Understanding the influence of distractors on workload capacity

Little, Daniel R.; Eidels, Ami; Fifić, Mario; Wang, Tony

doi:10.1016/j.jmp.2015.08.005

Cited by 44 publications

(67 citation statements)

References 26 publications

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“…Under these conditions, Little et al (2015) showed that the function does not reflect changes in workload, but instead captures how quickly the conflicting information is processed relative to the target information. We term this function resilience, R(t), to capture the idea that the function tells us something about how the system copes with conflicting information (see Eq.…”

Section: Resiliencementioning

confidence: 99%

“…Although each of these tasks involve different processes (e.g., with regard to attentional processes; Chajut et al, 2009;Shalev & Algom, 2000), the logical structure of conflict in these tasks is similar. Little et al (2015) showed how one could apply the capacity coefficient function to the compare performance on the congruent target, AB, to performance on the pair of incongruent stimuli, e.g., AY and XB (see Fig. 2), that satisfy only one of the disjunctive rules.…”

Section: Resilience and Resiliency Difference Functionsmentioning

confidence: 99%

“…The resilience function compares response times with congruent information to response times with incongruent information, whereas the capacity coefficient compares response times with congruent information to the sources of information in isolation. Little et al (2015) show that with conflicting information, the resilience function reflects the speed of processing of the conflicting information. On its own, this measure allows only limited inference about processing architecture, but by contrasting conflicting information of different salience, one can gain substantial information about the underlying processing architecture.…”

Section: Introductionmentioning

confidence: 99%

“…Resilience, as demonstrated in Little et al, (2015Little et al, ( , 2016 and summarized below, is affected by a combination of the four basic properties. For example, the presence of additional information, whether conflicting or not, affects workload (attribute 4 from the previous paragraph).…”

Section: Introductionmentioning

confidence: 99%

“…Like the list of information-processing attributes above, the initial investigation of conflict relied on qualitative contrasts between a functional measure of resilience, R(t), derived by Little et al (2015). The goal of this paper is to introduce a set of quantitative tools for the quantitative assessment of the resilience function and the closely related conflict contrast function.…”

Section: Introductionmentioning

confidence: 99%

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Statistical analyses of the resilience function

Houpt

Little

2016

Behav Res

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The extent to which distracting information influences decisions can be informative about the nature of the underlying cognitive and perceptual processes. In a recent paper, a response time-based measure for quantifying the degree of interference (or facilitation) from distracting information termed resilience was introduced. Despite using a statistical measure, the analysis was limited to qualitative comparisons between different model predictions. In this paper, we demonstrate how statistical procedures from workload capacity analysis can be applied to the new resilience functions. In particular, we present an approach to null-hypothesis testing of resilience functions and a method based on functional principal components analysis for analyzing differences in the functional form of the resilience functions across participants and conditions.

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Section: Resiliencementioning

confidence: 99%

Section: Resilience and Resiliency Difference Functionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistical analyses of the resilience function

Houpt

Little

2016

Behav Res

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Comparing Capacity Coefficient and Dual Task Assessment of Visual Multitasking Workload

Blaha

2017

Augmented Cognition. Enhancing Cognition and Behavior in Complex Human Environments

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How Do Information Processing Systems Deal with Conflicting Information? Differential Predictions for Serial, Parallel, and Coactive Models

et al. 2018

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In this paper, we analyze how different information-processing architectures deal with conflicting information. A robust finding in psychological research is that response times are slower when processing conflicting sources of information (e.g., naming the color of the word RED when printed in green in the well-known Stroop task) than when processing congruent sources of information (e.g., naming the color of the word GREEN when printed in green). We suggest that the effect of conflicting information depends on the processing architectures and derive a new measure of information processing called the conflict contrast function, which is indicative of how different architectures perform with conflicts at different levels of salience. By varying the salience of the conflicting information source, we show that serial, parallel, and coactive information processing architectures predict qualitatively distinct conflict contrast functions. We provide new analyses of three previously collected data sets: a detection task with Stroop color-word stimuli and two categorization experiments. Our novel measure provides convergent evidence about the underlying processing architecture in the categorization tasks and surprising results in the Stroop detection task.Keywords Response time . Information processing . Serial vs parallel . Coactivation . Conflict When people make decisions, they are sometimes confronted with sources that provide conflicting information. A driver must slow down upon detection of a pedestrian crossing the road, yet the traffic light could be green at the same time, signaling to go. Conflicting information can take toll on performance, in terms of error rate, response latencies, or both. Perhaps the most prominent laboratory example of a decision based on conflicting information is the Stroop task (e.g., Stroop 1935;Eidels et al. 2010): Naming the font color of a word when the color and word are incompatible (e.g., the word RED printed in green) is more difficult and takes more time than if the word and its color match (GREEN printed in green). Here, the word Bsource^and the color source can provide conflicting information as to the correct response. In general and across many psychological tasks, decision making is slower and more error prone when both sources are in conflict than when both sources provide congruent information. In this paper, we examine how the human information processing system resolves situations in which conflicting sources of information point to different decisions.The term conflict is colloquially used to describe a clash or disagreement between opposing forces. For scientific rigor, we need a more precise and specific definition for Bconflictb etween two stimulus dimensions. We draw on Livnat and Pippenger's (2006) game theoretic definition of conflict. The basic idea is that two Bagents^are in conflict if the utility resultant from one agent's Bbehavior^could have been higher if the other agent Bacted^differently. In adapting this definition to cognitive process model...

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Understanding the influence of distractors on workload capacity

Cited by 44 publications

References 26 publications

Statistical analyses of the resilience function

Statistical analyses of the resilience function

Comparing Capacity Coefficient and Dual Task Assessment of Visual Multitasking Workload

How Do Information Processing Systems Deal with Conflicting Information? Differential Predictions for Serial, Parallel, and Coactive Models

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