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混合观察通过对模型性能的更好估计有利于运动学习。

Mixed observation favors motor learning through better estimation of the model's performance.

作者信息

Andrieux Mathieu, Proteau Luc

机构信息

Département de kinésiologie, Université de Montréal, Station Downtown, P.O. Box 6128, Montréal, QC, H3C 3J7, Canada.

出版信息

Exp Brain Res. 2014 Oct;232(10):3121-32. doi: 10.1007/s00221-014-4000-3. Epub 2014 Jun 5.

DOI:10.1007/s00221-014-4000-3
PMID:24897947
Abstract

Observation contributes to motor learning. It was recently demonstrated that the observation of both a novice and an expert model (mixed observation) resulted in better learning of a complex spatio-temporal task than the observation of either a novice or an expert model alone. In the present study, we sought to determine whether the advantage of mixed observation resulted from the development of a better error detection mechanism. The results revealed that mixed observation resulted in a better estimation of the model's performance than that with other regimens of observation. The results also suggest that observational learning is improved when observation with knowledge of the results (KR) is followed by an observation phase without KR.

摘要

观察有助于运动学习。最近有研究表明,观察新手和专家模型(混合观察)比单独观察新手或专家模型能更好地学习复杂的时空任务。在本研究中,我们试图确定混合观察的优势是否源于更好的错误检测机制的发展。结果显示,与其他观察方式相比,混合观察能更好地估计模型的表现。结果还表明,当有结果反馈(KR)的观察之后紧接着是无KR的观察阶段时,观察学习会得到改善。

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