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Faculty of Medical Sciences

The Effect of Learning at Different Task Difficulties on Resisting a Perturbation

Latorre Erezuma, U. (Unai) (2019) The Effect of Learning at Different Task Difficulties on Resisting a Perturbation. thesis, Human Movement Sciences.

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Abstract

Introduction: External forces perturb our motor actions while performing ADL leading to injuries and accidents. Motor skill automatization is believed to help us cope with these physical perturbations by making us more robust against them. In the current study it is investigated how practice conditions, specifically experienced task difficulty, influence visuomotor learning and resistance against unexpected force perturbations. Methods: Healthy young participants (N=20) learned to trace a star as fast and accurate as possible in easy and hard conditions determined by the star bandwidth. Before and after practice, performance (i.e. movement time, percentage of errors, normalized jerk) was measured during the tracing of a neutral star. To assess the robustness of performance we simulated a physical perturbation during the neutral star tracing task by introducing a sudden force field produced by the joystick participants used to perform the task. Results: Task difficulty affected the experienced cognitive load during practice as indicated by the NASA-TLX. No significant differences in motor acquisition and resistance against the perturbation were found between the easy and the hard group. Both groups improved performance with and without perturbation over time. Conclusions: Task difficulty during practice did not have a mediating role on motor learning and robustness against external force interference. Learning without (or less) errors seems equally effective as learning with errors. Both learning with and without (or less) error seems equally effective. It seems that the optimal challenge framework fails to explain how learning occurs. The learning processes should focus on how much information is processed by the learners instead of focusing how much information the task offers. Keywords: Motor Learning, Task Automatization, Robustness Against Perturbation, Fine Motor-Task

Item Type: Thesis (UNSPECIFIED)
Supervisor name: Murgia, dr. A. and Caljouw, dr. S.R.
Faculty: Medical Sciences
Date Deposited: 23 May 2022 08:46
Last Modified: 23 May 2022 08:46
URI: https://umcg.studenttheses.ub.rug.nl/id/eprint/3417

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