Information Theoretic Models of HCI: A Comparison of the Hick-Hyman Law and Fitts' Law

Seow, Steven C.

doi:10.1207/s15327051hci2003_3

Cited by 102 publications

(65 citation statements)

References 107 publications

(168 reference statements)

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“…Even though the aim of the study was not to verify the fit of the RTs to the logarithmic function according to the Hick-Hyman law (Seow, 2005), the progressive reduction in increment of the RT with increasing number of choices (see the data above in the 1 st paragraph of the discussion) suggested the relevance to the logarithmic model of RTs and so the validity of the RTs obtained in this study. This conclusion was also supported by the results of the intra-individual comparisons of both the mean RT and median RT achieved in any couple of the RT tests with the different number of choices.…”

Section: Discussionmentioning

confidence: 74%

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The visual reaction time distribution in the tasks with different demands on information processing

Psotta¹

2014

Acta Gymnica

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Background: Reaction tests are a part of the neuropsychological assessment of the individual. The design of these tests and selection of the appropriate measures of reaction time (RT) should come out from the distribution qualities of RTs. According to the newer general theory of RT distribution, the quality of RTs also depends on the specific properties of a reaction task. Objective: The aim of the study was to examine the dependency of RT distribution on an amount of processed information in a visual reaction test, and to verify the stability of RT distribution between two series of RTs in male adolescents. Methods: 25 male adolescents, aged 17.1 ± 1.1 years, performed four different eye-hand visual reaction tests which differed in a number of choices -simple reaction test (RT 1 ), two, three and fourchoice RT tests (RT 2 , RT 3, RT 4 ). Each test involved 2 series with 20 reaction trials in each series, using the computerbased reactometer device. The first, second and third moments of the RT distribution were assessed -the measures of central tendency (mean, median), variability (% CV, median absolute deviation/median ratio -MAD/Mdn, interquartile range) and normality (Kolmogorov-Smirnov test, skewness and kurtosis coefficient α and β). Significance of differences of RTs was assessed by the Wilcoxon test (α = .05). Results: The analysis showed the non-Gaussian distributions of RTs (α = .01) with the skew to the right (α = 1.18-4.38) and leptocurtic distribution (β = 1.89-34.15) in all types of the RT tests. The measures of RT variability % CV and MAD/Mdn (%) were lower for the RT 1 test as compared to the RT 2 , RT 3 and RT 4 tests. No significant differences in RTs measured in the 1 st and 2 nd series of trials were found in the RT 1 test and RT 2 test in contrast to significantly shorter RTs in the 2 nd series of trials in the RT 3 test and RT 4 test (p = .006 and p < .001). RTs measured in the 2 nd series of trials of RT 1 , RT 2 and RT 4 tests manifested distribution with a higher skewness to the right and higher peakedness than the RTs in the 1 st series. Conclusions: The study supported the hypothesis on asymmetric distribution of RTs, specifically when measured in the both eye-hand visual simple and multiple-choice reaction tasks with two up to four choices. Thus, the nonparametric statistics show to be more appropriate for analysis of RTs than the parametric statistics. For both clinical and research purposes, the two series of twenty reaction trials in a computer-based test can provide a sufficient number of the RT data for reliable assessment of visual simple and choice-reaction abilities in the male adolescents.

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Section: Discussionmentioning

confidence: 74%

“…the Hick-Hyman law with definition of RT as a logarithmic function of the number of choices (Seow, 2005). SRTs and CRTs are usually used as the indicators of information processing capacities and psycho-motor executive functions in individuals (Moskowitz, 2003).…”

Section: Introductionmentioning

confidence: 99%

The visual reaction time distribution in the tasks with different demands on information processing

Psotta¹

2014

Acta Gymnica

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“…Many researchers, and certainly usability professionals, would generally take a, b, k direct from the literature rather than performing their own analyzes or experiments. Some authors use superficially different formulations of the Fitts Law, such as a + b d/w (Meyer et al, 1988) or, more generally, a + b(d/w) n (Seow, 2005) and ad b w c (Kvålseth, 1980). All that matters for the present paper is that the numerical values are sufficiently close to user performance -how the timings are computed is not our concern.…”

Section: A1 the Fitts Lawmentioning

confidence: 99%

“…For example, to use the Hick-Hyman Law (Seow, 2005) to add delays due to the varying complexity of choice users face, arcs may be labelled f (m, n) + h(v) where h(v) adds a time c log(δ + (v) + 1), where δ + is the non-trivial out-degree of v in G (the standard graph theoretic out-degree for the total closure of G is a constant, the number of actions). An example of this approach is given in Soukoreff and MacKenzie (1995) for estimating timing bounds on soft keyboard use.…”

Section: Basic Generalizations Of Action Graphsmentioning

confidence: 99%

Action graphs and user performance analysis

Thimbleby

2013

International Journal of Human-Computer Studies

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“…The underlying theme of the ensuing Hick-Hyman law was that response time is not only a function of the number of stimulus alternatives but can also be considered a linear function of stimulus information (entropy). This finding spawned a number of attempts to design optimal control and display codes for human-computer interaction [27][28][29] although others have remarked that there has been limited uptake of these early concepts [30]. Chan & Childress crafted theoretical relationships between human-machine noise and humanmachine output velocity [31], formulating the channel capacity of a human-machine system.…”

Section: Gauging Contextual Effects Through Information Theorymentioning

confidence: 99%

Mutual Information as a Measure of Contextual Effects on Single Switch Use

Memarian¹,

Venetsanopoulos²,

Chau

2009

TOREHJ

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We propose the use of mutual information as an objective means of measuring the impact of contextual factors on mechanical single switch usage. We show that common performance measures (e.g. sensitivity, specificity and response time) relating to switch use can be quantitatively unified within a mutual information measure. We exemplify the use of mutual information in the assessment of switch use in the presence of selected contextual factors. This information theoretic measure facilitates performance comparison amongst users and can potentially help in classification of contextual stimuli in terms of their impact (i.e. facilitating, barrier, neutral). Our examples with able-bodied participants and an individual with disability indicate that mutual information can be sensitive to changes in contextual factors. Mutual information may thus inform the design of individualized access technologies.

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Information Theoretic Models of HCI: A Comparison of the Hick-Hyman Law and Fitts' Law

Cited by 102 publications

References 107 publications

The visual reaction time distribution in the tasks with different demands on information processing

The visual reaction time distribution in the tasks with different demands on information processing

Action graphs and user performance analysis

Mutual Information as a Measure of Contextual Effects on Single Switch Use

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