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Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions
Journal article   Peer reviewed

Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions

Isabelle M. Shuggi, Hyuk Oh, Helena Wu, Maria J. Ayoub, Arianna Moreno, Emma P. Shaw, Patricia A. Shewokis and Rodolphe J. Gentili
Neuroscience, v 423, pp 232-248
15 Dec 2019
DOI: https://doi.org/10.1016/j.neuroscience.2019.07.001
PMID: 31325564

Abstract

assistive technologies human-robot interface mental workload reaching movements self-efficacy visuomotor learning
•Throughout learning, performance improves faster than attenuation of mental workload.•During learning mental workload is reduced faster than self-efficacy improvements.•Skill learning results in the emergence of a cognitive-psycho-motor efficiency. 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.

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Domestic collaboration
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Neurosciences
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