Shaw Emma P, Shewokis Patricia A, Gentili Rodolphe J
Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA.
Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA.
Neuroscience. 2019 Dec 15;423:232-248. doi: 10.1016/j.neuroscience.2019.07.001. Epub 2019 Jul 18.
The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the relationship between motor behavior and mental workload or self-efficacy in a performance context, a fairly limited effort focused on the combined examination of these notions during learning. Thus, this study aimed to examine their concomitant dynamics during the learning of a novel reaching skill practiced throughout multiple sessions. Individuals had to learn to control a virtual robotic arm via a human-machine interface by using limited head motion throughout eight practice sessions while motor performance, mental workload, and self-efficacy were assessed. The results revealed that as individuals learned to control the robotic arm, performance improved at the fastest rate, followed by a more gradual reduction of mental workload and finally an increase in self-efficacy. These results suggest that once the performance improved, less cognitive-motor resources were recruited, leading to an attenuated mental workload. Considering that attention is a primary cognitive resource driving mental workload, it is suggested that during early learning, attentional resources are primarily allocated to address task demands and not enough are available to assess self-efficacy. However, as the performance becomes more automatic, a lower level of mental workload is attained driven by decreased recruitment of attentional resources. These available resources allow for a reliable assessment of self-efficacy resulting in a subsequent observable change. These results are also discussed in terms of the application to the training and design of assistive technologies.
人类学习新运动技能的能力取决于认知 - 运动资源的有效参与,这可通过心理负荷以及心理机制(如自我效能感)来反映。虽然众多研究在表现情境中考察了运动行为与心理负荷或自我效能感之间的关系,但在学习过程中对这些概念进行综合考察的研究相对较少。因此,本研究旨在考察在多次练习中学习一种新的伸手技能时它们的伴随动态变化。个体必须通过人机界面,利用有限的头部运动来学习控制虚拟机器人手臂,共进行八次练习,并同时评估运动表现、心理负荷和自我效能感。结果显示,随着个体学会控制机器人手臂,表现提升速度最快,随后心理负荷逐渐降低,最后自我效能感增强。这些结果表明,一旦表现得到改善,所招募的认知 - 运动资源就会减少,从而导致心理负荷减轻。鉴于注意力是驱动心理负荷的主要认知资源,建议在早期学习过程中,注意力资源主要用于满足任务需求,而没有足够资源来评估自我效能感。然而,随着表现变得更加自动化,由于注意力资源的招募减少,心理负荷水平降低。这些可用资源使得能够可靠地评估自我效能感,从而导致随后可观察到的变化。还从这些结果在辅助技术训练和设计中的应用角度进行了讨论。