Williams Camille K, Tremblay Luc, Carnahan Heather
Rehabilitation Sciences Institute, University of Toronto, Toronto ON, Canada.
Faculty of Kinesiology and Physical Education, University of Toronto, Toronto ON, Canada.
Front Psychol. 2016 Dec 26;7:2010. doi: 10.3389/fpsyg.2016.02010. eCollection 2016.
Researchers in the domain of haptic training are now entering the long-standing debate regarding whether or not it is best to learn a skill by experiencing errors. Haptic training paradigms provide fertile ground for exploring how various theories about feedback, errors and physical guidance intersect during motor learning. Our objective was to determine how error minimizing, error augmenting and no haptic feedback while learning a self-paced curve-tracing task impact performance on delayed (1 day) retention and transfer tests, which indicate learning. We assessed performance using movement time and tracing error to calculate a measure of overall performance - the speed accuracy cost function. Our results showed that despite exhibiting the worst performance during skill acquisition, the error augmentation group had significantly better accuracy (but not overall performance) than the error minimization group on delayed retention and transfer tests. The control group's performance fell between that of the two experimental groups but was not significantly different from either on the delayed retention test. We propose that the nature of the task (requiring online feedback to guide performance) coupled with the error augmentation group's frequent off-target experience and rich experience of error-correction promoted information processing related to error-detection and error-correction that are essential for motor learning.
触觉训练领域的研究人员目前正在参与一场长期存在的争论，即通过体验错误来学习一项技能是否是最佳方式。触觉训练范式为探索关于反馈、错误和物理引导的各种理论在运动学习过程中如何相互交叉提供了肥沃的土壤。我们的目标是确定在学习一项自定节奏的曲线追踪任务时，最小化错误、增加错误和不给予触觉反馈如何影响延迟（1天）保持和迁移测试中的表现，这些测试表明学习情况。我们使用运动时间和追踪误差来评估表现，以计算整体表现的一个指标——速度准确性成本函数。我们的结果表明，尽管在技能习得过程中表现最差，但在延迟保持和迁移测试中，增加错误组的准确性（而非整体表现）明显优于最小化错误组。对照组的表现介于两个实验组之间，但在延迟保持测试中与任何一组均无显著差异。我们认为，任务的性质（需要在线反馈来指导表现）加上增加错误组频繁的偏离目标体验和丰富的纠错经验，促进了与错误检测和纠错相关的信息处理，而这对于运动学习至关重要。
