The adaptation of visual search to utility, ecology and design

Tseng, Yuan-Chi; Howes, Andrew

doi:10.1016/j.ijhcs.2015.03.005

Cited by 19 publications

(9 citation statements)

References 88 publications

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“…[ 18 ]) and to assess in an objective way whether participants achieved the best scores they could. This provides support for the notion that rational agents optimize their performance so as to maximize their payoff [ 18 , 35 , 53 – 56 , 68 ]. We showed that incentives have consequences for the strategies that are selected for interleaving attention and for performance on each of the individual task (e.g., total time spent typing, and maximum deviation of a cursor).…”

Section: Discussionmentioning

confidence: 79%

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

Janssen

Brumby

2015

PLoS ONE

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We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects). Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities.

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Section: Discussionmentioning

confidence: 79%

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

Janssen

Brumby

2015

PLoS ONE

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“…Computational rational agents have been used to model a number of phenomena in HCI (Payne & Howes, 2013). Applications relevant to this paper include menu interaction (Chen et al, 2015), visual search (Hayhoe & Ballard, 2014;Myers, Lewis, & Howes, 2013;Nunez-Varela & Wyatt, 2013;Tseng & Howes, 2015), and decision-making (Chen, Starke, Baber, & Howes, 2017).…”

Section: Example 2: Computational Rationalitymentioning

confidence: 99%

Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation

et al. 2019

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This paper addresses a common challenge with computational cognitive models: identifying parameter values that are both theoretically plausible and generate predictions that match well with empirical data. While computational models can offer deep explanations of cognition, they are computationally complex and often out of reach of traditional parameter fitting methods. Weak methodology may lead to premature rejection of valid models or to acceptance of models that might otherwise be falsified. Mathematically robust fitting methods are, therefore, essential to the progress of computational modeling in cognitive science. In this article, we investigate the capability and role of modern fitting methods—including Bayesian optimization and approximate Bayesian computation—and contrast them to some more commonly used methods: grid search and Nelder–Mead optimization. Our investigation consists of a reanalysis of the fitting of two previous computational models: an Adaptive Control of Thought—Rational model of skill acquisition and a computational rationality model of visual search. The results contrast the efficiency and informativeness of the methods. A key advantage of the Bayesian methods is the ability to estimate the uncertainty of fitted parameter values. We conclude that approximate Bayesian computation is (a) efficient, (b) informative, and (c) offers a path to reproducible results.

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“…Particularly, researchers call for more extensive usage of mathematical cognitive models that are currently "under-exploited" in HCI [4] (p. 2), and [2]. Today's trend in such models is consideration of utility for subjects [4] or costbenefit trade-offs [5], e.g., the ones optimizing the "expenditure" of perceptual-motor plus cognitive resources [6]. Among other things, they can predict the time spent by users in tasks of various difficulties so that the verification of UIs can be carried out without studies with the actual users [2,4].…”

Section: Introductionmentioning

confidence: 99%

What Makes a UI Simple? Difficulty and Complexity in Tasks Engaging Visual-Spatial Working Memory

Bakaev

2021

Future Internet

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Tasks that imply engagement of visual-spatial working memory (VSWM) are common in interaction with two-dimensional graphical user interfaces. In our paper, we consider two groups of factors as predictors of user performance in such tasks: (1) the metrics based on compression algorithms (RLE and Deflate) plus the Hick’s law, which are known to be characteristic of visual complexity, and (2) metrics based on Gestalt groping principle of proximity, operationalized as von Neumann and Moore range 1 neighborhoods from the cellular automata theory. We involved 88 subjects who performed about 5000 VSWM-engaging tasks and 78 participants who assessed the complexity of the tasks’ configurations. We found that the Gestalt-based predictors had a notable advantage over the visual complexity-based ones, as the memorized chunks best corresponded to von Neumann neighborhood groping. The latter was further used in the formulation of index of difficulty and throughput for VSWM-engaging tasks, which we proposed by analogy with the infamous Fitts’ law. In our experimental study, throughput amounted to 3.75 bit/s, and we believe that it can be utilized for comparing and assessing UI designs.

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The adaptation of visual search to utility, ecology and design

Cited by 19 publications

References 88 publications

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation

What Makes a UI Simple? Difficulty and Complexity in Tasks Engaging Visual-Spatial Working Memory

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