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Time-based expectancy in multitasking: From cognitive psychology to movement science

Team

Roland Thomaschk

Dr. Roland Thomaschke            

Principal Investigator

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Stefanie Aufschnaiter

Stefanie Aufschnaiter

PhD Candidate

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tba
 

tba.

PhD candidate

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Former Team Members

Irina Monno

Irina Monno

Research Fellow

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This project is done in close collaboration with Prof. Dr. Andrea Kiesel (Freiburg), Stefan Künzell (Augsburg), and Markus Raab (Köln).

 

Abstract (2018-2021)

The project investigates how time as a source of information supports multitasking. During the first funding period, experiments focused on the role time-based predictability in task switching scenarios, as they are common in cognitive psychology basic research on multitasking. When in task switching the duration of an empty preparatory interval predicts the type of the next task, participants behaviorally adapt to such regularity without getting aware of it. Results from the first funding period showed that this adaptation is relatively independent of the degree of predictability, and that it involves relative (e.g., short vs. long) instead of absolute (e.g., 500 ms vs. 1500 ms) representations of time. Further, adaptation to time-based predictability is also observable in other basic cognitive psychology paradigms, such as dual-tasking, or effect monitoring. However, the intense interaction between cognitive psychology and movement science in the priority program lead to preliminary experimental evidence that time-based predictability might also play a more fundamental role in multitasking. In addition to announcing which task to do next in task switching, time-based predictabilities might also assist multitasking when the predictability is embedded in one of two continuous concurrent tasks. Paradigms with continuous concurrent tasks, are predominant in the movement sciences. In collaboration with movement scientists within the priority program, a continuous concurrent multitasking paradigm has been developed, where time-based predictability is embedded in one of the tasks. A simple manual choice task (pressing on vibrating buttons) is combined, in an unsynchronized manner, with a mental arithmetic task. The duration of the short interval between two button vibrations predicts which button will vibrate next. Results from a preliminary study show that this predictability supports multitasking. Performance on the arithmetic task is better when the manual choice task is temporally predictable, relative to when it is not. The experiments proposed here will systematically investigate the mechanism underlying the effect from time-based predictability in one task on performance in a concurrent task. Hypotheses are derived from converging theorizing about predictability by multiple projects in the priority program. A first set of experiments will investigate how performance in both tasks is related to each other, and which interval durations primarily drive the effect. A second set of experiments is devoted to the domain specificity of the effects. Does time-based predictability in one task support timing related second tasks in particular? A last set of experiments will be deal with the cognitive representations of time processed in the adaptation effect. Does it involve relative representations, such as adaptation to task prediction? Or does it employ absolute representation, as typical for some related movement timing tasks?

Abstract (2015-2018)

Timing is a key factor in multi-tasking. Increasing the temporal distance between tasks usually reduces interference from the previous task and supports preparation for the next task (see Kiesel et al., 2010; H. E. Pashler, 1998; Vandierendonck, Liefooghe, & Verbruggen, 2010, for reviews). In many real-life multi-tasking situations, this temporal distance is highly predictive with regard to the next task. For example, the duration of the system response delay after clicking on a web-link is highly informative about which task will be required next. During the first seconds of the delay, it is likely that the page will load successfully, requiring one to navigate on the page. When, on the contrary, the delay takes longer, it becomes increasingly likely that an error message occurs instead, requiring one to search for another link (Thomaschke, Kunchulia, & Dreisbach, in press).
This time-based task predictability is likely to have a strong impact on cognitive processing and behavior in multi-tasking. It is known that the cognitive system uses task-predictability (e.g., by task sequence, or by explicit task cues) for task preparation, thereby substantially improving task performance (see Ruge, Jamadar, Zimmermann, & Karayanidis, 2013, for a review). The effects of time-based task predictability have, however, not yet been investigated. The proposed project aims at a first systematic investigation of this phenomenon.
The proposed experiments will elucidate how time-based task predictability is cognitively processed, as well as how flexible this processing is in different multi-tasking contexts.

 

Project Output

Aufschnaiter, S., Kiesel, A., & Thomaschke, R. (in press). Transfer of Time-based Task Expectancy across Different Timing Environments. Psychological Research. doi: 10.1007/s00426-017- 0895-1.

Aufschnaiter, S., Kiesel, A., Dreisbach, G., Wenke, D., & Thomaschke, R. (in press). Time-based Expectancy in Temporally Structured Task Switching. Journal of Experimental Psychology: Human Perception and Performance.

Bröker, L., Kiesel, A., Aufschnaiter, S., Ewolds, H., Gaschler, R., Haider, H., Künzell, S., Raab, M., Röttger, E.,Thomaschke, R., & Zhao, F. (in press). Why prediction matters in multitasking and how predictability can improve it. Frontiers in Psychology. doi: 10.3389/fpsyg.2017.02021.

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