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Task integration in complex, bimanual sequence learning tasks.

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Title: Task integration in complex, bimanual sequence learning tasks.
Authors: Beißel, Patrick (AUTHOR), Künzell, Stefan (AUTHOR)
Source: Psychological Research. Feb2024, Vol. 88 Issue 1, p207-221. 15p.
Subjects: Sequential learning, Motor ability
Abstract: Sequence learning and multitasking studies have largely focused on simple motor skills, which cannot be directly transferred to the plethora of complex skills found outside of laboratory conditions. Established theories e.g. for bimanual tasks and task integration thus have to be reassessed in the context of complex motor skills. We hypothesize that under more complex conditions, task integration facilitates motor learning, impedes or suppresses effector-specific learning and can still be observed despite partial secondary task interference. We used the Ξ-apparatus to assess the learning success of six groups in a bimanual dual-task, in which we manipulated the degree of possible integration between the right-hand and the left-hand sequences. We could show that task integration positively influences the learning of these complex, bimanual skills. However, the integration impedes but not fully suppresses effector-specific learning, as we could measure reduced hand-specific learning. Task integration improves learning despite the disruptive effect of partial secondary task interference, but its mitigating effect is only effective to some extent. Overall, the results suggest that previous insights on sequential motor learning and task integration can largely also be applied to complex motor skills. [ABSTRACT FROM AUTHOR]
Copyright of Psychological Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Task integration in complex, bimanual sequence learning tasks.
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  Data: <searchLink fieldCode="AR" term="%22Beißel%2C+Patrick%22">Beißel, Patrick</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Künzell%2C+Stefan%22">Künzell, Stefan</searchLink> (AUTHOR)
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  Data: Sequence learning and multitasking studies have largely focused on simple motor skills, which cannot be directly transferred to the plethora of complex skills found outside of laboratory conditions. Established theories e.g. for bimanual tasks and task integration thus have to be reassessed in the context of complex motor skills. We hypothesize that under more complex conditions, task integration facilitates motor learning, impedes or suppresses effector-specific learning and can still be observed despite partial secondary task interference. We used the Ξ-apparatus to assess the learning success of six groups in a bimanual dual-task, in which we manipulated the degree of possible integration between the right-hand and the left-hand sequences. We could show that task integration positively influences the learning of these complex, bimanual skills. However, the integration impedes but not fully suppresses effector-specific learning, as we could measure reduced hand-specific learning. Task integration improves learning despite the disruptive effect of partial secondary task interference, but its mitigating effect is only effective to some extent. Overall, the results suggest that previous insights on sequential motor learning and task integration can largely also be applied to complex motor skills. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychological Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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