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Algorithm-Based Practice Schedule and Task Similarity Enhance Motor Learning in Older Adults

Meysam Beik,H. Taheri,Alireza Saberi Kakhki,M. Ghoshuni

Published 2020 in Journal of Motor Behavior

ABSTRACT

Abstract According to the challenge point framework, task difficulty has to be appropriate to learner skill level. The pure blocked or random practice controls the task difficulty during practice monotonically. Therefore, the purpose of this study was to investigate the effect of algorithm-based practice schedule and task similarity on motor learning in older adults. For this purpose, 60 older adults were randomly assigned into six groups of blocked-similar, algorithm-similar, random-similar, blocked-dissimilar, algorithm-dissimilar, and random-dissimilar. Sequential motor tasks were used for learning. Participants practiced absolute timing goals in similar (1350, 1500, 1650 ms) or dissimilar (1050, 1500, 1950 ms) conditions according to their practice schedule. Twenty-four hours after the acquisition phase, retention, and transfer tests were performed. Algorithm-practice was a hybrid practice schedule (blocked, serial, and random practice in forward/backward switching) that switching the schedules was according to error trial number (n ≤ 33%) in each block based on error range of absolute timing goals (± 5%). The results showed that the blocked-practice outperforms the other groups during the acquisition phase, whereas the algorithm-practice outperforms the other groups in retention and transfer in both similar and dissimilar conditions. These findings were discussed according to the challenge point framework.

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