Switch rates vary due to expected payoff but not due to individual risk tendency.

When switching between different tasks, the initiation of task switches may depend on task characteristics (difficulty, salient cues, etc.) or reasons within the person performing the task (decisions, behavioral variability, etc.). The reasons for variance in switching strategies, especially in paradigms where participants are free to choose the order of tasks and the amount of switching between tasks, are not well researched. In this study, we follow up the recent discussion that variance in switching strategies might be partly explained by the characteristics of the person fulfilling the task. We examined whether risk tendency and impulsiveness differentiate individuals in their response (i.e., switch rates and time spent on tasks) to different task characteristics on a tracking-while-typing paradigm. In detail, we manipulated two aspects of loss prospect (i.e., "payoff" as the amount of points that could be lost when tracking was unattended for too long, and "cursor speed" determining the likelihood of such a loss occurring). To account for between-subject variance and within-subject variability in the data, we employed linear mixed effect analyses following the model selection procedure (Bates, Kliegl, et al., 2015). Besides, we tested whether risk tendency can be transformed into a decision parameter which could predict switching strategies when being computationally modelled. We transferred decision parameters from the Decision Field Theory to model "switching thresholds" for each individual. Results show that neither risk tendency nor impulsiveness explain between-subject variance in the paradigm, nonetheless linear mixed-effects models confirmed that within-subject variability plays a significant role for interpreting dual-task data. Our computational model yielded a good model fit, suggesting that the use of a decision threshold parameter for switching may serve as an alternative means to classify different strategies in task switching. [Abstract copyright: Copyright © 2022. Published by Elsevier B.V.

How visual information influences dual-task driving and tracking

The study examined the impact of visual predictability on dual-task performance in driving and tracking tasks. Participants (N = 27) performed a simulated driving task and a pursuit tracking task. In either task, visual predictability was manipulated by systematically varying the amount of advance visual information: in the driving task, participants drove at night with low beam, at night with high beam, or in daylight; in the tracking task, participants saw a white line that specified the future target trajectory for 200, 400 or 800 ms. Concurrently with driving or tracking, participants performed an auditory task. They had to discriminate between two sounds and press a pedal upon hearing the higher sound. Results show that in general, visual predictability benefited driving and tracking; however, dual-task driving performance was best with highest visual predictability (daylight), dual-task tracking performance was best with medium visual predictability (400 ms). Braking/reaction times were higher in dual tasks compared to single tasks, but were unaffected by visual predictability, showing that its beneficial effects did not transfer to the auditory task. In both tasks, manual accuracy decreased around the moment the foot pressed the pedal, indicating interference between tasks. We, therefore, conclude that despite a general beneficial impact of predictability, the integration of visual information seems to be rather task specific, and that interference between driving and audiomotor tasks, and tracking and audiomotor tasks, seems comparable

What is a task? An ideomotor perspective

Although multitasking has been the subject of a large number of papers and experiments, the term task is still not well defined. In this opinion paper, we adopt the ideomotor perspective to define the term task and distinguish it from the terms goal and “action”. In our opinion, actions are movements executed by an actor to achieve a concrete goal. Concrete goals are represented as anticipated sensory consequences that are associated with an action in an ideomotor manner. Concrete goals are nested in a hierarchy of more and more abstract goals, which form the context of the corresponding action. Finally tasks are depersonalized goals, i.e., goals that should be achieved by someone. However tasks can be assigned to a specific person or group of persons, either by a third party or by the person or the group of persons themselves. By accepting this assignment the depersonalized task becomes a personal goal. In our opinion, research on multitasking needs to confine its scope to the analysis of concrete tasks, which result in concrete goals as anticipated sensory consequences of the corresponding action. We further argue that the distinction between dual- and single-tasking is dependent on the subjective conception of the task assignment, the goal representation and previous experience. Finally, we conclude that it is not the tasks, but the performing of the tasks, i.e. the actions that cause costs in multi-tasking experiments

Why prediction matters in multitasking and how predictability can improve it

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission. Prediction1 is an omnipresent principle of human behavior that can be fostered by predictability in the environment. We regard prediction as the mental representation of future event states or anticipated action consequences, and predictability as a property of certain events in the environment. On the assumption that predictability and prediction are beneficial for any kind of behavior, we argue that their benefits to relieving the human system are most evident when encountering multiple tasks. However, we predicate that their impact on multitasking is understudied and so we aim at dissociating prediction and predictability within multitasking contexts and at outlining different sources of predictability that have not been conflated under this term so far. From our opinion it follows that future multitasking research requires experimental designs and analyses that consider and unveil principles of prediction and the impact of predictability on multitasking performance

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

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. [Abstract copyright: Copyright: © 2020 The Author(s).

Handlungssimulation: Funktionale Äquivalenz zur Ausführung und deren Einfluss auf motorisches Handeln und Lernen

Frank C, Naumann T. Handlungssimulation: Funktionale Äquivalenz zur Ausführung und deren Einfluss auf motorisches Handeln und Lernen. In: Augste C, Künzell S, eds. 15. Tagung der dvs-Sektion Sportmotorik vom 08. bis 10. März in Augsburg. Cogito Ergo Commoveo - Multitasking im Sport. Hamburg: Feldhaus; 2017: 31-39

Implicit and explicit knowledge both improve dual task performance in a continuous pursuit tracking task

The goal of this study was to investigate the effect of predictability on dual-task performance in a continuous tracking task. Participants practiced either informed (explicit group) or uninformed (implicit group) about a repeated segment in the curves they had to track. In Experiment 1 participants practices the tracking task only, dual-task performance was assessed after by combining the tracking task with an auditory reaction time task. Results showed both groups learned equally well and tracking performance on a predictable segment in the dual-task condition was better than on random segments. However, reaction times did not benefit from a predictable tracking segment. To investigate the effect of learning under dual-task situation participants in Experiment 2 practiced the tracking task while simultaneously performing the auditory reaction time task. No learning of the repeated segment could be demonstrated for either group during the training blocks, in contrast to the test-block and retention test, where participants performed better on the repeated segment in both dual-task and single-task conditions. Only the explicit group improved from test-block to retention test. As in Experiment 1, reaction times while tracking a predictable segment were no better than reaction times while tracking a random segment. We concluded that predictability has a positive effect only on the predictable task itself possibly because of a task-shielding mechanism. For dual-task training there seems to be an initial negative effect of explicit instructions, possibly because of fatigue, but the advantage of explicit instructions was demonstrated in a retention test. This might be due to the explicit memory system informing or aiding the implicit memory system