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Additive Effects of Prior Knowledge and Predictive Visual Information in Improving Continuous Tracking Performance Cover

Additive Effects of Prior Knowledge and Predictive Visual Information in Improving Continuous Tracking Performance

Open Access
|Oct 2020

Abstract

Visual information and prior knowledge represent two different sources of predictability for tasks which each have been reported to have a beneficial effect on dual-task performance. What if the two were combined? Adding multiple sources of predictability might, on the one hand, lead to additive, beneficial effects on dual-tasking. On the other hand, it is conceivable that multiple sources of predictability do not increase dual-task performance further, as they complicate performance due to having to process information from multiple sources. In this study, we combined two sources of predictability, predictive visual information and prior knowledge (implicit learning and explicit learning) in a dual-task setup. 22 participants performed a continuous tracking task together with an auditory reaction time task over three days. The middle segment of the tracking task was repeating to promote motor learning, but only half of the participants was informed about this. After the practice blocks (day 3), we provided participants with predictive visual information about the tracking path to test whether visual information would add to beneficial effects of prior knowledge (additive effects of predictability). Results show that both predictive visual information and prior knowledge improved dual-task performance, presented simultaneously or in absence of each other. These results show that processing of information relevant for enhancement of task performance is unhindered by dual-task demands.

DOI: https://doi.org/10.5334/joc.130 | Journal eISSN: 2514-4820
Language: English
Submitted on: Apr 28, 2020
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Accepted on: Sep 23, 2020
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Published on: Oct 13, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Laura Broeker, Harald Edwin Ewolds, Rita F. de Oliveira, Stefan Künzell, Markus Raab, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.